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KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

COLLEGE OF ARCHITECTURE AND PLANNING

DEPARTMENT OF BUILDING TECHNOLOGY

A GENERIC FRAMEWORK FOR CONSULTANCY PRICING: THE CASEOF

QUANTITY SURVEYING PRACTICE

A Master’s Thesis Submitted to the Department of Building Technology of the

Kwame Nkrumah University of Science and Technology in partial fulfillment of

the requirements for the award of a MASTER OF PHILOSOPHY (MPHIL)

degree in BUILDING TECHNOLOGY

Student

ADESI MICHAEL

BSc. (Hons.) Building Technology

SUPERVISOR

Dr. De-Graft Owusu-Manu

SEPTEMBER, 2013

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KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY

COLLEGE OF ARCHITECTURE AND PLANNING

DEPARTMENT OF BUILDING TECHNOLOGY

A GENERIC FRAMEWORK FOR CONSULTANCY PRICING: THE CASEOF

QUANTITY SURVEYING PRACTICE

A Master’s Thesis Submitted to the Department of Building Technology of the

Kwame Nkrumah University of Science and Technology in partial fulfillment of

the requirements for the award of a MASTER OF PHILOSOPHY (MPHIL)

degree in BUILDING TECHNOLOGY

ADESI MICHAEL

BSc. (Hons.) Building Technology

SUPERVISOR

Dr. De-Graft Owusu-Manu

SEPTEMBER, 2013

3

DECLARATION

I declare that I wholly undertook this research under supervision and where other scholarly

works have been used were duly acknowledged as such.

………………………………………. Date……………………………….

ADESI, MICHAEL (STUDENT)

I declare that I have supervised the student in undertaking the research reported herein and I

confirm that the student has effected all corrections suggested.

………………………………………. Date…………………………………

DR. DE-GRAFT OWUSU-MANU (SUPERVISOR)

……………………………………. Date…………………………………

PROF JOSHUA AYARKWA (HOD, Department of Building Technology)

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ABSTRACT

The consultancy industry provides services to clients in diverse sectors of economies globally to

the extent that their roles in the developmental agenda of nations and corporate institutions

cannot be underestimated. One of the key areas of consultancy services provision in the

construction industry is quantity surveying practice. Over the years, quantity surveyors have

provided services to clients in the construction industry at a consideration of a pricing (fees).

However, these prices determined by quantity surveying consultants were not sustainable enough

to ensure continual existence in business. The aim of this research was to explore quantity

surveying practice in Ghana; and to develop a generic framework for gauging quantity surveying

professional services consultancy services. An extensive literature review was conducted on the

consultancy industry; and quantity surveying practice. Similarly, framework on key pricing

concepts was adopted culminating into the postulation of twelve (12) key pricing hypotheses.

Philosophically, the study leaned towards the positivism paradigm culminating into the adoption

of quantitative methods in which survey questionnaires were administered to respondents

yielding a response rate of 72 per cent. The analytical tools utilized in data analysis include chi

square test of independence; factor analysis; and descriptive analysis. Adopting a wide range of

independent variables categorized mainly as risks, taxation and inflation; value, price catalysts,

cost(service cost) management and business management, the study found the dependent

variable (price robustness and level) to be significantly dependent on the independent variables.

The key findings led to the development of a generic framework for pricing quantity surveying

consultancy services.

Keywords: Quantity, surveying, generic, pricing, consultancy, services.

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ACKNOWLEDGEMENTS

I am most indebted to the Almighty God for giving me the clarity and soundness of mind and

good health generally over the period of conducting this research. I highly acknowledge the

protection of the Almighty God on two key separate occasions and would forever remain grateful

to HIM. I am very much thankful to my supervisor without who this research. I am very thankful

to my supervisor, Dr. De-graft Owusu-Manu for supporting me academically, morally and

financially. His mentorship style is enviable and unassailable; he is a father, a friend and a

brother in all respect without which this work would not have existed. I am also grateful to Dr.

Eric Oduro-Ofori of the Department of Planning of KNUST for his support. Professor Edward

Badu, the Provost of the College of Architecture and Planning of KNUST is highly

acknowledged for all his inputs over the period.

I am grateful to Mr Elias Megbetor, Emmanuel Kwami and many others not forgetting my

friends Ernest Kisi, Federick Amoako Sarpong, Meshack Quaye Dadzie and Korley Akutteh

Ebenezer ( my mates) for their support over the course of conducting this research.

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TABLE OF CONTENTS

DECLARATION ...................................................................................................................................... 3

ABSTRACT .............................................................................................................................................. 4

ACKNOWLEDGEMENTS .................................................................................................................... 5

CHAPTER ONE ................................................................................................................................... 13

1.0 INTRODUCTION TO THE RESEARCH ................................................................................... 13

1.1 BACKGROUND OF THE STUDY .............................................................................................. 13

1.2 STATEMENT OF THE PROBLEM ............................................................................................. 15

1.3 AIM AND OBJECTIVES OF THE RESEARCH ....................................................................... 17

1.3.1 AIM ................................................................................................................................................. 17

1.3.2 OBJECTIVES ............................................................................................................................... 18

1.4 JUSTIFICATION/ RELEVANCE OF THE RESEARCH ........................................................ 18

1.5 SCOPE OF THE RESEARCH ....................................................................................................... 20

1.6 RESEARCH METHODOLOGY ................................................................................................... 21

1.7 LIMITATIONS OF THE RESEARCH ........................................................................................ 23

1.8 ORGANIZATION OF THE RESEARCH ................................................................................... 23

CHAPTER TWO .................................................................................................................................. 26

THEORETICAL FRAMEWORK ....................................................................................................... 26

2.0 INTRODUCTION ........................................................................................................................... 26

2.1 Concept of Price and Value ............................................................................................................ 26

2.2 The Just Price .................................................................................................................................... 27

2.3 Importance, Objectives and Goals of Pricing ............................................................................... 28

2.4 Pricing Strategies ............................................................................................................................. 29

2.4 Project Pricing .................................................................................................................................. 30

2.5 Bid Pricing ........................................................................................................................................ 32

2.6 Production and Pricing .................................................................................................................... 33

2.7 The Concept of Risk ........................................................................................................................ 37

2.7.1 Risk and Price ................................................................................................................................ 38

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2.7.2 Types of Risk ................................................................................................................................. 40

2.7.3 Risks at Various Stages of Project Implementation ................................................................. 42

2.8 Concept of Taxation......................................................................................................................... 44

2.8.1 Taxation of consultancy services ................................................................................................ 45

2.8.2 Tax System in Ghana ................................................................................................................... 45

2.8.3 General Provisions under the Tax Law ...................................................................................... 46

2.8.4 Income and Profit Tax Legislation ............................................................................................. 46

2.8.5 The Implementation of VAT ....................................................................................................... 47

2.9. Concept of Inflation ........................................................................................................................ 48

2.9.1 Causes of Inflation ........................................................................................................................ 49

2.9.2 Economic Indicators of Inflation ................................................................................................ 49

2.9.3 Nominal and Real Prices .............................................................................................................. 50

CHAPTER THREE ............................................................................................................................. 52

THE CONSULTANCY INDUSTRY: A GENERAL OVERVIEW ............................................... 52

3.0 INTRODUCTION ........................................................................................................................... 52

3.1 CONCEPTUAL EXPLANATION OF CONSULTANCY ........................................................ 53

3.2 TOWARDS THE SEGMENTATION OF THE CONSULTANCY INDUSTRY ................. 55

3.2.1 THE SCOPE OF CONSULTING SERVICES ......................................................................... 56

3.3 CRITICALLY EXAMINING CONSULTANCY CONTRACTS ............................................ 58

3.4 CRTITICAL REASONS: TOWARDS AN EFFECTIVE CONSULTING ............................. 61

3.5 EXPLORING THE FUNCTIONS OF CONSULTING ............................................................. 64

3.6 EFFECTIVE CONSULTING: THE ROLE OF CONSULTANTS .......................................... 65

3.7 CLIENTS - CONSULTANTS RELATIONSHIP ....................................................................... 66

3.8 THE CONSULTANCY INDUSTRY: ITS CRITICISMS ......................................................... 69

3.8.1 ARGUMENTS SUPPORTING CONSULTANCY PRACTICE .......................................... 71

3.9 THE SELECTION OF AN EFFECTIVE CONSULTANCY FIRM ........................................ 72

3.10 CRITICAL FACTORS FOR SUCCESSFUL CONSULTING ............................................... 73

3.11 FACTORS RESPONSIBLE FOR CONSULTANCY FAILURES ........................................ 76

3.12 TERMS OF REFERENCE: THE BASIS OF AN EFFECTIVE CONSULTANCY ........... 77

3.13 THE ART OF PRICING CONSULTANCY SERVICES ........................................................ 79

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3.14 APPRAISAL AND SYNTHESIS OF THE LITERATURE REVIEW ................................. 82

CHAPTER FOUR ................................................................................................................................ 88

QUANTITY SURVEYING PRACTICE IN CONTEMPORARY GLOBAL............................... 88

4.0 INTRODUCTION ........................................................................................................................... 88

4.1 THE MEANING OF QUANTITY SURVEYING (QS) ............................................................ 89

4.2 THE ROLE OF THE QUANTITY SURVEYOR ....................................................................... 90

4.2.1 The Changing Roles of the Quantity Surveyor ......................................................................... 91

4.3 QUANTITY SURVEYING CONSULTANCY SERVICES..................................................... 92

4.3.1 NON-TRADITIONAL QUANTITY SURVEYING CONSULTANCY SERVICES ........ 96

4.4 QUANTITY SURVEYING CONSULTANCY SERVICES PRICING/FEES ....................... 97

4.4.1 CHALLENGES OF QUANTITY SURVEYING SERVICES PRICING/FEES ................. 99

4.5 CHALLENGES CONFRONTING QUANTITY SURVEYING PRACTICE ...................... 100

4.6 PROFESSIONAL MISCOUNDUCT IN QUANTITY SURVEYING PRACTICE ............ 101

4.7 ADOPTION OF ICT IN QUANTITY SURVEYING OPERATIONS .................................. 102

4.8 EXPLORING THE BILLS OF QUANTITIES (BOQ) IN QS PRACTICE .......................... 103

4.8.1 The Emergence of the BOQ ...................................................................................................... 103

4.8.2 The Definition of Bills of Quantities ........................................................................................ 104

4.8.3 Uses of the Bills of Quantities .................................................................................................. 105

4.8.4 Challenges Confronting BOQ Usage ....................................................................................... 106

4.8.5 The Relevance of BOQ in Modern Construction Industry .................................................... 106

4.9 AN EXPOSITION OF QUANTITY SURVEYING PRACTICE IN GHANA .................... 107

4.10 APPRAISAL AND SYNTHESIS OF THE LITERATURE REVIEW ............................... 109

CHAPTER FIVE ................................................................................................................................ 112

RESEARCH METHODOLOGY ....................................................................................................... 112

5.0 INTRODUCTION ......................................................................................................................... 112

5.1 PHILOSOPHICAL TRADITIONS AND CONSIDERATIONS ............................................ 112

5.1.1 METHOD OF SCIENTIFIC INQUIRY AND REASON ..................................................... 114

5.2 RESEARCH STRATEGY AND DESIGN ................................................................................ 115

5.2.1 Quantitative Research Paradigm ............................................................................................... 115

5.2.1.1 Objectivism and Realism ........................................................................................................ 116

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5.2.1.2 The Survey Process ................................................................................................................. 119

5.2.1.2 .1 Research Scope and Boundaries ....................................................................................... 120

5.2.1.2 .2 Sampling Techniques and Sample Frame ........................................................................ 121

5.2.1.2 .2 .1 Sampling Technique Adopted ....................................................................................... 123

5.2.1.2.3 Data Collection Methods ..................................................................................................... 124

5.3 DATA ANALYSIS METHODS.................................................................................................. 131

5.3.1 Descriptive Analysis ................................................................................................................... 131

5.3.2 Data Presentation Using Tables ................................................................................................ 131

5.3.3. Relative Importance Index (RII) .............................................................................................. 133

5.3.4 Inferential Analysis: Hypothesis Testing .............................................................................. 135

5.3.4.1 Steps for Hypothesis Testing ................................................................................................. 137

5.3.4.2 Approaches/Criteria to Hypothesis Testing ......................................................................... 139

5.3.4.3 Interpretation of Hypothesis Test Result .............................................................................. 140

5.3.4.4 Some Key Statistical Tools for Hypothesis testing ............................................................. 141

5.3.4.4.1 ANOVA ................................................................................................................................. 141

5.3.4.4.2 Correlation ............................................................................................................................. 141

5.3.4.4.3 Regression ............................................................................................................................. 141

5.3.4.5 Adoption of Chi Square Test for Hypotheses Testing ........................................................ 142

5.3.4.6 Framework Development: Utilizing Factor Analysis ......................................................... 145

5.3.4.6.1 Interpretation of Results Produced by Factor Analysis ................................................... 147

5.4 Summary of the Research Process ............................................................................................... 148

CHAPTER SIX....…………………………………………………………………………….153

ANALYSIS OF DATA AND DISCUSSION OF RESULTS ........................................................ 150

6.0 INTRODUCTION ......................................................................................................................... 150

6.1 DESCRIPTIVE ANALYSIS ........................................................................................................ 151

6.1.1 Respondents Profile .................................................................................................................... 151

6.1.2 Legal Status of Respondent’s firms .......................................................................................... 151

6.1.4 Rate of Work Acquisition .......................................................................................................... 153

6.1.5 Sectors of Operation ................................................................................................................... 153

6.2 RANKING OF KEY PRICING VARIABLES .......................................................................... 156

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6.2.1 Concept of Price and Value ....................................................................................................... 157

6.2.2 Project Pricing (Consultancy Pricing) ...................................................................................... 161

6.2.3 Concept of Risk ........................................................................................................................... 162

6.2.4 Concept of Taxation and Inflation ............................................................................................ 164

6.2.5 Quantity Surveying Consultancy Services Pricing Components ......................................... 166

6.2.6 Challenges confronting quantity surveying consultancy practice ........................................ 167

6.2.7 Quantity surveying consultancy services (Seeley, 1997; Olatunde, 2006) ......................... 169

6.3 INFERENTIAL ANALYSIS: HYPOTHESES TESTING ...................................................... 171

6.3.1 Price and Value Hypotheses ...................................................................................................... 172

6.4 FACTOR ANALYSIS................................................................................................................... 186

6.4.1 Concept of Price and Value (Variables) .................................................................................. 186

6.4.1.2 Components Extracted ............................................................................................................ 190


6.4.2.1 Initial Considerations .............................................................................................................. 191


6.4.3 Concept of risk ............................................................................................................................ 195

6.4.3.1 Initial Considerations .............................................................................................................. 195


6.4.4 Concept of taxation and inflation.............................................................................................. 199

6.4.4.1 Initial Consideration ................................................................................................................ 199


6.4.5 Quantity surveying consultancy services pricing components ............................................. 202



6.4.6 Challenges Confronting QS Consultancy Practice ................................................................. 206



6.5 DISCUSSION AND INTERPRETATION OF RESULTS...................................................... 210

6.5.1 Concept of price and value ........................................................................................................ 211

6.5.1.1 Component 1: Pricing strategies ............................................................................................ 211

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6.5.1.2 Component 2: Just Pricing ..................................................................................................... 212

6.5.1.3 Component 3: Pricing Roles .................................................................................................. 214

6.5.1.4 Component 4: Social influence .............................................................................................. 216

6.5.1.5 Component 5: Value................................................................................................................ 216


6.5.2.1 Component 1: Business management ................................................................................... 217

6.5.2.2 Component 2: Service cost management ............................................................................. 218

6.5.2.3 Component 3: Technical and financial capabilities ............................................................ 220

6.5.3 Concept of Risk ........................................................................................................................... 220

6.5.3.1 Component 1: Corporate internal risk................................................................................... 220

6.5.3.2 Component 2: Corporate external risk .................................................................................. 221

6.5.3.3 Component 3: Location Risk ................................................................................................. 222

6.5.4 Concept of Taxation and Inflation ............................................................................................ 223

6.5.4.1 Component 1: Taxes................................................................................................................ 223

6.5.4.2 Components 2 and 3: Price catalysts ..................................................................................... 224

6.5.5 Quantity Surveying Consultancy Services Pricing Components ......................................... 226

6.5.5.1 Component 1: Office Management ....................................................................................... 226

6.5.5.2 Component 2: Overheads ....................................................................................................... 226

6.5.5.3 Component 3: Administration and Training ........................................................................ 227

6.5.5.4 Component 4: Reimbursement and Payments ..................................................................... 228

6.5.6 Challenges confronting Quantity Surveying Consultancy Practice ..................................... 229

6.5.6.1 Component 1: Contractual and technology challenges ...................................................... 229

6.5.6.2 Component 2: Pricing Challenges ......................................................................................... 230

6.5.6.3 Component 3: Market forces .................................................................................................. 230

6.5.6.4 Component 4: Professional fees ............................................................................................ 231

A Generic Framework for Pricing QS Consultancy Services ......................................................... 231

CHAPTER SEVEN ............................................................................................................................ 233

CONCLUSION AND RECOMMENDATIONS ............................................................................. 233

7.1 INTRODUCTION ......................................................................................................................... 233

7.2 REVIEW OF RESEARCH OBJECTIVES ................................................................................ 233

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7.3 FINDINGS ...................................................................................................................................... 238

7.3.1 Special Relationships Identified ............................................................................................... 239

7.4 CONTRIBUTION TO KNOWLEDGE ...................................................................................... 240

7.5 RECOMMENDATIONS FOR PRACTITIONERS .................................................................. 242

7.6 FUTURE RESEARCH AGENDA .............................................................................................. 243

7.7 CONCLUSIONS ............................................................................................................................ 244

REFERENCES.………………………………………………………………………………248

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CHAPTER ONE

1.0 INTRODUCTION TO THE RESEARCH

This chapter presents an overview of the thesis which highlights the research in terms of the

background of the study and the statement of the research problem. The aim and objectives of

the study were also espoused and this is subsequently followed by the justification of the

research, methodology to be adopted, limitations of the research and finally the organization of

the research.

1.1 BACKGROUND OF THE STUDY

The contribution of the construction industry to sustainable economic growth and development

of a nation is very significant (Musa et al., 2010, Ogunsemi, 2006, Moavenzadeh and Rossow,

1976). Apart from the fact that the construction industry plays a major contribution to Gross

Domestic Product (GDP) and employment creation (Danso et al., 2011), it also provides the

basic infrastructure needed to accommodate the inputs of all other sectors of the economy

(Danso et al., 2011, Oforeh, 2006, Babalola, 2006). Clearly, the activities of the construction

industry, particularly, the execution of construction projects and the implementation of

infrastructural development projects require the services of built environment professionals

(BEP) as well as engineering professionals mainly; Quantity Surveyors(QS), Architects,

Planners, Valuers, Project Managers, Construction Managers, Engineers, Facility Managers and

Builders (Musa et al., 2010). According to Musa et al., 2010 and Oladapo, 2006, these

professionals are traditionally responsible for pre-contract planning services (i.e. project design,

production of tender and contract documents and selection of suitable contractor etc), contract

planning services (including project supervision and management, claims management, etc) and

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post-contract planning services (including project closure, commission, maintenance and facility

management).

Within the remits of these professional practices and services, Quantity Surveying Practice

(QSP) plays a critical role in planning, managing and controlling project cost, and the QS is

instrumental in relating and relaying project cost information to the client and other project

parties including contractors and other professionals (Adebola, 2006). Right from conception,

through the design and construction stages and indeed throughout the life of the project, the

consultants and other stakeholders rely strongly on reliable cost information from the QS in order

to discharge their contractual and technical obligations in a professional and objective manner

(Musa et al., 2010).

In spite of the tremendous role that the QS plays on the project team to ensure successful

delivery of projects within budget, the remuneration compensated to the QS stands accused of

not being able to commensurate the efforts and services rendered by the QS compared to the

other project professionals such as the architects and/ engineers (Oladapo, 2006 ). When looking

at other professionals, the architects’ fees increased with 16.9 % ( average over the different

categories) and civil/structural engineers have increased since 1992 by 13.7% ( average over the

different categories) (ASAQS, 2002 and Cruywagen & Snyman, 2005). This deficiency is as a

result of the apparent lack of homogeneity in the pricing of QS services and the lack of

transparency in the traditional process used in gauging consultancy fees of project professionals,

particularly, the QS (Grosskrurth, 2008). In attempt to address such deficiencies, a study

15

designed to develop a generic framework to aid in the pricing of QS services is timely and

necessary (Commonwealth of Australia, 2008 and ESCAP, 2008).

1.2 STATEMENT OF THE PROBLEM

At the turn of the 21st century, globalization has necessitated many construction firms and

practicing consultants (professionals) to position themselves in the wake of competitive business

environment (Anago, 2006 and Meyer, 2009 ). This global-wake of competition has prompted

the quantity surveying professionals (QSP) to offer competitive professional pricing to their

clients without losing sight of market forces (McGaw, 2007 and Cruywagen & Snyman, 2005).

That is, the pricing should be set within the purview of perceived risk factors to avoid the

obvious tendency of overpricing ( which would cause rejection of bids) and under-pricing

syndrome (which would affect profitability and future survival) ( McGaw, 2007, Cruywagen &

Snyman, 2005).

A recent empirical study by Adendorff et al. (2012) strongly highlighted the pricing challenges

confronting built environment consultant for that matter quantity surveyors that consultants in

the built environment are not remunerated for the actual services rendered to clients; there is

inadequate remuneration for consultants in the built environment; developers and employers

using the services of consultants of which the QS is inclusive in the built environment for no

price paid (Chinyiou, 2011); Clark (2012) observed that clients use the services rendered by built

environment consultants to their benefits and do not offer payment for the price of their services.

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Traditionally, Quantity Surveyors and other professionals have depended on the recommended

range of professional fees published by the various professional and regulating bodies such

Ghana Institution of Surveyors (Awal, 2010). Many authors have frequently accused the

published professional fees rates of inability to achieve value (Cruywagen and Snyman, 2005).

Despite the perceived easy way of accessing and utilizing such published professional fees rates

(PPFR), the PPFR stands accused of being outdated, as in many instances those in charge are

unable to update the rates frequently (McGaw, 2007, Cartlidge, 2009 and SACQSP, 2010).

Sadly, professionals who do not depend on the PPFR fix their professional rates arbitrarily

without any basis, and the tendency of over-pricing and under-pricing poses potential threats.

Within the developed world economy, significant researches have been enunciated, and recent

reports have revealed evidences in technology-based advancements and computerized pricing

models(softwares) of gauging consultancy services( Musa et al., 2010 and Oladapo, 2006).

Conversely, in developing countries, a potential lack of apposite and reliable quantity surveying

consultancy pricing frameworks continue to present challenges to practicing consultants. To

remedy this situation, and the need to lessen operational risk, pricing risk and financial risk

associated with professional (consulting) practice has sparked the interest of many academics,

policy-makers as well as practitioners the world over to explore alternative pricing frameworks

to aid consultants in gauging professional fees rate (Nagy et al., 2006 ). There is strong evidence

that suggests there is no scientific process or method for the pricing of consultancy services

(Amstrong & Green, 2011). It is also believed that the current practice of professional bodies

setting the fee (pricing) levels arbitrarily has led to the underpricing or over pricing of

consultancy services (Department of Finance, 2011). Consultancy firms for that matter QS firms

17

have been rendered bankrupt as a result of this practice by the setting of arbitrary fees in which

professional members do not have much input (McGaw, 2007). In a free market economy where

demand and supply determine price levels, it is incumbent that consultancy service providers be

given the needed opportunity to set their own price with their clients (Porter, 2008). This will

reflect the appropriate equilibrium or convergent of demand and supply (Smith, 2000).

Ofori (2012) in a comprehensive study on the development of the construction industry in Ghana

identified multifarious problems confronting consultants which include low level of fees, which

thwarts the development of their technical support system; and insufficient operating cash flow.

It is clear from the work of Ofori (2012) that the price (fees) that consultants for that matter QS

consultants receive in Ghana are not sufficient to keep them in business as indicated clearly by

the study that consultants for that matter quantity surveyors are experiencing problems with

operating cash flow. Unfortunately, the study conducted by Ofori (2012) does not suggest

modalities for improving the pricing of consultancy services provided in the construction

industry. It is important to investigate the dynamics of consultancy services pricing which is a

vehicle for revenue generation for consulting businesses in Ghana. It will therefore be noble and

innovative to develop a generic framework for pricing quantity surveying consultancy services.

1.3 AIM AND OBJECTIVES OF THE RESEARCH

1.3.1 AIM

The main aim of this research is to explore Quantity Surveying (QS) consultancy practice in

Ghana, and to develop a generic framework for gauging QS professional consulting services

pricing in Ghana.

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1.3.2 OBJECTIVES

In an attempt to achieve the above stated aim, the following specific objectives are set:

To conduct a realistic review of quantity surveying and general consultancy practice

including the rudiments of pricing;

To explore the underlying potential challenges confronting Quantity Surveying (QS)

consultancy pricing;

To identify the key determinants (indicators) in pricing QS consultancy service practice;

To establish the relationship between the key indicators of QS consultancy service

pricing; and

To develop a qualitative generic framework (criteria) for pricing QS consultancy service

practice based on identified indicators.

1.4 JUSTIFICATION/ RELEVANCE OF THE RESEARCH

It is of no stretch of imagination that a well-developed and robust generic framework would

inure to the benefit of consultancy practitioners particularly those in the built environment (BE)

(Helmlinger, 2005 and Liang, 2008). This research has the capacity of playing several roles in

the operations of several organizations throughout the world and for that matter Ghana. Hence

there is enough justification for engaging in a research of this nature. This justification can be

viewed in the quantity surveying practice as an opportunity to receive better reward for services

rendered and prices that commensurate the services rendered by quantity surveying (QS)

professionals. On a typical project initiated by a client, the architect renders services such as

preliminary design, detailed design and costing, drawings and specifications; the quantity

surveyor (QS) renders services such as feasibility study, detailed design and costing, tender

19

process and contract award, bills of quantities (BOQ), budget, contracts, planning, personnel

control, materials control and equipment control and the engineer renders services such as

detailed design and costing, tender process and contract award, bills of quantity (BOQ), contracts

and planning (Murray et al., 2001).

From the revelations of Murray et al. (2001), it can be seen that the services rendered by the key

consultants viz: the architect, the quantity surveyor (QS) and the engineer; the quantity surveyor

(QS) provides ten (10) services toward the successful implementation of the project; the architect

provides four (4) services and the engineer provides seven (7) services to the client. In some

instances, quantity surveyors (QS) manage the tender and documentation processes as well as

contract administration of engineered projects which are seen as the preserve of engineers. A

typical example is the road sector project implementation in Ghana where the QS manage all the

contract administration aspect of road projects at the Ghana Highways Authority and the

Department of Feeder roads in Ghana. In the light of the above exposition, it can be realized that

the pricing of services rendered by consultants will put the quantity surveying (QS) practitioners

in a better position and subsequently place the profession high on a pedestal among other

consultants in the built environment.

The development and acceptance of a generic framework for pricing in quantity surveying

practice will ensure the survivability of the quantity surveying consultancy practice in Ghana.

This is because professionals will not underprice to make loses leading to bankruptcy and over

price to lose customers/ clients. Similarly, a generic framework for pricing will inure to the

benefit of the client as they will pay consultants for services rendered towards the successful

20

implementation of the project and subsequently know the actual cost that will be incurred on

consultancy services. Consultancy cost is one of the factors that scare potential clients from

approaching the consultancy desk as a result of their lack of insight into consultancy costs for

that matter price but a well-developed and robust pricing framework for quantity surveying

consultancy pricing will be a panacea to this canker bedeviling the QS profession.

Furthermore, there is enough justification for a research of this nature as the government and

MDAs are concerned, as this framework will aid them in the planning of infrastructural projects,

estimation of the actual contribution of quantity surveying practice as a construction sub-sector

to GDP. A generic framework will aid tax authorities such as the Ghana Revenue Authority in

the determination of the tax obligations of consultants. This is because the framework will help

them to identify the services rendered on a particular project and subsequently, the pricing model

will help them to determine the quantum of income consultants receive for taxation purposes.

Finally, the justification for this research as far as the academia is concerned lies in the fact that

the literature review will serve as a knowledge gathering exercise on consultancy services and

pricing which are scattered in different writings in to one solid body for the development of the

consultancy industry especially quantity surveying practice which will enhance teaching and

learning as far as lecturers and students are concerned in universities and polytechnics.

1.5 SCOPE OF THE RESEARCH

The research study captured majority of services rendered by quantity consultancy practitioners

for the appropriate pricing of services (CIDB, 2005, Economic Commission for Africa, 2001 and

Jaatmaa, 2010). In particular, this research will focus on the pricing of quantity surveying

21

consultancy services (QSCS). The QS practitioners form a very crucial part, and play crucial

roles in the delivery of construction projects hence the focus on the QS practitioners is of much

vitality. Geographically and contextually, this research study would focus on registered quantity

surveying practitioners operating in Accra, the capital city of the Republic of Ghana. The

concentration of the study in Accra emanates from the fact that construction activities are highly

skewed towards Accra (c.f. Ahadzie, 2007). Similarly, there are forty-five (45) QS firms

representing 86.5 per cent of QS firms located in Accra out of a nationwide numerical strength of

52 QS firms (see for instance GhIS, 2012, 43rd Annual General Meeting report).

1.6 RESEARCH METHODOLOGY

In order to conduct a thorough and a robust research, the aim and objectives of the research was

addressed by adopting the appropriate epistemological and positivist philosophies which led to

the adoption of the quantitative approach to aid the collection of appropriate data and

subsequently the analysis and interpretation of the findings. An extensive and elaborate literature

review was conducted to identify the existing body of knowledge within the purview and remit

of the research to expand and reinforce a thorough understanding of the current pricing milieu as

well as the quantity surveying practice environment. The theoretical framework concentrated on

the theory of pricing and the various factors that affect pricing and formulation of hypothesis in

which the dependent variable(DV) was mainly pricing levels and the independent variables(ID)

were the various factors that affect pricing levels consisting of: value of a product or service,

affordability, the government, media action, pressure group, seller’s profit, customer’s intrinsic

value, customer’s affordability, objectivity, failure, success, image, pricing strategies, cost,

profit, demand, competition, time taken to solve the problem, materials used on the project, good

22

financial control system, record of past project costs, accurate forecast of future cost, production

of timely reports, finance, technical, experience, duration, capacity, reputation, business

development, materials, labour/support staff, capital/plant, entrepreneurial and managerial

talent/consultancy, associated business risks, financial risks, market related risks, logistical and

infrastructure risks, managerial and operational risks, technological risks, organizational and

societal risks, legal risks, regulatory risks, political risks, force majeure risks, personal income

tax, VAT/NHIL, corporate tax, profit tax, local rates, property tax, input prices, inflation,

production shortfall, effects of input market, government policies, international trade and trade

barriers.

The quantitative approach was used to collect data from the quantity surveying (QS)

practitioners in Ghana. In this vein, structured survey questionnaire was the main instrument

used. The research philosophies adopted enable statistical tools such as factor analysis, chi-

square test and relative importance index to be used in the analysis, interpretation of data and

discussion of results culminating into the development of an empirical framework for gauging

QS consultancy services pricing. The aim of factor analysis is to reveal any latent variables that

cause manifest variables to covary (Costello and Osborne, 2005), and factor analysis is a

collection of methods used to examine how underlying constructs influence the responses on a

number of measured variables (DeCoster, 1998). The relative importance index (RII) is used to

rank identified factors according to their place value or influences on the delivery of projects.

This is to identify the significance of the identified factors or variables via RII to the

development of a generic framework for QS consultancy services pricing.

23

1.7 LIMITATIONS OF THE RESEARCH

This research has its own limitations just like any other research in its conduct. It is envisaged

that the limitations of this research will be:

The effect of sampling and measurement errors which might affect the collection of data

and the kind of analysis to be carried out and the conclusions drawn;

Only published literature will be used in the analysis and review of literature; and

The analysis and conclusions of this research were based on data collected from

respondents by using questionnaire.

1.8 ORGANIZATION OF THE RESEARCH

This research has been divided into seven (7) independent interrelated chapters. Chapter one

contains the general introduction and background to the research. The problem has been

presented and the research justified. The research aim and its specific objectives, the scope and

limitations were also included. Chapter two dealt with theoretical framework which led to the

construction of cogent hypotheses for the research. The chapter consists of an elaborate review

of various pricing theories spanning over some applicable fields such as economics, marketing

and accounting. The independent variables(ID) used for the development of the theoretical

framework include: value, affordability, pricing strategies, profit, cost, materials, time taken to

solve problem, risk, taxation environment, overheads, inflation and input prices. The literature

review will be covered in chapters three which will consist of general overview of the

consultancy business, models for pricing professional consultancy practice and chapter four will

revolve round general overview of quantity surveying practice including its history and various

stages of development, services rendered, key determinants (indicators) in pricing Quantity

24

Surveying (QS) consultancy practice and the challenges confronting Quantity Surveying (QS)

consultancy in Ghana.

Chapter five consisted of the methodology adopted for the research viz: research philosophy,

sample population, sample size determination, sampling technique questionnaire design and

administration and statistical tools. Philosophically, the position of the research ontologically

will be that of objectivism. It is clear that the core issues that significantly affect the pricing of

consultancy services are real and not the inventions of the researcher. Chapter six consist of

analysis and discussion of results, and chapter seven will be devoted to Generic Framework

which will consist of model (pricing formula) development for gauging QS consultancy service

in Ghana. Chapter seven dwelt on conclusion and recommendations, which will consist of

review of research objectives among others. The simplified version of the conceptual framework

of the research process for the study is demonstrated in figure 1.1 below.

25

Figure 1.1: Conceptual Framework of the ResearchOrganization

Chapter

One

General Introduction

Background, Problem Statement,

Aim, Objectives, Justification,

Scope, Methodology, Limitation.

Chapter

Two

Theoretical Framework Concept of Pricing and Production, Risk,

Taxation, Inflation etc.

Hypothesis Formulation

Chapter

Three

General Overview of Consultancy

Business Types of Consultancy Business,

Consultancy Services, Pricing

Methods

Chapter

Four

General Overview of QS Practice

History and Development of QS

Profession, Professional Bodies,

Services Rendered, Pricing Methods

and key Indicators

Chapter

Five

Research Methodology Research Philosophy, Sampling

Frame, Instrument Design and

Administration, Tools for Statistical

Analysis

Chapter

Six

Analysis and Discussion of Results

Development of generic pricing

framework

Chapter

Seven

Conclusion and Recommendation Review of Objectives, Findings,

Further Research.

26

CHAPTER TWO

THEORETICAL FRAMEWORK

2.0 INTRODUCTION

This chapter delves in to the theoretical framework on pricing leading to the formulation of

hypotheses for the research. It is pertinent to look at some of the existing theories for pricing

goods and services. In this light hypotheses have been formulated as a result of the synthesis of

literature review on these pricing theories for testing to either prove their falsification. The

chapter also looks at the concept of production and subsequently the elements of price

determination.

2.1 Concept of Price and Value

Price is the amount for which product, service or idea is exchanged, or offered for sale regardless

of its worth or value to potential purchasers (Cannon, 1998), price is the value (or its equivalent)

placed on a good or service (Farese et al., 1991) and according to Perreault and McCarthy, 2002,

“price is the amount of money charged for “something” of value.” The key to pricing is

understanding the value buyers place on a product (Pontiskoski, 2009). Value is a matter of

anticipated satisfaction from a product (Zhilin & Robin, 2004, Grahame & Mark, 1997). If

consumers believe they will get a great deal of satisfaction from a product, they will place a high

value on it (Thompson, 2005). They will also be willing to pay a high price for it. A seller must

be able to gauge where a product will rank in the customer’s estimation- valued much, valued

little, or valued somewhere in between (Brand, 1998, Grehalva, 2004, Tommie et al., 2008). This

information can be taken in to decision. The seller’s objective is to set a price high enough for

27

the firm to make a profit and yet not so high that it exceeds the value potential customers place

on the product (Farese et al., 1991).

From the foregoing, therefore, it stands to reason that the ability of price setters to gauge the

value customers place on a good or service is vital in determining a workable price for goods and

services. Thus it is appropriate to hypothesize that:

Hypothesis 1: A significant key to successful pricing is dependent on: (H1a).value of a product

or service and (H1b). affordability

2.2 The Just Price

Underlying the discussion about price is the notion of the ‘fair’ or ‘just’ price, the price that

could be called correct on the basis of social considerations. A great deal of government,

pressure group and media action and discussion is geared towards achieving just prices, but it is

seldom fully appreciated how sensitive this concept is to the point of view of those discussing it

(Allison et al., 2011). To the seller a fair price is probably the amount needed for their offering in

order to make reasonable profit (Canonn, 1998). The notion of a reasonable profit itself has to be

discussed, as there are different approaches to this. To the customer a fair price probably refers to

some general idea of affordability allied to some sense of intrinsic value, with previous

experience a contributory factor. In entering into the exchange both are seeking some degree of

profit from it. Sellers want some excess income over costs, while buyers want an excess of

satisfaction from goods or services over the satisfaction from holding on to their money or

purchasing something else. In determining pricing policies the company needs to understand

both costs involved and alternatives open and the responses of the different groups and the value

they place on the goods or services (Canonn, 1998).

28

From the foregoing, it is therefore clear that both the seller and the buyer want to arrive at a fair

price which they will refer to as correct from the social point of view. At the same time, the

seller wants to make some excess money representing his profit for engaging in a business

venture and buyers would refer to a price as fair if they can afford the goods or services and

derive some satisfaction which is of intrinsic value. Hence it has become necessary to

hypothesize that:

Hypothesis 2: The achievement of just price levels is significantly dependent on: (H2a). the

government. (H2b). media action. (H2c). pressure group (H3d). seller’s profit. (H3e).

customer’s intrinsic value. (H3f). customer’s affordability.

2.3 Importance, Objectives and Goals of Pricing

Price is an important factor in the success or failure of a business because it helps establish and

maintain a firm’s image, competitive edge and profit. Many customers use price to make

judgments about products (Amstrong & Green, 2011, Rajneesh & Kent, 2003). Sometimes price

is the main thrust of a firm’s advertising strategy (Farese et al., 1991). Pricing objectives might

be: to increase profitability, to thwart the efforts of competitors to accept us as a price leader, to

restore order in a chaotic market, to increase market share and to smooth the seasonality of

purchases (Dwyer & Tanner, 2006). According to Farese et al. (1991), pricing objectives

“include share of the market, achieving a return on investment and meeting competition.” Pricing

objectives consist of profit oriented (i.e. target return and maximize profits), sales oriented (i.e.

sales growth and growth in market share) and status quo oriented (i.e. meeting competition and

non-price competition) (Perreault & McCarthy, 2002).

29

From the foregoing, it can be realize that objectivity is one of the critical pillars of price setting

and it plays a key role in the judgement of a firm’s image, success and failure. As a result it can

be hypothesized that:

Hypothesis 3: The role of the firm in setting price levels is significantly dependent on: (H3a).

objectivity. (H3b). failure. (H3c). success. (H3d). image.

2.4 Pricing Strategies

The formulation of a sound pricing strategy requires consideration of demand and cost factors in

a competitive environment (Robert, 2001, Andreea, 2011). A price strategy consists of a specific

approach to achieve the pricing strategies (Ashok et al., 2008, Ioannis, 2002 and Ashok et al.,

2008). Pricing strategies may include: to gain market share by concentrating on small users

served by full-line, to build customer trust by reducing prices on products having highly visible

cost reductions, to win customers from competitors by bundling at a low total price, including

items not carried by rivals (Dwyer & Tanner, 2006). Steps in setting price include: determine

pricing objectives, study costs, estimate demand, study competition, and decide on pricing

strategy and set price (Farese et al., 1991).

Basic pricing strategies include: “cost-oriented pricing: calculate first the costs of acquiring or

making a product and their expenses of doing business. Then they add their projected profit

margin to these figures to arrive at a price (Patsula, 2007, McTaggart & Kontes, 1993, Treacy &

Wiersema, 1993). It include markup pricing that is difference between the price of an item and

its cost; and cost-plus pricing that is all costs and expenses are calculated and then the desired

profit is added to arrive at a price ( Holland, 1998 and Ball, 2011). Demand oriented pricing is

30

used to determine what present consumers are willing to pay for given goods or services

(Patsula, 2007, KIPPRA, 2010, Cicchetti & Haveman, 1972). The key to using this method is the

consumers’ perceived value of the item, and competition pricing is studying competitors to

determine the prices of products (Gale & Swire, 2006; Lewis & Shoemaker, 1997 and Essel,

1996). Sales, costs and expenses determine a firm’s profit (Kaplan, 2006, Roberts et al., 2011).

As a result businesses constantly monitor, analyse and project prices and sales in the light of

costs and expenses (FTC, 2005; CAS, 2003; Burnett, 2008). Businesses improve a product by

adding more features or upgrading the materials used in order to justify a higher price (Farese et

al., 1991).

From the foregoing, therefore it can be seen that there are various strategies of determining price

and fundamental to the success of every pricing strategy is the accurate determination of costs

and expenses and key in every pricing strategy lays demand and competition. Hence it can be

hypothesized that:

Hypothesis 4: The fundamentals of every pricing strategy of a firm depend on:

(H4a). Cost. (H4b). Profit (H4c). Demand (H4d). Competition

2.4 Project Pricing

Another service industry which can be used to illustrate a further problem of setting prices is

pricing projects, which are a form of the special (one-off) product pricing issue (IMP, 1982). In

the consultancy industry, many systems companies have to establish pricing strategies (Brodie,

2009). From the selling company’s perspective the low-risk pricing policy on a ‘time and

materials basis’, whereby the time taken to solve the problem is charged to the client at an agreed

31

daily rate together with any materials used on the project (Jenkins, 2006). However, this low risk

on the part of the selling company means that the customer has the high risk and is potentially

signing a blank cheque to the supplier (OFT, 2008). Therefore as a way of differentiating

themselves from competition some companies started to quote fixed prices for solutions to client

problems (Patsula, 2007). For this pricing strategy to be successful, the company needs to have a

very good financial control system which should be organized to provide accurate information

on a project basis (Rodin-Brown, 2008). The control system should allow managers to learn

about past project costs and hence to be able to forecast more accurately in the future (The World

Bank, 1998). The system should also produce timely reports on current projects compared to

plan so that managers can make decisions and take action on any projects which show signs of

overrunning (IFC, 2007). This means that plans and actual costs have to be capable of being

compared against achievement milestones, not just expenditure levels (Flyvbjerg et al., 2003).

In the construction industry, this problem of pricing and cost control is also a major concern to

customers and it is particularly so when a number of different suppliers ( for example, the actual

building company, architects, quantity surveyors, specialist contractors) are involved in any

major contract (Haider, 2009). Out of this complexity, a new service has been developed,

particularly by quantity surveyors who are expert in construction measurement, which provides

the client with ‘total project management.’ This service should ensure that the client gets what

was wanted for the fixed cost which was agreed at the start of the project, and thus the project

manager resolves any cost overruns and frees the client from any detailed involvement in the

project. Clearly, the client pays a fee for the service provided, but it is a good example of the

complexity of pricing leading to a marketing opportunity for a new product (Ward, 1994).

32

From the foregoing it can be seen that the pricing of projects for that matter construction projects

is beset with some complexities and risks to both the client and the seller of the consultancy

service. In this regard pricing normally takes in to significant consideration the time taken to

solve problems, and materials used on projects. For project pricing to be successful it is pertinent

to take serious note of the financial control system, record of past costs (cost history of projects),

cost forecast and timely delivery of deliverables. As a result, it is therefore of much significant to

hypothesize that:

Hypothesis 5: The successful criteria for consultancy services pricing is dependent on: (H5a).

time taken to solve the problem. (H5b). materials used on the project. (H5c). good financial

control system. (H5b). Record of past project costs. (H5c). accurate forecast of future cost; and

(H5d). production of timely reports.

2.5 Bid Pricing

Bid pricing means offering a specific price for each possible job rather than setting a price that

applies for all customers (Meissner & Strauss, 2010). Bid pricing is more complicated; a big

problem is estimating all the costs that will apply. A complicated bid may involve thousands of

cost components (Reguant, 2011 and Koomey et al., 2009). Further, management must include

an overhead charge and a charge for profit. This system does not allow the seller to set a price

based on the precise situation and what marginal costs and marginal revenue are involved

(McAfee, 2008, Nwokeji, 2007, Anderson & Ross, 2005). Bids are usually based on purchase

specifications provided by the customer. Sometimes, the seller can win the business, even with a

higher bid price, by suggesting changes in the specs that save the customer money (Perreault &

McCarthy, 2002). Competitive bidding is very common in government and quasi- public

33

institution (schools, hospitals, social services agencies) largely to satisfy external constituencies

that otherwise have difficulty auditing performance (Kosar, 2011 & Keidel, 2007). Competitive

bids provide some assurance of input efficiency (Hamilton, 2008 and IFC, 2007). A successful

bid is one that meets the goals of both buyer and seller (Dwyer & Tanner, 2006; Froeb &

McAfee, 1988).

From the foregoing, it has been demonstrated that bidding is just another form of pricing which

considers costs and competition from other bidders. Bidding takes serious and elaborate

cognizance of finance, technical capacity, reputation, experience, and duration and business

development of firms in to consideration. These are therefore fundamental to every bidding

process. Bidding is therefore not a pricing strategy for every product or service; it is mostly

suitable for customized projects for governments and quasi-public institutions. In this light, it is

necessary to hypothesize that:

Hypothesis 6: The success of a bid price is significantly dependent on: (H6a). financial capacity,

(H6b). technical capacity, (H6c). experience, (H6d). duration, (H6e). reputation, (H6f). business

development, and (H6g) Profit and overhead

2.6 Production and Pricing

The basic principles of price determination are not different for factor services than for products

(Porter, 2008 and Leamer, 1995). In the perfectly competitive factor service markets, demand

and supply establish the equilibrium factor price which equates quantity demanded to quantity

supplied (Piermartini & Teh, 2005). Other things equal, the greater the demand for a service or

the less the supply of it, the higher its market price (Lee et al., 1997 and Trostle, 2008). Factor

34

services encompass both material services such as capital equipment or land and personal

services of human beings that is labour and entrepreneurship (Kiriga et al., 2002 and Kapila,

2006). The quantities and prices of the factors involved in the selected technology determine the

cost of the firm, cost stems from the production of a good or service by the business firm

(Swanson & Guttman, 1996 and Cohen & Bailey, 1997). Activities such as property valuation,

land surveying, designing a machine or a building, developing software, editing manuscripts,

teaching, providing consultancy service and selling bananas must all be regarded as production (

Opoku-Afriyie, 2007).

Production activity involves conversion or transformation of certain objects or the services

provided by objects or persons called factor inputs or factors of production into objects or

services called output (Chidambaram et al., 1999). Production is the combination of factors such

as land, because raw materials and auxiliary materials do not transform themselves, some human

intervention is needed to take place, labour, is the factor which provides the human intervention

(c.f. Lynden, 2000; Kefela, 2010 and Opoku-Afriyie, 2007). Other forms of human intervention

required for production are referred to as entrepreneurial talent and managerial skill (Papulova &

Makros, 2007 and Ogechukwu & Latinwo, 2010). These provide mental intervention, notably,

leadership, supervision, planning, coordination and control of production activities. In converting

raw and auxiliary materials into output, various tools, machines, equipment, other physical

implements and often buildings are required; these are collectively referred to as capital.

Firms are interested in output in as much as it contributes to revenue and through profit. The use

of factor inputs, as indicated on the right-hand side of the production function involves cost as

35

the inputs must be paid for. Thus firms are also concerned about the cost of production that is the

value of factor inputs used in as much as it affects profit. The cost of production can be

expressed as the cost function as follows: K= K1V1 + K2V2 + …………. + KnVn, where K is the

total cost of production and K1, …………… Kn, and V1 , ……..Vn, the prices of the inputs

respectively (Opoku- Afriyie, 2007).

In principle, pricing is an important issue among the various activities that the consultancy

industry undertakes, the transfer of knowledge and expertise relating to how to do various tasks,

how to measure and how to communicate the fact and the extent of it to the public. Each of these

is of some potential benefit, achieved only at a cost and pricing in the consultancy industry

mediates between these benefits and costs (Young et al., 2003). The attitude will gradually shift

back to that of one where firms are willing to price higher value services (like consultancy

services) at a higher rate. Business owners are willing to pay more for services that have positive

impact on their businesses even now. Pricing depends on value perceptions of the client, many

firms are being less “fee aggressive” because their clients are being approached by more firms

selling on price (Lewis, 2011).

Firms that have successfully implemented value pricing throughout their practice do so by:

Designing a package deliverable whose value can be understood by the client.

Pricing the deliverable in a manner that considers the market value based on

comparables or by considering the value that is inherent in its utility to the specific client

situation.

Designing the production of the deliverables so that it can be produced profitably (Sinkin

& Putney, 2011).

36

Price trends for different products and services must be measured and indices calculated before

the current prices can be converted in to fixed prices. The services producer price index (SPPI) is

a producer price index for services that aims to measure price trends in industries that produce

business services. The prices may differ from one area to the next especially regarding strategic

issues, where the price can vary as much as 50 percent in comparison with other areas.

Sometimes, a customer may order services within a certain area of activity. There are several

components that affect the price of a service, which can vary considerably depending on the

company. The following components may affect the price of the tender:

How many consultants does the service require?

Which categories of consultants does the service require?

Which areas of activity (also known as “service line”) does the service involve?

How long will it take to perform the service?

How extensive is the service? Geographically? Resource – Demanding?

Who is the customer? (Larsson, 2007).

The variation of price can be arbitrary (we disregard the fact that price changes cannot actually

be smaller than a certain quantity- a ‘tick’). In order to describe the random process X for which

the result is a real number, one uses a probability density P( X ), such that the probability that X

is within a small interval of width dx around X= x is equal to P(x)dx. The mean or the expected

value of X, which we shall note as m in the following, is the average of all possible values of X,

weighted by their corresponding probability: m = ∫ xP(x)dx ( Bouchaud & Potters, 2003).

37

Drawing on from the above, the production of firms involves the combination of factor services

of which the consultancy industry is of no exception. The prices and quantities of these factor

services involved in a selected technology determine the cost incurred by the firm arising out of

production of goods and services. The combination of these factors also known as factor inputs

by firms result into objects or services called output. These factor inputs comprises of: materials,

labour (Support staff), capital (plant) and entrepreneurial and managerial talent (consultants).

The motivation for firms (consultancy firms) for the combination of input factors is to make

profit, and this act of input factor combination gives rise to cost. Finally the use of probability

theorem and indices for services provision can lead to the determination of consultancy pricing

which is the combination of input factor costs and profit.

2.7 The Concept of Risk

Risk is measurable uncertainty (likelihood) for something to occur that lets projects fail,

decreases their utility or increases their costs and duration. Further, to know certain risk alone

does not suffice, risk has to be weighed against the benefits, should the stated goals be achieved

and the activity is successful (European Union, 2010). In the construction industry, risk is often

referred to as the presence of potential or actual threats or opportunities that influence the

objectives of a project during construction, commissioning, or at time of use (RAMP, 1998).

Risk is also defined as the exposure to the chance of occurrences of events adversely or

favourably affecting project objectives as a consequence of uncertainty (Al-Bahar, 1990).

Risky events can be characterized by their magnitude, scope or spread, frequency and duration,

and their history – all of which affect vulnerability (Heitzmann et al., 2002). Risks can be

38

classified as idiosyncratic risks that usually affect individual firms and covariate risks that affect

many firms simultaneously(e.g. major drought or floods, fluctuating market prices) (Skees et al.,

1999). Risk is the possibility that an event will occur that will potentially have a negative impact

on the achievement of a firm’s performance objectives (Boisnier & Chatman, 2002). Expected

losses from risky event include both tangible and intangible losses, and short and long-term

losses (Jaffee et al., 2008). It is critical to consider losses in terms of how they affect short term

outcomes versus livelihoods and outcomes in the longer term (IFC, 2007 and Morduch & Haley,

2002). Thus, in addition to examining whether risks are idiosyncratic or covariate, it is important

to examine if they impact performance flows (e.g. movement of goods and services, incomes)

and/ or also damage assets. The expected losses are a function of probability of a risky event

actually occurring and the exposure to that risky event i.e how performance outcomes might be

influenced if the risk materializes (Jaffee et al., 2008).

From the foregoing contextualization of risk, it can be seen that risk is the occurrence of any

event which can affect almost all the facets of business activities and it is probabilistic in nature

and can cause serious changes to activities such as price setting, performance and maintenance of

quality standard.

2.7.1 Risk and Price

Price uncertainty and price volatility are problems (Dehn, 2000; Dana, 2005 and Fischer & Orr,

1994). In analyzing price risk issues, it is important first to differentiate between direct risk and

indirect risk (Dana, 2005 and Inderst, 2009). Direct risk is the impact of price on specific

commercial transactions: purchase of goods, sales of goods, processing of goods, and lending

39

which supports any of these activities (Andam, 2003; European Union, 2010 and Dana, 2005).

Direct price risk is only experience by market participants who are engaged in these transactions

(Dohring, 2008; Dana, 2005 and Papaioannou, 2006). Direct risk can be classified as financial

and physical (Malkiel, 2003 and Santomero, 1997). Financial risk is the financial impact or

profit/loss position of a producing entity. Financial risk can be quantified by: net risk position, it

can be ‘long’ or ‘short’. A long position describes the commercial position where a fixed priced

inventories or purchase commitment without having equal and offsetting fixed sales contracts

(Dana, 2005 and Jaffee et al., 2008). The risk of long position is that prices will fall below the

level of the purchase price committed (Rappaport, 2005; Elwell, 2011and McCue & Belsky,

2007).

A short position is the opposite scenario. A price level is the price basis at which the inventories

are valued or purchased/sales commitment made (Dana, 2005; Treacy & Wiesema, 1992 and

Beechy & Conrod, 1998). The price level of the risk is expressed in terms of the local price

basis, and if applicable, the corresponding international market or exchange price basis (Kojima,

2009 and Dana, 2005). The difference between the two prices is the cost of getting the product or

service to the market (processing, local transportation, insurance, freight), and a premium or

discount for cash price (Tseng et al., 2005, McAfee, 2008, Micco & Perez, 2002). The terminal

market price is referred to as basis risk (Taylor, 2011 and Huang & Wang, 1997). Volume of

inventories and/or purchase commitments; duration, the time period for which the entity is ‘long’

or ‘short’ and exposed to price movements which may be unfavourable ( Stevenson & Bear,

1970 and Dana, 2005). Physical risk is different from financial risk because it focuses on the

trade of the physical product and issues of volume, quantity, timing and delivery (UNEP, 2004

40

and Morrison et al., 2009). Price risk falls within the category of financial risks. Indirect risks are

the knock-on effects of direct risk felt in the system. Indirect impacts occur when direct price

risk problems experienced at one level create uncertainty or economic and financial instability

(Dana, 2005).

From the above exposition, it is crystal clear that business activities encounter situations which

are classified as direct risk and indirect risk. Among these, the direct risk which has a component

financial risk significantly impacts on price levels. In this case it will be appropriate to posit that:

Hypothesis 7: Consultancy services price levels are dependent on financial risks.

2.7.2 Types of Risk

Market related risks exist for inputs and outputs and for the critical services which support

supply chains such as finance and logistics (Jaffee et al., 2008). Generally, market risks are

related to issues which affect price, quality, availability, and access to necessary products and

services, (Stader & Shaw, 1998 and Jaffee et al., 2008), of these market risks are typically the

most volatile (Buehler et al., 2008). Logistical and infrastructural risks are related to logistics

and infrastructure that affect the availability and timing of goods and services, energy and

information (Jaffee et al., 2008; Tseng et al., 2005 and Malhotra, 2005). Thus logistics related

risks are closely related to price and market related risks, including the driving decisions on

product lines and input use which can affect future production, processing, marketing decisions

(Jaffee et al., 2008; Ioannis, 2002 and Wind, 1981). Managerial and operational risks are closely

associated with human judgment and response- i.e. errors and actions and inaction, commission

and omission (Flouris et al., 2010). These risks are mostly associated with productivity

41

reductions, and how quality of products and unreliable delivery of inputs and outputs and support

services (Jaffee et al., 2008).

Demand risk relates to potential or actual disturbances to flow of product, information and cash

emanating from within the network between the focal firm and its market (Braithwaite, 2003;

Wilding, 2007; IMP, 1982). In particular, it relates to the processes, controls, assets and

infrastructure dependencies of the organization downstream and adjacent to the focal firm

(Mungofa, 2009; Belkin, 2008; Braithwaite, 2003 and Teece et al., 1997). Supply risk is the

upstream equivalent of demand risk; it relates to potential or actual disturbances to the flow of

product or information emanating within network upstream of the focal firm. Environmental risk

is associated with external and, from the firm’s perspective, uncontrollable events. The risks can

impact the firm directly or through its suppliers and customers (Braithwaite, 2003).

Technological risks are all those risks that lead to non-completion, underperformance or false

performance of the procured good and service (Edler, 2010 and Pissas, 2007). The risk lies in

technical characteristics of the service or product in its production and thus originates in the

supply side (European Union, 2010 and UNCTAD, 2008). This risk appears in particular

relevance in procurement of products in the fluid phase (European Union, 2010 and Barringer,

2003). Organizational risks are all those risks of procurement failing or under- delivery for

reasons situated within the organization that procures (WTO, 2004). Societal risks are those

related to a lack of acceptance and uptake by the users of the new or changed service delivered

within society (European Union, 2010 and WHO, 2003). Finally, turbulence risks- in fact

turbulence uncertainties as they are hard to predict and measure are associated with large scale

42

projects and emerge from a range of unforeseen events that lead various actors in the whole

process to reassess their priorities or change their expectations (European Union, 2010).

From the above, it is clear that there are myriad of risks facing business entities for that matter

consultancy firms from various sources such as market, demand and supply, financial, physical,

logistics, technological, organizational and societal. It is of no doubt that risks from any of these

sources will affect the price level set by consultancy firms since they operate in environment that

their business activities are related to these sources of risks. Hence it stands to hypothesize that:

Hypothesis 8: The robustness of consultancy pricing is significantly dependent on the existence

of: (H8a). Market related risks (H8b). Logistical and infrastructural risks

(H8c). Managerial and operational risks (H8d). Technological risks (H8e). Organizational and

societal risks.

2.7.3 Risks at Various Stages of Project Implementation

According to UNEP (2006) risks occurring during project implementation are: risks during the

project implementation phase- between the project concept and its implementation stage there

are several steps that require significant time and resource input. There is however, the

possibility that the project concept will never reach implementation stage on account of the

project being considered infeasible or economically unviable. Hence the project does not receive

the necessary regulatory approvals or the project fails to achieve financial closure i.e. raise the

required funds to implement the project (IFC, 2007 and UNEP, 2006). However, the probability

of delays in receiving the regulatory approvals and achieving financial closure is relatively high.

Risks during the construction phase: completion risk- the nature of risk factors associated with

43

completion being time overrun, cost overrun or completed project not being up to the required

technical specifications (Kreydieh, 1996).

The probability of time and cost overruns is pretty high and the extent of impact on account of

these is also relatively high (UNEP, 2006 and Guo, 2004). Counterparty risks- when construction

is undertaken by a construction contractor, there is a risk that the contractor does not perform as

per contract, which results in time and cost overruns (Smith, 2009; UNEP, 2006 & Haider,

2009). Risks during the operation phase include performance risk- the nature of risks associated

with performance is similar to that in the case of infrastructure projects with there being the

possibility of equipment not performing as per required standard (Harris, 2003, UNEP, 2006 and

IFC, 2007). Counterparty risk- when operations are performed and managed by a contractor

there is a risk that the contractor does not perform as per contract which may result in sub-

standard performance. Generic risks for all phases include: financial risk- fluctuations in interest

rate, currency exchange rate and inflation can affect project economics (Kreydieh, 1996; Gray &

Irwin, 2003, Nair & Yescombe, 2008). The probability of fluctuation of these factors is high and

the extent of impact is linked to the extent of fluctuation (Pirog, 2005 and Baker et al., 2008).

Legal risk- there is often problems with respect to contract enforcement as well as contract re-

negotiations in developing countries on account of a poor legal infrastructure (Samuels, 2006 and

Likosky, 2009). The probability of contractual default is high and the extent of impact is also

relatively high (UNEP, 2006). The only way of mitigating this risk is by obtaining some form of

a sovereign guarantee from the host government (Ramamurti & Doh, 2003, Bedoucha, 2010, and

Gupta et al., 2002, UNEP, 2006). Regulatory risk- even where the price is locked in through a

purchase agreement (PA) (Antolin & Stewart, 2009; UNEP, 2006; Finon & Perez, 2008), there is

44

a risk that the regulators may mandate a revised price leading to a renegotiation of the PA

(Grabel, 2002 and UNEP, 2006). Political risk- restriction on currency convertibility may restrict

the repatriation of profits. Political violence may restrict operations and result in damage to

equipment as well. The probability of occurrence of these events is relatively low but the extent

of impact is very high (Hillson & Hulett, 2004). Force majeure risk- natural catastrophes such as

floods, earthquake, etc as well as man-made events such as a war, strike etc, could hamper or

stop activities both during the construction as well as operations phase (UNEP, 2006). The

probability of occurrence of is low but the extent of impact is very high (Chomitz & Gray, 1996).

From the above, it has been clearly demonstrated that the generic risks which run through all the

phases of project implementation affect the provision of consultancy services hence the need for

their pricing. Financial, legal, regulatory, political and force majeure risks have very high extent

of impact on projects as well as consultancy pricing. In the light of this, it is appropriate to

hypothesize that:

Hypothesis 9: The level of consultancy pricing is dependent on: (H9a). Financial risk (H9b).

Legal risk (H9c). Regulatory risks (H9d). Political risk and (H9e). Force majeure risks.

2.8 Concept of Taxation

Economic growth increases the taxable capacity of a country and enables a larger sphere of the

private sector’s resources to be ceded to the government as taxes to provide public goods and

services. Many countries, therefore, depend mainly on taxation as a means of generating the

required resources to meet their expenditure requirements. These countries will likely find

45

themselves in growing fiscal imbalance when their revenue productivity falls below their

expenditure (AERC, 1998).

2.8.1 Taxation of consultancy services

Local tax liabilities originating from consultancy services contracts are often the cause of unclear

proposals and of unsatisfactory contracts. The identification and calculation of local tax amounts

are a difficult and time-consuming task for consultants with little knowledge of the tax system.

Such local taxes generally include the following: indirect taxes, that is ad valorem taxes(VAT)

on contract items for example VAT on consultant remuneration, duties on imported equipment

and supplies later exported by the consultants, for example personal computers, scientific

equipment; duties and levies on equipment imported or locally acquired by the consultants that is

treated as property of client, for example cars, office equipment and local income taxes on the

remuneration of services rendered locally(World Bank, 2002).

2.8.2 Tax System in Ghana

The tax structure in Ghana is generally composed of direct taxes, indirect taxes and international

trade taxes. For the direct taxes, the factors that produce the income are assumed to pay the

associated taxes while for the indirect taxes and international trade taxes, households or firms

that consume or import/export the taxed items are assumed to pay the associated taxes (Owusu-

Afriyie, 2009).

46

2.8.3 General Provisions under the Tax Law

Income tax is levied in each year of assessment on the total income of both resident and non-

resident persons in Ghana. With respect to resident persons, the income must be derived from

accrued in, brought into or received in Ghana. For non-resident persons, the income must be

from or accrued in Ghana. An individual is resident for tax purposes if that individual is a citizen

of Ghana, other than a citizen who has a permanent home outside Ghana for the whole of the

year; present in Ghana for a period or periods equal in total to 183 days or more in any twelve-

month period that commences or ends during the year; an employee or official of the

Government of Ghana posted abroad the year; a Ghanaian who is temporarily absent from Ghana

for a period not exceeding 365 continuous days where that Ghanaian has a permanent home in

Ghana. A company is resident for tax purposes if that company is incorporated under the laws of

Ghana; or has its management and control exercised in Ghana at any time during the year

(Pricewaterhousecopers, 2008).

2.8.4 Income and Profit Tax Legislation

Principle legislation regarding direct taxation is the Income Tax Act 592 (2000) which comprises

both Personal Income Tax (PIT) and corporate Income Tax (CIT). Recently, the Act was

amended by Amendment 622 (2002). The Act sets out tax policy as well as tax procedures. Profit

tax legislation is also part of the Income Tax Act. Profits are calculated on an accrual base.

According to the Act, tax rates on profits are differentiated accordingly into six sectors or

branches, and variate between the region in which the business operates. Companies listed at the

stock exchange are subject to a rate of 30 per cent. The highest rate for ‘other business’ reaches

out to 32.5 per cent (Romer & Romer, 2007; Witt & Lautenbacher, 2003).

47

2.8.5 The Implementation of VAT

VAT was originally established in 1995 to replace the old sales and service tax system. As the

rate was set at 17 per cent, the VAT was fiercely resisted and eventually suspended: the rate was

seen as too high, the threshold (annual turnover of 25 million cedi) was too low; the information,

campaigning and taxpayer education was too poor. After three years of reconsideration, VAT

was successfully introduced in 1998 under VAT Act 546. This time the added value of all goods

(except agriculture and basic goods) and services were taxed with a rate of 10% and a threshold

of 200 million cedi annual turnover (suppliers of goods). In 2000, a major review of the VAT

system was completed, which resulted in a tax rise to 12.5% and a broadening of the tax base by

lowering the threshold for suppliers of goods to an annual turnover 1oo million cedi( Witt &

Lautenbacher, 2003). Other than exempt goods and services, Value Added Tax (VAT) and the

National Health Insurance Levy (‘NHIL’) are charged on the following: every supply of goods

and services made in Ghana, every importation of goods, supply of any imported service. The tax

shall be charged on supply of goods and services where the supply is a taxable supply and made

by a taxable person in the course of his business. The tax shall be paid: in the case of taxable

supply by taxable person making the supply, in the case of the imported service, by the receiver

of the service (Pricewaterhousecopers, 2008).

From the foregoing, it has been realized that by the laws of Ghana, all businesses operating in the

country are obliged by the law to pay taxes. Taxes payable by firms include corporate tax,

income tax of employees, VAT/ ‘NHIL’; profit tax, property tax and local rates. Taxes form the

48

expenditures of firms as the cost of doing business and must be recovered through pricing. In the

light of the above, it is appropriate to hypothesize that:

Hypothesis 10: The level of consultancy prices is significantly dependent on taxes such as:

(H10a). personal income tax (H10b). VAT/ ‘NHIL’ (H10c). Corporate tax (H10d). Profit tax

(H10e). local rates (H10f). Property tax.

2.9. Concept of Inflation

What exactly is inflation? A persistent increase in the level of consumer prices or a persistent

decline in the purchasing power of money, caused by an increase in available currency and credit

beyond the proportion of available goods and services. Inflation occurs when the price level rises

from one period to the next (Robinson, 2007). There is an inverse relationship between the prices

of goods and services and the value of money in an economy. Other things equal, as prices rise

over time, a given amount of money will be able to purchase fewer goods and services. Inflation

has an additional effect on prices when businesses, workers and others experiencing a loss in

purchasing power attempt to adjust upward what they receive for their goods and services in

order to keep pace with their rising costs (FEWS NET, 2009).

From the exposition above we can say that a persistent increase in the price of goods and

services, and for that matter input prices for firms or consultancy service providers will cause

inflation in the economy hence prices set by firms will be affected. Hence it is appropriate to

hypothesize that:

Hypothesis 11: Price level is significantly dependent on: (H11a). input prices (H11b). Inflation

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2.9.1 Causes of Inflation

The price of any good is influenced by different market forces that can change the balance

between supply and demand (Schnepf, 2006 and FEWS NET, 2009). Many of these forces come

from domestic as well as regional and international markets. This section discusses the causes of

inflation. Production shortfall- for locally produced goods, the differences in product prices

reflect differences in local conditions of supply and demand (FTC, 2005; FEWS NET, 2009,

Ghemawat, 2006; Meijerink & Roza, 2007). In general, prices are lower in regions of surplus

production and higher in densely populated regions of deficit production. Effects of input

markets- if the cost of inputs used in production of a good increases; this can cause a rise in the

cost of production. Government policies can take many forms and could potentially cause

inflationary pressure; and international trade and trade barriers (FEWS NET, 2009).

In summary, it can be seen that price levels for that matter inflation can rise as a result of

production shortfall, effects of input markets, government policies and international trade and

trade barriers. These can cause changes in prices hence it is pertinent to hypothesize that:

Hypothesis12: Significant changes in price levels are dependent on inflationary causes: (H12a).

production shortfall (H12b). Effects of input market (H12c). Government policies; and (H12d).

International trade and trade barriers.

2.9.2 Economic Indicators of Inflation

Leading indicators are those which are believed to change in advance of changes in the economy,

giving a purview of what is going to happen before the change actually. Generally, economic

indicators of inflation are statistical data showing general trends in the economy. Those with

50

predictive value are leading indicators; those occurring at the same time as the related economic

activity are coincident indicators; and those that only become apparent after the activity are

lagging indicators. The most important indicator is the Gross Domestic Product (GDP) report

(Robinson, 2007).

2.9.3 Nominal and Real Prices

The nominal price of anything is simply its stated price; measured in the national currency. The

real price of a commodity, on the other hand is its price adjusted to reflect changes in the overall

price level. A commodity’s real price is therefore its particular price compared to the general

level of all prices. Changes in real prices are a better measure of the real economic burden or

significance of a price, than changes in nominal prices (Robinson, 2007). Nominal prices are

prices that have not been adjusted for inflation (Mills, 1996; FEWS NET, 2009, Ball & Mankiw,

1994). The nominal price is equal to the money that is paid for a unit of a good or service in the

market, at the shop (FEWS NET, 2009). Real prices are prices that have been adjusted for

inflation (Stanford, 2008; FEWS NET, 2009). Real prices hold the value of currency constant,

and allow you to compare the exchange value of a good or service in different time periods. The

most common measure of inflation is the Consumer Price Index (CPI) (Morrison & Labonte,

2008 and FEWS NET, 2009). The CPI is a measure of change in the purchasing power of a

currency. The CPI expresses current prices of a typical consumer basket of goods and services in

terms of the prices during the same period in a previous year( reference to a base year), to show

the effect of inflation on purchasing power. The CPI can be used to calculate inflation using the

following equation:

INFLATION= [(current period CPI)-(Previous period CPI)] / (Previous period CPI.

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If the information on the CPI is available, we can adjust nominal prices in order to calculate real

prices using the following formula:

REAL PRICE current year = (CPI base year/ CPI current year)* nominal price current year.

If inflation from base year is known we can compute the real prices using the formula:

REAL PRICE = Nominal prices/ (1+ Inflation Rate) (FEWS NET, 2009).

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CHAPTER THREE

THE CONSULTANCY INDUSTRY: A GENERAL OVERVIEW

3.0 INTRODUCTION

There is very little literature on the subject of consultancy in general, and none provides a

comprehensive agenda for describing the consultancy industry (Young et al., 2003 & Hovland,

2003). In the light of the above, Young et al. (2003) advocated that it is imperative to examine

the structure of the consultancy industry; number of firms operating in the consultancy industry

and their definition; and its segmentation. According to Young et al. (2003) and Porter (2008),

the consultancy industry consists of firms that offer similar services to their clients; and

monopolistic firms. Pilsbury and Meaney (2009) perceive the consultancy industry as the

composition of popular firms; few dominant firms in their own sector of operation and large

firms with market power competing with firms of same nature. Fundamental issues in the

consultancy industry clearly borders on conduct, pricing, competition, similarity of firms and

cartel formation; product diversity; and provision of services of right value to clients (Morrill,

2004).

In view of the above exposition, the aim of this chapter is to thoroughly review existing literature

on the consulting industry; and to identify the best practices in the industry and areas that need

urgent improvement. In a bid to achieve the stated aim, this review shall assess critical issues

such as: conceptual explanation of consulting; the segmentation of the consulting industry; the

scope of consulting services; critical reasons for effective consulting assignment; exploration of

the functions of consulting; the role of consultants for the achievement of an effective consulting;

clients-consultants relationship; criticisms against consulting and arguments supporting

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consulting practice; effective selection of consultants; factors critical for successful consulting;

factors responsible for consulting failures; terms of reference; effectively pricing consulting

services; and finally summarizing and drawing conclusions on some of the pertinent issues

identified.

3.1 CONCEPTUAL EXPLANATION OF CONSULTANCY

Consulting involves the cross-fertilization of best practices, analytical techniques, change

management and coaching skills, technology implementations, strategy development or even the

simple advantage of an outsider’s perspective (INSEAD, 2011). Greiner and Metzger (1983)

opined that consulting is an advice-giving service contracted for and provided to organizations

by expressly trained and qualified persons who assist, in an objective and independent manner,

the client organization to identify management problems, analyze such problems, and help, when

requested, in the implementation of solutions. Adding on, Pittinsky and Poon (2005) clearly

asserted that consulting is a phenomenon in which one person has a difficulty and seeks

assistance from a professional with a special skill. Consultancy can also be defined as activity,

recommending appropriate action and helping to implement those recommendations (Naarmala

& Tuomi, 2006).

Consultancy has been categorized into two main aspects comprising management consultancy

which includes services contracted for and provided to organizations by specially trained and

qualified persons, who assist in an objective and independent manner, the client organization to

identify management problems, analyze such problems, recommend solutions to these problems,

and help, when requested, in the implementation of solutions; and engineering consultancy

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which is the application of physical laws and philosophies of engineering consisting of the

application of scientific principles to practical ends as the design, construction, and operation of

efficient and economical structures, equipment and systems to a broad range of activities in the

areas of construction, manufacturing, mining, transportation and environment (Consultancy

Development Centre, 2006).

According to Nees and Greiner (1985) consultants are categorized into five groups in accordance

with their approach to deliver the services enshrined in their terms of contract comprising of the

mental adventurer who analyses unyielding problems such as development problems by

application economic methods; the strategic navigator bases service delivery on the contribution

of rich quantitative understanding of the market and competitive dynamics to the development of

the client and recommends the courses of action without too much regard of the client’s own

perspective; the management physician provides recommendations from a profound

understanding of the internal dynamics of the client organization, often willingly sacrificing

some objectivity to gain a realistic viewpoint on what is practicable; the system architect is much

concerned about helping the client in the redesigning of methods, customs, and systems- always

in tandem with the client; the friendly co-pilot provides guidance to senior managers as a catalyst

rather than as an specialist, and has no aspiration to provide new information to the client.

The demand for consulting services tends to increase with the economic development of a

particular country (Weller, 2001); the requirement for consultancy services stems from a diverse

range of clients, largely governed by the large corporate sector and the Government in various

forms, viz: country, institutions, and bilateral/multilateral agencies; and the development of

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consultancy capabilities and business is directly proportional to growth in economic and

industrial development (Consultancy Development Centre, 2006). In view of the above,

especially the views of Weller (2001) a further empirical study on the relationship between

economic development and demand for consultancy services would be a novelty to undertake at

a higher level of research.

3.2 TOWARDS THE SEGMENTATION OF THE CONSULTANCY INDUSTRY

In exploring the consultancy industry, the Islamic Development Bank (2005) and The World

Bank (2002) noted that the industry operatives or firms can be segmented as independent

consulting firms which is made up of private companies, partnerships, corporations(globally and

nationally), financial institutions and procurement agencies; autonomous/semi-autonomous

government organizations; UN-agencies; or non-governmental organizations (NGOs);

universities/research institutes; consulting firms formed by trade associations like contractors or

manufacturers; and individual consultants. Since the origin of the consultancy industry;

consulting firms have been characterized by diverse functional areas such as engineering,

accounting, law, or banking; consulting organizations are generally classified as management

consultancy organizations, engineering consultancy organizations and others which include legal

consultancy organizations, socio economic consultancy organizations and financial consultancy

organizations (Consultancy Development Centre, 2006).

Consultancy firms operate along some detailed philosophies in their attempt to render services

to their clients and this in turn establish the nature of services they render as professional service

firms (among which they include Arthur D. Little and the big accountancy firms; specialist

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consultants; non-governmental organizations and public interest groups; membership

organizations; business schools (in which include their own organization); independent

consultants set up by practitioners recently moved from the corporate sector (Young et al.,

2003). Consulting assignments are in all sectors, from socio economic and environmental

projects to reforms of state and financial sectors, privatization, information technology, and

infrastructure (The World Bank, 2002).

3.2.1 THE SCOPE OF CONSULTING SERVICES

The expression “consulting services” is defined as services of an intellectual and advisory nature

provided by consultants using their professional skills to study, design, and organize specific

projects, advice clients, conduct training, and transfer knowledge; also consulting services

consist of preparation services(master plans, feasibility studies, design studies); implementation

services(tender documents, procurement assistance, construction supervision, project

management, quality management and commissioning); and advisory services (policy and

strategy, reorganization/privatization, institution building, training/knowledge transfer,

management advice and technical/operating advice) (ACENZ, 2004 and The World Bank, 2002).

Other forms of consulting services include advisory or counseling services comprising staffing,

training and institution building and specific advice on issues and projects; pre-investment

studies consisting of identification, pre-feasibility and feasibility studies include regional or

sectoral planning, policy and investment priorities (Jobeus & Sikorski, 2000).

57

In addition to the identified services above, consulting services nomenclature include

engineering and design studies having detailed services to encompass preparation of drawings,

specifications, cost estimates, tender documentation and evaluation, contract administration and

procurement; implementation or supervision services expenditure management (Construction

Industry Development Board (CIDB, 2005); and certification of materials submitted by

contractors and suppliers(IFAD, 2010); introducing modification in design as demanded by the

client; project management ( Islamic Development Bank, 2005 and McDowell, 2011). Similarly

other consulting services typology comprise project planning and feasibility studies; quality

management; project assessment studies; construction management; financial analysis; cost

management; environmental studies and impact; contract management; assessments; consultancy

for commissioning and sustainability studies; decommissioning; geological and soils

investigations, maps; valuation services; architectural/engineering design; failure investigation;

preparation of tender documents; forensic services; evaluation of bids; technical training;

construction supervision; risk analysis and management; project management; operation and

maintenance; research and development (ACENZ, 2004).

Consulting services can also be purely management bias Public Relation and Communication

oriented in nature namely supply chain; business strategy issues; finance strategy issues;

functional areas; HR issues; IT consultancy; customer relationship management(CRM); investor

relations; marketing PR; business communication; crisis communication; internal

communication; public affairs (lobbying); global analysis/surveys ( Larsson, 2007). The project

management consultant acts as the beneficiary’s executing arm in all matters connected with the

execution of a project; and in this particular case, there is no standardized model according to

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which services under this category are rendered; sometimes a consultant may be engaged to act

as the sole project consultant often with enormous powers; or an independent consultant may be

appointed under a project manager and be entrusted with the delivery of comprehensive tasks

(Islamic Development Bank, 2005).

3.3 CRITICALLY EXAMINING CONSULTANCY CONTRACTS

Two main considerations determine what type of contract to adopt in consultancy assignments:

the nature and degree of definition of the assignment; and the distribution of risks between the

client and the consultants (Appelbaum & Steed, 2004); and the level of contract supervision

(Islamic Development Bank, 2005). The types of contracts prevailing in the consultancy industry

comprise of lump sum; time-based; retainer and/or success fee; percentage; and indefinite

delivery (The World Bank, 2002 and Islamic Development Bank, 2005).

Similarly, the Islamic Development Bank (2005) identified consultancy contracts to encompass

lump sum contracts for complex assignments; lump sum contracts for simple assignments; time-

based contracts for complex assignments; time-based contracts for simple assignments; and lump

sum and time-based contracts for individual consultants. Lump-sum contracts are used for

assignments which involve wide ranging services and demands delivery of services in a precise

manner (Ministry of Finance, 2010). The lump sum contracts require that the client pays a fixed

sum of money for particular services provided by the consultant according to certain critical

requirements notably study reports; project design; tender document; timely delivery; and quality

(van Rijn, 2005).

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According to ADB (2010) lump-sum contracts are uncomplicated, well defined and appropriate

for assignments such as planning and feasibility studies, environmental studies, detailed design

of infrastructures, preparation of databases, and surveys. Lump-sum contracts are also adopted in

multifaceted situations and clear-cut assignments in which external factors delay and substantial

changes do not influence the outcome of the advice or study being provided (Palmer, 2000 and

The World Bank, 2002). Recompense is fixed for the duration of the contract; and contingencies

are not provided largely (The World Bank, 2002 and ADB, 2010). Payments are made in

harmonization with a contractually agreed upon timetable at the delivery of an agreed upon

service (ADB, 2010). The next type of contract in consulting practice is the time-based contracts

borders on the provision of services on timely basis; the services provided must be in consonance

with quality specification for which the consultant is paid based upon an agreed unit rates

multiplied by the time utilized by the consultant’s staff in delivering the assignment plus

reimbursable expenses at agreed units (The World Bank, 2002; ACENZ, 2004 and CEBC, 2011).

Time-based contracts require the transfer of cost to clients; monitoring and control systems for

progress of service delivery in order to prevent the incentivization of consulting firms from

putting too much resources and personnel in to the assignment delivery to inflate cost to better

their payment (Wideman, 1987 and ACENZ, 2004). Time-based contracts are appropriate for

consulting assignments whose nature and scope of the services are such that the terms of

reference (TOR) cannot establish them with sufficient precision (The World Bank, 2002;

ACENZ, 2004; ADB, 2010 and Touwen, 2001). For instance in the case of complex or unusual

assignments that are hard to define notably management of complex institutions or studies of

new approaches; the duration and quantity of services depends on variables that are beyond the

control of the consultants, or the services are related to activities by third parties-for instance,

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supervision of implementation assignments; then in this situations the output required of

consultants is difficult to assess, such as for technical assistance, institutional development, or

emergency situations, in which the client’s needs for assistance may evolve during execution of

the assignment (Panayotou et al., 2000; ACENZ, 2004; ADB, 2010 and The World Bank, 2002);

and transfer of knowledge and training between the consultant and client’s trainees is required

(ADB, 2010).

Another type of consulting contract to be considered is the retainer and/or success fee which are

adopted with the intention of remunerating financial and management advisers who deliver

services to clients in the sale of assets, such as privatization operations (ACENZ, 2004).

Retainer/success fees are suitable when success is related to the efforts of the firms involved and

is relatively easy to quantify (The World Bank, 2002). The retainer/success fee is generally

structured by taking two factors into account namely the value of the asset against which

advisers will be rewarded; and the structure of the incentive itself. The widely used form of

contract in consulting is the percentage contracts; in this type of consultancy contracting,

consultants receive an agreed upon percentage of the actual project cost or of the transaction sale

price (ACENZ, 2004). The percentage form of contract is widely used currently by consultants

operating architecture and construction but there are attempts in some jurisdiction to discourage

its utilization in pricing consultancy services because it offers no incentive to lower the cost of

the services; similarly it has the tendency to induce consultants to adopt more expensive design

solutions in order to increase the absolute value of their remuneration (The World Bank, 2002).

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3.4 CRTITICAL REASONS: TOWARDS AN EFFECTIVE CONSULTING

It is important at this juncture of this review to critically examine and demonstrate the rationale

for the existence of the consultancy industry. This is to identify copiously the factors that compel

clients to seek consulting services. Indeed, empirical research confirms that clients turn to

outside consultants primarily for new ideas, proficiency, and impartiality/objectivity (Gattiker &

Larwood, 1985). Consultants will be hired to provide services as they provide competence not

available elsewhere; they have varied experience outside the client; they have time to study the

problem; they are professionals; they are independent; and they have the ability to create action

based on their recommendations (Bower, 1982).

Consultants offer clients a more efficient allocation of resources by providing specialized

services for limited amounts of time without any obligation of permanent employment on the

part of the client. Consultants, engaged for their superior knowledge, transfer skills and upgrade

the knowledge base of their client while executing the assignment. Knowledge transfer from

consultants to the client often forms an important part of the assignment. Consultants can offer

independent advice to their client on the most suitable approaches, methodologies, and solutions

for their projects (The World Bank, 2002). It is equally important for management to resort to

consulting in circumstances when “management believes that performance could be better but is

not sure what to do to gain improvements; management does not have the specific knowledge

and skills necessary to solve the problems it has identified; management has the necessary

knowledge and skills but not the time or personnel to solve problems; management’s efforts have

not produced the desired long-term improvements; and management requires an independent,

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third party opinion, either to confirm a decision or to provide alternatives” ( Washburn et al.,

2002).

Uncertainty is one of the major reasons upon which most clients sought to employ consultants to

solve organizational problems; this is clearly demonstrated in Wittreich (1966) that frequently a

client who wishes to acquire a specialized service senses that he has a problem, but is uncertain

as to what the specific character of his problem really is. As long as organizational problems

exist in industries, states, economies; and every organization managed by humans, managers

will always consult to find solution to the daily problems that confront the organization, this

assertion is very significant as ‘the consultancy industry exists because of the existence of

persistent organizational and management problems which creates an ambiance of uncertainty

and exerts difficulty on managers to be seen to be acting both rationally and innovatively

(Blunsdon, 2002). Consultants play variety of roles that will be to the advantage and

improvement of their clients. These multi-faceted roles that consultancy engagements play is

very much demonstrable and copious as consultants fulfill a number of roles that they judge to be

appropriate for the client; the state of affairs; and their own approach (Lippitt & Lippitt, 1986).

Consultants can play array of roles depending on the demands of the condition (Chapman, 1998).

It is very crucial that the consultant in a bid to play its role selects the appropriate roles that will

commensurate with the expectation of the client for the realization of a successful assignment

(Massey & Walker, 1999).

The rationale for consultancy is not only the ability of consultants to identify and analyze

problems thus ‘the importance of consulting has changed from solving problems to building

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clients competence for diagnosing situations on their own and thus managing more effectively;

consultants are worth their fees not only because of their ability to analyze client problems and

provide sound recommendations, but also because of their skills in conducting a human process

that facilitates needed learning and change (Turner, 1988). Lindon (1995) claims that

consultancy is to aid clients to resolve their problems whilst not being eventually answerable for

solving them. Consulting provides a scholarship situation for clients to identify what they need to

know for enhancement and competence of organizations; thus Steele (1975) observed that

learning is the spirit of the consulting process. For instance, in problematic situations; individuals

within an organization experience a problematic situation and enquire into it on the

organization’s behalf that lead them to modify their images of organizational phenomena and to

restructure their activities so as to bring outcomes and expectations (Argyris & Schön, 1978).

Today’s complex business environment requires high transaction costs to function. This in turn

increases demand for symbolic analysts, the kinds of professionals found in modern consulting

firms (Marra & Carlei, 2011 and Canback, 1998). In transaction-cost terms, the external

consultant is more likely than an internal counterpart to lessen the bureaucratic narrow-

mindedness of top management and to reduce internal transaction costs due to misallocation of

resources within and between functions (Canback, 1999, 1998). External consultants can build

experience more effectively than inside consultants; and having seen similar problems before,

the cost to external consultants for leveraging this knowledge base will be low; in contrast,

internal consultants are experts in how their own company works, but seldom are they in a

position to create an experience base by problem type (Papulova & Mokros, 2007). Further ,

specialization in identifying management problems and in developing methodical solutions

(economies of scope) associated with scale advantages due to repeated use of standardized

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methods (economies of scale) allow consultancies to achieve a greater degree of efficiency than

any single firm would be able to acquire (Canback, 1998). The consultant often has the

opportunity to engage in joint problem solving with colleagues (Paroush, 1985).

Reasons for contracting an external consultant can be related to three decisive issues in

management decision making. The first issue is the management capability for information

gathering and analysis that may be extended as consultants for instance consultants having time

to study the problems and have additional proficiency. Consultants’ experience and specific

knowledge can be considered to be another issue, e.g. allowing to perceive where your position”,

to convey knowledge from other industries, to shun reinventing the wheel and “focusing

attention”. As a third issue it is necessary to recognize that consultants may enforce decisions,

“facilitating highly politicized decision-making” when no agreement can be found without

external intervention (Nippa & Petzold, 2002). Permanent exposure to many different problems

and situations in a number of different industries can be considered the main characteristic and at

the same time the unique advantage of consultants (Drucker, 1979).

3.5 EXPLORING THE FUNCTIONS OF CONSULTING

The decision to hire an external consultant may signal concern about employees and about

survival of the organization. Engaging consultants may also serve to mollify dissatisfied groups

and thus prevents de-motivation and low performance or helps to reduce conflicts (Nippa &

Petzold, 2002). Consultancy becomes means to enforce the favored alternative by providing an

accepted, sometimes unquestionable reference; and as consultants do not belong to the client

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company; responsibility for certain decisions and their consequences can be attributed to them

(GIZ, 2010 and Nippa & Petzold, 2002).

Clients are willing to pay more for a higher price signaling quality, when facilitating the

enforcement of their interests (Nippa & Petzold, 2002 and Janes, 2011). In order to prevent a loss

of personal reputation within the social community of the company, as well as a loss of personal

market value, managers may hire consultants especially for risky, difficult or unpopular tasks

and decisions such as lay-offs; if consultants fail or third parties complain about unfair treatment,

insufficient consideration of their goals, or wrong decisions, managers may blame it on the

consultants making them scapegoats. However, if consultants are successful, managers can at

least claim to have hired the right consultants or they can even claim the success their own

achievement (Nippa & Petzold, 2002). Consulting companies fulfill the important function of

transferring and spreading knowledge between organizations and industries. General information

on other industries, competitors, market structures, technological advancements etc. are at first

non-specific and can be used repeatedly. Only through filtering, adapting, and interpreting

provided information the general information becomes firm specific and perceiving consulting

companies as institutions that span boundaries between companies (Scott, 1998). Consulting

firms also act as intermediaries between business research, and university education and the

practical application.

3.6 EFFECTIVE CONSULTING: THE ROLE OF CONSULTANTS

Schein (1990) has significantly demonstrated the critical roles of consultants by the use of three

main categories of models as purchase of expertise, doctor-patient, and process consultation.

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Schein (1990) asserted that the purchase-of-expertise requires clients to hire consultants to render

independent services that address the challenges of the client in a detached manner; the doctor-

patient model has the consultant focusing on using a diagnostic approach to scrutinize the client

organization’s problems. The experience, knowledge and diagnostic ability of consultants aid

them to identify strategic and organizational problems. According to Schein (1990), the process

consultation model considers the consultant as a facilitator with the client actually providing

much of the relevant expertise. Turner (1982) developed the eight task categories to demonstrate

the roles of consultants as: providing information to a client; solving a client’s problem; making

a diagnosis, which may necessitate redefinition of the problem; making recommendations based

on the diagnosis; assisting with implementation of recommended actions; building a consensus

and commitment around a corrective action; facilitating client learning; and permanently

improving organizational effectiveness.

3.7 CLIENTS - CONSULTANTS RELATIONSHIP

Most consultancy assignments originate with the request from the client. A useful technique for

identifying the real decision-maker early in the project is to propose several reasonable outcomes

for the client's problem (IFC, 2007). The reaction to these reasonable ideas indicates whether or

not the consultant is dealing with the real client or the decision-maker. In consulting sector, the

clients are broadly classified into different categories i.e. Government institutions, funding

agencies (Bilateral Agencies and Multilateral Agencies), corporate clients and others like Non-

Government Organizations (Consultancy Development Centre, 2006). It is generally accepted

that how the consultant puts together the consulting process will affect the relationship with the

client and consequently the success of the project (Appelbaum & Steed, 2004 and Curtain,

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2000). In consultancy engagements clients have expectations for the assignment and it is

necessary to examine such expectations of clients for successful consulting thus ‘clients look for

new ideas and an objective perspective. Interviews with 250 executives confirmed that clients are

looking for expert advice. There is also an expectation that consultants will convey their

competencies to company personnel’ (Vogl, 1999). Consulting projects must take time to

importune inputs for execution planning; stakeholder information is also a critical input; proper

project management process must be followed; and the impacts on employees must be

considered and solutions provided to help employees deal with change. There must also be

effective guidance of senior management (Smith, 2002).

Clients require consultants to appreciate their situation; and that they put into consideration not

being overly theoretical; and clients crave tailor made solutions which mirror the challenges they

face, not formulas applied as general panaceas (Appelbaum & Steed, 2004). Consultancy

provides emotional support to both parties, Lundberg and Young (2001) claim that flourishing

consultants need to be in touch with and have ways of dealings with their own concern, their own

moods and sentimental reasons, so as to feel reasonably alert, secure, comfortable and centered

to interact with their clients. Chapman (1998) demonstrates that consultants are engaged in

helping the relationship with the client, rather than simply being a provider of expertise and little

more. Lundberg and Young (2001) affirmed the earlier assertion by Chapman (1998) that

turning emotional anguish into constructive organizational action, even excitement, after all is

what all consultants are really about.

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The most important thing in the work of a consultant is building and maintaining a relation with

client (De Jong & Van Eekelen, 1999). Since emotions are involved in every phase of the

consultancy process, consultants must learn to work smoothly; consultants must be able to create

a climate where clients feel that they can trust the consultant, however (Appelbaum & Steed,

2004), the consultant is to provide exclusive and sole attention to the client and his objectives.

Consultants should never serve more than one master; and consultants should place the client’s

interest ahead of theirs’ (Shenson, 1990). The lack of team and institutional relationship success

is directly related to the failure of the consultants to develop their personal approach to create or

connect with team and institutional marketing efforts (Stumpf & Longman, 2000). Stumpf and

Longman (2000) further opine that a long term relationship must produce a mutually beneficial

result.

McLachlin (1999) significantly demonstrated that climate is critically important, if you find that

your thinking and the clients are not on the same wavelength, do not hang around. Werr et al.

(1997) claim that the consultant and client must be expected to have quite different schemas of

the change process at the beginning of the project. The divergence of opinions forces consultants

to cram to deal smoothly with frail situations (Kakabadse et al., 2006); and one has to develop

the skill of telling clients they are wrong in such a way that they thank you for giving helpful

advice; and one has to learn how to disagree without being disagreeable (Stumpf & Tymon Jr,

2001). It is of immerse importance that the consultant display an enormous proactive behavior

which is necessary for an effective consultant-client relationship thus being upbeat in consulting

implies that the consultant thinks even of those needs and necessities of which a client has not

been aware, and helps the clients to realize all his or her possibilities, and needs (Kubr, 1996).

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The management of the consultant-client relationship cannot be underestimated thus care must

be taken not to scare clients with an uninterrupted flow of words and ideas but rather you have to

listen and try to understand what is their main concern before offering anything, and when you

do that, always use the simplest way’ (Crucini & Kipping, 2001).

3.8 THE CONSULTANCY INDUSTRY: ITS CRITICISMS

The role and efficiency of consultants is subject to numerous criticisms and one cannot write on

consultancy without mentioning the main criticisms overwhelming the role of business

consultants (Kakabadse et al., 2006). Thus Williams (2001) affirms that, external consulting is

never far from criticism; Ormerod (1997) claims that consultants are “opportunistic”; and further

opined that as consultants secure one contract, they are thinking about the next one. Consultants

are perceived to be hypocritical in their pursuit to secure contract from clients (Bloch, 1999). De

Burgundy (1995) also noted that consultants do not render any spectacular services and that their

agenda is to continually keep a particular group of people in employment which of course does

not inure to the relieve of client organizations from their problems.

Consultants are aware of the turbulent environment of managers and that instead of relieving

them from that feeling of uncertainty, managers are kept in that state of mind in order to sell

even more consulting services (Kakabadse, et al., 2006). Massey (2003) argues that consultants

are not at all times conscious of the major theoretical frameworks for organizational consulting.

Even the pervasive nature of consultants has drawn sharp criticisms from both observers and

participants of the industry to the extent that unfavourable jokes about consulting bordering on

unethical behaviours have found their way into critical literature (O’Shea & Madigan, 1997;

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Wooldridge, 1997; Ashford, 1998 and Pinault, 2000). Numerous phrases have been used in

literature to critique the consultancy industry comprising the potential harm that flows from

unworkable or faulty consulting advice (O’Shea & Madigan, 1997); the large sums of money

spent on consultants; the tendency of consultants to sell standardized solutions (Pringle, 1998);

the role of consultants as peddlers of management whims (Gill & Whittle, 1993; Huczynski,

1993; Abrahamson, 1996 and Kieser, 1997); by portraying consultants as folk-devils (Cohen,

1972); and the increasing reliance of managers on consulting advice (Micklethwait &

Wooldridge, 1996 and Shapiro, 1996).

Other criticisms of the expert model of consultancy included the failure of consultants to take

responsibility for their advice, their failure to stay and assist in the implementation of their

recommendations, and that consultants fake standard methodologies or patterns of advice from

client to client irrespective of the specific industry or context (Curtain, 2000 and Appelbaum &

Steed, 2004). Fundamental to these criticisms was a belief that meaningful organizational change

could only result from a consultant who had a detailed understanding of the oddity of the client’s

organization, and that this required long-term and cherished involvement in the client

organization (Kitay & Wright, 2004). Clients complain that consultants’ competencies are rarely

as high as promised, social and emotional skills are scarcely recognizable, advice given, and

results accomplished do not correspond with raised expectations and charged fees, as well as that

consultants would spend most of the time on identifying new problems than on those they have

been contracted for ( Pinault, 2000).

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3.8.1 ARGUMENTS SUPPORTING CONSULTANCY PRACTICE

As a result of the declining philosophy of do-it-yourself over the decades and the inability of

senior executives to utilize problem solving techniques couple with the increasing complexities

in organizational management, it is imperative to seek external support in the very nature of

consulting (Simon, 1976). Arnaud (1998), made a startling revelation that considerable fees

charged demonstrate that the consultant is only interested in money, but if the fee is low, or if the

consultant offers the service free of charge commonly referred to as pro bono, the only possible

interpretation is that the consultant is using the client as a guinea-pig. Williams (2004) contends

some criticisms against the consulting industry are simplistic and just popular views held by

many people which have not been thoroughly investigated.

It has been clearly refuted in Crucini and Kipping (2001) that the perception of consultants as

using vocabulary and words that clients do not understand by making a case that the very nature

of some projects such as process engineering, JIT demands the usage of such terms. There are

unquestionably grounds for criticizing particular consultants in specific instances; however;

broad-brush negative portrayals of the industry appear to contain as much exaggeration and hype

as the purported excesses of their targets (Cohen, 1972); and Kitay and Wright, (2004) also

supported the earlier assertion of Cohen (1972) by claiming that criticisms against consultancy

practice are oversimplification of existing complex issues. In response to the business limitations

of the external role and the critique of expert consultancy, a growing trend within the consulting

industry has been the concept of relationship consulting, whereby a consultancy seeks to develop

long-standing and close relationships with core clients (Perry, 1987 and Brizz, 1998). The

development of closer relations with clients also seeks to deflect criticisms of the expert model

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of consultancy, by emphasizing the consultant’s ability to assist in the implementation of

strategic recommendations (Morris, 2000).

3.9 THE SELECTION OF AN EFFECTIVE CONSULTANCY FIRM

In every assignment engagement, consultants are chosen from diverse background based solely

on technical qualifications since expertise is crucial to the success of the assignment (APEGGA,

2006). The Islamic Development Bank (2005) identified price consideration and cost as selection

criteria for potential consultants to execute projects but concluded that cost is given a higher

weight than price during selection of consultants. The main activities involved in the selection of

consultants comprise of short listing of qualified consultants; determination of selection method

and criteria; issuance of Request for Proposal to short listed consultants; technical and financial

evaluation; and negotiation, award and signing of contract; preparation of the Terms of

Reference (TOR); preparation of the cost estimate (budget); notification and advertising of the

envisaged consulting assignment; drawing up a short-list of qualified consultants; agreement on a

selection method and criteria between the beneficiary; preparing and issuing a Request for

Proposals (RfP) (Islamic Development Bank, 2005). In a bid to ensure the sanctity of selection of

consultants, selection methods have been devised to ensure fairness, clarity, transparency and

confidentiality (JICA, 2009; ADB, 2010; Islamic Development Bank, 2005 and The World

Bank, 2002). In promoting the virtues espoused above, the integrity of the selection process

ought to be maintained by treating critical information confidentially and notifying the winning

consultancy firm for the award of contract and it should be strictly adhered to once a winner has

been notified of an award (Ministry of Finance, 2009 and The World Bank, 2002).

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Depending on the selection method adopted, the selection process carried out by the client

includes the following steps: preparation of the TOR of the assignment; preparation of the cost

estimate to determine the budget of the assignment; advertising to invite expressions of interest

from consultants; short listing to identify consultants qualified for the assignment; preparation

and issuance of the RFP; preparation and submission of proposals by the consultants; evaluation

of technical proposals- quality evaluation; evaluation of financial proposals- cost evaluation;

final combined quality and cost evaluation to select the winning proposal (QCBS); and

negotiations and signing of the contract between the borrower and the consultants (The World

Bank, 2002).

Seven methods for the selection of consultants are provided under the Consultant guidelines; and

these include the following: Quality and Cost Based Selection (QCBS); Quality Based Selection

(QBS); Selection under a Fixed Budget (SFB); Least Cost Selection (LCS); Selection Based on

Consultant’s Qualifications (SBCQ); Single Source Selection (SSS); and Commercial Practices

(CP). The choice of the appropriate method of selection is related to the nature, size, and

complexity, likely impact of the assignment, technical and financial considerations, and the

particular circumstances of the borrower. It is therefore necessary to carefully define the

assignment, particularly the objective and the scope of the services, before deciding on the

selection method (Ministry of Finance, 2009; DevComm, 2005 and The World Bank, 2002).

3.10 CRITICAL FACTORS FOR SUCCESSFUL CONSULTING

The factors that will influence the selection of a consultant are very critical to the consulting

process; and these are crucial for a thorough consultation exercise to occur; thus the key factors

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include breadth of experience that encompasses and goes beyond the situation as defined;

demonstrated ability to complete assignments within budget and on schedule; demonstrated

ability to develop practical recommendations and to have them implemented successfully;

demonstrated ability to work with people diplomatically and effectively and to minimize

disruption of ongoing operations; and degree of trust and rapport established with management

during initial contacts ( Washburn et al., 2002). Schaffer (2002) developed a model of three

specific results necessary for a consulting project to be regarded as a success: firstly, the

consultant must provide a solution or a method new to the client; secondly, the client must

accomplish measurable improvement in its results by adopting the client’s solution; and thirdly,

the client must be able to maintain the improvement over time.

Based on anecdotes; conceptual frameworks; and empirical studies, consulting engagements are

deemed to be successful when they are hinged upon the factors comprising the recruitment of

competent consultants; an emphasis on client results versus consultant deliverables; clear and

well communicated expectations and outcomes; visible executive support and adaptation to

client readiness; an investment up front in learning the clients environment; defined in terms of

incremental successes; real partnership with consultants; and inclusion of the consultants through

the implementation phase (Appelbaum & Steed, 2004).

Adding on to the critical factors necessary for successful consulting, Rynning (1992) advanced

clarity in need/problem formulation; number/quality of new ideas; new knowledge; special

planning; new ways of thinking; level of planning; level of co-operational abilities;

management of time; planning capabilities; efficiency of execution; strategy formulation;

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problem solving; implementation; follow-up; and economy. Consultants gather information

about their client to increase their understanding of the group they were working with and to

develop their intervention, and interpret data for the client, and who provided feedback to the

organization to enhance successful consulting assignment (IFC, 2007). Consultants must exhibit

integrity, in particular by always putting the client’s best interest first; clients must be involved in

the project, and ready to change (Stumpf & Longman, 2000 and IMCA, 2010). It is pertinent

that there is a clear agreement, which may or may not be a formal contract, concerning project

requirements and expectations; the client must ultimately control the engagement, partly by

using clear and limited assignments; the consultants must be competent. Finally, there must be a

good fit between clients and consultants along a number of dimensions, including models of

consultancy, client expectations, consultant capabilities, and consultant type (McLachlin, 1999).

Drawing on from the above, it has been copiously demonstrated by the literature review that

consulting success factors purely borders on both the efforts of consultant, the client and in some

cases both the client and the consultant. Table 3.1 below summarizes the key factors responsible

for successful consulting engagements.

Table 3.1: Summary of consulting success factors

CONSULTING SUCCESS FACTORS LITERATURE SOURCE

A. Consultant

1. Emphasis on client result Appelbaum and Steed(2004)

2. Clear and well communicated outcomes Appelbaum and Steed(2004)

3. Efficiency of execution Rynning (1992)

4. Gathering information about the assignment and interpret it

to the clients

IFC (2007)

5. Exhibiting integrity Stumpf and Longman (2000)

and IMCA (2010)

6. Provide solution to the client Schaffer (2002)

B. Client

1. Effectively control the engagement McLachlin (1999)

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2. Active involvement in the project and accepting change Stumpf and Longman (2000 )

and IMCA (2010)

3. Clarity in problem formulation Rynning (1992)

4. Ability to sustain improvement Schaffer (2002)

5. Adopting the client’s solution for considerable improvement Schaffer (2002)

Source: Author’s Construct (2013)

3.11 FACTORS RESPONSIBLE FOR CONSULTANCY FAILURES

Comparatively only a small number of consulting projects seem to be successful as majority of

projects achieve their goals only partly and with considerable delays (Klenter & Möllgard,

2006); Brunesson (2000) also admitted that consulting projects are sometimes abandon in the

implementation phase while Obolensky (2001) confirmed that numerous implementation plans

do not survive contact with reality. Some consultants acknowledge in general that regardless of

all our efforts and good intentions, many of their methods and interventions do not meet the

desired goals of their engagement in totality (Warren, 2004). Others suggest a failure rate

between 25 and 50 percent (Czander, 2001), or estimate that even 80 percent of all consulting

interventions fail (Zackrison & Freedman, 2003). In other cases, the consultants’

recommendations have disastrous consequences for the organization (O’Shea & Madigan, 1997;

Byrne, 2002; Sorge & van Witteloostuijn, 2004). At other times, failure is attributable to

personal characteristics of the consultant and client (lack of skills), technical shortcomings

(ineffective project management), unstable or bad consultant -client relationships (lack of

communication), and/or socio-political aspects of the client organization (e.g. hidden agendas;

unreadiness for/resistance to change) ( Seidl &Mohe, 2007). The two issues responsible for most

failed consultations are notably the intrusion of internal politics into the consultation process and

the failure to clearly establish and maintain consensual goals (Lister & Pirrotta, 1996). The most

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critical reasons for failed consulting projects are the absence of tight project controlling and an

bloating of projects cost (Klenter & Mollgard, 2006).

Drawing on from the above, it has been realized that consulting failures emanates from diverse

sources hinged on the opinions of several authors in consulting research. It is important to

summarise the key factors responsible for consultancy failures in Table 3.2 below.

Table 3.2: Summary of consulting failure factors

CONSULTING FAILURES LITERATURE SOURCE

1. Considerable delays (Klenter and Möllgard ( 2006)

2. Project abandonment at implementation phase Brunesson (2000)

3. Executing unpractical implementation plans Obolensky (2001)

4. Methods adopted not meeting the desired goals of

engagement

Warren (2004)

5. Implementing disastrous consulting recommendations O’Shea & Madigan (1997); Byrne(

2002); Sorge & van Witteloostuijn(

2004

6. Lack of desirable personal characteristics for

Consulting.

Seidl & Mohe (2007)

7. Internal politics in organizations creeping into the

consultancy process

Lister & Pirrotta (1996)

8. Lack of consensual goals Lister & Pirrotta (1996)

9. Absence of project control and inflating project cost Klenter & Mollgard (2006)

10. Bloating of project cost Klenter & Mollgard (2006)

Source: Author’s Construct

3.12 TERMS OF REFERENCE: THE BASIS OF AN EFFECTIVE CONSULTANCY

The Terms of Reference (TOR) is the key document in the Request for Proposal (RFP). It

explains the objectives, scope of work, activities, tasks to be performed, respective

responsibilities of the client and the consultant, and expected results and deliverables of the

assignment (Westland, 2007). The TOR constitute the basic document defining the work that the

consultant is required to perform and, together with any modifications thereof at the negotiation

stage, becomes part of the contract that is eventually entered into between the consultant and the

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client. The Islamic Development Bank (2005) and The World Bank (2002) detailed the

composition of the TOR to include the scope and objective of the project (GNPC, 2009 and

ADB, 2010); relevant background; types of services required; implementation schedules and

outcomes; transfer of technology and training; method of remuneration; responsibility of clients

and consultants; main terms of conditions of appointment; and duration for execution of

assignment. Transfer of knowledge have also been identified recently to be critical part of TOR

formulation for projects; in this instance, the TOR provides for specific inputs of consultants

regarding the training approaches and methods the consultants intend to propose to the client for

consideration ( NPA, 2007; Ministry of Finance, 2009 and The World Bank, 2002 ). A key

requirement contained in the Terms of Reference that cannot be swept under the carpet in any

consulting engagement is reports and their schedules of delivery. It is in this direction that

several forms of report have been identified to include inception report (NEPA, 2009; The World

Bank, 2002; SADC and ZRA, 2006); progress reports(The World Bank, 2002 and Ministry of

Finance, 2009); and interim reports(The World Bank, 2002).

In particular, TOR should include name of the client; project location; rationale of the project;

project history (what has been done so far and by whom); list of relevant studies and basic data;

need for consultants in the project and issues to be resolved; activities to be carried out by the

consultants; source of financing for the assignment; and supervision arrangements (ACENZ,

2004). Adequate and clear TOR is important for the understanding of the assignment and its

correct execution; and reduces bottlenecks in the nature of extra works and expenses; delays;

ambiguities in proposal preparation, contract negotiation and execution (Ministry of Finance,

2009).

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3.13 THE ART OF PRICING CONSULTANCY SERVICES

In principle, pricing is an important issue; among the numerous activities that the consultancy

industry undertakes notably the transfer of knowledge and expertise relating to how to do various

tasks, how to measure and how to communicate the fact and extent of it to the public (ACENZ,

2004 and ADB, 2010). The potential benefit of each of these activities can be achieved only at a

cost; and pricing is the medium through which these benefits can be realized by mediating

between benefits and costs. At a social best, costs and benefits would be equated at the margin

and this would require the prices of consultancy industry products and services to be neither too

high nor too low (Young et al., 2003 and Jacquemin, 1990). In an oligopolistic market, there is

no achievement of optimum pricing as identified above rather the market is witnessed by price

wars; collusive pricing agreements; and implicit collusion (Young et al., 2003).

Consultancy pricing is affected by a number of factors including the client’s need for special

knowledge and experience; how much competition for clients there is; the consultant’s

reputation; and, if known, the benefit to the client of a successful outcome (ACENZ, 2004).

Consultancy pricing manifest in diverse shades by stage pricing till the final submission of

reports; flat fee pricing; and payment in advance (ACENZ, 2004). Serving in advisory position

on consulting assignments gives the opportunity to consultants to price their services by flat fee

nomenclature for each advisory session that services are provided (ADB, 2010). Variations to

pricing consultancy services occurs when consultants encounter clients preferring contingency

pricing; this form of pricing consultancy services may work depending on the cardinal principles

of integrity from both client and consultant (ACENZ, 2004 and ADB, 2010).

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Consultancy services cost include expenses for travel, entertainment, communications, and

special services on monthly intervals (Washburn et al., 2002); consultant staff remuneration;

travel and transport; mobilization and demobilization; staff allowances; communications; office

rent, supplies, equipment, shipping, and insurance; surveys and training programs; report

translation and printing; taxes and duties; and contingencies (JICA, 2006 and The World Bank,

2002); salary and wages; net profit; staff benefits; and overheads (CEBC, 2011). In terms of

travels and transport remuneration structure comprises local travel and transport costs based on

local tariffs; number and type of vehicles including operation and maintenance costs while

mobilization and demobilization may include reasonable travel time, a medical checkup, hotel

costs, local transportation, and miscellaneous items and costs for shipping personal effects

should also be estimated (TRF, 2011 ).

Cost estimates in consultancy pricing take cognizance of number of experts required for

assignment (Elliott, 2009 and ADB, 2010). It is important to define these inputs as accurately as

possible when preparing cost estimates, it is useful to draft bar charts indicating the time needed

to carry out each main activity (activity schedule) and the time to be spent by the consultant staff

(staffing schedule) (Department of Energy, 2011).

Cost estimates include a breakdown of the total costs of the assignment; hence consultant staff

remuneration may be subdivided into professional or high-level specialists and support staff

(Butcher & Demmers, 2003). Remuneration rates for staff vary according to sector and depend

on the experience, and qualifications of the consultants (ADB, 2010 and The World Bank, 2002).

In general, staff remuneration rates include different proportions of the following components,

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depending on company and industry specific factors and country laws namely basic salary;

social charges; overhead; fees or profit; and allowances (Ministry of Finance, 2009).

As far as communication cost is concerned, reasonable monthly allocation for international and

local telecommunications; and teleconferencing and the Internet are tolerable (PPB, 2003). In the

case of cost build up for office utilization to deliver consulting services to clients, consideration

is given to office rent; supplies, office equipment and insurance (c.f. The World Bank, 2002).

Taxes and duties also form part of the costing of consultancy services for pricing agenda, taxes

and duties that normally form part of consultancy services cost include value added tax(VAT)

and levies (ACENZ, 2004 and The World Bank, 2002). Contingencies in pricing of consultancy

services are twofold in the nature of physical contingency ranging from 10 to 15 percent

encompassing issues notably price items; providing for unforeseen work; monetary inflation

(Washburn et al., 2002 and The World Bank, 2002); and price contingencies which are

considered to cushion inflationary impacts (The World Bank, 2002).

It is essential that the cost estimate fully cover the requirements of the TOR to ensure that the

financial commitments of the consultants fully reflect their technical proposals, which if

inaccurate could result in deficient proposal evaluation and contract award, and unsatisfactory

contract implementation (Washburn et al., 2002 and Islamic Development Bank, 2005). Finally,

consultancy costs are categorized as remuneration (fees) and reimbursable cost items (travel and

transport, communications, office rent, local staff salaries, local taxes, etc.). Local taxes (indirect

and direct) and customs duties on imported equipment and supplies shall be identified separately

(Islamic Development Bank, 2005).

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3.14 APPRAISAL AND SYNTHESIS OF THE LITERATURE REVIEW

In view of the elaborate review of the above literature on various aspects of the consulting

industry, it is imperative to draw some conclusion on the subject matter. It can be concluded that

consultancy is a process of finding solution to perceived genuine problems existing in

organizations by soliciting the expertise of individuals or organizations that are not part of the

customer organization to study, analyze and suggest solutions to the existing problem for

implementation. Consultancy can be classified into management consultancy and engineering

consultancy. Engineering consultancy involves the use of physical laws and engineering

principles to solve problems in the fields of design, construction, and operation of structures,

mining, manufacturing, transportation, structures and environment. Management consultancy

deals with the analysis of management problems in organizations and recommending solutions

for these problems for implementation. This type of consultancy is suitable for areas such as

accountancy, auditing, management public relations and communication, customer care

management, lobbying, global analysis and others like the legal consultancy. Consultants can be

classified according to the manner in which they approach their consulting assignment; hence

consultants can be seen approaching their duties as mental adventurers, strategic/navigator,

management physician, system architect and friendly co-pilot. The structure of the firms

operating in the consultancy industry is demonstrated as partnerships, private companies,

corporations, financial institutions, procurement agencies, government organizations, NGOs,

universities and research institutes.

It has also been identified that the consultancy industry is segmented along the specialization of

industry practitioners, this thus make the industry to be purely a knowledge base industry. The

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works of Consultancy Development Centre (2006); Young et al. (2006); The World Bank (2002)

and Islamic Development Bank (2005), copiously demonstrated that the consultancy industry can

be in functional areas such as banking, accounting, management, law and all aspects of

technology and engineering. Consultancy services are the ‘goods’/ ‘products’ manufactured by

the consulting industry. In this light, any services rendered intellectually and advisory in nature

to clients by the use of skills/expertise of consultants can be regarded as consulting services. The

literature review revealed consulting services as master plans, feasibility studies, design studies,

tender documentation, procurement assistance, construction supervision, project management,

policy and strategy, knowledge transfer, commissioning, management, institution building,

identification and investment priorities, planning, valuation, cost estimates, preparation of

drawings, specifications, project management, implementation, environmental studies and

impact, financial analysis, forensic, research and development and IT. It is important to note that

as long as knowledge continues to evolve and problems keep on emanating in areas that are new

to humans, consultancy services will emerge from these areas. This assertion is strongly

reinforced by the evidential evolution of the computer age leading to rise in Information

Technology (IT) consulting services which were not part of the traditional consulting services.

Contracts serve as the basis for the definition of roles and responsibility of the parties to a

consulting assignment. Contracts also serve as the conduit or modalities for the payment of

consultancy fees by clients to consultants. The literature review led to the identification of

consulting contracts consisting of lump-sum, time-based, retainer and/or success fees and

percentage contracts. The type of contract arrangement chosen is determined by the nature of the

consultancy assignment. It is also imperative to identify the rationale as well as the situations that

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necessitate the procurement of consultancy services. In this vein, the services of consultants are

engaged by clients to provide: new ideas, proficiency; where impartiality is needed; to inject

competency not existing into the system; provide and infuse experience gathered into the client’s

organization and in addition; consultants have time not available to the client to study problems;

consultants are professionals and have wealth of expertise; and upgrading client’s knowledge by

transferring skills. Situations which necessitate consulting manifest in organizations as a result of

management’s quest to realize an improved performance but do not know the process of

achieving such a goal; when it is obvious that the client does not have the requisite skills and

knowledge to solve problem; in situations where the efforts of the client does not produce the

desired result; when the client has the knowledge and skills but not the time or personnel to solve

the problem.

Consultancy functions in diverse ways by making clients as well as customers robust and

efficient. The review of literature on the consultancy industry revealed vital functions of

consultancy such as conflict reduction; helping to enforce favoured alternative; preventing the

loss of personal reputation and market value; serving as intermediary between research and

business. In order to facilitate these functions of consultancy enumerated above, consultants

ought to play crucial roles such as provision of independent perspective to bear on the challenges

facing clients; diagnostic approach in the examination of the client’s problems; and the serving

as a facilitator in all respect as far as the consulting assignment is concerned.

The client-consultant relationship is very vital to the realization of both the functions of

consultancy and the role of consultants. The manner in which the consultant institutes the

consulting process will affect the relationship with the client and consequently the success of the

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consulting assignment. It is demonstrated in the works of Appelbaum and Steed (2004) that the

client-consultant relationship is fundamentally linked to the success of the consultancy

assignment. Consultants provide emotional support to their clients and customers by making

them alert, secure, comfortable and interactive. The consultant ought to be proactive in behavior,

and must ensure that his words and ideas do not scare clients and customers. The types of clients

also determine the nature of the relationship that exists between client and consultant. Clients in

the consultancy industry include: contact clients, intermediate clients, unwitting clients, indirect

clients and ultimate clients.

Enormous literature have revealed that consultants are criticized as being opportunistic; not

performing any real practical role; consultancy has done little to revive management; consultants

keep managers in the state of uncertainty to sell their consultancy services; having pervasive

influence; the harm that flows from consultancy advice; huge sums of money spent on

consultancy; consultants do not take responsibility for their advice; and their inability to stay and

assist in implementation. In spite of these criticisms, other works demonstrated their support for

consultancy; and these supports in favour of the industry that; the decline in the ‘do it yourself’

philosophy as a result of inefficiency has brought the consultancy industry in to the fore. The

accusation that the consultancy industry charges high fees is untenable since price is

axiomatically the measure of value and quality which goes to support the fact that consultancy

services are of high standards. Again, all the criticisms against the consulting industry have not

been empirically verified, they are just the thought or the imaginations being expressed and

oversimplification of issues.

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The selection of consultants or consultancy firms is also an important area in the industry.

Technical qualification and price consideration are very pertinent in the selection process. The

selection process is to ensure fairness, clarity, transparency and confidentiality. The selection of

consultants consists of short listing qualified candidates, determination of selection methods and

criteria. The seven methods of selecting consultants consist of Quality and Cost based Selection

(QCBS); Quality based Selection (QBS); Selection under a Fixed Budget (SFB); Least cost

Selection (LCS); Selection Based on Consultant’s Qualifications (SBCQ); Single Source

Selection (SSS) and Commercial Practices (CP). The appropriateness of each method is based on

the nature, size, and impact, technical and financial considerations.

The factors responsible for successful consultancy assignment cannot be underestimated in any

attempt to have a critical overview of the industry. These factors are crucial for a vibrant and

thriving industry. Works such as Washburn et al.(2002); Appelbaum and Steed (2004); Rynning

(1992); Stumpf and Longman (2000) have copiously demonstrated the successful factors for

consultancy as: experience beyond the situation defined; ability to complete the assignment

within the stipulated budget and time; diplomacy; trust and rapport; ability to develop practical

recommendations; competence; excellent communication; executive support; partnership; clarity

in problem formulation; quality of ideas and follow-ups. In so far there are factors that propel the

consulting industry; there exist factors that contribute to its failure. Czander (2001) contends that

the failure rate of successfully executing a consulting assignment is between twenty-five (25)

and fifty (50) percent; this is further supported strongly by Zackrison and Freedman (2003) that

eighty (80) percent of all consulting interventions fail. Consulting failures manifest as a result of:

technical inadequacy; poor personal characteristics of both client and consultant; unstable client-

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consultant relationship; poor social and political environment of the client’s organization and

unwillingness to change on the part of the client.

The Terms of Reference (TOR) is a vital document in the request for proposal (RFP); it serves as

the basis for effective consulting and defines the objective, scope, activities, tasks,

responsibilities, expected results and deliverables of the consulting assignment. The TOR helps

in the effective pricing of consulting services rendered to the client. Pricing is the medium

through which the consultant receives remuneration and it is a vital process in the consulting

industry. The consultant’s remuneration for that matter price (fees) is significantly affected by:

competition; consultant’s reputation; the need for special knowledge; and experience.

Consultants’ remuneration as fees come in the form of flat fees; contingency basis; billing

separately for expenses. The most reliable way of arriving at these fees is by cost estimating. The

cost estimate for consultancy assignment encompasses consultant’s staff remuneration; travel

and transport; mobilization and demobilization; communication; staff allowances; rent;

equipment and supplies; taxation; shipping; surveys; training programs; legal; and accounting

services. These components of the cost estimate for consulting can be classified as direct cost

and overhead/indirect cost.

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CHAPTER FOUR

QUANTITY SURVEYING PRACTICE IN CONTEMPORARY GLOBAL

ENVIRONMENT: A GENERAL OVERVIEW

4.0 INTRODUCTION

This chapter is very pertinent to this research, in view of the fact that it comprehensively

reviewed quantity surveying practice in order to position well in the globalize complex

construction industry. The review consist of the meaning of quantity surveying; the role of the

quantity surveyor; the changing roles of the quantity surveyor; quantity surveying consultancy

services; non-traditional quantity surveying consultancy services; quantity surveying consultancy

services pricing(fees); challenges confronting quantity surveying services pricing; challenges

confronting quantity surveying practice; professional misconducts in quantity surveying practice;

the adoption of ICT in quantity surveying operations; and bills of quantities (BOQ), the most

valuable working document of the quantity surveyor.

According to Olatunde (2006); the Quantity Surveying Profession has developed a long way

spanning over two centuries ago when it was only a measurement and accounting profession.

Over the years the role of the Quantity Surveyor (QS) increased, partly to the rapid development

and urbanisation of cities and town and with increased emphasis placed upon costs of building

(Olatunde, 2006). In order to accurately forecast and control costs the profession began to

develop various methods. Only initial costs in use were taking into account. The importance and

work of the Quantity Surveyor expanded during the 1980s due to the interest in whole life cycle

costing.

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Various challenges faced the profession by the end of the twentieth century. The Profession has

been able to develop and utilize skills more usefully due to the increased activities associated

with information technology which removed some of the repetitive tasks associated with their

work. In addition to solely considering initial costs of construction emphasis has shifted to

identifying and adding value to the development process. All over the world Quantity Surveyors

are now involved in a variety of projects ranging from homes, airports, power stations, highways,

sports stadium to offshore oil rigs. They are involved at all levels of the process, starting with

advising on the initial proposal for a project to meeting the client’s needs, right through its

working life and even how to recycle the building. They provide complex solution based services

on a scale that few have imagined. Although Quantity Surveyors (QSs) do still provide

traditional services, they now service new industries and offer a wider spread of services to a

wider spread of clients. This is opening new commercial possibilities for QSs whether working

for companies, client groups, contractors or other advisory and consulting firms.

4.1 THE MEANING OF QUANTITY SURVEYING (QS)

Anago (2006) observed that quantity surveying, as a basically cost-literate profession, should

play a key role in developmental resource allocation, the core- efficiency driver in economic

development. Quantity surveying as a numeric discipline has a peculiar dynamism that should

enable it drive competition in the market place (Anago, 2006). According to Olawale (2006), a

quantity surveyor is the financial professional of the construction industry whose training and

experience qualify him to advise on cost and arrangement of projects and to prepare contract

documents in respect of such project. As opined by Westcott and Burnside (2003); quantity

surveying is the central importance of measurement or quantification is clearly confirmed, as it

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distinguishes us (the QS) from the architect as designer and the engineer who delivers function.

According to RICS (1991) a quantity surveyor is a professional who ensures that the resources of

a construction industry are used to the best advantage by providing sound financial management

and consultancy service to the client during the construction process. The quantity surveyor is

appointed to provide advice to the client; offer alternative design solutions; and be responsible

for specific aspects of the project where integration of knowledge from various subject areas is

concerned (Bonnar, 2007).

4.2 THE ROLE OF THE QUANTITY SURVEYOR

As a professional of the construction industry, the quantity surveyor acts in liaison with other

professionals particularly the architects, the builders, the engineers, the estate surveyors and

valuers, the constructors/contractors and the suppliers to safeguard the client’s interest. A large

part of the quantity surveyor’s work is directly or indirectly related to aim of achieving a

reasonable contract price (Olawale, 2006). According to Eke (2006), quantity surveyors take a

methodical and balanced approach to all tasks, an approach which is often lacking in other

professionals allied to the building industry. Again Eke (2006) asserted that it is in the area of

cost control that the QS play the dominant role. As the financial expert it is incumbent on the QS

to establish maintain and update realistic cost reporting and monitoring and financial

management procedures, which take full account of the client’s requirements and cater for all

aspects of the particular infrastructure (Eke, 2006).

McGaw (2007) opined that clients employ quantity surveyors to maintain budget surplus thus

controlling the finance of the project; providing realistic price for development as shown on the

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drawing supplied by the architect; provide adequate feedback on documentation provided for

tender purposes, thus reducing the uncertainty placed on the developer who must carry the

burden of construction contingency. In similar manner, McGaw (2007) further asserted that the

quantity surveyor provides budgetary options in the post contract when design deficiencies need

to be resolved; the position of McGaw (2007) is further confirmed by Burnside and Westcott

(1999) that the traditional role of the quantity surveyor is to provide advice about cost and

financial management of construction process. Also, Bonnar (2007) adds that the quantity

surveyor is a professional with myriad of expertise in technical ( understanding of the methods

of construction, materials used, and the principles of building design); professional (quantifying

drawn information to provide bills of quantities or other documentation for pricing); managerial

(understanding the principles and processes of management construction, project and resource);

financial undertaking the responsibility for cost control( setting budget limits at inception,

financial control during construction, settlement of the final account on completion); and

provision of legal (advice on appropriate procurement routes (forms of contract) including the

rights, obligations and remedies of each party to the contract).

4.2.1 The Changing Roles of the Quantity Surveyor

As globalization is increasing, the role of all professions over the world is changing and the

quantity surveyor is of no exception; Ashworth (1981) pointed out that the role of the quantity

surveyor has changed significantly over the decades. Ashworth (1981) further buttressed this

point by asserting that thirty years ago, the of the quantity surveyor was the preparation of bills

of quantities and the final account only but in recent years the role of the quantity surveyor has

changed from cost to value with emphasis on procurement and management skills (Ashworth,

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1994; RICS, 1991). This claims were further confirmed by the empirical study of Keel et al.

(1994) in which they found that 80% of clients see the role of the quantity surveyor as changing;

and 67% of respondents in the study see the role of the quantity surveyor to be increasing in

areas of project management, lead consultancy, cost and value management, mechanical and

electrical services and advising on overseas methods and costs.

4.3 QUANTITY SURVEYING CONSULTANCY SERVICES

In terms of contract phases; Olatunde (2006) variedly classify consultancy services provided by

quantity surveying professionals in contract phases or stages as pre contract work (sector-

specific design advice; early stage comparative cost planning; advising on cost of design

options; analysis and scheduling of work; measuring work to define rules; preparing cost

estimates; preparing tender documents; drafting contracts; assembling frameworks;

benchmarking and value management; funders/mergers and acquisitions due diligence); post-

contract work (acting as contracts administrator; valuation of variations; valuation of work in

progress; valuation of variations; settling final accounts contractual advice; evaluation of

claims for additional cost; settling final accounts; setting capital allowances calculations; acting

as adjudicator or mediator; acting as expert witness or arbitrator; risk management). In

management of contracts the consultancy services provided by quantity surveyors; Olatunde

(2006) further identify services rendered by quantity surveyors in terms of management by

clearly demonstrating project management services as (the management of the overall planning,

control and co-ordination of a project, or portfolio of projects, from inception to completion to

deliver the clients' objective); facilities management (this encompasses capital expenditure,

facilities management and lifecycle costing, preparing frameworks through procuring service

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and implementing performance driven solutions; building engineering and ground maintenance

and health and safety issues); program management ( this consist of all facets of major

programme such as project controls, communication platforms, design standards and

management, policies and procedures, resourcing and procurement).

Olatunde (2006) observed that critical future program management roles are likely to include

provision of services in the energy sector in the building of power stations and distribution of

energy to consumers); development management (this involves the management and co-

ordination of all key areas of the development process, from site location searches and studies,

preparing feasibility studies, managing the design and procurement process, construction process

and design team to facilities management of completed building); supply chain management

(supply-chain management is a radical approach to procurement. It aims to set up long-term

relationships with suppliers in order to develop leaner, value-adding and more efficient ways of

working. It offers simplification and risk reduction and significant cost savings); construction

management (it entails construction advice, design management, logistics, programming,

procurement of trade packages, direction and control of the construction site, commercial

management and payments, safety management and quality management); and project

monitoring (quantity Surveyors providing this service ensure that planning conditions are

cleared, surveys have been undertaken, insurance levels are correct for the type of project and

chosen procurement route and building contract is correct for the project) (Olatunde, 2006).

Olawale (2006) also demonstrated clearly the services that quantity surveyors render to their

clients as estimating and cost advice often referred to as preliminary cost advice; advising on

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contractual methods; advising on contractor selection; preparing tender documents; obtaining or

negotiating tenders; cost planning; valuing construction work; preparing and agreeing accounts

with contractors; preparing expenditure statements for tax and accounting; technical auditing;

and assessing replacement values for insurance; project control; giving expert evidence in

arbitration and disputes; feasibility studies; investment appraisals; cost control and post contract

management; project management and co-ordination; value management; risk management;

security management; financial analysis; condition surveys; expert witness advice; property

management; asset management; property condition appraisals; and facilities management.

Anago (2006) asserted that quantity surveying is an aggregation of various skills and disciplines

which come under the umbrella of procurement management (consisting of preliminary cost

advice; estimating; measurement and quantification; advising on contractual methods; advising

on contractor’s selection; preparing tender documents; obtaining or negotiating tenders/bids;

valuing construction work; preparing and agreeing accounts with contractors; project control;

cost control and post contract management; project management and co-ordination; scheduling

and planning; technical auditing); management advisory services(consisting of feasibility and

viability studies; cost planning/management; property management; facility management; asset

management; property conditions appraisals; risk management; conditions survey; value

management, analysis and engineering; and replacement cost for insurance purposes); financial

advisory services( consisting of investment appraisals; financial analysis; life cycle costing;

expenditure statements for taxation and account purposes; capital allowance management; and

due diligence studies); and legal advisory services( includes expert testimony/litigation support;

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arbitration; dispute and conflict management (ADR); advice on claims preparation and claims

defense; contract auditing).

Burnside and Westcott (1999) identified the traditional services rendered on technical basis by

the quantity surveyor as preparing the cost plan and the bills of quantities, tender documentation

and tender appraisal, interim payments, measuring and valuing variations, advising on

anticipated final costs and preparing the final account. Seeley (1997) clearly pointed out the

services provided by quantity surveyors as preliminary cost advice; cost planning and cost

checking; advice on contracting methods; construction procurement systems; valuation of

construction work; preparing tender documents and negotiating contract prices; preparing

contract documents and participating in contract administration; preparing cash flow forecasts

and exercising cost control over the project; value management; interim valuations and

payments; financial statements; variations, final account preparation and agreement; project

management; settlement of contractual claims; and giving expert evidence in arbitrations and

disputes. The services identified by Seeley (1997) are provided in wide range of projects as

identified by Davis et al. (2007) to include building construction, civil and structural

engineering, mechanical building and engineering services, petro-chemical, mineral extraction,

planning and urban.

The Canadian Institute of Quantity Surveyors, CIQS (2002) adds cost consulting (consisting:

feasibility studies and conceptual estimating; project budgeting; cost planning / cost control

estimates (in either elemental or trade format); assembly of tender packages; tender review and

contractor selection; functional cost analysis; review and recommendation of project progress

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payments; review and negotiation of change orders and contractual claims) ; mortgage

monitoring (consisting: review and verification that project budget is adequate to complete

project; progress draw review and monitoring of costs incurred; and verification of borrower

payments; value management( incorporating: review of project program, design and cost studies;

service provider for value management workshops; evaluating processes and components;

preparation of recommendations); life cycle costing( including: life cycle cost plans; discounted

cash flows; sensitivity analysis); and Other Services( consisting: reserve fund studies and cost to

complete reports; property condition reports; risk analysis; insurance replacement cost

assessment; project management; project scheduling; construction management; construction and

project cash flows; mediation and arbitration; expert witness; bills of quantities and/or materials;

material take-offs).

4.3.1 NON-TRADITIONAL QUANTITY SURVEYING CONSULTANCY SERVICES

Olatunde (2006) again identify services that quantity surveyors can provide in seemingly non-

traditional sectors as in oil and gas (quantity surveyors provide services such as management of

capital expenditure, procurement management and construction management); in rail network,

quantity surveying (QS) services include cost and business planning, procurement and supply

chain management, commercial management, facilities management of stations, risk and value

management and whole life cycle cost management; in the power sector, Olatunde (2006)

observed cost planning and budgeting, program management and construction management,

expertise in maintenance programme, providing advice on procurement strategy, contract

administration, project management, development and facilities management.

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According to Olatunde (2006) the expertise of the QS in the telecommunication sector

encompasses cost planning, cost management and reporting; and in airports and air

transportation, Olatunde (2006) opined that quantity surveyors are needed for preparing

development appraisals, advising client on project brief, preferred procurement route and cash-

flow, advising whole life costs, planning the construction process, controlling the project on

behalf of the employer, to risk and value management.

4.4 QUANTITY SURVEYING CONSULTANCY SERVICES PRICING/FEES

According to Fee Bureau (2011) quantity surveying fees relate to the full service provided by

quantity surveyors at the pre-contract and post-contract stages of a project; and fees are

expressed as a per cent of total building construction cost. The Fees Bureau(2011) further

asserted that the services rendered for fees consist of preparing full bills of quantities; tender

documents; tender reports and contracts; valuation of works in progress; preparing final

accounts. The Fee Bureau (2011) opined that fees exclude expenses and VAT.

The Alberta Infrastructure and Transportation (2005) clearly pointed out that fee calculation

should be based on the anticipated construction cost, the schedule and the scope and nature of

work contained within the approved budget for the project. The Alberta Infrastructure and

Transportation (2005) uses the project phase, report provided by cost consultant (quantity

surveyor) and the amount in percentage as key guidelines in the calculation of fees. For instance

the Alberta Infrastructure and Transportation (2005) adopted the following criteria for its fee

calculation as a feasibility report at the functional phase of a project attracts five percent(5%) of

the amount of project cost; design selection studies in the block schematics phase attracts seven

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and half percent (7.5%) of project amount; schematic design cost plan at the selected sketch

design phase of a project attracts twelve and half percent (12.5%); design development cost

check at the design development phase attracts twenty percent(20%) of the project amount; cost

checks, pre-tender estimate reports at the construction documents preparation phase attracts fifty-

five percent(55%) of the project cost; and tender analysis report during the bidding phase attracts

fifty-five percent (55%) of the project amount.

These guidelines of Alberta Infrastructure and Transportation (2005) are in consonance with the

practice of The South African Council for the Quantity Surveying Profession (2010) which

opined that appropriate percentage the basic fee shall be apportioned to each category before

multiplying each apportionment by the applicable appropriate percentage. In contrast The South

African Council for the Quantity Surveying Profession (2010) apply the appropriate percentage

for fess in categories such as alteration works, building works, redecoration works, replication,

multiple procurement contracts, civil engineering works, electrical engineering works,

mechanical engineering works and process engineering works. The Alberta Infrastructure and

Transportation (2005) opined that the agreed fee may be varied for any of the following reasons:

a significant approved variation in scope or nature of the project; a significant approved variation

in schedule of the project; project suspension or abandonment; and termination or suspension of

cost consultant services. Any variation in fee amount shall take into account the cost of the

services completed. Snyman (2004) in a survey identified factors influencing fee proposals as

prospects of follow-up work 44% ; credibility of client 31%; affordability of the fee 20%; type of

contract 20%; and competitiveness of the market 7%. Other fee influencing factors identified in

Snyman (2004) consist of availability of suitable personnel; location of the project; programme

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of the project; current workload; level of service required; complexity of the work; and client

involvement. According to Cruywagen and Snyman (2005) the services rendered by quantity

surveyors can be priced in stages namely estimating and cost advice attracting ten percent (10%)

fee; tender documentation which attract twenty percent (20%) fees; contract administration stage

with forty seven and half percent (47.5%); and final account stage which attracts twenty-two and

half percent (22.5%).

4.4.1 CHALLENGES OF QUANTITY SURVEYING SERVICES PRICING/FEES

Just like any other profession which is bedeviled with challenges, the quantity surveying

profession is not an exception; thus Cruywagen and Snyman (2005) observed that it has become

a norm for professional quantity surveyors to offer reduced professional fees on construction

projects as a result of the competitive nature of the market. Cruywagen & Snyman (2005) further

opined that these reduced professional fees offered by quantity surveying practitioners usually

fall far below what is considered a fair remuneration for services rendered. In their empirical

studies, Cruywagen and Snyman (2005) asserted that quantity surveying fees can be rendered

affordable on a particular project types but the quantity surveyor will be more exposed to risk;

and that the risk further increases with a decrease in project value. In tandem with the findings of

Cruywagen and Snyman (2005) on fee reduction; Smith (2004) in a survey on trends in the

Australian quantity surveying profession identified fee cutting as a threat to the quantity

surveying profession. In a descriptive survey conducted, Snyman (2004) found out that eighty-

six percent (86%) of quantity firms offer discount in the between sixteen percent(16%) and

twenty(20%) on the recommended fees of Association of South African Quantity Surveyors

(ASAQS) to their clients in the Gauteng province of South Africa. Hoxley (1998) observed that

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the fee cutting syndrome is prevalent among quantity surveying practitioners even to the point of

venturing in to loss-making territory. Also Cruywagen and Snyman (2005) opined that it is

universally accepted that the fee reduction syndrome invariably compromises quality; this

position is supported by Hoxley (1998), that most players in the market acknowledge that the

quality of work suffers when fees get below certain point.

In the light of the above shortcomings of the professional fees, Cruywagen and Snyman (2005)

in their empirical research posed some pertinent questions which are worthy of critical

consideration, namely on what basis is the tariff of professional fees calculated? Are there

differences between various types of construction projects? How do quantity surveyors

determine their proposed fees on construction projects? and how can an affordable fee be

calculated on construction projects? Also Cruywagen and Snyman (2005) observed a fluctuation

in the tariff of fees charged by quantity surveyors and concluded that poses a risk allocation to

the quantity surveyor.

4.5 CHALLENGES CONFRONTING QUANTITY SURVEYING PRACTICE

There are numerous challenges confronting the QS profession especially in contract

arrangements for execution of projects. Thus according to Odeyinka (2006), the QS faces

response challenges in contractual arrangements such as Private Finance Initiative (PFI) and

Public Private Partnership (PPP); supply chain management; partnering and alliancing; prime

contracting; and performance based contracting. Again Odeyinka (2006) identify other

challenges facing the QS profession as the challenge of appropriate response to shift from

traditional technical competence to business and management competence to be able to function

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in new areas such as: facilities management, project management, value management,

commercial management and risk management; the challenge of appropriate response to

information technology and communication revolution; and the challenge of integrating the

outputs of applied research into the practice of Quantity Surveying.

Cartlidge (2002) summed up the challenge for the profession with the observation “quantity

surveyors must get inside the head of their clients, fully appreciate their business objectives, and

find new ways in which to deliver value and conversely remove waste from the procurement and

construction process.” Ashworth and Hogg (2000) reviewed the development of quantity

surveying and identified a shift in emphasis from cost to value with many QS firms extending the

range of services that they offer clients. Eke (2006) observed some of the challenges confronting

the QS profession as the impact of competition, the changing natures of client demand and the

advances in information technology. Cartlidge (2000) identified the challenges confronting the

QS as higher clients' requirements through the increasing complexity of modern construction

projects; impact of computerization; and competition from other professionals.

4.6 PROFESSIONAL MISCOUNDUCT IN QUANTITY SURVEYING PRACTICE

The quantity surveying profession is not an exception when it comes to ethical misconducts that

plague other professional bodies. Thus Ferrell and Weaver (1978) identify practices that could be

considered as negative to include the attempt to provide trade secret for inducements;

compromise to discharge professional service with very low level of honesty; and negligence and

denial of fault. McDonald and Zepp (1988) added the tendency to exaggerate services to deceive

clients; Olatunji (2007) reports that there are cases where quantity surveyors connive with greedy

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contractors to defraud unsuspecting clients; falsification of reports to favour selfish interests;

concealment of errors to justify negligence.

Quantity surveyors also misconduct themselves professional by helping to save other

consultants whose roles cause project failure (Newstom and Ruch, 1975; Albratt et al., 1992;

Olatunji et al., 2006). Receiving bribes, gifts and inducements during site visitation and

valuation at the inception stage to compromise professional responsibility constitute professional

misconduct (Olatunji, 2007). Dubinsky et al.(1980) also add abuse of office, misappropriation of

organization, official time and resources for personal use to include some of the notable

professional misconducts in the quantity surveying profession. Other misconducts include

wasting longer time on a job than envisaged (Ferrell & Weaver, 1978); indolence at work

(Albratt et al., 1992); compromising personal standards or professional principles to fulfill

employer’s demand at the expense of the client or the public at large (Dolecheck and Dolecheck,

1984); and forming cartel to prevent free flow of competition (Dubinsky at al., 1980).

4.7 ADOPTION OF ICT IN QUANTITY SURVEYING OPERATIONS

Globalization has influenced the operations of quantity surveying profession especially in the

way services are rendered to clients (Smith, 2004 and Peansupap, 2004); as a result quantity

surveying firms since the late 1980s have been adopting the Information and Communication

Technology (ICT) in the delivery of quality services (Akintoye, 2001; Peansupap, 2004; and

Ayeni, 1989). According to Musa et al. (2010), it is pertinent to adopt technology in improving

the quality of services delivered to clients. Thus Page et al. (2004) opined that the critical roles

of the quantity surveyors have placed them potentially at the centre of ICT that will integrate the

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contributions of all the participants of the design team. This ICT integration in quantity

surveying practice will ensure that resources are used to the best advantage of project partners by

providing financial management and cost consultancy services during the construction process

(Musa et al., 2010). The shift paradigm shift from paper-based operations to computer based

(digital) cost information production and exchange has necessitated the adoption of ICT in

quantity surveying practice (Oladepo, 2006 and Musa et al., 2010). According to Musa et al.

(2010), a new work order has evolved through the advent of technological innovations with the

main aim of optimizing resources; thus Goyal (1991) opined that this new work order for

quantity surveyors involves collection, storage, processing and transmission of cost information,

electronically, using computer and modern telecommunication networks.

Hinged on the above, Adeoye (1996) pointed out that the adoption of new technologies for new

order of work will involve the development of specialist software packages for performing the

array of tasks involved in work practices of quantity surveyors. In this vein, Musa et al. (2010)

identified software packages for quantity surveying in a globalize competitive environment to

include Digitizers, Autocard, Autosketch, Super Project, Master Bill, WinQs, QSlotus, Computer

Aided Taking Off (CATO), Estimator Pro.MB 3, QS Cad, RIPAC, EVEREST, Kwikest inter

alia for processing of operations.

4.8 EXPLORING THE BILLS OF QUANTITIES (BOQ) IN QS PRACTICE

4.8.1 The Emergence of the BOQ

The Bills of Quantities (BOQ) was introduced in to the United Kingdom’s construction industry

after the industrial revolution in the 19th century. They were used by master tradesmen for paying

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their workmen and claiming payments from building owners (Rashid et al., 2006). In its early

stage, the BOQs were prepared by “measurers” who were also known as “custom surveyors” or

“surveyors” who acted for master tradesmen (contractors for today). The “measurers” quantify

the work after completion and submit partisan final account to the building owner for payment

(ASAQS, 2006). The BOQ since then has become a tool for project costing and obtaining

tenders from contractors (Rashid et al., 2006). In addition, architects and other consultants use it

to have a bird’s eye view in terms of controlling project cost and finance (Rashid et al., 2006).

Kodikara et al. (1993) pointed out that the purpose of the BOQ is to give equal opportunity to all

contractors a level playing field to price the same characteristics of work items during bidding.

4.8.2 The Definition of Bills of Quantities

According to Hackett and Robinson (2003); and Chan (2002), the BOQ is a document that

stipulates the qualitative and quantitative aspects of every constituent parts of a proposed

construction project. Similarly, it is a book containing the all the list of items needed for

construction; and these items are complete with description in terms of materials, labour and

workmanship for the work and its quantity (NSW Legislative Council, 1991 and Marsden, 1998).

Willis (2002) adds that the BOQ is document with in-depth information on the type, nature and

quantities of the finished works in a construction. The BOQ is prepared together with the form of

tender, specification, preliminary bill and list of drawings to form a tender document. According

to Adnan et al. (2011) the BOQ is a document that itemizes the quantities of materials and labour

in a construction project. It is usually prepared by a professional quantity surveyor of the client

or the contractor (David & Baccarini, 2002) provide the quality control, cost analysis, cost

planning and to provide basis for financial reporting/cash flow.

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4.8.3 Uses of the Bills of Quantities

Chan, (2003) has identified various purposes of the BOQ to include: to avoid unnecessary effort

from multiple Contractors to prepare the bill, to According to Rashid et al. (2006), the BOQ is

used for cost planning; projected cash flows and budget, for valuation of interim payments and

variation orders and for settlement of final account; and are used for preparing materials

schedules or bills of materials in the contractors’ organization (Wainwright & Whitrod, 1980;

and Molloy, 2001). Other uses of the BOQ include bid evaluation (Rashid et al., 2006); are part

of the tender and documentation process; a tool for obtaining bids and maintaining cost control

during the contract (Rashid et al., 2006). According to El-Mashaleh (2010); the BOQ is useful in

making decision during bidding. It is also used for post-tender works such as cost planning,

projected cash flow and budget, valuation of interim payments and variation orders and for

settlement of final account (Kodikara et al., 1993). Numerous studies have identified the various

uses of BOQ and these include It enables the contractor to insert suitable rates to the list of

descriptive quantitative items( Adnan et al., 2011); the BOQ helps contractors at the pre-tender

stage in the formulation of their tenders (Davis & Baccarini 2004); it breaks down works in

formal detailed and structured manner for tendering (Adnan et al., 2011); the BOQ helps in the

observation, and analysis of risks for monitoring and controlling of construction process (Bu-

Qammaz et al., 2009); it assists in the valuation and payments of progress payments (Davis &

Baccarini , 2004); the BOQ provides a financial structure for contract administration (Adnan et

al., 2011); and it provides information for on-site checking (Jaggar, et al., 2002).

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4.8.4 Challenges Confronting BOQ Usage

Royal Institution Chartered Surveyors (RICS, 1991); in a study conducted revealed that the

usage of BOQ in the building construction sector has decline by 10% between 1984 and 1989.

The study also suggested that BOQ usage may totally disappear from the construction industry in

the future (Rashid et al., 2006). The use of non-traditional form of contracting such as the

turnkey, design and build, management contracting and build-operate-transfer contracts account

for this phenomenon of abandoning the use of BOQs (Rashid et al., 2006). Other reasons

adduced for abandoning the use of the include inability of the project team to fully utilized the

BOQ (Ing, 1984); many are not able to relate to the BOQ for everyday project development

process (Rashid et al., 2006); the use of the BOQ usually come to an end when the contractor

signs the contract (Rashid et al., 2006).

4.8.5 The Relevance of BOQ in Modern Construction Industry

The relevance of the BOQ in today’s construction industry needs to be examined in spite of the

challenges that confront the usage of the BOQ. Thus to the contractor; any project that involves

tendering will demand the preparation of a BOQ by the owner’s quantity surveyor or the

contractor’s quantity surveyor; in doing so the BOQ serve as a source of information effective

carry out the project management process (Rashid et al., 2006). The descriptions in the BOQ in

help the contractor to accurately arrive at a tender price; prepare project budget and cash flow;

compute the quantities of materials for the project; prepare labour requirements and schedules;

and to prepare claims (Rashid et al., 2006). Furthermore, Rashid et al. (2006) asserted that the

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BOQ helps the contractor’s planner to prepare the master programme for the project which helps

in the determination of project duration.

To the client, the relevance of the BOQ lies in the fact that it is a source of information for

monitoring cost, time and quality which are the concerns of every clients; furthermore, the

information in the BOQ helps in the preparation of cash flows, periodic project account and cost

variation for project management processes (Rashid et al., 2006). To the consultant, the BOQ

contains invaluable description and quantitative financial information for the use of the

consultant in project cost management right from the pre-construction to construction phase;

tender evaluation and selection of contractors for a project (Rashid et al., 2006).

4.9 AN EXPOSITION OF QUANTITY SURVEYING PRACTICE IN GHANA

Badu and Amoah (2004) in their work on Quantity surveying education in Ghana revealed that

the quantity surveying profession is a received profession from the British colonial masters as a

building accounting course incorporated. The QS profession in Ghana received the much needed

boost by the promulgation of Professional Bodies Registration Decree 1973 (National

Redemption Council Decree No. 143, Section 18:20) which give the nod to only qualified

members of the Quantity Surveying Division of the Ghana Institution of Surveyors to practice

the profession (ibid). Entry into the quantity surveying profession in Ghana is by written and

practical training examination where in the latter nomenclature candidates are expected to be

affiliated to seasoned quantity surveying firms for practical training (c.f. Badu & Amoah, 2004;

Laryea & Hughes, 2011).

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In a related development, a study conducted by Addai et al. (2009) on the “the Ghanaian quantity

surveyor and the emerging oil and gas industry” remains the most current existing research work

on quantity surveying practice in Ghana. The paper published in “The Quantity Surveyor” was

very in-depth and its review will be very crucial to this study. According to Addai et al. (2009),

it is very necessary for practitioners of the quantity surveying profession to “reinvent” the

profession of quantity surveying in order to meet the current global trend.

Knowledge and skills set of Ghanaian quantity surveyors encompasses technical skills,

knowledge and training project controls and contract procurement services (ibid). Traditional

services provided by Ghanaian quantity surveyors comprise of preparation of bills of quantities;

cost planning, estimating, bid and contract documentation and contract administration; non-

traditional services include feasibility studies, mediation, expert witness, appraisal, valuations,

project/construction management and facilities management; emerging services which Ghanaian

quantity surveyors must take advantage of in the oil and gas industry include estimating, cost

planning, cost control and procurement services (Addai et al., 2009). In order to provide services

efficiently, quantity surveyors ought to improve their soft skills in terms of communication,

leadership, teamwork and time management which are acknowledged by Addai et al. (2009) as

overlooked in Ghana (ibid).

Numerous challenges confronting the quantity surveying profession in Ghana as identified by

Addai et al.(2009) to be currently the most worrying include computing and information

systems; in this regard, quantity surveyors are “generally” conservative in the adoption and usage

of information technology(ibid); globalization and stiff completion as most of the services

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provided by quantity surveyors are no longer restricted to the QS practitioner; the higher level of

client expectation currently pervading the built environment fraternity will require quantity

surveyors to upgrade their skills and capabilities in meeting the demands of their clients in order

to stay in control of the market (c.f. Addai et al., 2009). The need to re-brand the quantity

surveying profession is the pragmatic step to take in resuscitating the profession; in this

direction, core expertise and competencies; usage of information technology, development of

new knowledge areas through research and development; specialization and diversification are

key steps to take in salvaging the quantity surveying profession (ibid). In concluding, Addai et

al. (2009) asserted that quantity surveyors need to quiver their risk averse attitude to become

more enterprising and change agent.

4.10 APPRAISAL AND SYNTHESIS OF THE LITERATURE REVIEW

From the review of extant literature on quantity surveying practice, Anago (2006); Olawale

(2006); Westcott and Burnside (2003); and RICS (1991) agreed quantity surveying profession is

a financial management position endowed with critical duties of measurement or quantification

inter alia. Identifiable roles of quantity surveyors has been variously and extensively identified

and recognized as one of the important roles provided by the professions in the built

environment. This position was strongly made clear in the literature by Olawale (2006); Eke

(2006); McGaw (2007); Burnside and Westcott (1999) and Bonnar (2007) who variously

identified the roles of quantity surveyors in their work. The changing roles of quantity surveyors

was espoused by the literature review notably in Ashwoth (1981) noting that quantity surveying

roles has significantly changed; a position strongly affirmed by the works of RICS (1991);

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Ashworth (1994) and reinforced by Keel et al. (1994) that 80% of clients perceive the roles of

quantity surveyors to be changing.

Numerous quantity surveying services were identified in the review of extant literature on

quantity surveying practice from various jurisdiction of the world. For instance Olatunde (2006)

was very extensive in this regard classifying quantity surveying services rendered to clients in

contract stages as pre- contract stage and post contract stage services; and further went on to

categorize the quantity surveying services in managerial nomenclature as project management

services; facilities management; and programme management. The classification of services of

the quantity surveying profession in Olatunde (2006) is largely similar to the works of

Anago(2006); Olawale (2006); Burnside and Westcott( 1999); Seely (1997); Davis et al. (2007)

except a slight difference in the works of Canadian Institute of Quantity Surveyors, CIQS(2002)

classification with variations notably mortgage monitoring and verification of borrower

payments. Pricing is the vehicle through which quantity surveyors recover the cost incurred and

earning reward for risk taken in providing services to clients. Varied dimensions of quantity

surveying consultancy pricing exist; some based on the stages of construction viz pre-contract

and post contract; in this case quantity surveyors price services actually provided at each stage of

construction project execution.

The review of extant literature uncovered percentage pricing/fee of the cost of construction as

the main quantity surveying consultancy pricing strategy; this is very clear in the works of Fees

Bureau (2011) and the Alberta Infrastructure and Transportation (2005) and The South African

Council for the Quantity Surveying Profession (2010). The phenomenon of percentage

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pricing/fees has the inherent deficiencies of under-pricing and over pricing as extensively

espoused in Owusu-Manu et al. (2012). This dilemma of under-pricing and over pricing raises

the issue fair pricing which is the focus of this research study. Hoxley (1998); Cruywagen and

Snyman (2005) alluded to massive consultancy services pricing/fee reduction leading to loss of

profit and overhead by quantity surveyors as a challenge confronting the profession. Odeyinka

(2006) added to the challenges of the quantity surveying profession identified by earlier works of

Hoxley(1998) inter alia; and supported by Cartlidge (2002) proffering by a sum up, the

mounting challenge confronting quantity surveying practitioners that they ought to get into the

head of their client to figure out their expectation.

Professional misconduct and unethical practices are part of most professional organizations;

recent misconducts in quantity surveying practice abounds in literature and include falsification

of reports to favour selfish interest; exaggeration of services rendered to deceive clients to better

pricing position; bribery and cartel formation to dupe clients especially when pricing consultancy

services were unanimously raised by Ferrell and Weaver (1978); McDonald and Zepp (1988);

Olatunji (2007); Newstom and Ruch (1975); Albratt et al. (1992); Olatunji (2007); Dubinsky et

al. (1980); and Dolecheck and Dolecheck (1984). The non-adoption of ICT in quantity surveying

practice has been underscored by the literature review with all the reviewed works pointing to

the fact that the quantity surveying profession is lagging behind.

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CHAPTER FIVE

RESEARCH METHODOLOGY

5.0 INTRODUCTION

This chapter discusses the research methodology adopted for this research study. It delves into

the principles upon which the research process is based leading to the adoption of survey

instrument for data collection and analysis. In this chapter the “what is done”, “why” and “how it

was done” aspects of the research will be the cardinal point of this chapter. In this thinking, the

research methodological terms and concept will be thoroughly discussed followed by the

exposition of their application in the research process.

5.1 PHILOSOPHICAL TRADITIONS AND CONSIDERATIONS

Guba and Lincoln (1994, 1998) categorize research paradigms into four namely positivism, post

positivism, critical theory and constructivism. According to Guba (1990), a paradigm is a basic

set of beliefs that guide an action. Denzin and Lincoln (1998) were of the view that a paradigm

consists of three main elements namely: epistemology, ontology and methodology. According to

Jacob (1987), epistemology is how we know the world; ontology is about the reality of nature;

and methodology is about how we gain knowledge of the world. Epistemology is a research

philosophy branch which controls the structure and processes of social research (Sarantakos,

2005). Epistemology informs the methodologies about the nature of knowing or about what

counts as a fact and where knowledge is to be sought (Campana, 2010). Simply put,

epistemology is the science of knowing (Babbie, 1995). Gall et al. (2003) added that

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epistemology is about studying the nature of knowledge and the process of acquiring knowledge

and its validation.

Babbie (1995) asserted that the concept of knowing is positivism. Positivist researchers develop

knowledge by collecting numerical data on observable behaviours of samples and then

subjecting these data to numerical analysis (Campana, 2010). Researchers over the years have

clearly indicated that the aim of positivism is to explain, predict and control a phenomenon

(Guba & Lincoln, 2004). Positivism concerns epistemological doctrine that physical and social

reality are independent of those who observe it; the observation of this reality is unbiased and

constitute scientific knowledge (Gall et al., 2003). According to Weber (2004) positivist

philosophy assumes that theoretical based predictions can be tested with data collected from the

objective world. Quantitative research is taken as identical to positivist research since it

contains epistemological characteristics that show how the methodology should control the

research (Sarantakos, 2005). Sarantakos (2005) pointed out that positivist research paradigm

consist of realist or objectivist ontology that guides the strategy of quantitative methods.

In consonance with the tenets of epistemology which is about where knowledge is to be sought;

and leaning greatly towards positivism, the researcher distributed the questionnaires to only

practitioners of quantity surveying consultancy as they have in-depth knowledge of what was

being investigated. In doing this only what counts as facts were collected as data for analysis in

order to churn out reliable and workable results. The survey instruments administered were

designed using key variables from the theoretical framework and the statistical tools which are

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mathematical and scientific in nature of analysis were adopted for data analysis. This clearly

positions the study within the positivist tradition.

Similarly, idealism branch of philosophy is cardinal to this research as the research seeks to

establish existing truth about pricing phenomenon using statistical analysis which is the cardinal

point of idealism. In this direction, the research endeavor to establish preexisting unchangeable

facts about consultancy pricing. Idealist believed that contemporary problems are deeply rooted

in the past hence the need to give the past prominence in the diagnosis of current pricing

phenomena. Idealism lays much emphasis or pertinence on past literature to chart a new path. In

this direction, this research study conducted a very elaborate literature review of pertinent issues

of pricing ranging from theoretical issues of pricing to the practice of general consultancy and

quantity surveying.

5.1.1 METHOD OF SCIENTIFIC INQUIRY AND REASON

Having adopted the positivism, it is appropriate to reason along the line of deductive logic in the

conduct of this research in attempt to unravel the phenomenon of pricing which is a social and

quantitative dynamic in nature. This is because, social issues and intrinsic (psychological) issues

affect pricing which is numerically communicated. Deductive reasoning operates from a general

to specific perspectives drawing conclusions based on facts (Burney, 2008); pricing is the

anticipation of reward for services rendered, this position is supported by adoption of deductive

reasoning, a stance advocated by Collis and Hussey (2003) that deduction allows the expectation

of a phenomenon; likewise, Robson (2002) sequentially outlined deductive logic in research as

deduction of hypothesis from theory; operationalization of the hypothesis (how the variables are

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to be tested) to determine the relationship between specific concepts and variables; testing the

hypothesis; confirmation or modification of the outcomes; and verification of the theory using

the findings.

Based on the above, the theoretical framework (refer to chapter two) was adopted in which

various concepts and theories of pricing were reviewed and synthesized leading to the

postulation of twelve (12) key hypothesis with fifty-three(53) independent variables and the

dependent variable mainly was pricing. The Chi Square test was adopted using the SPSS in

testing the hypothesis. The Chi Square test of independence was the specific type of chi Square

test used because to the nature of the hypothesis, they were composed of Dependent variables

(DV) and independent variables (IV). The conventional p-value of 0.005 was adopted in

determining the existence of relationship between the dependent and independent variables of

testing the hypotheses. The chi square value denoted by X2 and the p-value were used to accept

or reject the null hypothesis and to determine relationship between DV and IV. Where the X2cal

(calculated) > X2α (value from chi square table) the null hypothesis is rejected and when the p-

value ≤ 0.005, this indicate that a significant relationship exist between the DV and the IV.

5.2 RESEARCH STRATEGY AND DESIGN

5.2.1 Quantitative Research Paradigm

According to Wadsworth (1997), quantitative research is the systematic scientific investigation

of quantitative properties and their relationships. Quantitative studies are concerned with

behaviours consisting of measures or observation scales (or both) and they focus on the cause-

and-effect relationship between two variables (Krathwohl, 2004). Wadsworth (1997) stated that

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quantitative research is about “how many; to what extent, or how much aspect which involves

counting and other data analysis. The objective of quantitative research is to develop and employ

mathematical models, theories, hypotheses concerning the natural phenomena (Sarantakos,

2005). Measurement process is key to quantitative research because it provides the basis for

connection between empirical observation and mathematical expression of quantitative

relationships (Gall et al., 2003). The quantitative research generally uses critical approaches

such as the generation of models, theories and hypotheses; the development of instruments and

measurement; experimental control and manipulation of variables; collection of empirical data;

modeling and analysis of data; and evaluation of results (Gall et al., 2003). A positivist,

objectivist and realist approach (quantitative research) investigate and explain how one variable

affects another (Creswell, 2005). According to Creswell (2005), variables are the attributes that

the researcher studies. Sarantakos (2005) argued that as a strategy the quantitative research

(hinged on positivist, objectivist and realist approach) consist of vital criteria such as the use of

empirical methods; objectives; clarity in design and reliance on methods and procedures;

distance between the researcher and the participants; measurement and quantification; validity,

reliability, accuracy and precision; and ethical considerations. Quantitative research is an

appropriate educational research approach in which the researcher is free to choose what to

study, especially what is of interest to the research, asks specific and narrow questions, collects

numeric data from participants, analyses the data using statistics in an objective and unbiased

manner (Creswell, 2005).

5.2.1.1 Objectivism and Realism

Campana (2010) opined that realism is a feature of quantitative method because it perceives

reality to be objective, simple and fixed. Sarantakos (2005) adds that reality comprises of sense

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of impressions, which is what is perceived through the senses. Researchers perceive the features

of the social environment as having both social and physical reality. Objective reality means that

these features must exist independently of the individual who created or is observing them (Gall

et al., 2003). According to Guba and Lincoln (2004), a researcher who adopts the positivist

position believe that scientific inquiry must form the basis for the study of multiple social reality,

which means different individuals interacting with the social environment. Sarantakos (2005)

asserted that objectivism is significantly linked to reality as reality and truth exist objectively,

and can be discovered and adequately measured. Also, Creswell (2005) opined that the

observance of objective detachment, value neutrality, and unbiased approach must be taken by

researchers to quantitative research.

Drawing on from the above works cited, quantitative research studies explore behaviours with

much emphasis on the cause-and-effect relationship between variables; positivist researchers are

concerned about collecting data on numerical behavior of individuals for analysis. The art of

pricing borders heavily on consumer behavior and meaningful assessment of the variables

underlying pricing behavior and this can be identified quantitatively. Again, quantitative

research permits an objective and fair data analysis using statistics. The issue of fairness in

pricing is highly fundamental to this research and it is the basis upon which the research study is

hinged. This issue of fairness in pricing has made the adoption of the quantitative research

approach a non-negotiable issue and the most apposite method to be adopted as far as the

research is concerned. The quantitative research method adopted for the research is positioned in

philosophical paradigms such as epistemology (what is the fact and where the fact is to be

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sought); positivism (explaining, predicting, and controlling phenomenon); and objectivism and

realism (perception through the senses and social phenomenon).

The researcher adopted the quantitative approach to test the hypotheses postulated. The

presentation of results collected using tables and other visual techniques for ease of

comprehension and assimilation of the results are all features of the quantitative method of

analysis. In adopting the quantitative approach to this research, the objective perspectives of the

research was both descriptive and correlation in nature determined by the testing of hypotheses

using chi-square test. The correlational (i.e. relational in this case) aspect of the research borders

on the postulation and testing of hypotheses to determine the relationship between pricing as a

dependent variable (DV) and the independent or explanatory variables (IV) that can influence or

alter pricing levels. This is because the study seeks to investigate the attitude of consultants

concerning decisive factors that influence the pricing of their services.

The adoption of this strategy of testing hypothesis is crucial in order to generalize the findings of

the research since pricing is a universal phenomenon. The decision of pricing services by

quantity surveying consultants is individualistic hence it is pertinent for the researcher to be

detached from the study of this phenomenon to be able to identify the dynamics that are

independent in nature without the feelings and sentiments of the researcher. This assertion gives

much impetus to the adoption of the quantitative approach in this study. Pricing is a multifaceted

phenomenon which is expressed quantitatively hence the adoption of the quantitative method

with its attendant philosophical underpinnings is espoused in the research process as follows:

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5.2.1.2 The Survey Process

Cohen et al. (2005) observed that researchers who adopt positivist perception use a range of

traditional options such as surveys and questionnaires. According to Isaac and Michael (1997),

survey research is an avenue for answering questions that have been raised, to solve problems

that have been posed or observed, assess needs and goals set, to determine whether or not

specific objectives have been met, to establish baselines against which future comparisons can be

made, to analyze trends across time, and generally to describe what exist, in what amount and in

what context. Kraemer (1991) opined that survey research is used to quantitatively describe

specific aspects of a given population which consist of relationship between variables. Kraemer

(1991) further pointed other characteristics of survey research by asserting that the data required

for the survey research are collected from people by using certain portion of the population from

which findings can later be generalized back to the population. According to Glasow (2005)

independent and dependent variables are used to define the scope of survey research; and that

before the commencement of the research, the researcher must predicate a model of relationship

existing among the variables.

Survey design consist of two steps namely development of sampling plan and obtaining

population estimate from the sample data. The sampling plan involves the selection of sample;

determination of an adequate sample size; and the choice of media through which the survey will

be administered which comprises of telephone interview, face-to-face interviews and mailed

surveys using postal or electronic mail (Levy & Lemeshow, 1999 and Salant & Dillman, 1994).

In keeping with the above works demonstrated in extant literature, the rationale for adopting

the survey process for this study is embedded in the philosophy of the researcher that the survey

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process enables data to be gathered from large number of respondents in order to generalize the

results of the study. Again, the survey process was adopted because of its ability to allow for the

aggregation of the opinions and attitude of respondents on the various facets of quantity

surveying pricing under investigation. The sample for this study involves professionals

categorized as quantity surveyors by training and education and are working in firms. Survey is

appropriate for because of the intention to ascertain the relationship between key variables of the

researcher. Also the use of the survey process provided the basis for the testing hypothesis by chi

square test of independence; ranking of variables by relative importance index and the

classification and reduction of variables based on the common factors by the use of factor

analysis.

5.2.1.2 .1 Research Scope and Boundaries

The research was conducted in Accra the administrative and political capital of the Republic of

Ghana. The population of Accra constitute 16.3 per cent of the population of Ghana (Ghana

Statistical Service, 2012). Accra is also the capital of the Grater Accra region of Ghana bounded

by the Central Region, Volta Region, Eastern Region and the Gulf of Guinea. Accra is the key

industrial hub of Ghana, being home to every aspect of the Ghanaian economy ranging from

agriculture to tertiary services like the consultancy industry. Construction is one of the key

industrial sectors in Accra. This phenomenon is underpinned by its industrial nature and the

concentration of job seekers in the construction sector by people migrating from the rural areas.

As construction activities boom in Accra, it implies that more professionals including quantity

surveyors in the construction industry will gravitate towards the Greater Accra.

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Figure 5.1: Map of Greater Accra Region (Source: UN-HABITAT, 2009)

5.2.1.2 .2 Sampling Techniques and Sample Frame

Salant and Dillman (1994) pointed out that sample selection is hinged on population size; the

sample media and its cost of use; and the degree of precision required. Participants in the sample

must be selected at random with equal chance (ibid). A prerequisite to sample selection is to

define the target population as narrowly as possible (Salant & Dillman, 1994). On the contrary, it

is sometimes not possible to know the true population hence Attewell and Rule (1991) proposed

that a theoretical sample may be used; theoretical sample purposively selects organizations that

demonstrate the desired characteristics that are the focus of the researcher’s study.

According to Ghana Institution of Surveyors, GhIS (2012), the membership of the quantity

surveying division of consist of 68 firms; 37 fellows; 282 professionals; and 53 technicians; this

sum up to 372 members and 68 firms. Therefore the sampling frame for this research is 372

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quantity surveyors operating in 68 quantity surveying firms and other institution but are

performing QS functions. Having determined the sampling frame for this study, the researcher

adopted the Kish (1965) formula which is popularly used in most empirical works as evidenced

in the works of Bolstein and Crow (2008) as follows:

n¹

n =

1+ n¹/ N

Where;

n = sample size

N = total population size

s2

n¹ = v2

s = maximum standard deviation in the population element at a

confidence interval of 95%

s2 = p (1-p)

p = the proportion of population elements

v = standard error of the distribution at 0.05

s2 = 0.5(1- 0.5)

s2 = 0.25

0.25

n¹ = 0.052

n¹ = 100

Now N = 372

100

Therefore, sample size, n = 1 + 100/ 372

n = 78.8

Hence, Sample Size, n = 79

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Therefore the appropriate sample size for the study was 79 respondents (quantity surveyors).

This means that questionnaires should be distributed to 79 respondents to achieve 95%

confidence interval.

5.2.1.2 .2 .1 Sampling Technique Adopted

Consistent with the assertion of Salant and Dillman (1994), the respondents for the research were

selected by using simple random sampling technique to give each respondent an equal chance of

being selected as active participant of the survey process. This is necessary because the roll of

QS practitioners is available. Similarly, the adoption of simple random sampling will enable the

generalization of the research findings to be easier than the utilization of other sampling

methods. In order to pursue randomization in the selection process, a random number table (see

Appendix 2) was utilized in that regard. Using the rules of simple random sampling, and the

information available to the researcher: 372 of registered professional quantity surveyors, 79 QS

were selected (i.e. sample size) to participate in the survey. Hinged on the rule that each member

of the survey population (sampling frame) must have an equal chance of being selected to

participate, the random table in appendix two was the main tool for the execution of the task of

selecting 79 respondents from a survey population randomly. Based upon the above data and the

random table available, 3-digit numbers are required. It is also necessary to enter the random

number table randomly. This was accomplished by pulling out one of the Ghana Cedi notes from

pocket which turned out to be twenty Ghana Cedis (GH₵ 20.00) with a serial number of

VL7745452. The last two digits being 52 were selected as entry point. Now the row and the

column would have to be determine randomly, therefore a twenty pesewa (20p) coin was tossed,

a head showing implies the first digit is 5 which was designated as the entry column and 2 was

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designated as the entry row and vice versa. With this procedure, the researcher tossed the twenty

pesewa coin and a tail showed which means the second digit designated the column which is 2

and 5 designated the row. Hence the random table was entered as indicated with arrows in

appendix two. The names of all members of the target population were arranged alphabetically

and serialized. With this, the random selection began by using the first random number of 3114,

this number was separated to 31 and 14, and reading from the right to left on the random table,

the QS with number 31 was selected to be the first respondent. Moving down the column, the

next number was 2463 and separating this random number because the sample size was a two-

digit number and reading from the right to the left of the table, the QS with serial number 24 was

selected. Numbers selected which were not within the sample size range of 1 to 79 were ignored

and the next number within the column was considered. The process continued until the sample

size was exhausted. Numbers already selected were crossed out from the survey population list.

5.2.1.2.3 Data Collection Methods

A data collection strategy that quantitative researchers mostly prefer is survey or questionnaires

(Sarantakos, 2005). Surveys questionnaires are the most frequently used method of data

collection in the social sciences and are mostly mistaken as a method of social research

(Sarantakos, 2005). Cohen et al. (2005); Creswell (2005); and Krathwohl (2004) asserted that

survey questionnaires are used in diverse ways as an instrument for data collection. Survey

questionnaires are excellent techniques (method) of data collection with closed and open ended

questions (Sarantakos, 2005). Creswell (2005) opined that quantitative research uses an

instrument to measure variables in a study; this instrument consists of specific questions and

response alternatives or possibilities that the researcher has established as a priori to the study.

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According to Campana (2010), survey questionnaires are adopted to generalize the results

collected from a smaller number to a larger number. Survey questionnaires are recognized as the

suitable method of data collection from a large number of participants when the researcher is

able to clearly convey the appropriate information of interest across with suitable measures of

variables (Creswell, 2005; Gall et al., 2003; Krathwohl, 2004; and Sarantakos, 2005).

Survey questionnaires also aim at one or more groups of people in obtaining their opinions and

attitudes concerning a phenomenon under study (Funnell, 1996). Survey questionnaires have

numerous advantages consisting of the ability to access a large number and geographically

dispersed population; gathering of data by means of voluntary participation devoid of

compulsion or force; reduction of researcher bias; and minimization of time requirement for the

respondent and the researcher (Creswell, 2005). A good questionnaire consists of questions that

elicit different types of information from respondents (Gall et al., 2003). Questionnaires must be

kept short, questions organized in easy manner and avoiding double-barreled questions (Gall et

al., 2003). According to Creswell (2005), quantitative investigators use both ordinal and interval

scales; of these, interval scales provide the most variation of responses and lend themselves to

stronger statistical analysis. Sarantakos (2005) and Creswell (2005) suggest that the Likert scale

is particularly suitable for studying attitudes; Cohen et al. (2004) adds that the use of Likert scale

gives the researcher the opportunity to build differences, measure attitudes, and generate hard

data on the respondents; and it also offers information such as frequency, flexible responses and

linkage between opinion and quantity. The Likert scale is a five point response scale used to

measure responses to a set of statements; and permits the measurement of degrees of difference

but not the specific amount of difference (Kapadia-Kundu & Dyalchand, 2007). Attitudes and

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perceptions have traditionally been measured on a five point Likert scale and its variants

(O’Keefe, 1991).

The design of an effective survey questionnaire is hinged on four critical pillars namely question

wording, categorization, coding of variables and general acceptance (Sarantakos, 2005). Survey

instrument design must be preceded by firstly defining clearly the focus of the study; and

secondly, translating the study objectives into measureable factors that contribute to the focus of

the research (Salant & Dillman, 1994). According to Fowler and Floyd (1995) a good question is

one that produces answers that are reliable and valid measures of something that we want to

describe. McIntyre (1999) observed that survey questions must use words that commensurate the

educational levels of respondents. Fowler and Floyd (1995) added that both the question and the

response options must be clear to both the respondent and the researcher. The wording should

prevent alternative interpretations or incomplete sentences that would allow misinterpretation

(Browne & Keeley, 1998; Fowler & Floyd, 1995; and Salant & Dillman, 1994). Survey

questions should not be combined where the respondent might wish to answer affirmatively for

one part, and negatively for the other part (Glasow, 2005).

Survey questions must be feasible to answer and respondents must be willing to answer them

(Fowler, 1995). Questions must be civil and ethical (McIntyre, 1999); questions that ask

respondents for data they do not have must be avoided and those questions that assume the

respondent knows something about the subject must not be asked; personal questions,

objectionable statements that reflects the researcher’s bias and questions that require difficult

calculations must be avoided; and Undefined abbreviations, acronyms, and jargons should not be

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used (Salant & Dillman, 1994). Onerous questions, double negatives questions and long

questions that lose the respondents in the reading must be avoided (McIntyre, 1999).

In questionnaire type of data collection, standards such as validity and reliability are very crucial

in which researchers look for two types of responses at group level and individual level (Gall et

al., 2003). According to Cohen et al. (2005) validity can be achieved by choosing an appropriate

time frame; selecting an appropriate methodology; selecting and designing an appropriate

instrument to collect data; and ensuring that the study comply with its original hypothesis.

Sarantakos (2005) supported the assertion of Cohen et al. (2005) on validity by suggesting that

validity in quantitative research is hinged on the instrument that measures relevance; precision;

accuracy and compliance with the research hypothesis. Burns (2000); Cohen et al.(2003); Gall et

al.(2003) and Sarantakos (2005) all agree that internal validity is necessary for ensuring validity

in a research; thus internal validity refers to internal study mechanisms that ensure research

design, method and approach do not have impact on the results of the study. According to

Campana (2010), instrument design; instrument changes during the study; diverse methods of

data collection over the study periods; changes in personnel in the study; and inconsistent

recording techniques will affect the outcomes of the study. Campana (2010) clearly pointed out

that validity and reliability are critical to conduct and data collection of a research study. In this

thinking Campana (2010) identified validity broadly as content and construct. Content validity is

ensured by piloting the questionnaire with qualified practicing personnel to ascertain details

concerning wording of questions and industry relevance while construct validity is address by

ensuring statistical procedures; tabulation of results; and application of non-statistical results in

examining, discussing and interpreting the scores align to the questions (Campana, 2010). The

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key issues of validity and reliability were achieved by the adoption of factor analysis in which

the KMO values and Barlett test of sampling adequacy were used to ascertain validity and

reliability (refer to factor analysis in chapter 6 and section 5.3 of this chapter).

Sarantakos (2005) clearly pointed out nine keys for ethical consideration consisting of:

explanation of research purpose; risk assessment; confidentiality and privacy; informed consent;

data access and ownership; data collection; advice; mental harm; and research approvals through

ethics committees. Creswell (2005) opined that a cover letter should accompany the

questionnaire soliciting responses from respondents to assure them of confidentiality and

anonymity. Similarly, Cohen (2005); Creswell (2005); and Gall et al.(2003) all agree that the

cover letter is key to the research project and enhances a positive view if the study and fulfilling

the principles of ethics at the in addition. Glasow (2005) suggests the respondent is a source of

error; and responses to survey questions may not reflect the actual beliefs, attitudes or behaviours

of respondents. Browne and Keeley (1998) added that respondents may intentionally provide

false responses to invalidate the survey results or choose not to reveal their true insight for

personal reasons, which reasons may not be rational or even understood by the respondent. Isaac

and Michael (1997) identified two errors of measurement as the tendency to agree with a bias

inherent in the wording of a question to the extent that the respondent more readily agrees with

positively worded questions; and respondents may consistently give high or low ratings,

reflecting a rater bias that depart from the validity of the results.

Drawing on from the above existing works extensively, the source of data for this study was

primary as a result of the adoption of idealist perspective that issues be holistically examined. In

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this research, idealism was fulfilled as a result of elaborate literature review conducted within the

general consultancy practice milieu, quantity surveying practice environment and a theoretical

framework on the general pricing theories that are widely acceptable. This review culminated

into the identification of key variables for the research study. The data was ordinal in nature as a

result of the five point Likert scale adopted to measure the perception of respondents.

The tool for data collection was a survey questionnaire fitted onto four pages of A4 sheets

measuring various aspects of the research of interest to the researcher. There were eleven

questionnaires addressing key aspects of the research notably the aim and objectives of the

research which sought to tackle the general pricing milieu in quantity surveying practice and

these questions touched on price and value; just price; objectives of pricing; pricing strategies

and parameters; criteria for consultancy bid price success; dynamics of pricing risks; taxation

and inflation; components of quantity surveying consultancy services pricing; challenges

confronting QS consultancy practice and the QS consultancy services. Questions on the profile

of respondents bordered on the status of their firms; working experience; rate of work acquisition

and sectors of operation. These questions were necessary to ensure internal validity of the data

collected. Questionnaires are suitable for survey processes to gather data on social phenomenon

on individuals, groups and institutions located within large geographical areas. In using

questionnaire as a tool for gathering data in this study, care was taken in the construction of

questions. In the first place, the questions were closed-ended requiring respondents to provide

responses on key variables. Standardization was carefully observed in order to ensure all

respondents answer the same questions with the same responses; this is one of the reasons for

using questionnaire as a tool because control is of essence in survey process unlike laboratory

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research where samples are under control in confinement and conditioning. In ensuring

uniformity, same wording of questions were maintained throughout the questionnaire and the use

of jargons or technical words were minimal. In terms of ethics and communication, an

introduction was provided bordering on the title of the research, the aim and objectives of the

research and respondents were highly assured of their confidentiality. The sequence of the

questions were such that they draw the respondents gradually into the interaction with the

questionnaire beginning with issues that respondents are very familiar with by graduating the

questions from simpler to thought provoking professional issues in practice. The questions were

devoid of sensitive issues and the privacy of respondents was highly respected. Practicality and

relevance of questions were achieved by crafting questions that are of much interest to

respondents in the practice of quantity surveying consultancy services pricing. To aid

respondents’ responses to avoid measurement errors, tables were used to profile the variables to

majority of the questions to help in ticking appropriate boxes based on the instructions provided

in the introductory section of the questionnaire; this will also make the recording, aggregation,

analysis and organization of data into standardized format easier for the researcher.

The questionnaire was self-administered to respondents by the researcher. Respondents were

given time to respond to the questions within four (4) weeks. The questionnaires were later

retrieved after four weeks by which time majority of the respondents had considered and

responded to the questionnaire. In all a total of 110 questionnaires were distributed in order to

achieve the appropriate sample size of 79. At the end of the four week field work of

questionnaire administration to respondents, 79 questionnaires were retrieved producing a

response rate of 71.8 per cent.

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5.3 DATA ANALYSIS METHODS

A variable’s measurement scale determines which statistical methods are appropriate (Agresti,

2002). A variable is a characteristic that is measured on individuals (Tebbs, 2006). According to

Ryan (2004) a variable depict the characteristics of a population which can contain different

values. According to Agresti (2002) variables are suitable for measuring attitudes and opinions;

and the subjective evaluation of certain characteristics. In a research, response scales measure

attitudes, attributes, client satisfaction, cultural beliefs and values; they are means of collecting

responses from people on an instrument (Kapadia-Kundu & Dyalchand, 2007).

5.3.1 Descriptive Analysis

After the collection of data using the questionnaire, there exist an enormous data that needs to be

presented to audience. As a matter of fact, the data collected require summarization in order to

deduce meaningful information from it. The descriptive statistics is the analytical tool for this

agenda. According to Ryan (2004), descriptive statistics consists of methods for presenting and

summarizing data. The descriptive statistics in the analysis of data as a priori to easy digestion

and understanding of large quantities of data; and provision of opportunity to communicate the

research results to others (Ryan, 2004).

5.3.2 Data Presentation Using Tables

Good tables are integral part of packaging and presenting data to audience. Tables help to

minimize the amount of data values in a text; and aid in eliminating less important variables in

discussing the data (UN, 2009). According to Miller (2004), good tables must aid audience to

find and understand numbers within the table; and both the layout and labeling must be

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straightforward and unobtrusive in order to draw substantive attention to the data which is

conveying information to audience. Tables should contain concise and well-organized data that

supports the analysis to be made (ibid, 2009). The UN (2009) clearly pointed out that tables

should be able to stand on their own; and should contain descriptive title; indicate source. The

UN (2009) identified the five support components needed to describe data presented in a format

to include the table title (should give a clear and accurate description of the data, it should

answer the three questions “what”, “where” and “when.”); column headers (at the top of the

table, should identify the data presented in each column of the table and provide any relevant

metadata (e.g. unit of measurement, time period or geographic area); row stubs (in the first

column of the table, should identify the data presented in each row of the table); footnotes(at the

bottom of the table, may provide any additional information needed to understand and use the

data correctly (e.g. definitions); and the source line (at the bottom of the table, should provide

the source of the data, i.e. the organization that produced the data and the data collection method

(e.g. population census or labour force survey).

Drawing on from the above, the data collected from the field through the use of questionnaire

was presented in table format which belong to the demonstration or presentation categories of

tables in order to highlight key figures and as this research is analytical. The results were

presented in table format as it will aid in the analysis of key and critical results. The tables were

corresponding to the number of questions from 1 to 11 in the questionnaire and the number of

hypothesis tested and the each case of factor analysis. The tables were designed to suit the five

components of table design identified by UN (2009) as follows; table title which comprised of

legal status; firm’s years of experience; rate of work acquisition; sectors of operation; concept of

price and value; project pricing(consultancy pricing); concept of risk; concept of taxation and

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inflation; quantity surveying consultancy services pricing components; challenges confronting quantity

surveying consultancy practice; and quantity surveying consultancy services; the column headers

comprised of the weighting, Relative Importance Index(RII) and rankings; the row stubs consisted of key

variables encapsulated in the respective table titles; and the source line indicated.

5.3.3. Relative Importance Index (RII)

According to Soofi et al. (2000), the relative importance index refers to quantities that compare

the contribution of individual explanatory variables to a response variable. Carpio et al.(2007)

asserted that the relative importance index is used for determining the relative significance of

attributes in a decision maker’s choice of one out of several alternatives in the revealed

preference setting. Carpio et al. (2007) opined that the determination of the relative importance

of attributes is required for the construction of an index summarizing the overall effect of a group

of attributes; the calculated indexes are then used to compare and rank the attributes. According

to Carpio et al.(2007), the RII proposed by Soofi et al.(2000) is one of the measures that can be

used to gauge the relative importance of variables. The Likert scale is a five point response scale

used to measure responses to a set of statements (Kapadia-Kundu & Dyalchand, 2007). Attitudes

and perceptions have traditionally been measured on a five point Likert scale and its variants

(O’Keefe, 1991).

The frequently used measure of relative importance is the unstandardized coefficients (Carpio et

al., 2007); these unstandardized coefficients signify the impact of “one- unit” difference in the

independent variable on the dependent variable (Carpio et al., 2007). As a panacea to this one-

unit paucity in use of unstandardized coefficients; Menard (2004) strongly advocated for the use

of standardized coefficients in the determination of relative importance for two main reasons:

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firstly, for variables with no natural metric such as (1= strongly disagree, 2 = disagree, 3 =

neutral, inter alia) a “scale free” standardized coefficient may be more significant than

unstandardized coefficient; and for variables measured in natural metric, it is unclear whether a

one unit-change, or a 0.1 unit change, is “big” or “small” with respect to the scale.

Indeed, the relative importance index (RII) has been widely used by numerous researchers

notably Badu et al. (2013); Nkado (2001); Johnson (2000); and Jeyamathan and Rameezdeen

(2005) in identifying the significance of variables of different dimensions in their research work,

hence the adoption of the RII is appropriate for this study as it has been used by other seasoned

researchers in built environment as indicated above. Another justification for using the RII lays

in the fact that the relative importance analysis can be performed for groups of variables and not

for only individual variables (Carpio et al., 2007). According to Wilen and Abbott (2006)

relative importance serves as useful measures of significance.

Hinged on the above works cited, and in keeping with the advocacy of Menard (2004) the

Relative Importance Index (RII) was used to ascertain the perception of respondents on critical

pricing variables since pricing is attitudinal it is therefore necessary to measure the significance

of the key pricing variables in order to be fully aware of their vitality in the determination of

quantity surveying consultancy services pricing.

The RII was determined by:

Σ W

RII =

A*N

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Where W = weight given to each pricing variable by respondents ranging from 1 to 5 on a likert

scale; A = highest response integer, 5; and N= total number of respondents (c.f. Badu et al.,

2013).

5.3.4 Inferential Analysis: Hypothesis Testing

Inferential analysis intends to make generalizations from a sample to the wider population

(Gabrenya, 2003). Inferential analysis largely dwells on the deployment of statistical techniques

in testing hypothesis to derive implications from a research (Baddie & Halley, 1995; Kolawole,

2001). Inferential analysis have been categorized into two main streams namely parametric

analysis consisting of t-test, analysis of variance and Pearson Product Moment Correlation

Coefficient; and non-parametric analysis comprising chi-square test, the kolmogorov-Sminov

test, Mann-Whitney U test, Sign test, Wilcoxon matched-Pairs Signed–ranks test and the

Lambda symmetrical/ asymmetrical test (Adeyemi, 2009; Berenison, & Levine, 1979). The

choice of these two types analysis(parametric and non-parametric) is dependent on key factors

associated with the study instrument which were used by the researcher or the nature of the study

which will later manifest in the type of data collected for analysis. In this regard, Adeyemi

(2009) pointed out factors which determine the choice of parametric or non-parametric analysis

to include scale of measurement of data collection instruments, sampling method adopted,

sample size and the number of independent variables. Non-parametric tests are distribution-free

tests appropriate for samples drawn deemed to be not normal (Champion, 1970). They are

equally suitable for data obtained through the utility of nominal scale of measurement; ordinal

measurement and processed in ranked order of 1st, 2nd, 3rd, 4th and indefinitely. Non-parametric

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analysis is also suitable when the research does not have idea about the nature of the distribution

(Siegel, 1988).

Hypothesis testing is a technique adopted by researchers to draw conclusion on the results of a

data collected in a research investigation in order to make useful conclusions on a population of

interest (Deveries, 2007). Hun (2010) asserted that a hypothesis is an assumption about the

characteristic of a particular population of interest. Hun (2010) clearly noted that a first-class

hypothesis should be precise enough to be falsifiable to make it acquiescent to testing. A wide

range of procedures exist for the testing of hypothesis, notable among them are z-tests, t-tests,

correlations, ANOVAs, chi square inter alia (Deveries, 2007).

According to Deveries (2007), hypothesis testing is conducted by researchers to identify the

effect that a variable of interest will have on a particular population. Testing hypothesis for a

research study is also aimed at the utilization of the sample data and to infer from the results to

determine the level of real relationship between variables. According to Kochanski (2005),

hypothesis testing is apposite for critical application or for drawing conclusion. Hypothesis

testing results into either ‘null hypothesis (Ho)’ or the ‘alternative hypothesis (H1); for which the

p-value is the probability of obtaining a result as large as that observed in the sample if the null

hypothesis were true; and Alpha, the probability of falsely rejecting the null hypothesis

Typically, the alpha is set at .05 or .01( Anglim, 2007). The p-value is about the statement of

values that never occurred; it is computed based on the distribution of the test statistic assuming

the null hypothesis is true (Anderson et al., 2000). According to Anderson et al. (2000), the

appropriate interpretation of the p-value is based on the probability of the data given the null

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hypothesis is not the converse. The p-value indicates the degree of consistency of the data with

the null hypothesis (Ho) (Anderson et al., 2000). Similarly, the p-value is perceived as the degree

of risk that researchers take in rejecting the null hypothesis (Hun, 2010). When the p-value is less

than 1%, then there is an overwhelming evidence to infer that the alternative hypothesis is true

then conclude that the test is highly significant; p-values between 1% and 5% are deemed to

possess strong evidence to infer that the alternate hypothesis is true hence the result is

significant. Similarly, if the p-value is between 5% and 10% then there is a weak evidence to

support that the alternate hypothesis is true; when the p-value is greater than 5% then the test is

not statistically significant; and in the event that the p-value is greater than 10% then the there is

no evidence to infer the alternative hypothesis is true.

According to Anglim (2007), if the p-value is less than alpha (for instance .05), the probability of

the null hypothesis being true is low, hence reject the null hypothesis and accept the alternative

hypothesis. According to Anderson et al.(2000) a test statistic is first calculated from the

sampled data and judged against its hypothesized null distribution to assess the consistency of

the data with the null hypothesis; if the values of the test statistic are more extreme, then it

implies that the sample data are not consistent with the null hypothesis. In addition, an arbitrary

level (α) is set as a cutoff to serve as the basis for deciding statistically significant and

statistically non-significant results (Anderson et al., 2000).

5.3.4.1 Steps for Hypothesis Testing

Hypothesis testing which is part of the scientific method is conducted according to set criteria in

order to achieve a successful result; thus Deveries (2007) and Hun (2010) identified the criteria

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for hypothesis testing as stating the hypotheses (the null hypothesis(H0) must be stated which

intends that there is no change as a result of the study. The null hypothesis (Ho) postulates that

the independent variables will have no effect on the dependent variables which makes the

population mean to remain same. The alternate hypothesis (H1) which establishes that there will

be an amount of change in the population mean as a result of the study seeks to suggest the

independent variable will have an effect on the dependent variable. It is worthy to note, the

alternate hypotheses are not meant to determine the direction of change, and they can

demonstrate that a change is either positive or negative).

The second criteria is setting the critical region ( this involves defining the alpha level and the

critical region which consist of two extreme scores that are very difficult to obtain if the null

hypothesis(H0) is true. Indeed the result has to be beyond these two extreme scores for them to

be statistically significant. The alpha level in this instance is a probability value and it sets the

critical region indicating that the probability that a result occurs beyond the critical region is by

chance). Collecting data and computing statistics (the researcher conducts study collects data

and manipulate the data using statistical test; the statistical test results are then used to determine

if the null hypothesis should be accepted or rejected). Making a decision (this involves the

rejection of the null hypothesis which implies that the is a significant change in the population

mean this goes to explain that the alternate hypothesis must be accepted; and failing to reject the

null hypothesis which means that there was no change in the population mean). The null

hypothesis is rejected in order to avoid the result of the study from being falsified through further

research (Deveries, 2007).

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5.3.4.2 Approaches/Criteria to Hypothesis Testing

Hun (2010) also added to the approaches to testing hypothesis by advocating test statistic

approach; p-value approach; and Confidence Interval(CI) approach (state H0 and H1; determine

test size α or 1- α, and a hypothesized value; construct the (1- α)100% confidence interval; reject

Ho if a hypothesized value does not exist in CI; and substantive interpretation). According to Hun

(2010), the test statistic approach calculates a test statistic from the empirical data and compares

it with the critical value and a test statistic larger than the critical value leads to the rejection of

the null hypothesis; in adopting the p-value approach, researchers compute the p-value on the

basis of a test statistic and then compare it with the significance level(test size), if the p-value is

smaller than the significance level, the null hypothesis is rejected; and finally, the confidence

interval approach create confidence interval and check if the hypothesized values fall within this

interval, if the hypothesized value cannot be found within the confidence interval, the null

hypothesis is rejected. Figure 5.2 below demonstrates the methods for hypothesis testing as

advocated by Cohen (2010).

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Statistical Testing Confidence Intervals

Figure 5.2: Methods for hypothesis testing ( Adapted from Cohen, 2010)

5.3.4.3 Interpretation of Hypothesis Test Result

The results of a hypothesis test ought to be interpreted to give optimum meaning to the outcome

of the test. The kind of interpretation or inference drawn depends on the test approach adopted;

in the case of statistical testing approach, whenever the p-value is greater than α, the null

hypothesis is not rejected and the inference is that the difference or the association of observed

groups is likely due to chance; and in using the confidence interval approach, a null hypothesis is

not rejected if the confidence interval encloses the pre-established null value and in this instance

it is proper to infer that the difference or the association of observed groups is likely due to

chance (Cohen, 2010).

Set α

Compare p-value to α

p > α

Obtain test statistic and

Corresponding p-value

Conduct Statistical test

p < α

Reject H0

Set confidence limits and

establish null value

Calculate point estimate and

confidence interval (CI)

Determine if confidence

interval includes null value

Null is not

included in

CI

Null is

included in

CI

Do not reject H0

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5.3.4.4 Some Key Statistical Tools for Hypothesis testing

5.3.4.4.1 ANOVA

Tang et al. (2008) pointed out that the ANOVA is used to test the perceptions of respondents

concerning the phenomenon being investigated. The higher the F value; the significant the

difference in perception among respondents. According to Underwood (1997), analysis of

variance (ANOVA) provides tremendous and powerful tool for statistical tests of factors and

their interactions in experiments. Anderson (2006) opined that the fundamental nature of analysis

of variance is to compare variability within groups versus variability among different groups,

using the ratio of the F-statistic. The larger the value of F, the more likely it is that the null

hypothesis (H0) of no differences among the group means (i.e. locations) is false (Anderson et

al., 2006).

5.3.4.4.2 Correlation

According to Varalakshmi et al. (2005), correlation is an analytical tool that measures the extent

of relationship between two or more variables. Correlation expresses the inter-dependence of two

sets of variables upon each other. Correlation involves measuring relationships between price

and quantity; costs, sales and price; income and expenditure, price and supply, demand and

supply; and it serves as the basis for the concept of regression.

5.3.4.4.3 Regression

According to Varalakshmi et al.(2005), regression is the measure of the average relationship

between two or more variables in terms of the original units of a data. Sykes (2000) asserted that

regression analysis is a statistical tool for investigating the relationship between variables in

which the investigator intends to seek the causal effect of one variable upon another variable.

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According to Sykes (2000), a key fundamental requirement for a regression study is the

formulation of hypothesis about the relationship between variables of interest. Sykes (2000)

opined that multiple regression techniques allow additional factors to enter the analysis

separately so that their effect can be estimated. Multiple regression is valuable for quantifying

the impact of various simultaneous influences upon a single dependent variable even when the

investigator is only interested in the effects of one of the independent variables. After identifying

the relationship that exists between two or more variables, there may be the need to predict the

value of one variable given the value of the other variable (Varalakshmi et al., 2005). The

prediction is hinged on the average relationship derived statistically by regression analysis

(Varalakshmi et al., 2005). Regression has several uses including the establishment of functional

relationship between two or more variables; a viable tool in economics and business research as

a result of its potential to establish cause and effect relationship; and the prediction values of

dependent variables from values of independent variables (Varalakshmi et al., 2005).

5.3.4.5 Adoption of Chi Square Test for Hypotheses Testing

Two key underlying assumptions of the Chi-square test state that the sample size must not be less

that 5 (Champion, 1970); and samples must be achieved through independent observation

(Adeyemi, 2009). Chi-square test is appropriate for an entire population irrespective of whether

the data fits normal distribution (Adeyemi, 2009). The three main types of Chi-square test

include Chi-square Goodness of Fit Test; One-Dimensional Chi Square; and Chi square Test for

Two Independent Samples (ibid, 2009). The Chi-Square test is a non-parametric test of

significance targeted at testing the differences or relationship between two variables (Adeyemi,

2009). According to ITS (2010) the chi-square test is an analytical tool used to examine the

differences between nominal or categorical variables; it analyzes whether the observed frequency

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distribution of a categorical or nominal variable is consistent with the expected frequency

distribution. It is normally useful for estimating how close an observed distribution matches with

expected distribution; testing hypothesis; and determining whether two random variables are

independent.

Scheaffer (1999) observed that the chi square test indicates the relationship in data. According to

Zibran (2007), the chi-square test is appropriate for data in frequencies; and the most common

use is to ascertain the probability of association or independence of facts. The key ingredients of

the chi-square test identified by Zibran (2007) consist of the population, sample being the subset

of the population; parameter which is the value generated from or applied to a population;

variable which is anything that can be codified; and can have value from a set (domain) of more

than one values; nominally scaled variable; and contingency table. According to Zibran (2007)

the chi-square test is given by:

(Oi - Ei)2

X2 = ;

Ei

where Oi= observed frequencies; Ei= expected frequencies; i= 1, 2, 3…….n, and n= number of

cells in the contingency table. The use of the chi-square test is restricted to large samples (ibid,

2007). Zibran (2007) concludes that the chi-square test helps in ascertaining whether the

classifications on a given population are dependent on each other or not.

Drawing on from the above extant literature extensively, the Chi-Square test is adopted for this

research as a result of the scale of measurement adopted in data collection which is mainly

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ordinal. Another reason for using the chi square to test hypothesis is the objective of ascertaining

the relationship between pricing as the main dependent variable and independent variables which

have the potential of affecting pricing to cause changes in price levels. Chi-square Test was

conducted using the SPSS to determine if significant relationships exist between dependent and

independent pricing variables. Pricing is the main dependent variable and factors relating to

pricing are independent variables; in this case independents variables are all variables within the

concept of price and value; pricing strategies; project pricing(consultancy pricing); concept of

price and risk; taxation and inflation in pricing; and components of consultancy services pricing.

In the conduct of this research, the Chi-Square test result was reported by first stating the X2

(Chi-Square value), followed by the chi square value from the chi square distribution table( Xα);

the degrees of freedom (df); and the significance level represented by p-value in a bracket.

Therefore, the Chi-Square test results for hypotheses tested in this research were reported in the

format (X2, Xα, df, and p-value). The exact significance levels were reported but in

circumstances where they are less than .001, they were denoted as p < .001. In this research, a

pricing variable was considered to be significant if its significance level represented by p-value

on the hypothesis result table is less than the conventional or the alpha value (α) = 0.005 which

was adopted for the test using the SPSS. The assumptions underlying the Chi-Square Test for

Independence adopted for this research are that: the respondents were randomly selected;

expected frequencies are grater or equal to 1 (E ≥1); and not more than 20% of expected

frequencies are less than 5. The null hypotheses were denoted by Hoi while the alternative

hypotheses were denoted by H1i; where i represent the serial number of the hypothesis being

tested.

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5.3.4.6 Framework Development: Utilizing Factor Analysis

For factor analysis to be suitable, the number of variables in a study must in the range of 20 to 50

(Po-Yi & Chen, 2004). Factor analysis is conducted for varied purposes including the quest for

improving measures; evaluation of construct validity; hypothesis testing; development and

enhancement of instrument’s scales (McCauley et al., 1994); and reduction of data and the

comprehension of its intrinsic characteristics and constructs (Conway & Huffcutt, 2003;

Williams et al., 2012). The reasons for factor analysis are to reduce the number of variables; to

determine the relationship between variables; to discover and evaluate the unidimensionality of a

theoretical concept; to examine the validity of a scale; to ensure the simplification and

effectiveness of analysis and interpretation; to address phenomenon of high correlation between

two or more variables; to develop theoretical frameworks (which is the focus of this particular

research); and to confirm or reject theories ( Williams et al., 2012).

According to Po-Yi and Chen (2004), factor analysis must be conducted in accordance with

these procedures: Bartlett’s Test of Sphericity to test for the existence of common factors within

a collected data to necessitate the conduct of the factor analysis. Estimation of common factors

to ascertain the suitability of the sampled questionnaire for the factor analysis, the principal

component factor analysis is adopted as it has assumed popular usage (Po-Yi & Chen, 2004).

Most studies adopt ‘1’ as the common factor for value for the diagonal line of the matrix;

extraction of components, exploratory factor analysis is adopted for the identification of new

attributes or variables to develop a framework, the method of principal axes is used to extract

common factors; factor extraction is categorized as common factor model and component model

also christened principal component analysis (PCA) (Gorsuch, 1983). Common factor models

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are used for the identification of dormant variables responsible for relationship between

measured variables in a study; and the target of the PCA is to reduce the number of variables by

linear combination to uphold essentially original measures (Conway & Huffcutt, 2003).

Deciding common factor number, the factor analysis combine variables that are highly

correlated and the representation of their meanings, for instance Po-Yi and Chen (2004) adopted

the value of ‘1’ as the benchmark for the selection of common factors in their study on

evaluating the performance of VE study using factor analysis and AHP.

Other means of determining the number of factors in factor analysis include the scree test,

parallel analysis; a priori theory; and the retention of variables that produce high proportion of

variance explanation (Conway & Huffcutt, 2003). The scree plot is irrelevant in most cases as it

allows for the subjectivity of the researcher in the interpretation of the plotted line to determine

the number of factors; hence an alternative to the scree plot is the deployment of parallel analysis

by comparing correlation matrices to eigenvalues and in this case of parallel analysis factors

derived from the real data must be greater than the eigenvalues ( Fricker et al., 2012). The

common factor model is suitable for deriving meaning for the variables observed (Conway &

Huffcutt, 2003). Selection of rotation method is necessary when the factors are more than one

to acquire deduce solution (Conway & Huffcutt, 2003) to curtail the problems associated with

interpretation. The main rotation methods include the orthogonal rotation method and oblique

rotation method, the oblique method was adopted by Po-Yi & Chen (2004). Oblique rotations

are more favoured than orthogonal rotations. A simple structure approach is advocated by

Fabrigar et al. (1999) in which each factor has a set of variables with high loadings and the other

set of factors with low loadings.

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5.3.4.6.1 Interpretation of Results Produced by Factor Analysis

The interpretation of the results churned out by factor analysis output is guided by the following

criteria, common degree which is determine by the conduct of the Barlett test in which the KMO

value is used to ascertain the suitability of the variables for factor analysis. A KMO value above

0.5 implies that the Bartlett’s test is appropriate reinforcing the suitability of the original

variables (Po-Yi & Chen, 2004); factor characteristics and variable explanation values larger

than ‘1’ for respective variables under consideration are considered. Interestingly, factor rotation

does not change the characteristic value and variable explanation hence a careful study of the

factor characteristic value and variable explanation would translate into the identification of the

common characteristic among factors (variables). Factor name, for common factors, a group

name would have to be obtained by the observation of the common characteristic among the

group of factors.

Dwelling extensively on information provided by extant literature above, the factor analysis

was adopted for data analysis to reduce the large amount of data involved in the study and to

classify the variables of the same underlying characteristics. The factor analysis aided in the

development of the grand pricing framework emanating from the systematic development of

subclass framework. The deployment of factor analysis helped in utilizing the KMO to compare

the correlation between variables to identify potential factors. In all the cases of applying the

factor analysis the KMO values were above 0.5 which demonstrated the sampling adequacy of

the research. Similarly, the KMO was used to measure the strength of relationship between

dependent variables (DV) and independent variables (ID) in this study. The KMO values in this

regard proved that the magnitude of partial correlation is significant as a result of KMO values

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above 0.5 in all cases. This explained that the factors identified in this study are potential pricing

variables in the quantity surveying consultancy services pricing milieu. The KMO values

provided the needed validity for this study which gave the research results the needed impetus

for generalization.

5.4 Summary of the Research Process

The research methodology first of all reviews the existing environment regarding the

philosophies, methods and statistical tools to be adopted for the research. This is then followed

by the justification for the choice of a particular process. Once the key characteristics of the

research philosophies, methods and analytical tools have been examined and justified, the

researcher proceeded with a detailed description of how they were applied in the conduct of this

research study. The methodology adopted for the research process is summarized in figure 5.2

below.

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Figure 5.3: Research Approach Adopted

Review of

Research problem,

research objectives

and framework

Descriptive

: RII

Grand

Generic QS

Consultancy

Services

Pricing

Framework

Research Problem

Research Aim and

Objectives

Research Philosophies

Positivism Epistemology

Quantitative

Method

Survey

Process

Instrument: Questionnaire Design

Data Analysis

Inferential:

Chi Square

test of

Independence

Factor

Analysis: Data

reduction,

classification

and subclass

framework

development

Tripartite

Discussion

involving RII,

Chi Square

test of

Hypotheses

and Factor

Analysis

Theoretical

Framework:

Pertinent Pricing

Theories/concepts

Review of Pertinent

Literature: General

and QS consultancy

Milieu

Postulation of

12 Key Pricing

Hypotheses

112 Operationalized Variables

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CHAPTER SIX

ANALYSIS OF DATA AND DISCUSSION OF RESULTS

6.0 INTRODUCTION

This chapter of the research details the analysis and the discussion of the results realized after the

administration of the key research instrument, the questionnaire which churn data to provide the

basis for this chapter. The data collected using the questionnaire provide the information on the

critical pricing variables under investigation within the context of this research work; the data

also provided other key information which are very crucial for the analysis and will improve the

validity and acceptability of the research. The data in this chapter will provide the manifestations

(Leedy & Ormrod, 2005) of the key pricing variables hitherto unexplored within the arena of the

marketing mix. The data within the analysis and discussion of this chapter will give better

insights on pricing variables that are neglected during the pricing of economic activities

especially services in the nature of those provided by quantity surveying practitioners and other

services providers. The analysis is applicable to other practitioners especially consultants in the

built environment for the fact that pricing is a universal language understood by all.

The nature of data analysed in this chapter is purely primary data; primary data is significant in

this domain of pricing investigation because of their ability to be closer to the layer of truth

(Leedy & Ormrod, 2005). The logical reasoning in this analysis is purely deductive relying on

the data collected using the questionnaire crafted as a result of the general review of extant

literature and critical pricing theories or concepts to postulate critical pricing hypotheses to be

tested to enable inferences to be made for generalization.

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6.1 DESCRIPTIVE ANALYSIS

6.1.1 Respondents Profile

This aspect of the analysis seeks to delve into the background of respondents in order to ascertain

the degree of credible information they have acquired as a result of quantity surveying practice.

It consists of the status of firms; years of experience; rate of work acquisition; and the sectors of

operation. Earlier researchers analysed these critical phenomenon on respondents; for instance

Dogbegah (2009), Otu-Nyarko (2010); Osei-Hwedie (2010); and Saleh (2008) all explored these

aspects of respondents in their study to give much credence to the data behind the results being

analysed and discussed.

6.1.2 Legal Status of Respondent’s firms

Statutory regulations have made it a ritual for all firms to regularize their operations by

registration with statutory authorities in most jurisdictions for socio-economic reasons. The legal

status of firms is crucial as clearly indicated by Owusu-Manu (2008) that the legal character of

the firm depicts the caliber of activity they undertake. Table 6.1.1 demonstrates the legal entities

that respondents in this study belong. It is clear that majority of respondents representing 56

percent practice in private limited firms; while sole enterprise/sole proprietorship;

partnership/joint venture; and other category of firms were represented by respondents below 20

percent. This explains that nature of firms in the construction industry is largely private owned

hence majority of QS practitioners found themselves in these caliber of firms. This result is in

consonance with Otu-Nyarko (2010) and other previous works conducted in similar cases in

Ghana. The reason for the private limited company being in the majority in this regard as far as

Ghana is concerned relates to the fact that QS practitioner firms belong to the construction

industry in which the government is the largest employer operating with procurement regulations

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which do not recognize sole proprietorship. Similarly, most enterprising individuals prefer

owning their businesses as a result of prestige and enjoyment of profits.

Table 6.1.1 :Firm Status

Firms Status Frequency Percent Valid Percent Cumulative Percent

Valid Enterprise/Sole proprietorship 10 12.7 12.7 12.7

Private Limited Company 44 55.7 55.7 68.4

Partnership/Joint Venture 13 16.5 16.5 84.8

Others 12 15.2 15.2 100.0

Total 79 100.0 100.0

6.1.3 Years of Existence of Firms (Age)

The years of existence for that matter the age of firms has been recognize as a critical factor in

the life of every business establishment including quantity surveying firms as well. In this regard,

Stinchcombe (1965) suggested that older firms are more experience; have learned more over

time and are not susceptible to the liabilities of newness and have the benefits of better

performance. Drawing on from Table 6.1.2, 37 percent of respondents practice in firms that are

under 10 years and between 10 to 20 years of establishment respectively. The age of the firm will

determine the experiences of its employees in the acquisition of knowledge and know how in the

pricing of their consulting services.

Table 6.1.2: Years of existence

Years of Experience

Frequency Percent Valid Percent

Cumulative

Percent

Valid Under 10 years 29 36.7 37.2 37.2

10-20 years 29 36.7 37.2 74.4

21-30 years 7 8.9 9.0 83.3

Over 30 years 13 16.5 16.7 100.0

Total 78 98.7 100.0

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Missing Missing 1 1.3

Total 79 100.0

6.1.4 Rate of Work Acquisition

The rate of work acquisition is necessary for the learning throughout the life cycle of a firm. The

more frequent a firm acquires work or consulting engagements, the better their experiences and

sharpness in pricing skills hence their information becomes reliable and more valid than firms

that do not acquire work frequently. From Table 6.1.3, majority of respondents’ firms have work

acquisition rate of 42 percent, while the next significant work acquisition rate is moderately

frequent with 33 percent.

Table 6.1.3: Rate of Work Acquisition

Work Acquisition

Frequency Percent

Valid

Percent

Cumulative

Percent

Valid Not frequent 7 8.9 9.1 9.1

Moderately frequent 26 32.9 33.8 42.9

Frequent 33 41.8 42.9 85.7

Very frequent 11 13.9 14.3 100.0

Total 77 97.5 100.0


Total 79 100.0

6.1.5 Sectors of Operation

It is also important to examine the sectors that consulting QS practitioners operate in order to

identify the areas that they are well-informed. It will also serve as the direction and identification

of opportunities yet untapped in the economy. For instance Olatunji et al. (2009) acknowledged

that the quantity surveying discipline is an important profession in the construction industry. In

furtherance of this assertion and to compare with other allied sectors in the construction industry

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where the role of the quantity surveying profession may be required, this research explored

sectors such as civil and structural engineering; Mechanical building and engineering services;

petro-chemical; mineral extraction; and urban planning. In the construction sector, the frequency

of operation is 35 percent; civil and structural engineering is 15 percent frequent; mechanical

building and engineering services is 5 percent frequent; petro-chemical is 4 percent frequent;

mineral extraction is 1 percent frequent and 5 percent very frequent; and urban planning had 6

percent frequent and 3 percent very frequent as demonstrated in Tables 6.1.4a, b, c, d, e and f

below.

From the result above, it is clear that QS professionals operate in the building construction

sector more than the other sectors examined in this research; this result is in consonance with the

earlier assertion of Olajunji et al. (2009). On the contrary, the low level of operation by QS

practitioners in other sectors examined including petro-chemical is an opportunity for

enterprising QS practitioners to venture into since those sectors are unsaturated with QS

practitioners hence their services will be in dire need in those sectors.

Table 6.1.4a: Building construction

Responses Frequency Percent Valid Percent

Cumulative

Percent


Less frequent 4 5.1 5.1 9.0

Moderately Frequent 23 29.1 29.5 38.5

Frequent 27 34.2 34.6 73.1

Very frequent 21 26.6 26.9 100.0

Total 78 98.7 100.0


Total 79 100.0

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Table 6.1.4b : Civil and structural engineering


Cumulative

Percent


Less frequent 23 29.1 29.1 40.5


Frequent 12 15.2 15.2 93.7

Very frequent 5 6.3 6.3 100.0

Total 79 100.0 100.0

Table 6.1.4c : Mechanical building and engineering services


Cumulative

Percent


Less frequent 24 30.4 30.4 88.6


Frequent 4 5.1 5.1 100.0

Total 79 100.0 100.0

Table 6.1.4d: Petro-chemical


Cumulative

Percent




Frequent 3 3.8 3.8 100.0

Total 79 100.0 100.0

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Table 6.1.4e: Mineral extraction


Cumulative

Percent




Frequent 1 1.3 1.3 94.9


Total 79 100.0 100.0

Table 6.1.4f: Urban planning


Cumulative

Percent


Less frequent 27 34.2 34.2 72.2


Frequent 5 6.3 6.3 97.5


Total 79 100.0 100.0

6.2 RANKING OF KEY PRICING VARIABLES

This section of the descriptive analysis of data employs the Relative Importance Index (RII) in

the ranking of pricing variables. The RII has been preferred over the mean and standard

deviation as they are not credible and reliable tools for examining the overall ranking of key

attributes (Chan & Kumaraswamy, 1997). In a different dimension, Ferguson (1978) contended

that relevant attributes must be identified by imagination and common sense; Chan &

Kumaraswamy (1997) supported Ferguson by indicating that the identification of significant

variables from a vast amount of variables should be guided by sensibility and reasonability; and

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to improve these ranking and identification of attributes hypothesis testing must be objective and

robust (Beeston, 1983 and Gilchrist, 1984). In view of the above revelation by earlier researchers

on the ranking of variables, the art of ranking pricing variables in this research observed the rule

of falsifiability (underpinning discussions with solid facts and stating other works that contradict

the findings), validity(drawing sensible conclusions), parsimony (keeping it simple; “getting the

job done with the simplest tool” ) (Levine, 1996). The analysis and ranking of key pricing

variables were within the context of price and value; project pricing (consultancy pricing);

concept of risk; concept of taxation and inflation; quantity surveying consultancy services

pricing components; challenges confronting quantity surveying consultancy practice; and

quantity surveying consultancy services.

6.2.1 Concept of Price and Value

According to Ramirez (1999) value is the parameter for the measurement of worthiness. Value is

assessed through the anticipated results balanced against cost. Table 6.2.1 demonstrates variables

for achieving realistic pricing. These variables are crucial in the 21st century to the extent that

business organizations that intend to break-even ought to price within the framework of these

variables in order to achieve realistic prices for services provided to clients. The problem

bedeviling QS practice borders on the inability to recover cost incurred in the provision of

services to their clients. Drawing on from Table 6.2.1, price and value concepts that affect

pricing were categorized into price and value which consist of: value of a product or service

(RII= 0.78), affordability (RII= 0.71); just price concepts consisting of the government (RII=

0.58); seller’s profit (RII= 0.67); customer’s intrinsic value (RII= 0.63); customer’s affordability

(RII= 0.71); media action and pressure group had RII fairly below the significant level of 0.5.

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Another aspect examined was the role of the firm in price setting and this includes the goals,

importance and objectives of pricing. In this category key significant variables include: firm’s

image (RII= 0.77); firm’s objectivity (RII= 0.76); firm’s success ( RII = 0.76); and firm’s failure

(RII= 0.64). The pricing strategy category as indicated by the results in Table 6.2.1 is one of the

most pricing and value concepts considered by respondents as variables within this category

were demonstrated to be very significant consisting of demand (RII= 0.79), cost(RII= 0.79),

profit (RII= 0.78) and competition (RII= 0.77).

Drawing on from the above results, extant literature has placed much emphasis on the concept of

price and value thus in their works, Cannon (1998) perceived price and value to be equable or

comparable; and Farese et al.(1991) considered price as value placed on services rendered to

clients. Perreault and McCarthy (2002) noted price is the money placed on value while

Pontiskoski (2009) advocated that the gateway to successful pricing is understanding the value

clients place on the service provided. Other research studies that have underscored the role of

value in price setting include Zhilin and Robin (2004); and Grahame and Mark (1997)

conceptualize value to be anticipated satisfaction derived from a service or product. Within the

context of the above literature and empirical results, it is clear that price and value concepts are

important ingredients in gauging price, as it is evident that the key variables value of product or

service and affordability were clearly above the higher order of significant. It is therefore

imperative for QS practitioners to ensure that clients have value for their services. This will aid

them in setting realistic prices for their services because if the value is greater than affordability,

the service provider (consultant) and the client will gain.

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Some aspects of the just price have not been observed fully over the years as indicated in the

empirical results of this research (see Table 6.2.1). Among them seller’s profit and customer’s

intrinsic value were fairly above the middle order of pricing variables; on the contrary,

customer’s affordability was above the high order of significance while others were insignificant.

The underlying dynamics for relegating key just price concepts notably the government, media

action and pressure group is democratization and the dominance of capitalism over socialism as

governments do not interfere directly in the capitalist market by setting minimum prices to affect

goods and services.

From the above discussion, the main role of the quantity surveyor is to be successful in gauging

the price of services provided to clients to sustain the business of consulting. Within the domain

of pricing roles, the image of the firm; the objectives of the firm; and firm’s desire to be

successful are all active roles in consultancy services price gauging. The objectives of the firm

regarding pricing include cost recovery, profit margin maximization, profit maximization,

revenue maximization, quality leadership, quantity maximization, status quo and survival

(Channon, 1986; Cannon and Morgan, 1990; Bonnici, 1991; Payne, 1993; Palmer, 1994;

Bateson, 1995; Woodruff, 1995; Drake and Llewellyn, 1995; Ansari et al., 1996; Lovelock,

1996; Meidan, 1996; Zeithaml and Bitner, 1996; Hoffman and Bateson, 1997; Langeard, 2000;

and Owusu-Manu et al., 2012). One limitation of this research is that these specific pricing

objectives were not explored in detail; a further research agenda to explore the detail dynamics

of pricing objectives with much emphasis on their influence on price levels will be a novel

undertaking in research.

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Pricing strategies considered by respondents to be higher order pricing variables include demand,

cost, profit and competition were raked first, second, third and fourth with RII above 0.7

respectively. It is clear that among the price and value concepts, pricing strategies are the most

significant in the fixing of quantity surveying consultancy services prices. Quantity surveyors

just like any other professionals as well as business entities intend to make profit, recover cost

incurred in rendering services to clients. These must be attained within the challenges of

competition and accurate estimation of demand for quantity surveying services. Several

strategies have been adopted in pricing over the decades to achieve pricing quality (Owusu-

Manu et al., 2012) some of which include competitive pricing and multiple pricing. Pricing

strategies affect profitability in the sense that a particular pricing strategy adopted might not

yield the needed profit level required to stay in business. A recent study by Hinterhuben and

Liozu (2012) revealed that both researchers in the academia and industry practitioners adopt key

pricing strategies of cost-based pricing; competition-based pricing; and customer value-based

pricing which are in tandem with the pricing strategies identified in this study as cost,

competition and demand.

Table 6.2.1: Concept of Price and value

Concept of Price and Value

A. PRICE AND VALUE N SUM RII RANKING MISSING

1. Value of a product or service 79 287 0.73 8

2. Affordability

79 280 0.71 10

B. JUST PRICE 1. The Government 79 231 0.58 14

2. Media action 79 171 0.43 16

3. Pressure Group 79 175 0.44 15

4. Seller’s profit 79 263 0.67 11

5. Customer’s intrinsic value 79 249 0.63 13

6. Customer’s affordability

78 277 0.71 9 1

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C. IMPORTANCE, OBJECTIVES AND GOALS OF PRICING(ROLE OF THE FIRM) 1. Firm’s objectivity 79 300 0.76 6

2. Firm’s failure 79 254 0.64 12

3. Firm’s success 79 299 0.76 7

4. Firm’s image

79 304 0.77 5

D. PRICING STRATEGIES

1. Cost 79 313 0.79 2

2. Profit 79 309 0.78 3

3. Demand 79 313 0.79 1

4. Competition 79 305 0.77 4

6.2.2 Project Pricing (Consultancy Pricing)

Quantity surveying practitioners are in the business of rendering services in the construction and

its allied sectors. Projects are not manufactured products hence their related services such as

consultancy services which QS practitioners render are for a fixed duration. Similarly, services

provided in the construction sector are tailor made, therefore require different pricing approach.

In addition, the requirements for engaging QS consultants are different from suppliers or

providers of manufactured products. Table 6.2.2 demonstrates the key issues of consultancy

services provision during project execution. These consultancy pricing variables have been

classified into pricing parameters/ criteria and bid price success (c.f. Table 6.2.2). From Table

6.2.2, the variables relating to pricing criteria and bid price success are all within the higher order

pricing variable category with RII above 0.70 except business development and overhead and

profit while technical capacity and materials used on the project have RII above 0.80 and were

ranked first and second respectively.

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Table 6.2.2: Consultancy Pricing

Project Pricing (Consultancy Pricing)

A. PRICING PARAMETERS/ CRITERIA

N SUM

RII

RANKING

MISSING

1. Time taken to solve the problem 79 314 0.79 3

2. Materials used on the project 79 315 0.80 2

3. Good financial control system 79 298 0.75 10

4. Record of past project costs 79 288 0.73 12

5. Accurate forecast of future cost 79 289 0.73 11

6. Production of timely reports

79 302 0.76 9

B. BID PRICE SUCCESS 1. Financial capacity 79 310 0.78 5

2. Technical capacity 79 319 0.81 1

3. Firm’s experience 79 311 0.79 4

4. Duration to render the service 79 303 0.77 8

5. Firm’s reputation 78 300 0.77 7 1

6. Business development 79 271 0.69 13

Overhead and profit 79 308 0.78 6

6.2.3 Concept of Risk

Risk is any event related to a consulting engagement that has the potential of making the

consulting endeavor a failure. Risk is related to consultancy services pricing in two main ways:

the risk associated with the project being undertaken; and the risk associated with pricing. It is a

fact that if the project has elapsed prematurely then the whole of the consultation period has

come to an end. It is therefore clear that consulting engagement is complimentary to project

execution in the built environment. Risk in their nature can occur at different stages of the

project and those associated with consulting pricing can affect consultancy services pricing.

Table 6.2.3 has categorized risks investigated in this research into price associated risks; and

risks likely to occur at the various stages of projects that will have impact on consultancy

services pricing. From Table 6.2.3 risk at the various stages of projects affecting consultancy

services pricing were highly ranked by respondents; notable among these variables include

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financial risk (RII = 0.73); legal risk (RII = 0.70); regulatory risk (RII= 0.70); political risk (RII

= 0.69) are all in the higher order variables. Similarly, pricing risks relate to the activities of the

consultant during pricing. These risks include financial risk (RII= 0.73); market related risk

(RII=0.68); associated business risk (RII=0.68); technological risk (RII= 0.67) and

organizational risk (RII = 0.63). Among these direct risks of consulting, financial risk is

perceived to be a higher order pricing variable while the rest comprising of market related risk

inter alia are perceived to be marginally above the middle order ( Chappel, 1994 and Doloi,

2008) pricing variables with average RII= 0.60. Similarly, risks at the various stages of projects

or consulting engagements affecting price levels which are indirect risks to the consulting entity

were professed to be in higher order pricing variables comprising of financial risk (RII= 0.73,

ranked first); legal risk (RII= 0.70, ranked third); regulatory risk (RII= 0.70, ranked fourth);

political risk (RII= 0.69, ranked fifth); and force majeure risks (RII= 0.61, ranked twelfth).

The indirect risks associated with projects are apparently significant pricing variables that can change the

levels of consultancy services pricing. It is clear from the result that financial risk is both direct and

indirect consultancy services pricing risk of significant proportion. The economic crisis being experience

globally has brought serious financial risks to the consulting industry, for instance Adendorff et al. (2012)

clearly asserted that the current global crisis has intensified the risks of completed projects and decreased

the amount of work completed in the built environment. This assertion has demonstrated the gravity of

indirect risks to consultancy services pricing. In view of the above result, it is important for price setters

in the consulting industry to envisage the probability of any of the category of the risks identified

occurring in the execution of projects for which consulting services are emanate. It is therefore important

to be vigilant and resourceful in environmental analysis to identify the potential risk as far as pricing

consulting services are concerned.

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Table 6.2.3: Concept of Risk

Concept of Risk

A. PRICE AND RISK(Direct risks)

N SUM RII RANKING

MISSING

1. Associated business risk 79 268 0.68 7

2. Financial risk 78 298 0.73 1 1

3. Market related risk 79 269 0.68 6

4. Logistical and infrastructural risk 78 240 0.62 11 1

5. Managerial and operational risk 79 261 0.66 9

6. Technological risk 79 263 0.67 8

7. Organizational and societal risk 79 248 0.63 10

B. RISKS AT VARIOUS STAGES OF PROJECTS AFFECTING CONSULTANCY

PRICE LEVELS(Indirect risks) 1. Financial risk 79 287 0.73 2

2. Legal risk 79 277 0.70 3

3. Regulatory risk 79 276 0.70 4

4. Political risk 79 273 0.69 5

5. Force majeure risks 79 239 0.61 12

6.2.4 Concept of Taxation and Inflation

Economic activities notably manufacturing and economic services provision are subject to

taxation in many countries globally to generate revenue for governments. In pursuant of this

agenda, numerous nomenclature of taxes exist which are burdens imposed on service providers

and clients. These taxes are factored into the price formulation of services provided by

consultants in order to recover their invested resources into service delivery to clients. Table

6.2.4 examines the various forms of taxes, inflation and subsequently inflationary causes

affecting change in consultancy price levels that consulting entities may encounter in the

delivery of their services to clients and setting of appropriate prices. Inflationary causes affecting

consultancy price levels are perceived to be potential price altering agents in any economic

activity. It is clear from Table 6.2.4 that in this category of variables, effects of input market (RII

= 0.70, ranked third); government policies (RII = 0.69, ranked fourth); international trade and

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trade barriers (RII = 0.68, ranked fifth); and production shortfall (RII = 0.68, ranked sixth) have

in most cases demonstrated that they are marginally significant except effects of variable inputs

affecting the levels of consultancy services pricing. It is a fact that these phenomena affect the

commercial transactions of consultancy firms in the purchase of materials and other relevant

supplies to aid them in delivering services to clients. The two variables in the inflation category

were ranked high by respondents; thus inflation (RII = 0.77, ranked first); and input prices (RII =

0.75, ranked second) were in higher order variables. Though respondents acknowledge operating

and pricing within the framework of inflation, inflationary causes affecting change in

consultancy price levels and various tax obligations are marginally considered in pricing, the

only notable case is VAT/NHIL. This phenomenon could be attributed to non-payment of taxes

or tax evasion as a result of the inability of the tax authorities to locate consultants to fulfill this

statutory obligation as a result of improper planning and layout policies of offices. However,

consulting entities rendering services to government establishment may not escape the tax net

because of the regulations of the Procurement Act 663. This finding is a pearl for the tax

authorities to dwell on in expanding their tax net to mobilize more revenue for government

coffers for development. It is equally important for the consulting entities to take cognizance of

inflation and its causes that will affect consultancy services pricing.

Table6.2.4: Concept of Taxation and inflation

Concept of Taxation and inflation

TAXATION

N

SUM RII

RANKING

MISSING

1. Personal income tax 79 239 0.61 8

2. VAT/ NHIL 79 252 0.64 7

3. Corporate tax 79 218 0.55 11

4. Profit tax 79 221 0.56 10

5. Local rates 79 224 0.57 9

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6. Property tax 79 218 0.55 12

B. INFLATION 7. Input prices 79 297 0.75 2

8. Inflation 79 302 0.77 1

C. INFLATIONARY CAUSES AFFECTING CHANGE IN CONSULTANCY PRICE

LEVELS 9. Production shortfall 79 267 0.68 6

10. Effects of input market 79 275 0.70 3

11. Government policies 79 273 0.69 4

12. International trade and trade barriers 79 267 0.68 5

6.2.5 Quantity Surveying Consultancy Services Pricing Components

Inflation and taxation policies in Table 6.2.4 above have the potential of affecting the major consultancy

services pricing components notably materials for report preparation and training programmes; travel and

transport; supplies and equipment; and communication. Table 6.2.5 clearly demonstrate the various

components of quantity surveying consultancy services pricing comprising of profits (RII = 0.76); travel

and transport (RII = 0.75); staff allowances (RII = 0.74); consultant staff remuneration (RII = 0.74);

report preparation and contingencies (RII = 0.72) respectively; and taxes and duties; and mobilization and

demobilization (RII = 0.71) respectively. Other variables demonstrated in Table 6.2.5 are largely above

the middle order of significance with average ranking of 0.68. These components except profits and

contingencies represent the cost component of consulting entities in the delivery of their services to

clients (Washburn et al., 2002; JICA, 2006; The World Bank, 2002; CEBC, 2011 and TRF,

2011). In reference to earlier analysis on concept of price and value (See Table 6.2.1 ), cost

(RII= 0.79, ranked second) was in the higher order pricing variables among pricing strategies

variables. Juxtaposing this against the performance of pricing components, it is proper to assert

that when cost of consultancy services is high all components of consultancy services pricing will

be proportionally high except profit and contingencies.

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Table 6.2.5: Quantity surveying consultancy services pricing components

Quantity surveying consultancy services pricing components

PRICING COMPONENTS N SUM RII RANKING

1. Profits 79 302 0.76 1

2. Travel and transport 79 295 0.75 2

3. Staff allowances 79 294 0.74 3

4. Consultant staff remuneration 79 293 0.74 4

5. Report preparation 79 285 0.72 5

6. Contingencies 79 284 0.72 6

7. Taxes and duties 79 282 0.71 7

8. Mobilization and demobilization 79 281 0.71 8

9. Communications 79 272 0.69 9

10. Supplies and equipment 79 272 0.69 10

11. Insurance 79 272 0.69 11

12. Office rent 79 266 0.67 12

13. Training programmes 79 260 0.66 13

6.2.6 Challenges confronting quantity surveying consultancy practice

There are numerous challenges that quantity surveying consultancy practitioners encounter in the

delivery of services to clients. These challenges are classified as general challenges and those

that are price-related. Referring to Table 6.2.6 below, the critical general challenges confronting

the quantity surveying profession perceived to be in higher order by respondents include impact

of competition ( RII= 0.72, ranked first); changing nature of client demands (RII= 0.71, ranked

second); slow response to information and communication technology revolution (RII= 0.70,

ranked third); and complexity of modern construction( RII= 0.70, ranked fourth). Other

challenges notably inability to integrate applied research outputs into practice; slow response to

changing contractual arrangements; and challenge of appropriate response to emerging services

were ranked with RII ranging from 0.65 to 0.69.

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From the above, the identifiable general challenges confronting quantity surveying practitioners

are serious, and though some of these challenges are perceived to be general they can also affect

pricing. These challenges include the impact of competition; slow response to information and

communication technology; complexity of modern construction projects inter alia. Specifically,

Odeyinka (2006) identify key modern construction project arrangements that the quantity

surveyor will face as challenging to include Private Finance Initiative (PFI) and Public Private

Partnership (PPP); supply chain management; partnering and alliancing; prime contracting; and

performance based contracting. Other emerging areas that the quantity surveyor will face

challenges which will subsequently affect consultancy services pricing comprise of facilities

management, project management, value management, commercial management and risk

management; these challenges Odeyinka (2006) averred that the quantity surveyor will have to

be prepared in the areas of business and management competence to be equipped to properly

deliver in these project nomenclature. Based on the assertion of Odeyinka (2006) and the above

result of this research, it is appropriate that quantity surveying professional bodies and

educational institutions notably universities and polytechnics begin training students in business

management and entrepreneurial pedagogy.

The price-related challenges were within the middle order variables implying that their effect is

averagely influential when pricing services. The dominance of capitalism has weakened the

power of professional bodies in price determination and control leading to haggling between

demand (client) and supply (consultant) to set their price levels hence price-related challenges

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are deemed to be moderately significant in the pricing of quantity surveying consultancy services

except in the cases of market forces.

Table 6.2.6: Challenges confronting quantity surveying consultancy practice

A. GENERAL CHALLENGES

N SUM RII RANKING

1. Slow response to changing contractual arrangements 79 262 0.66 7

2. Challenge of appropriate response to emerging

Services

79 257 0.65 8

3. Slow response to information and communication

technology revolution

79 277 0.70 3

4. Inability to integrate applied research outputs into

practice

79 273 0.69 5

5. Changing nature of clients’ demand 79 280 0.71 2

6. Impact of competition 79 286 0.72 1

7. Complexity of modern construction projects 79 275 0.70 4

B. PRICING/FEES CHALLENGES

1. Reducing fees to loss-making territory 79 251 0.64 10

2. Exposure to risks 79 266 0.67 6

3. Decrease in project value 79 257 0.65 9

4. Fluctuation in professional tariff of fees 79 240 0.61 11

6.2.7 Quantity surveying consultancy services (Seeley, 1997; Olatunde, 2006)

Services rendered are priced in the services industry to rope in revenue to recover cost and to

provide reward for the efforts of service providers via profits. In quantity surveying professional

practice, numerous services exist that practitioners can render and price accordingly. These

services were acknowledged variously in literature by notable authorities namely Seeley (1997);

Olatunde (2006) inter alia. This research classified quantity surveying services as traditional and

non-traditional (emerging) services (See Table 6.2.7a and Table 6.2.7b) below. Traditional

services are the most dominant services rendered by QS consultants while the non-traditional

services or the emerging services remain the less dominant within the framework of services

provided by QS consultants to clients. The demonstration of the results From the Tables6.2.7a

and Table 6.2.7b below implies that traditional services are the most significantly priced while

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the non-traditional services remain the less priced. It is worthy to note that one of the key non-

traditional service sectors that the quantity surveyor can explore which is not yet saturated by

other QS practitioners is the oil and gas sector. The competition in the non-traditional service

sectors of QS practice is not intensive hence innovative QS practitioners venturing into the oil

and gas and other non-traditional services of quantity surveying have the opportunity of making

substantial profit and are open to the prospect of enjoying some significant level of monopoly for

some considerable period of time.

Table 6.2.7a: Quantity Surveying Traditional Services

Quantity Surveying Consulting Services N Sum RII Ranking

1. Preparing tender documents 79 318 0.81 1

2. Interim valuations and payments 79 308 0.78 2

3. Valuation of construction work 79 306 0.77 3

4. Valuation of variations 79 301 0.76 4

5. Cost control of projects 79 296 0.75 5

6. Final account preparation and

agreement 79 296 0.75 6

7. Claims preparation 79 286 0.72 7

8. Financial statements 79 285 0.72 8

9. Cost planning and cost checking 79 280 0.71 9

10. Advice on contracting methods 79 279 0.71 10

11. Preliminary cost advice 79 278 0.70 11

12. Participating in contract administration 78 274 0.70 12

13. Preparing cash flow forecasts 79 273 0.69 13

14. Advice on construction procurement

systems 79 272 0.69 14

15. Negotiating contract prices 79 260 0.66 15

16. Project management 79 248 0.63 16

17. Value management 79 239 0.61 17

18. Arbitrations and disputes resolution 79 183 0.46 18

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Table 6.2.7b:Non-Traditional (Emerging) Services

NON-TRADITIONAL(EMERGING) SERVICES

Quantity Surveying Consulting Services N Sum RII Ranking Missing

1. Advice on procurement strategy 78 175 0.45 1 1

2. Contract administration 78 175 0.45 2 1

3. Project management 78 174 0.45 3 1

4. Construction management 77 168 0.44 4 1

5. Procurement management 78 169 0.43 5 1

6. Development and facilities management 78 169 0.43 6 1

7. Construction management 78 168 0.43 7 1

8. Program management 78 167 0.43 8 1

9. Expertise in maintenance programme 78 166 0.43 9 1

10. Cost planning and budgeting 78 162 0.42 10 1

11. Procurement and supply chain

management 78 156 0.40 11

1

12. Whole life cycle cost management 78 152 0.39 12 1

13. Cost and business planning 78 151 0.39 13 1

14. Risk and value management 78 151 0.39 14 1

15. Commercial management 78 150 0.38 15 1

16. Management of capital expenditure 78 146 0.37 16 1

17. Facilities management of stations 78 146 0.37 17 1

6.3 INFERENTIAL ANALYSIS: HYPOTHESES TESTING

Inferential analysis deals with parameter estimation and hypothesis testing. Several statistical

techniques are employed in these cases to manipulate data for analysis and interpretation. In this

research work, inferential analysis is solely limited to hypothesis testing (see chapter three for

more details) by adopting Chi-Square test. Utilizing the relative importance index (RII) which is

a descriptive technique is not enough to generalize the result to the population, as some results

may be due to chance. In order to ascertain the significance of the results, hypothesis testing has

been adopted to achieve this goal. The Chi-Square test was adopted because of its admissibility

of all types of scale (nominal, ordinal, interval and ratio) used in collecting data. Also, the ranked

nature of the preliminary results analysed above has made the Chi-Square test apt for this test of

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significance. The hypothesis tested were crafted from a carefully constructed theoretical

framework covering key pricing concepts notably price and value; just price; role of the firm

(importance, objectives and goals of pricing); pricing strategies; pricing parameters; bid price

success; price and risk concepts; risks associated with various stages of projects affecting

pricing; taxation and inflation; and quantity surveying consultancy services pricing components.

6.3.1 Price and Value Hypotheses

Ho1: A significant key to successful pricing is not dependent on: (H1a) value of a product or

service and (H1b) affordability.

H1 1: A significant key to successful pricing is dependent on: (H1a).value of a product or service

and (H1b). affordability

A chi-square test conducted to determine the relationship between successful pricing (a

dependent variable) and pricing variables (independent variables) as demonstrated in Table H1

below revealed that there was significant relationship between the value of a product (X2 =

61.190, X2α = 14.860, df = 4, p < 0.001); and affordability ( X2 = 52.329, X2α = 14.860, df = 4, p

< 0.001). Since X2cal

> X2α at p < 0.05, reject the null hypothesis. The results clearly suggest that

there is relationship between the independent variables and the dependent variable hence the

alternate hypothesis holds implying that the successful pricing of quantity surveying consultancy

services is dependent on the value of the service provided to clients and the ability of clients to

afford for the services (ability to pay the services). These pricing variables, “value of a product

or service” and “affordability” were higher order pricing variables with RII of 0.73 and 0.71

respectively. The hypothesis testing of these variables further gives much statistical credence to

the relative ranking of these variables. This result clearly suggests that the value of the services

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that QS consultants provide to clients has significant bearing on the prices they charge. Poor

services in value will require low prices being attained while quality services provided to clients

will definitely require sustainable pricing that will result in break-even. In another vein,

providing value services alone will not inure to realistic pricing or successful pricing being

chalked but the ability of the client to afford or pay for a price determined based on the value of

the services provided. It is therefore necessary to determine the parameters for ascertaining the

value of services provided by QS consultants to their clients. However, this phenomenon has not

been addressed by this study hence a research agenda to explore the criteria for value of QS

services will be novel and apt. Similarly, a study to determine the willingness to afford or pay

(WTP) for consultancy services will be a step in the right direction.

Table H 1: Test Statistics

Independent Variables Chi-Square (X2) df Asymp. Sig.

1. Value of a product or service 61.190a 4 0.000

2. Affordability 52.329a 4 0.000

a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.-

Ho2: The achievement of just price levels is not significantly dependent on: (H2a). the

government. (H2b) media action. (H2c) pressure group (H3d). Seller’s profit. (H3e). customer’s

intrinsic value. (H3f) customer’s affordability.

H12: The achievement of just price levels is significantly dependent on: (H2a). the government.

(H2b). media action. (H2c). pressure group (H3d). seller’s profit. (H3e). customer’s intrinsic

value. (H3f). customer’s affordability.

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The chi-square test conducted with respect to hypothesis 2 is demonstrated in Table H2 below.

The test result revealed that there is significant relationship between media action ( X2 = 34.861,

X2α = 14.860, df = 4, p < 0.001); pressure group ( X2 = 36.886, X2α = 14.860, df = 4, p < 0.001);

Seller’s profit ( X2 = 28.278, X2α = 14.860, df = 4, p < 0.001); customer’s intrinsic value ( X2 =

27.899, X2α = 14.860, df = 4, p < 0.001); and customer’s affordability ( X2= 76.359, X2α =

14.860, df = 4, p < 0.001). Since X2cal

> X2α at p < 0.005, reject the null hypothesis in terms of

these group variables, hence there is significant evidence that these group variables are related to

the achievement of just price levels. However there is significant evidence that the variable ‘the

government’(X2 = 1.316, X2α = 14.860, df = 4, p = .859). Since X2cal

< X2α at p > 0.005, accept

the null hypothesis in terms of this group variable (the government). The media has been

powerful since the emergence of democratization in Ghana. The media can influence price level

to the extent that the consultant’s objective of making profit can be achieved or dashed.

Customer’s/clients intrinsic value can also be influenced by the media and this will subsequently

affect the decision of the client on the services being acquired leading to the determination of a

price level that will be beneficial to the consultant or vice versa. It is therefore important for

practitioners of QS consultancy to be mindful of media action when setting price for their

services. QS consultancy price setters hence forth ought to consider the media landscape and

other pricing variables when fixing prices for clients.



1. The Government 1.316a 4 .859

2. Media action 34.861a 4 .000

3. Pressure Group 36.886a 4 .000

4. Seller’s profit 28.278a 4 .000

5. Customer’s intrinsic value 27.899a 4 .000

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6. Customer’s affordability 76.359b 4 .000

a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.

b. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.6.

Ho3: The role of the firm in setting price levels is not significantly dependent on: (H3a)

objectivity. (H3b) failure. (H3c) success. (H3d) image.

H1 3: The role of the firm in setting price levels is significantly dependent on: (H3a). objectivity.

(H3b). failure. (H3c). success. (H3d). image.

The Chi-Square test conducted with regards to Hypothesis 3 above is demonstrated in Table H3

below; the result revealed that there is significant relationship between the role of the firm in

setting prices and firm’s objectivity ( X2 = 49.544, X2α = 14.860, df = 4, p < 0.001); firm’s

failure (X2 = 14.861, X2α = 14.860, df = 4, p = 0.005); firm’s success (X2= 68.658, X2α = 14.860,

df = 4, p < 0.001); and firm’s image (X2 = 42.456, X2α = 14.860, df = 4, p < 0.001) and the role

of the firm in setting prices. Since, X2cal > X2α (14.860) at p < 0.005 in all the cases of the group

variables, we reject the null hypothesis H0 at a significance level of 0.005. Therefore there is

significance relationship between the role of the firm in setting price levels and the objectives of

the firm’s objectivity; firm’s failure; firm’s success; and the firm’s image). It has been

statistically evident that the role of the firm in fixing consultancy prices would result in the

failure of the firm; prices set by the firm would have impact on their image before their clients;

and this leads to the success of the firm. It is imperative to note that the determinant of the three

key variables above is pricing objectives. QS consultancy firms must determine their objectives

prudently in within the parameters of the above pricing outcomes ( image, success and failure).

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1. Firm’s objectivity 49.544a 4 .000

2. Firm’s failure 14.861a 4 .005

3. Firm’s success 68.658a 4 .000

4. Firm’s image 42.456a 4 .000


Ho 4: The fundamentals of pricing strategy of a firm are not dependent on: (H4a). Cost. (H4b).

Profit (H4c). Demand (H4d). Competition

H1 4: The fundamentals of every pricing strategy of a firm are dependent on: (H4a). Cost. (H4b).

Profit (H4c). Demand (H4d). Competition

The Chi-Square result for hypothesis 4 in Table H4 below demonstrates that a significant

relationship exist between the pricing strategy and group variables( independent variables)

namely cost (X2 = 42.873, X2α = 12.838, df = 3, p < 0.001); profit ( X2 = 59.038, df = 4, p <

0.001, X2α = 14.860 ); demand ( X2 = 33.354, df = 3, p < 0.001, X2α = 12.838 ); and competition

( X2 = 40.557, df = 4, p < 0.001, X2α = 14.860 ). Since the X2cal > X2α at p < 0.005 in all the

cases of the group variables, reject the null hypothesis H0 at a significance level of 0.005.

Therefore, there is significant evidence to suggest that pricing strategy is dependent on cost,

profit, demand and competition. This will mean that consultancy services pricing must take

cognizance of these variables of cost, demand, competition and profit. Having established the

evidence of these variables (demand, cost, competition and profit) as the fundamentals of

pricing, it is novel that a further research at advanced level to conduct an in-depth study to

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investigate on the dynamics of each of these variables in influencing consultancy services

pricing.



1. Cost 42.873a 3 .000

2. Profit 59.038b 4 .000

3. Demand 33.354a 3 .000

4. Competition 40.557b 4 .000



Ho5: The successful criteria for consultancy services pricing is not dependent on: (H5a). time

taken to solve the problem. (H5b). materials used on the project. (H5c). good financial control

system. (H5b). Record of past project costs. (H5c). accurate forecast of future cost; and (H5d).

production of timely reports.

H1 5: The successful criteria for consultancy services pricing is dependent on: (H5a). time taken

to solve the problem. (H5b). materials used on the project. (H5c). good financial control system.

(H5b). Record of past project costs. (H5c). accurate forecast of future cost; and (H5d).

production of timely reports.

The Chi-Square test conducted for hypothesis 5 above has its result depicted in Table H5 below.

The results revealed that there was a significant relationship between successful criteria for

pricing consultancy services and the independent variables namely time taken to solve the

problem ( X2 = 62.722, df = 3, p < 0.001, X2α = 12.838); materials used on the project ( X2 =

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34.468, df = 3, p < 0.001, X2α = 12.838); good financial control system ( X2= 17.456, df = 3, p =

0.001, X2α = 12.838); record of past project costs (X2 = 50.177, df = 4, p < 0.001, X2α =14.860);

accurate forecast of future cost ( X2 = 55.873, df = 4, p < 0.001, X2α =14.860); and production

of timely reports (X2 = 43.722, df = 4, p < 0.001, X2α =14.860). Since the X2cal > X2α at p <

0.005 in the case of the group variables, reject the null hypothesis H0 at a significance level of

0.005. Therefore, there is a statistical evidence to advocate that the success criteria for

consultancy services pricing is significantly dependent on the time taken to solve the problem;

materials used on the project; good financial control system; record of past project costs;

accurate forecast of future cost; and production of timely reports. Drawing from the result of

hypothesis 5, practitioners of QS consultancy services must operate within the framework of

these success criteria in order to be successful in pricing their services. Theoretically, pricing of

services within the consultancy services provision has been improve as this provides enough

scientific bases for consideration these variables in future pricing development.



1. Time taken to solve the problem 62.722a 3 .000

2. Materials used on the project 34.468a 3 .000

3. Good financial control system 17.456a 3 .001

4. Record of past project costs 50.177b 4 .000

5. Accurate forecast of future cost 55.873b 4 .000

6. Production of timely reports 43.722b 4 .000 a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 19.8.


Ho 6: The success of a bid price is not dependent on: (H6a). financial capacity, (H6b). technical

capacity, (H6c). experience, (H6d). duration, (H6e). reputation, (H6f). business development

and (H6g) profit and overhead.

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H1 6: The success of a bid price is dependent on: (H6a). financial capacity, (H6b). technical

capacity, (H6c). experience, (H6d). duration, (H6e). reputation, (H6f). business development,

and (H6g) profit and overhead.

The Chi-Square test result for Hypothesis 6 above is demonstrated in Table H6 below, the results

supports the existence of significant relationship between the dependent variable bid price for

consultancy services pricing and the independent variables namely financial capacity ( X2 =

44.734, df = 4, p < 0.001, X2α =14.860); technical capacity ( X2 = 69.165, df = 4, p < 0.001, X2α

=14.860); firm’s experience( X2 = 69.671, df = 4, p < 0.001, X2α =14.860); duration to render the

service ( X2 = 52.456, df = 4, p < 0.001, X2α =14.860); firm’s reputation ( X2 = 59.692, df = 4, p

< 0.001, X2α =14.860); business development ( X2 = 12.595, df = 3, p = .006, X2α =12.838); and

profit and overhead ( X2 = 41.443, df = 4, p < 0.001, X2α =14.860). Since X2cal < X2α, and the p

> 0.005, accept the null hypothesis Ho for the group variable business development, hence bid

price success for consultancy services is not dependent on the business development agenda of

the firm. However, the result demonstrates that in the case of other independent variables X2cal >

X2α at p < 0.005, at this instance, reject the null hypothesis Ho at a significance level of 0.005.

Hence there is statistical evidence to suggest that bid price success for consultancy services is

significantly dependent on financial capacity; technical capacity; firm’s experience; duration to

render the service; firm’s reputation; and profit and overhead. The rejection of the null

hypothesis is a testament that bid price success which is the focus of most consultancies is

important and reinforces the application of the independent variables in the examination of bid

price quotations from consultants. The acceptance of the null hypothesis in terms of business

development underpins the fact that in spite of business development strategies adopted by

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consultancies if they do not adhere to successful bid pricing criteria, they are bound to fail in the

pricing of their services.


Independent Variables Chi-Square ( X2) df Asymp. Sig.

1. Financial capacity 44.734a 4 .000

2. Technical capacity 69.165a 4 .000

3. Firm’s experience 69.671a 4 .000

4. Duration to render the service 52.456a 4 .000

5. Firm’s reputation 59.692b 4 .000

6. Business development 12.595c 3 .006

7. Overhead and profit 41.443a 4 .000



c. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 19.8.

Ho 7: Consultancy services price levels are not dependent on financial risks.

H1 7: Consultancy services price levels are dependent on financial risks.

A Chi-Square test was conducted to find out whether consultancy services price levels are

dependent on associated financial risk. The results demonstrated that there is significant

relationship between consultancy price levels and financial risks (X2= 78.532, df = 4, p < 0.001,

X2α =14.860). Since X2cal > X2α at p < 0.005, reject the null hypothesis. Hence there is

significant evidence statistically to advocate that consultancy services price levels are dependent

of financial risks. Hitherto financial risks do not feature in the price composition of consultancy

services provisions. The test of this hypothesis would practically improve the pricing of

consultancy services by ensuring that financial obligations are shared among project

stakeholders. However, it is important to explore the nature of consultancy financial risks to

181

establish its true level of influence and other associated encumbrances in pricing in a future

study.


Independent Variable Chi-Square (X2) df Asymp. Sig.

Financial risk

78.532a

4

.000 a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.

Ho 8: The robustness of consultancy pricing is not dependent on the: (H8a).Market related risks

(H8b). Logistical and infrastructural risks (H8c). Managerial and operational risks (H8d).

Technological risks (H8e). Organizational and societal risks.

H1 8: The robustness of consultancy pricing is dependent on: (H8a).Market related risks (H8b).

Logistical and infrastructural risks (H8c). Managerial and operational risks (H8d).

Technological risks (H8e). Organizational and societal risks.

The Chi-Square result conducted revealed that the robustness of consultancy services pricing is

significantly dependent on market related risks ( X2 = 35.076, df = 3, p < 0.001, X2α =12.838);

logistical and infrastructural risk ( X2 = 57.769, df = 4, p < 0.001, X2α =14.860); managerial and

operational risk ( X2= 29.405, df = 3, p < 0.001, X2α =12.838); technological risk( X2 = 14.924,

df = 3, p = 0.002, X2α = 12.838); and organizational and societal risk ( X2= 37.646, df = 4, p <

0.000, X2α =14.860). Since the X2cal > X2α at p < 0.005, reject the null hypothesis H0 and

conclude that the robustness of consultancy services pricing is dependent on market related risks;

logistical and infrastructural risks; managerial and operational risks; technological risks; and

organizational and societal risks. The ingredients for consultancy price robustness have eluded

practitioners over the decades. The test result of this hypothesis has the potential of creating the

awareness of price robustness among consultancies and contributing to theory development by

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setting the tone for in-depth studies in this area in consultancy pricing and other disciplines as

well.



1. Market related risk 35.076a 3 .000

2. Logistical and infrastructural risk 57.769b 4 .000

3. Managerial and operational risk 29.405a 3 .000

4. Technological risk 14.924a 3 .002

5. Organizational and societal risk 37.646c 4 .000 a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 19.8.


c. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8

Ho 9: The level of consultancy pricing is independent of: (H9a). Financial risk (H9b). Legal risk

(H9c). Regulatory risks (H9d). Political risk and (H9e). Force majeure risks.

H19: The level of consultancy services pricing is dependent on: (H9a). Financial risk (H9b).

Legal risk (H9c). Regulatory risks (H9d). Political risk and (H9e). Force majeure risks.

The Chi-Square result for Hypothesis 9 above as demonstrated in Table H9 below disclosed that

there is significant relationship between the level of consultancy pricing and financial risk ( X2 =

58.795, df = 4, p < 0.001, X2α = 14.860); legal risk (X2 = 37.266, df = 4, p < 0.001, X2α

=14.860); regulatory risk ( X2= 38.911, df = 4, p < 0.001, X2α =14.860); political risk ( X2=

22.962, df = 4, p < 0.001, X2α =14.860); and force majeure risks ( X2 = 19.165, df = 4, p = 0.001,

X2α =14.860). Since the X2cal > X2α at p < 0.005, reject the null hypothesis Ho and conclude that

the level of consultancy services pricing is significantly dependent on financial risk; legal risk;

regulatory risk; political risk; and force majeure risk. This implies that consultants must price

their services within the framework of these risks in order to realize appreciable price levels for

their services. Theoretically, the relationship between risk and pricing levels are least

investigated in consulting and other fields as well, this revelation has the potential of igniting

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novel studies in the research community towards unfolding deeper dynamics regarding price

levels and risk.

Table H 9: Test Results


1. Financial risk 58.795 4 .000

2. Legal risk 37.266 4 .000

3. Regulatory risk 38.911 4 .000

4. Political risk 22.962 4 .000

5. Force majeure risks 19.165 4 .001

a. 0 cells (0%) have expected frequencies less than 5. The minimum expected frequency is 15.6.

b. 0 cells (0%) have expected frequencies less than 5. The minimum expected frequency is 15.8.

Ho 10: The level of consultancy prices is not dependent on these taxes: (H10a). personal income

tax (H10b). VAT/ ‘NHIL’ (H10c). Corporate tax (H10d). Profit tax (H10e). local rates (H10f).

Property tax.

H1 10: The level of consultancy prices is dependent on these taxes: (H10a). personal income tax

(H10b). VAT/ ‘NHIL’ (H10c). Corporate tax (H10d). Profit tax (H10e). local rates (H10f).

Property tax.

The Chi-Square result of Hypothesis 10 above depicted in Table H10 revealed that there is

significant relationship between the level of consultancy services prices and personal income tax

( X2 = 20.051, df = 4, p < 0.001, X2α =14.860); VAT/ NHIL ( X2 = 27.519, df = 4, p < 0.001, X2α

=14.860); corporate tax ( X2 = 36.506, df = 4, p < 0.001, X2α =14.860); profit tax ( X2= 31.063,

df = 4, p < 0.001, X2α =14.860); local rates ( X2 = 22.203, df = 4, p < 0.001, X2α =14.860); and

property tax ( X2= 22.835, df = 4, p < 0.001, X2α =14.860). Since the X2cal > X2α at p < 0.005 in

all cases of the variables, reject the null hypothesis Ho and conclude that the level of consultancy

services price is dependent on personal income tax; VAT/ NHIL; corporate tax; profit tax; local

rates; and property tax. The phenomenon of taxes in pricing is least investigated theoretically

184

especially in QS consultancy services pricing, the result of this hypothesis implies that awareness

would be created to engender the consideration of taxes in the development of consultancy

services pricing theories especially in the determination of price levels. Practically, price setters

would henceforth consider the various tax burdens that they encounter in the delivery of services

to clients.



1. Personal income tax 20.051 4 .000

2. VAT/ NHIL 27.519 4 .000

3. Corporate tax 36.506 4 .000

4. Profit tax 31.063 4 .000

5. Local rates 22.203 4 .000

6. Property tax 22.835 4 .000 a. 0 cells (0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8

Ho 11: Consultancy services price level is not dependent on: (H11a). input prices (H11b).

Inflation

H1 11: Consultancy services Price level is dependent on: (H11a). input prices (H11b). Inflation

The Chi-Square results of Hypothesis 11 above as demonstrated in Table H11 unveiled that there

is significant relationship between input prices ( X2= 43.722, df = 4, p < 0.001, X2α =14.860) and

inflation ( X2 = 43.154, df = 4, p < 0.001, X2α = 14.860). Since the X2cal > X2α at p < 0.005,

reject the null hypothesis Ho and conclude that consultancy services price level is dependent on

input prices and inflation. The result of this hypothesis underpins the consideration given to

components of consultancy services pricing which serve as inputs to the delivery of the services

to clients. These inputs include materials and supplies, communication expenses among others.

Practically, this hypothesis gives a scientific impetus to their inclusion in the development of the

185

pricing framework. Inflation is not considered in the existing pricing of consultancy services

since majority of consultancies adopt percentage pricing where a percentage of the project cost is

normally taken to be the consultancy services price. This hypothesis also provides a further

reason for the consideration of inflationary rate in the pricing of service especially over long

project duration.



1. Input prices 43.722 4 .000

2. Inflation 43.154 4 .000 a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.

b. 0 cell (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.6.

Ho12: Changes in consultancy services price levels are independent of inflationary causes:

(H12a). production shortfall (H12b). Effects of input market (H12c). Government policies; and

(H12d). International trade and trade barriers.

H112: Changes in consultancy services price levels are dependent on inflationary causes:

(H12a). production shortfall (H12b). Effects of input market (H12c). Government policies; and

(H12d). International trade and trade barriers.

The Chi-Square test result of Hypothesis 12 as in Table H12 below revealed that there is

significant relationship between changes in consultancy services price levels and production

shortfall ( X2 = 27.266, df = 4, p < 0.001, X2α =14.860); effects of input market ( X2 = 40.304, df

= 4, p < 0.001, X2α = 14.860); Government policies ( X2 = 26.127, df = 4, p < 0.001, X2α

=14.860); and international trade and trade barriers ( X2= 23.595, df = 4, p < 0.001, X2α

=14.860). Since the X2cal > X2α at p < 0.005, reject the null hypothesis Ho and conclude that

changes in consultancy services price levels are dependent on production shortfall; effects of

186

input market; government policies; and international trade and trade barriers. Globalization has

made the world to be closer in trade and its related issues. International trade has the potential of

altering the level of consultancy price levels. An increase in input prices in the world market in a

different jurisdiction can affect the pricing of services provided input materials are purchased

from the international market. In the light of this, pricing QS consultancy services must take due

cognizance of international trade dynamics especially in the delivery of services that are

international in nature.

6.4 FACTOR ANALYSIS

There are sixty-six (66) independent variables. In view of the numerous independent variables

involved in this research, it is possible there will be significant amount of variables measuring

the same pricing phenomenon. Hence factor analysis wass adopted to reduce the repeatability of

variables and to empirically aid in the development of the pricing framework by classifying key

pricing variables of the same characteristics.

6.4.1 Concept of Price and Value (Variables)

6.4.1.1Initial Consideration

The reliability of factor analysis is determined by the sample size as correlation coefficients

changes from one set of sample to another. From Table F 1 below using the Kaiser-Meyer-Olkin

(KMO) measure of sampling adequacy which is approximately 0.7 signifies the adequacy of the

sample size of the data for the factor analysis to be conducted. This implies that factor analysis

has been given a clean sheet to proceed. Similarly, communalities in Table F 2 after extraction

were above 0.5 (c.f. Po-Yi & Chen, 2004), and this further strengthen the adequacy of the sample

187

size; hence the communalities in the Table F2 are significant. The Bartlett's Test of Sphericity is

also significant since the KMO is above 0.5. These phenomena of the data as demonstrated by

the KMO and the Bartlett's Test of Sphericity clearly indicate that there is a strong relation

among the pricing variables, this aspect of the result clearly dovetail into the objective of the

research of ascertaining the nature of relationship among the quantity surveying consultancy

pricing variables. After ascertaining the suitability of the data on price and value concepts, the

data was analysed using the Principal Component Analysis (PCA) and Varimax with Kaiser

Normalization. The communalities involved were ascertained as indicated in Table F 2 below to

account for the number of variables to be extracted finally. A critical examination of the

extraction column of Table F 2 indicated that the average of communalities extracted were above

0.60 indicating how well the extracted components represent the factors/ pricing variables hence

the extracted components are very good representation of the factors price and value factors.

Table F 1: KMO and Bartlett's Test (Price and value)

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .673

Bartlett's Test of Sphericity Approx. Chi-Square 524.433

df 120

Sig. .000

Table F 2: Communalities (Price and Value)

Variables Initial Extraction

1. Value of a product or service 1.000 .704

2. Affordability 1.000 .643

3. The Government 1.000 .802

4. Media action 1.000 .837

188

5. Pressure Group 1.000 .723

6. Seller’s profit 1.000 .866

7. Customer’s intrinsic value 1.000 .722

8. Customer’s affordability 1.000 .670

9. Firm’s objectivity 1.000 .736

10. Firm’s failure 1.000 .561

11. Firm’s success 1.000 .691

12. Firm’s image 1.000 .605

13. Cost 1.000 .662

14. Profit 1.000 .618

15. Demand 1.000 .741

16. Competition 1.000 .666

Extraction Method: Principal Component Analysis.

From Table F 3, five components have been extracted to represent the price and value factors or

variables. The total variance explained by each component extracted include, the first principal

component (component 1) version is 27.965% of the total variance; second principal component

(component 2) version is 15.216% of the remaining variance not accounted for by the first

component while the third principal component (component 3) version is 11.757% of the

remaining variance unaccounted for by the first and second component; the fourth principal

component (component 4) accounted for 8.197% of the remaining variance not explained by the

previous components; and finally, the fifth component (component 5) accounted for 7.15% of the

remaining variance not explained by the previous four principal components. In all, the five (5)

components extracted cumulatively accounted for 70.285% of the variation inherent in the data,

a phenomenon which is in compliance with the criterion that extracted components must explain

at least 50% of the variance. This therefore implies that five (5) principal components have been

extracted to represent key pricing variables or factors whose eigenvalues are greater than 1. The

remaining 11 factors or variables have their eigenvalues less than one hence they have been

189

ignored as a result of not being able to meet the criteria for selection which is eigenvalues greater

than 1. These factors with high eigenvalues explained about 70% of the variables, therefore the

factor (variables) can be reduced to these set of variables with a loss of 30% information.

Table F 3: Total Variance Explained (Price and value)

Comp

onent

Initial Eigenvalues

Extraction Sums of

Squared Loadings

Rotation Sums of

Squared Loadings

Total % of

Variance Cum. % Total

% of


% of

Variance Cum. %

1 4.474 27.965 27.965 4.474 27.965 27.965 2.702 16.885 16.885

2 2.435 15.216 43.181 2.435 15.216 43.181 2.654 16.588 33.473

3 1.881 11.757 54.938 1.881 11.757 54.938 2.613 16.329 49.802

4 1.312 8.197 63.135 1.312 8.197 63.135 1.863 11.642 61.444

5 1.144 7.15 70.285 1.144 7.150 70.285 1.415 8.841 70.285

6 0.851 5.320 75.605

7 0.724 4.523 80.128

8 0.600 3.749 83.877

9 0.512 3.203 87.08

10 0.496 3.102 90.182

11 0.393 2.457 92.638

12 0.332 2.073 94.711

13 0.300 1.875 96.586

14 0.237 1.482 98.068

15 0.189 1.178 99.247

16 0.121 0.753 100


Table F 4: Rotated Component Matrixa ( Price and value)

Component

Variables 1 2 3 4 5

1. Value of a product or service .079 .038 .219 -.060 .803

2. Affordability .509 .175 .017 .194 .561

3. The Government .096 -.675 .234 .521 -.102

4. Media action -.114 -.085 -.032 .887 -.171

5. Pressure Group -.073 .220 -.071 .783 .225

190

6.4.1.2 Components Extracted

The results of the factor analysis above are promising. The data was summarized to 70% of the

variance in the 16 factors with 5 components. Each component has at least 1 factor and at most 4

factors which can be represented as factors which are significant in pricing decision with regards

to price and value concepts. Table F5 below summarizes the components and their respective

factors of price and value. Factors are interestingly grouped according to their heading (themes).

Table F 5: Component Profile of the concept of Price and value

Description of Components and Variables Factor

Loading

Variance Explained

Component1: Pricing Strategies

1. Cost .692 27.965%

2. Profit .764

3. Demand .796

4. Competition .637

Component 2: Just Price

1. The government -.675 15.216%

2. Seller’s profit .919

6. Seller’s profit .035 .919 -.048 .035 -.126

7. Customer’s intrinsic value .281 .775 .036 .094 .179

8. Customer’s affordability .094 .664 .407 .094 .213

9. Firm’s objectivity .301 -.051 .779 .090 .165

10. Firm’s failure .269 .382 .519 .145 -.229

11. Firm’s success .001 -.034 .810 -.053 .176

12. Firm’s image .232 .089 .717 -.159 .060

13. Cost .692 .119 .151 -.246 .292

14. Profit .764 .157 .094 -.004 -.008

15. Demand .796 .094 .235 -.109 .179

16. Competition .637 -.134 .447 .032 -.204


Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 6 iterations.

191

3. Customer’s intrinsic value .775

4. Customer’s affordability .664

Component 3:Pricing Roles

1. Firm’s objectivity .779 11.757%

2. Firm’s success .810

3. Firm’s image .717

Component 4: Social Influence

1. Media action .887 8.197%

2. Pressure group .783

Component 5: Value

1. Value of a product or service .803 7.15%


6.4.2.1 Initial Considerations

For this aspect of the analysis, there are 13 variables involved and it is likely there would be

variables that feature in various aspect of consultancy pricing. It is therefore necessary to

summarize the dataset for simplification and easy comprehension. This attempt is in tandem with

the overall objectives of the study which is to develop a framework. The reduction and

summarization of the data is organized into manageable and appreciable level. The first step in

the conduct of every factor analysis is to verify the adequacy of the survey data. The KMO test

and Bartlett's Test of Sphericity (see Table F 6) below are used to verify the adequacy of the data

for the factor analysis of consultancy pricing variables. From Table F 8, the adequacy of the data

is excellent since the KMO value is .855. The KMO statistic ranges from 0 to 1 and a KMO

value closer to 1 is considered better than KMO values far from 1.

192

Table F 6: KMO and Bartlett's Test (Price and value)



df 78

Sig. .000

After ascertaining the suitability of the data on price and value concepts, the data was analysed

using the Principal Component Analysis (PCA) and Varimax with Kaiser Normalization. The

communalities involved were ascertained as indicated in Table F 7 below accounted for the

number of variables to be extracted finally. A critical examination of the extraction column of

Table F 7 indicated that the average of communalities extracted were slightly above 0.60

indicating an average extracted components representing the factors/ project pricing variables

hence the extracted components are to a larger extent an average representation of the factors of

project pricing.

Table F 7: Communalities (Project Pricing/consultancy pricing)


1. Time taken to solve the problem 1.000 .642

2. Materials used on the project 1.000 .650

3. Good financial control system 1.000 .738

4. Record of past project costs 1.000 .564

5. Accurate forecast of future cost 1.000 .577

6. Production of timely reports 1.000 .614

7. Financial capacity 1.000 .548

8. Technical capacity 1.000 .613

9. Firm’s experience 1.000 .664

10. Duration to render the service 1.000 .671

11. Firm’s reputation 1.000 .599

12. Business development 1.000 .814

13. Overhead and profit 1.000 .582

193

Table F 7: Communalities (Project Pricing/consultancy pricing)


1. Time taken to solve the problem 1.000 .642

2. Materials used on the project 1.000 .650

3. Good financial control system 1.000 .738

4. Record of past project costs 1.000 .564

5. Accurate forecast of future cost 1.000 .577

6. Production of timely reports 1.000 .614

7. Financial capacity 1.000 .548

8. Technical capacity 1.000 .613

9. Firm’s experience 1.000 .664

10. Duration to render the service 1.000 .671

11. Firm’s reputation 1.000 .599

12. Business development 1.000 .814

13. Overhead and profit 1.000 .582


Drawing on from Table F 8 below, three (3) components of the total variance explained have

been extracted comprising of the first principal component christened component 1 accounted

for 45.587% of the total variance; component 2 explained 9.41% of the other components not

accounted for by component 1; and component 3 accounted for 8.673% of the variance not

explained by the first and second components of the remaining variation. In all, the three

extracted components cumulatively accounted for 63.67% which is well above the accepted

variance criterion that the cumulative extracted components must be at least 50% of the variance.

Table F 8: Total Variance Explained (Project Pricing/consultancy pricing)

Compo

nent

Initial Eigenvalues

Extraction Sums of

Squared Loadings

Rotation Sums of Squared

Loadings

Total

% of


% of


% of

Variance

Cum.

%

1 5.926 45.587 45.587 5.926 45.587 45.587 2.767 21.287 21.287

2 1.223 9.410 54.997 1.223 9.41 54.997 2.765 21.269 42.556

194

3 1.127 8.673 63.670 1.127 8.673 63.67 2.745 21.114 63.670

4 0.938 7.212 70.882

5 0.697 5.362 76.244

6 0.589 4.528 80.771

7 0.485 3.729 84.501

8 0.472 3.634 88.135

9 0.409 3.146 91.281

10 0.368 2.834 94.116

11 0.309 2.375 96.491

12 0.294 2.26 98.751

13 0.162 1.249 100


Table F 9: Rotated Component Matrixa (Project pricing/consultancy pricing)

Component

Pricing Variables 1 2 3

1. Time taken to solve the problem 0.078 0.794 0.075

2. Materials used on the project 0.151 0.653 0.448

3. Good financial control system 0.272 0.805 0.123

4. Record of past project costs 0.303 0.618 0.300

5. Accurate forecast of future cost 0.512 0.517 0.217

6. Production of timely reports 0.127 0.172 0.754

7. Financial capacity 0.214 0.291 0.646

8. Technical capacity 0.454 0.331 0.546

9. Firm’s experience 0.648 0.266 0.417

10. Duration to render the service 0.709 0.162 0.376

11. Firm’s reputation 0.580 0.243 0.451

12. Business development 0.881 0.157 -0.116

13. Overhead and profit 0.086 0.066 0.755 Extraction Method: Principal Component Analysis.




The results of the factor analysis are auspicious. The data was summarized to 64% of the

variance in the 13 factors with 3 components. Each component has three factors which represent

significantly project pricing/consultancy pricing variables. Using Table F9 above, Table F 10

195

below clearly demonstrates the extracted components with their key variables. Factors are

grouped according to appropriate headings (themes).

Table F 10: Component Profile of Project pricing/consultancy pricing

Description of Components and Variables Factor Loading Variance Explained

Component 1: Business management

1. Firm’s experience 0.648 45.587%

2. Duration to render service 0.709

3. Business development 0.881

Component 2: Project/service cost management

1. Time taken to solve the problem 0.794 9.41%

2. Materials used on the project 0.653

3. Good financial control system 0.805

4. Record of past project cost 0.618

Component 3: Technical and financial

capabilities

1. Production of timely reports 0.754 8.673

2. Financial capacity 0.646

3. overhead and profit 0.755

4. technical capacity 0.546

6.4.3 Concept of risk

Pricing is affected by risks of various dimensions. The pricing of quantity surveying services is

not devoid of risks. The study examines various degrees of risk and it is important to critically

categorize or summarize these risks into their appropriate domain empirically. The factor

analysis has been adopted for the purposes of data reduction, summarization and framework

development.

6.4.3.1 Initial Considerations

The most important prelude to the conduct of factor analysis is the determination of the

suitability of the data set. Examining the Barlett test conducted to ascertain the existence of

196

common factors with regards to the concept of pricing risks in this study. Referring to the KMO

measure of sampling adequacy, it is clear that the sampling adequacy is deemed to be above

average; hence the factor analysis proceeds (see Table F11).

Table F 11: KMO and Bartlett's Test (Concept of risk)

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .691


df 66

Sig. .000

Having examined the suitability of the data using Table F11 above, the Principal Component

analysis PCA was used to establish the communalities for the factor analysis. Table F 12 below

presented the variables to be extracted. The average communalities to extract are marginally

above average (i.e. 0.607).

Table F 12: Communalities(Concept of risk)


1. Associated business risk 1.000 .643

2. Financial risk 1.000 .526

3. Market related risk 1.000 .472

4. Logistical and infrastructural risk 1.000 .596

5. Managerial and operational risk 1.000 .605

6. Technological risk 1.000 .584

7. Organizational and societal risk 1.000 .629

8. Financial risk 1.000 .431

9. Legal risk 1.000 .582

10. Regulatory risk 1.000 .691

11. Political risk 1.000 .794

12. Force majeure risks 1.000 .731


197

From Table F 13 below, three (3) components of the total variance explained have been

established for extraction. Component 1 accounted for 34.469% of total variation; component 2

version is 14.268% of the variation not explained by the component 1; and component 3

accounted for 11.972% of the total variance not explained by components 1 and 2. The three

components altogether accounted for 60.709% which is above the accepted criterion of

cumulative extracted components to be at least 50%.

Table F 13: Total Variance Explained (Concept of risk)

Compo

nent

Initial Eigenvalues

Extraction Sums of

Squared Loadings


Loadings

Total

% of


% of

Variance Cum.% Total

% of

Variance Cum. %

1 4.136 34.469 34.469 4.136 34.469 34.469 3.108 25.903 25.903

2 1.712 14.268 48.737 1.712 14.268 48.737 2.446 20.385 46.288

3 1.437 11.972 60.709 1.437 11.972 60.709 1.731 14.422 60.709

4 0.838 6.985 67.694

5 0.801 6.673 74.367

6 0.759 6.321 80.688

7 0.678 5.648 86.336

8 0.438 3.652 89.988

9 0.43 3.587 93.575

10 0.319 2.657 96.232

11 0.262 2.185 98.417

12 0.19 1.583 100


Table F 14: Rotated Component Matrixa (Concept of risk)

Rotated Component Matrixa

Component

Concept of risk(variables) 1 2 3

1. Associated business risk 0.727 -0.188 0.281

2. Financial risk 0.709 0.152 -0.004

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3. Market related risk 0.629 0.254 -0.11

4. Logistical and infrastructural risk 0.710 0.133 0.273

5. Managerial and operational risk 0.727 0.272 -0.049

6. Technological risk 0.485 0.564 -0.175

7. Organizational and societal risk 0.155 0.766 0.136

8. Financial risk 0.553 0.332 0.121

9. Legal risk 0.259 0.710 0.106

10. Regulatory risk 0.045 0.83 0.004

11. Political risk 0.115 -0.012 0.883

12. Force majeure risks 0.028 0.155 0.841





The extracted components with their respective variables comprising component 1 with four (4)

variables; component 2 with three (3) variables; and component 3 consist of two (2) extracted

variables. In all nine (9) variables have been extracted cumulatively at 60.709%. Three variables

were eliminated because of the insignificance of their eigenvalues which are far below 1. The

respective components with their themes are demonstrated in Table F 15 below.

Table F 15: Component Profile of concept of risk


Component 1: Corporate internal risk

1. Associated business risk 0.727 34.469

2. Financial risk 0.709

3. Logistical and infrastructural risk 0.710

4. Managerial and operational risk 0.727

Component 2: Corporate external risk

1. Organizational and societal risk 0.766 14.268

2. Legal risk 0.710

3. Regulatory risk 0.830

Component 3: location risk

1. Political risk 0.883

2. Force majeure risks 0.841 11.972

199

6.4.4 Concept of taxation and inflation

Taxes and inflation affect prices of services rendered to clients by consultants. In most cases,

these two indicators of prices have become the concerns of the business world. In this study,

varied form of taxation and inflationary forces were examined to ascertain the opinion of

respondents on these issues with regard to the pricing of QS consultancy services.

6.4.4.1 Initial Consideration

In view of the numerous taxes examined, it is important to summarize and classify them

appropriately hence the adoption of factor analysis for such a purpose. Prior to the conduct of

factor analysis, a preliminary test on the sample size adequacy of the dataset in order to proceed

with the analysis. Also required is the determination of the existence of common factors within

the data through the Barlett test. A critical examination of the KMO statistic in Table F 16

regarding the dataset of concept of taxation and inflation revealed that the adequacy of sampling

for factor analysis is above average since the KMO statistic is 0.726; hence the factor analysis

proceeds.

Table F 16: KMO and Bartlett’s Test (Taxation and inflation)


Bartlett’s Test of Sphericity Approx. Chi-Square 420.665

df 66

Sig. .000

Table F 17 demonstrates communalities before and after extraction; before extraction the

communalities are all to be 1. The communalities in the extraction column of Table F 17

demonstrate the common variance existing in the data structure. Referring to the Table F17,

200

0.708 (70.8%) of the variance in relation to personal income tax is common (refer to Table F 17

for this information regarding other variables). The average of the communalities is 0.65.

From Table F 18 below, three (3) components of the total variance explained have been

established. Component 1 accounted for 34.444% of total variance explained; component 2

version produced 20.858% of the total variance not explained by component 1; and component 3

accounted for 9.708% of the total variance not accounted by component 1 and 2. The three

components together accounted for 65.010% which meets the criteria that cumulative extracted

components must be at least 50%.

Table F 18: Total Variance Explained (Taxation and inflation)

Comp

onent

Initial Eigenvalues

Extraction Sums of

Squared Loadings


Loadings

Total

% of


% of


% of

Variance Cum. %

Table F 17: Communalities (Taxation and inflation)


1. Personal income tax 1.000 .708

2. VAT/ NHIL 1.000 .558

3. Corporate tax 1.000 .571

4. Profit tax 1.000 .560

5. Local rates 1.000 .554

6. Property tax 1.000 .720

7. Input prices 1.000 .727

8. Inflation 1.000 .788

9. Production shortfall 1.000 .651

10. Effects of input market 1.000 .758

11. Government policies 1.000 .686

12. International trade and trade barriers 1.000 .520


201

1 4.133 34.444 34.444 4.133 34.444 34.444 3.689 30.741 30.741

2 2.503 20.858 55.302 2.503 20.858 55.302 2.813 23.439 54.180

3 1.165 9.708 65.010 1.165 9.708 65.010 1.300 10.830 65.010

4 .980 8.167 73.177

5 .838 6.986 80.163

6 .600 5.003 85.166

7 .430 3.587 88.752

8 .405 3.378 92.130

9 .316 2.630 94.760

10 .235 1.959 96.720

11 .220 1.831 98.551

12 .174 1.449 100.000

Extraction Method: Principal

Component Analysis.

Table F 19: Rotated Component Matrixa (Taxation and inflation)

Component

Variables 1 2 3

1. Personal income tax .824 .169 .016

2. VAT/ NHIL .730 -.007 .158

3. Corporate tax .724 -.035 .212

4. Profit tax .738 .106 -.063

5. Local rates .735 .015 .120

6. Property tax .812 .110 -.221

7. Input prices .272 .293 .753

8. Inflation .153 .659 .574

9. Production shortfall .019 .799 .108

10. Effects of input market -.064 .868 .025

11. Government policies .145 .816 .006

12. International trade and trade barriers .294 .425 -.503




202


Referring to Table F 19 above, six (6) variables were extracted from component 1. Component 2

had four (4) variables extracted; and component 3 consist of only one (1) extracted variable. In

all, eleven (11) variables were extracted while one (1) variable was ignored because its

eigenvalue is low in all the three components. The three components with their interpretation are

demonstrated in Table F 20 below.

Table F 20: Component Profile (Taxation and inflation)


Component 1: Taxes 1. Personal income tax

.824

34.444

2. VAT/ NHIL .730

3. Corporate tax .724

4. Profit tax .738

5. Local rates .735

6. Property tax .812

Component 2:Price catalysts

1. Inflation .659 20.858

2. Production shortfall .799

3. Effects of input market .868

4. Government policies .816

Component 3: Input prices

1. Input prices .753 9.708

6.4.5 Quantity surveying consultancy services pricing components

After examining the parameters of consultancy pricing, it is important to delve into the various

components of quantity surveying (QS) consultancy services pricing. Varied forms of QS

consultancy pricing components exist which this study intends to classify appropriately using

factor analysis to eventually develop a robust framework for QS consultancy pricing.

203


The reliability of factor analysis is dependent on the adequacy of the sample size involved in the

data collection. It is in this direction that preliminary analysis using KMO statistic as depicted in

Table F 21 is vital. The KMO value is .786 which is above average hence the reliability of factor

analysis is guaranteed. The KMO value ranges from 0 to 1, the closer the KMO value to 1 the

more reliable the factor analysis. Similarly, the Barlett test conducted indicated the existence of

common factors in the data. Since the reliability of the factor analysis is assured; its conduct is

appropriate for data reduction and classification of quantity surveying consultancy services

pricing components variables to develop a framework.

Table F 21: KMO and Bartlett's Test (QS consultancy services pricing components)



df 78

Sig. .000

Table F 22 below contains the communalities before and after extraction, the communalities

before extraction are assumed to be 1 while communalities after extraction are above 1. The

loadings in the extraction column depict the amount of common variance present in the data as

far as each variable is concerned. The average communality (8.937/13) is 0.687.

Table F 22: Communalities (QS consultancy services pricing components)


1. Consultant staff remuneration 1.000 .684

2. Travel and transport 1.000 .798

3. Mobilization and demobilization 1.000 .521

4. Staff allowances 1.000 .719

204

5. Communications 1.000 .672

6. Office rent 1.000 .682

7. Supplies and equipment 1.000 .714

8. Training programmes 1.000 .721

9. Report preparation 1.000 .617

10. Insurance 1.000 .743

11. Contingencies 1.000 .749

12. Taxes and duties 1.000 .620

13. Profits 1.000 .697


In Table F 23 below, four (4) components were established of the total variance explained.

Component 1 accounted for 37.889% of total variance explained; component 2 revealed

12.948% of the total variance not accounted for by component 1; component 3 depict 9.357% of

total variance unaccounted by the component 1 and component 2; and component 4 portray

8.571% of the total variance not demonstrated by the previous three components. The four

components together accounted for 68.765% of total variance explained which satisfy the criteria

that the cumulative extracted components must be at least 50% of the total variance explained.

Table F 23:Total Variance Explained (QS consultancy services pricing components)

Comp

onent

Initial Eigenvalues

Extraction Sums of

Squared Loadings


Loadings

Total

% of


% of


% of

Variance Cum. %

1 4.926 37.889 37.889 4.926 37.889 37.889 2.533 19.487 19.487

2 1.683 12.948 50.837 1.683 12.948 50.837 2.331 17.927 37.414

3 1.216 9.357 60.194 1.216 9.357 60.194 2.243 17.254 54.667

4 1.114 8.571 68.765 1.114 8.571 68.765 1.833 14.097 68.765

5 .842 6.476 75.241

6 .692 5.322 80.562

205

7 .564 4.336 84.898

8 .524 4.034 88.932

9 .375 2.884 91.816

10 .326 2.510 94.326

11 .294 2.258 96.584

12 .228 1.752 98.336

13 .216 1.664 100.000


Component Analysis.


From Table F 24 above, three (3) variables have been extracted with regard to component 1,

Table F 24: Rotated Component Matrixa (QS consultancy services pricing components)

Variables Component

1 2 3 4

1. Consultant staff remuneration .462 -.235 .315 .562

2. Travel and transport .223 -.120 .817 .258

3. Mobilization and demobilization .238 .371 .254 .512

4. Staff allowances .776 .004 .110 .323

5. Communications .500 .299 .555 -.158

6. Office rent .755 .295 .117 .104

7. Supplies and equipment .783 .244 .136 .152

8. Training programmes .074 .343 .771 -.055

9. Report preparation .058 .422 .616 .238

10. Insurance .350 .779 .102 -.058

11. Contingencies .138 .828 .195 .086

12. Taxes and duties .028 .546 .185 .536

13. Profits .164 .024 -.052 .817




206

component 2 and component 4 respectively except component 3 which had four (4) variables

extracted. It is worthy to note that consultant staff remuneration; mobilization and

demobilization; communications; and taxes and duties had their eigenvalues marginally above

0.50 hence the extraction of these variables can be deemed to be mediocre. Table F 25 below

demonstrates the components, their descriptions with respective variables extracted.

Table F 25:Component Profile (QS consultancy services pricing components)


Component 1: Office management

1. Staff allowances .776 37.889 2. Office rent .755

3. Supplies and equipment .783

Component 2: Overheads

1. Insurance .779 12.948 2. Contingencies .828

3. Taxes and duties .546

Component 3: Administration and training

1. Travel and transport .817 9.357 2. Communications .555

3. Training programmes .771

4. Report preparation .616

Component 4: Reimbursement and payments

1. Consultant staff remuneration .562 8.571 2. Mobilization and demobilization .512

3. Profits .817

6.4.6 Challenges Confronting QS Consultancy Practice

Every professional practice has its own challenges and QS consultancy practice is not an

exception. The QS profession has been confronted with numerous challenges that need urgent

examination and redress. The study examine key challenges undermining QS professional

207

practice and intends to categorize them based on some underlining factors that are common to

them using factor analysis.


In the conduct of factor analysis, the sample size affects the reliability of the output hence

preliminary analysis is required using the KMO statistic. Table F 26 clearly reflects the KMO

statistic for the data on the challenges of QS practice. A KMO value of .664 provides an average

basis for the reliability of the factor analysis hence the factor analysis proceeds.

Table F 26: KMO and Bartlett’s Test (QS consultancy challenges)


Bartlett’s Test of Sphericity Approx. Chi-Square 227.777

df 55

Sig. .000

Table F 27 below contains the communalities before and after extraction, the communalities

before extraction are assumed to be 1 while communalities after extraction are above 1. The

loadings in the extraction column represent the amount of common variance existing in the data

as far as each variable is concerned. The average of communalities (7.482/11) is 0.680.

Table F 27: Communalities (QS consultancy challenges)


1. Slow response to changing contractual arrangements 1.000 .630

2. Challenge of appropriate response to emerging services 1.000 .661

3. Slow response to information and communication technology revolution 1.000 .686

4. Inability to integrate applied research outputs into practice 1.000 .536

5. Changing nature of clients’ demand 1.000 .577

208

6. Impact of competition 1.000 .794

7.Complexity of modern construction projects 1.000 .609

8. Reducing fees to loss-making territory 1.000 .755

9. Exposure to risks 1.000 .714

10.Decrease in project value 1.000 .686

11. Fluctuation in professional tariff of fees 1.000 .834


From Table F 28 below, four (4) components of total variance explained were established for

extraction. Component 1 accounted for 27.385% of total variance explained; component 2

portrays 18.966% of total variance not accounted for by component 1; component 3

demonstrates 12.172% of total variance not portrayed by components 1 and component 2; and

component 4 accounted for 9.497% of total variance explained not accounted for by components

1, 2 and 3. The four components accounted for 68.021% of the total variance explained which is

well above with the acceptable criteria of cumulative extracted components to be at least 50%.

Table F 28: Total Variance Explained(QS consultancy challenges)

Comp

onent

Initial Eigenvalues

Extraction Sums of

Squared Loadings


Loadings

Total

% of


% of


% of

Variance Cum. %

1 3.012 27.385 27.385 3.012 27.385 27.385 2.512 22.837 22.837

2 2.086 18.966 46.351 2.086 18.966 46.351 2.054 18.677 41.514

3 1.339 12.172 58.523 1.339 12.172 58.523 1.630 14.821 56.334

4 1.045 9.497 68.021 1.045 9.497 68.021 1.285 11.686 68.021

5 .821 7.463 75.484

6 .649 5.897 81.381

7 .540 4.905 86.287

8 .504 4.578 90.865

209

9 .411 3.736 94.600

10 .341 3.100 97.700

11 .253 2.300 100.000


Component Analysis.

Table F 29: Rotated Component Matrixa (QS consultancy challenges)

Variables Component

1 2 3 4

1. Slow response to changing contractual arrangements .735 -.224 .191 -.054

2. Challenge of appropriate response to emerging services .803 -.044 .099 -.070

3. Slow response to information and communication technology

revolution .755 .282 .169 .084

4. Inability to integrate applied research outputs into practice .719 .101 -.088 .042

5. Changing nature of clients’ demand .412 .127 .618 -.091

6. Impact of competition -.064 .076 .886 .011

7. Complexity of modern construction projects .218 .070 .565 .487

8. Reducing fees to loss-making territory .113 .840 .071 -.176

9. Exposure to risks -.010 .842 .008 .074

10. Decrease in project value -.026 .686 .236 .398

11. Fluctuation in professional tariff of fees -.068 .028 -.036 .910





From Table F 30 above, four (4) variables have been extracted for component 1; component 2

had three ( 3) extracted variables while component 3 is represented by two (2) variables; and

component 4 had only one (1) extracted variable. Table F 30 below demonstrates the

components and their descriptions with respective variables extracted.

210

Table F 30: Component Profile (QS consultancy challenges)

Description of Components and Variables Factor Loading Variance

Explained

Component 1: Contractual and technology challenges

1. Slow response to changing contractual

arrangements

.735 27.385

2. Challenge of appropriate response to

emerging services

.803

3. Slow response to information and

communication technology revolution

.755

4. Inability to integrate applied research

outputs into practice

.719

Component 2: Pricing challenges

1. Reducing fees to loss-making territory .840 18.966 2. Exposure to risks .842

3. Decrease in project value .686

Component 3: Market forces challenges

1. Changing nature of clients’ demand .618 12.172 2. Impact of competition .886

Component 4: Professional fees challenges

1. Fluctuation in professional tariff of fees .910 9.497

6.5 DISCUSSION AND INTERPRETATION OF RESULTS

This section focuses on the discussion and interpretation of the results. It combined the

descriptive analysis utilizing the RII (relative importance index) for ranking of variables; the

inferential analysis results using chi square to test hypotheses; and the factor analysis meant to

classify and reduce variables for development of the generic framework. This section would

adopt the procedure of Leedy and Ormrod (2005) for the discussion and interpretation of results

by relating the findings of the research to the hypotheses advanced; relating the findings to extant

literature, concepts, theories and research studies; determining if the findings have practical and

statistical significance; and identifying the limitations of the research.

211

It is important to recap the problem statement of the research within the context of this

discussion and interpretation in order to be well guided. The problem statement confronting this

research include the need to offer competitive consultancy pricing; setting pricing within

perceived risk factors; the phenomenon of overpricing and under-pricing syndrome which can

cause substantial loss to consultants hence their extinction; existence of serious pricing

challenges confronting built environment consultants in the form of non-payment on the part of

clients for services rendered to them; prices set by professional bodies to which built

environment consultants belong (QS) do not achieve value ( that is absence of value in pricing);

and finally absolute lack of apposite and reliable framework for consultancy services pricing.

6.5.1 Concept of price and value

6.5.1.1 Component 1: Pricing strategies

Pricing strategies are very important in all pricing endeavours. Pricing strategies hinged on cost,

profit, demand and competition have factor loadings of .692, .764, .796 and .637 respectively.

These pricing strategies were in higher order ranking by respondents, having obtained RII above

0.80 respectively. Verifying the statistical significance of these pricing strategies in this study by

employing the chi square test of independence, it is crystal clear there is a significant relationship

between cost, demand, competition and profit hence the acceptance of the hypothesis that cost,

demand, competition and profit are fundamentals of pricing strategies. Extant literature is in

consonance with the acceptance of the above hypothesis in terms of the pricing strategies hence

Robert (2001) advocated that a sound pricing strategy must give much consideration to the

pricing variables of cost, demand, competition and profit.

212

In developing a realistic framework for quantity surveying consultancy pricing, it is crucial to

consider the recovery of cost incurred in providing services to clients; the profit that will accrue

as a reward; the competition from other quantity surveyors in terms of pricing (c.f. Rahim et al.,

2013); and the nature of demand from the perspective of clients. Drawing on from the above, a

sub class pricing framework will be appropriate and novel as demonstrated in figure 6.5.1.1

below.

Figure 6.5.1.1: Pricing Strategies sub framework

Practically, cost oriented strategy and profit oriented strategy are mostly adopted in pricing than

others because most price setters think first of cost recovery to stay in business, and profit to

reward their effort. However, it is appropriate to consider infusing all these strategies in to the

pricing agenda whenever pricing. Each of the above pricing strategies identified namely, demand

oriented; competition oriented; profit oriented; and cost oriented have their own nature and

dynamics which will require a future research study to thoroughly examine their characteristics.

6.5.1.2 Component 2: Just Pricing

The pricing variables classified under this component comprise of seller’s profit; customers

intrinsic value; customer’s affordability; and the government. The eigenvalues of the government

Pricing Strategies

Profit Oriented Competition

Oriented Cost oriented

Demand

oriented

213

and customer’s affordability are slightly above average (-.675 and .665 respectively) hence are

mediocre but examining these variables practically, the two variables are critical in the dynamics

of QS consultancy. The chi square test result revealed that there is no significant relationship

between the government and the achievement of just price; similarly, the variable ‘the

government’ was ranked with an RII of 0.58 which is also mediocre hence it is deemed

eliminated, likewise, the chi square test result revealed that the variable ‘the government’ is not

significantly related to the achievement of just price. However, the chi square test result proved

that just price is significantly dependent on seller’s profit; customer’s intrinsic value; and

customer’s affordability. Practically, the role of governments regarding pricing in capitalist and

democratic economies is very minimal; however, their actions or decisions can indirectly affect

the manner in which demand (client) and supply (consultant) interact in setting a just price or an

equilibrium price.

From the above discussion, the sub pricing framework for just price achievement for the

establishment of equilibrium in consultancy pricing between the client and the quantity surveyor

is demonstrated below in figure 6.5.1.2.

Figure 6.5.1.2: Just/equilibrium pricing sub framework

Just Price

Seller’s profit Customer’s

affordability

Customer’s

intrinsic value

214

A perusal of figure 6.5.1.1 and figure 6.5.1.2 revealed a special relationship between just price

and pricing strategies. In this relationship, profitability exists in both just pricing and pricing

strategies. This phenomenon produces another pricing framework depicted in figure 6.5.1.2a

below.

Figure6.5.1.2a: Pricing strategy and just price relationship

6.5.1.3 Component 3: Pricing Roles

The variables extracted under component 3 include firm’s objectivity; firm’s success; firm’s

image, and firm’s failure with eigenvalues of .779, .810, .717 and .519 respectively; referring to

the ranking by respondents the RII of these variables are above 0.70; similarly, the chi square

result indicated that the role of the firm is significantly dependent on the objectivity, success

image and failure of the firm. The sub pricing framework is demonstrated in figure 6.5.1.3

below.

Pricing

Strategies Just Price

Demand

oriented

Competition

Oriented

Cost

oriented

Customer’s

intrinsic

value

Customer’s

affordability

Profitability

215

Figure 6.5.1.3: Pricing roles sub framework

Practically, the objective of the firm determines the pricing strategy to be adopted in setting

prices hence QS consultancy practitioners must be mindful of their roles and bear in mind that

setting price for clients will either affect their image and ultimately their success in consultancy

business. Comparing figure 6.5.1.3 and figure 6.5.1.2a above, pricing objectivity has created a

relationship between pricing roles and pricing strategies; hence the sub class framework is

depicted in figure 6.5.1.3a.

Figure 6.5.1.3a: Grand sub pricing framework

Pricing Roles

Outcome

Failure

Success

Image

Pricing Objective

Pricing

Roles

Pricing

Objective

Pricing

Strategy

Outcome

Failure

Success

Image

Just Price Profitability

Customer’s

intrinsic

value

Customer’s

affordability

216

6.5.1.4 Component 4: Social influence

Social influence affect pricing; and prominent among them are media action and pressure group.

Media action and pressure group after extraction have factor loading of .783 and .887

respectively. The ranking by respondents also revealed that media action and pressure group

have their RII below 0.50. The chi square test result also produced a p-value below .005 hence

there is significant statistical evidence that social influence is related to quantity surveying

consultancy pricing. Therefore, the sub pricing framework is demonstrated in figure 6.5.1.4

below.

Figure 6.5.1.4: Social influence, sub pricing framework

6.5.1.5 Component 5: Value

Value is important to pricing; component 5 has an extracted variable ‘value of a product or

service’ with factor loading of .803 and an RII of 0.73 in higher order of variable ranking.

Considering the chi square test results of hypotheses in this regard, value of a product or service

has a p-value less than .005 which makes it statistically significant. Equally linked to value is

intrinsic value which is innate to the customer and has the potential of influencing whether the

customer will afford the service. It therefore implies that a relationship is created between value

and just price by intrinsic value and customer affordability. Similarly, social influence can affect

the value system of the client through media advertising, marketing and the actions of consumer

Social

influence

Pressure

group

Media

action

217

protection groups to exert pressure on QS consultancy price setters. In this direction, the grand

sub pricing framework will be represented in figure6.5.1.5 below.

Figure 6.5.1.5: Grand sub pricing framework

This study has not critically examine the key aspects of value pricing in detail, it is novel to

conduct a future study to explore the dynamics of value pricing as far as QS consultancy services

pricing is at stake.


6.5.2.1 Component 1: Business management

Business management has the tendency to affect pricing. Component 1 comprises of firm’s

experience in pricing; duration of service provision; and business development with factor

loadings of .648, .708 and .881 respectively. The ranking of these variables revealed that

duration of service provision (RII= 0.77); firm’s experience (RII= 0.79); and business

development (RII= 0.69) are above average ranking. The chi square test of independence

adopted for testing hypothesis indicated the null hypothesis relating to business development was

Outcome

Failure

Success

Image

Pricing

Roles

Social influence

Pricing

Strategy

Just Price Pricing

Objective

Profitability

Value Systems

Intrinsic value

Affordability

218

accepted hence business development is not dependent on the success of bid price of QS

consultants. A perusal of the ranking of business development is clearly in consonance with the

hypothesis, therefore, there is no statistical evidence to suggest that business development is

dependent on pricing success. However, per the ranking and hypothesis testing, there is statistical

evidence to advocate the dependency of bid price success on duration to render service and

firm’s experience. Practically, clients are interested in the duration of service delivery and the

experience of the consultant to ensure value for money; these would be met by the consultant

based on sound business management practices. Figure 6.5.2.1 demonstrate the sub pricing

framework in terms of achieving realistic QS consultancy services pricing.

Figure 6.5.2.1: Business management, sub pricing framework

6.5.2.2 Component 2: Service cost management

The manner in which the consultant manages cost, value and client attraction (demand) will

reflect the pricing strategy leading to the determination of price levels for clients. The variables

in component 2 comprises of time taken to solve a problem; materials used on the project; good

financial control system; and record of past project cost with factor loadings of .794, .653, .805

and .618 respectively. The ranking of these variables by respondents indicated that time taken to

solve a problem (RII= 0.79); materials used on the project (RII= 0.80); and good financial

control system (RII= 0.75) were in higher order of ranking. The chi square test of hypothesis

Business Management

Duration to render

service

Firm’s Experience

219

relating to these variables revealed a statistical evidence to suggest, a successful criteria for QS

consultancy pricing is significantly dependent on the time taken to solve the problem; materials

used on the project; and good financial control. In view of the above dynamics, the sub pricing

framework is depicted in figure 6.5.2.2 below.

Figure 6.5.2.2: Service cost management, sub pricing framework

Observing figure 6.5.2.1 and figure 6.5.2.2, time taken to solve a problem; and duration to render

service have created a relationship between business management and service cost management.

Hence, the combined framework is depicted in figure 6.5.2.2a as:

Figure 6.5.2.2a: Consultancy (service) management, sub pricing framework

Service Cost

Management

Time taken to

solve problem Good financial

control

Materials used

on the project

Consultancy

(service)

Management

Business

management

Service cost

management

220

6.5.2.3 Component 3: Technical and financial capabilities

The art of pricing is dependent on key elements. Component 3 clearly captures them as

production of timely reports; financial capacity; overhead and profits; and technical capacity

with eigenvalues of .754, .646, .755 and .546 respectively. Equally, the ranking of these

variables, production of timely reports (RII= 0.76); financial capacity (RII=0.78); overhead and

profit (RII= 0.78); and technical capacity (RII= 0.81) are deemed to be in higher order. The chi

square test of hypothesis on these variables indicated that there is significant evidence to suggest

that bid price success is dependent on production of timely reports; financial capacity; overhead

and profit and technical capability. Hence figure 6.5.2.3 demonstrates the sub class framework

for technical and financial capabilities below.

Figure 6.5.2.3: Technical and financial capabilities

6.5.3 Concept of Risk

6.5.3.1 Component 1: Corporate internal risk

Corporate internal risks are directly related to the consultancy firm and affects pricing of services

provided to clients. Component 1 comprises of associated business risk; financial risk; logistical

and infrastructural risk; and managerial risk and operational risk with factor loadings of .727,

.709, .710 and .727 respectively. Similarly, the ranking of these variables revealed associated

business risk (RII= 0.68); financial risk (RII= 0.73); logistical and infrastructural risk (RII=

0.62); and managerial and operational risk (RII= 0.66). The chi square test hypothesis result of

Technical and financial capabilities

Technical

capacity

Overhead

and profits

Production of

timely reports

Financial

capacity

221

these variables demonstrates that there is significant statistical evidence to claim that the

robustness and levels of consultancy services pricing is dependent on financial risk; logistical

and infrastructural risk; and managerial and operational risk. The sub pricing framework is

demonstrated in figure6.5.3.1 below.

Figure 6.5.3.1: Corporate internal risk sub pricing framework

6.5.3.2 Component 2: Corporate external risk

Corporate external risks are not directly related to the core activities of the QS consultancy firms

but they have the potential of affecting the manner in which services are priced. Component 2

comprises of organizational and societal risk; legal risk; and regulatory risk with their

eigenvalues of .766, .710 and .830 respectively. Respondents rank these risks as follows:

organizational and societal risk (RII= 0.63); legal risk (RII= 0.70); and regulatory risk (RII=

0.70). The chi square test of hypothesis revealed enough statistical evidence to suggest that QS

consultancy robustness is dependent on organizational and societal risk; legal risk; and

regulatory risk. In the light of the above, the pricing sub framework is demonstrated in in figure

6.5.3.2 below.

Corporate internal

risk

Financial risk

Managerial and

operational risk

Logistical and

infrastructural risk

222

Figure 6.5.3.2: Corporate external risk

6.5.3.3 Component 3: Location Risk

Location risk occurs as a result of the geographical positioning of the pricing entity. This risk

manifests in various forms like political upheavals and acts of God which may lead to the

disruption of the consultancy process. Component 3 comprises of political risk; and force

majeure risk with associated factor loadings of .883 and .841 respectively. Referring to the

ranking of these risks, political risk (RII = 0.69); and force majeure risk (RII = 0.61). The chi

square test of hypothesis revealed that there is statistical significance to claim that the level of

consultancy pricing is dependent on political risk and force majeure risk. Therefore, the sub

pricing framework is demonstrated in figure 6.5.3.3 below.

Figure 6.5.3.3: Location risk sub pricing framework

Corporate External Risk

Organizational

and societal risk

Regulatory

Risk Legal risk

Location Risk

Force majeure risk Political risk

223

Considering the sub pricing frameworks in figures 6.5.3.1, 6.5.3.2 and figure 6.5.3.3 for

corporate internal risk, corporate external risk and location risk respectively, it is clearly

demonstrated that QS consultancy pricing robustness and level is affected by corporate internal

risk; corporate external risk; and force majeure risk. Hence the sub grand framework for risk

when considering QS consultancy pricing is depicted in figure 6.5.3.3a below.

Figure 6.5.3.3a: Sub grand Pricing risk framework

6.5.4 Concept of Taxation and Inflation

6.5.4.1 Component 1: Taxes

Component 1 consists of taxes which the consultant has to honour as part of statutory duty.

These taxes are considered in this study as pricing variables because they have the capacity to

alter the level of prices set by consultants whom the client has to pay. These taxes include

personal income tax; corporate tax; profit tax; local tax and property tax with factor loading of

.824, .730, .724, .738, .735 and .812 respectively. The ranking of these variables revealed

personal income tax (RII= 0.61); corporate tax (RII= 0.55); profit tax (RII= 0.56); local rate

(RII= 0.57); and property tax (RII= 0.55). The rankings by respondents demonstrated a mediocre

consideration attached to the issues of taxation when pricing consultancy services. The chi

square result of hypothesis testing revealed that there is significant statistical evidence to suggest

Pricing

Robustness and

Level

Location risk Corporate internal

risk

Corporate external

risk

224

that a relationship exist between QS consultancy services levels and the tax variables since their

p-values < .005. Therefore, the sub pricing framework is demonstrated in figure6.5.4.1 below.

Figure6.5.4.1: Taxes sub pricing framework

6.5.4.2 Components 2 and 3: Price catalysts

Some circumstances precipitate QS consultancy price levels and robustness remotely. This

research study christened those price hastening circumstances as price catalysts. The price

catalysts are categorized in components 2 and 3 comprising of inflation, production shortfall,

government policies and input prices with factor loadings of .659, .799, .868 and .816

respectively. The ranking of these price variables revealed inflation (RII= 0.77), production

shortfall (RII= 0.68); effects of input market (RII= 0.70); government policies (RII= 0.69; and

input prices (RII= 0.75). The consideration given to these pricing variable by respondents

through ranking is fairly higher. It is therefore necessary to consider the chi square test of

hypothesis which demonstrated clearly that QS consultancy services price levels are significantly

dependent on inflation, production shortfall, effects of input market and government policies. In

the light of the above, the pricing sub framework is depicted in figure 6.5.4.2 below.

QS Price

Levels

Profit tax Personal

income tax Local

rates

Property

tax

225

Figure 6.5.4.2: QS consultancy price catalyst sub framework

So far it has been realized that the QS consultancy price levels and robustness are affected by

risk and tax liabilities of the consultancy entities. These key variables of risk and tax liability will

depend on the location of the consultancy firm and the environment of the consultancy

engagement hence location has the potential of altering the gauge of QS consultancy services

pricing. Combining figures 6.5.3.3a, 6.5.4.2 and 6.5.4.2 above produces a combined pricing

framework for risk, taxes and price catalysts would produce a sub grand framework

demonstrated in figure 6.5.4.2a below.

Figure 6.5.4.2a: QS pricing level and robustness, sub grand framework

Government

Policies

Inflation

Price

Catalysts

Production

shortfall

Effects of

input market

Input prices

PRICE LEVELS

Taxes Pricing Risk

QS Price Levels and Robustness

Price Catalysts

Input Prices

226

6.5.5 Quantity Surveying Consultancy Services Pricing Components

Having considered the influential factors that relate to the generic pricing environment of QS

consultancy services provision, this section will concentrate on the various components of

consultancy pricing as follows:

6.5.5.1 Component 1: Office Management

Office management is important in every corporate organization. Costs are incurred in the

management of offices which must be recovered through pricing, Component 1 comprises of

staff allowances; office rent; and supplies and equipment with factor loadings of .776, .755 and

.783 respectively. Similarly, respondents ranking of these key variables unfolds as staff

allowance (RII= 0.74); office rent (RII= 0.67); and supplies and equipment (RII= 0.69). It is

clear that QS consultancy services pricing must appreciate office management in order to stay in

business. Hence the sub framework in this regard is depicted in figure 6.5.5.1 below.

Figure6.5.5.1: QS pricing sub framework for office management

6.5.5.2 Component 2: Overheads

Overheads are expenses incurred as a result of providing services to clients. They are

expenditure indirectly related to the core services of the consultancy engagement but are needed

to keep the consultancy machinery moving. Component 2 examines the composition of

overheads for QS consultancy pricing. It consists of insurance, contingencies; taxes and duties

Office

Management

Supplies and

equipment Staff

Allowances Office rent

227

with factor loadings of .779, .828 and .546 respectively. The ranking of these variables indicated

insurance (RII= 0.69); contingencies (RII= 0.72); and duties and taxes (RII= 0.71). In spite of

taxes and duties obtaining higher order ranking from respondents, its eigenvalue of .546 is

mediocre. In addition to the consideration given to taxes by respondents earlier, it is appropriate

to ignore the component related to taxes and duties to avoid double counting or taxation.

Therefore the pricing sub framework is depicted below in figure 6.5.5.2 below.

Figure 6.5.5.2: Overheads pricing sub framework

6.5.5.3 Component 3: Administration and Training

Consultants are often engaged for the training of individuals of corporate organizations or

professional bodies. The expenses incurred in providing the training services must be recovered

for the consultant to stay in business. Component 3 is designated administration and training. It

comprises of variables: travel and transport; communications; training programmes and report

preparation with factor loadings of .817, .555, .771 and .616 respectively. It is also necessary to

refer to the ranking of these variables by respondents which unfolded as travel and transport

(RII= 0.75); communication (RII= 0.69); training programme (RII= 0.66); and report preparation

(RII= 0.72). Observing the factor loading and the ranking of these variables, it is appropriate to

ignore communication because it has a mediocre eigenvalue and ranking but in practical sense, it

Overheads

Contingencies Insurance

228

is impossible to successfully render consultancy services without employing various forms of

communication with the client. Therefore, it is appropriate to include communication in the

framework, hence the sub pricing framework for this component is demonstrated in figure

6.5.5.3 below.

Figure 6.5.5.3: Administration and training sub pricing framework

6.5.5.4 Component 4: Reimbursement and Payments

It is important to reimburse or reward the consultant for services provided to clients. Component

4 comprises of consultant staff remuneration; mobilization and demobilization; and profits with

eigenvalues of .562, .512 and .817 respectively. Referring to respondents ranking of these

variables, consultant staff remuneration (RII= 0.74); mobilization and demobilization (RII=

0.71); and profits (RII= 0.76). Examining the eigenvalues, it is novel to ignore consultant staff

remuneration and mobilization and demobilization because most consultancy engagements are

activities are operated in an office, this is the reason office rent is crucial to the running of

consultancies. Similarly, consultant staff remuneration was considered under the component

office management. In an international engagement, the consultancy would have to relocate to a

different geographical area hence pricing for mobilization and demobilization will be appropriate

in that regard but within the purview of this study, mobilization and demobilization will be

Administration and Training

Training

programme

Communication Report

Preparation

Travel and

transport

229

ignored. The sub pricing framework in terms of reimbursement and payments is demonstrated in

figure 6.5.5.4 below.

Figure 6.5.5.4: Reimbursement and payments sub pricing framework

6.5.6 Challenges confronting Quantity Surveying Consultancy Practice

Every professional practice has its own challenges. In like manner, quantity surveying practice

has its own challenges bedeviling the profession in diverse ways. It is therefore appropriate to

examine the critical challenges inimical to the vivacity of QS professional practice.

6.5.6.1 Component 1: Contractual and technology challenges

This component comprises of variables: slow responses to changing contractual arrangements;

lack of appropriate response to emerging services; slow response to information and

communication technology revolution; and inability to integrate applied research outputs into

practice with eigenvalues of .735, .803, .755 and .719 respectively. The ranking of these

challenges by respondents indicated an average RII of 0.70 which demonstrated that the severity

of these QS practice challenges is slightly above average. Practically, the QS profession is noted

for being conservative to the application of information technology and research integration.

However, the current wave of research revolution on building information modeling (BIM) gives

much hope to overcoming these challenges.

Reimbursement and

payments

Profits Consultant staff

remuneration

230

6.5.6.2 Component 2: Pricing Challenges

QS consultants are confronted with pricing challenges. These are categorized in component 2 as

reducing fees to loss making territory; exposure to risk; and decrease in project value with

eigenvalues of .840, .842, and .686 respectively. The respondents consider these challenges as

having moderate impact on the pricing of services. In a situation where fees are tied to the total

cost of the entire project, the fluctuation or the unstable nature of the project as a result of

variations introduced will affect the level of consultancy pricing.

6.5.6.3 Component 3: Market forces

Market forces influence pricing and should not be ignored. From Table F31, these market forces

have been categorized under Component 3 as the changing nature of demand; and impact of

competition with eigenvalues of .618 and .886 respectively. The perception of respondents on the

impact of these challenges on pricing indicated that changing nature of clients’ demand (RII=

0.71); and impact of competition (RII= 0.72). From these, it can be deduced that the impact of

market forces on Qs consultancy services pricing is much higher than other challenges explored

in this research study. It is therefore vital for practitioners to be very cautious of market forces.

QS professionals are also facing challenges from other professionals who are venturing into QS

practice. This scenario looks ugly for the traditional practitioners of the QS profession as it is

bound to create stiffer competition within the QS consultancy market. For instance, Rahim et al.

(2013) clearly pointed out that the scarcity of projects in the construction industry is a catalyst

for competition among quantity surveying practitioners. Another phenomenon of competition in

the quantity surveying profession is fee competition (Rahim et al., 2013).

231

6.5.6.4 Component 4: Professional fees

In most cases, professional fees in the construction industry especially quantity surveying fee in

many jurisdiction are determined by professional bodies and political authorities(Rahim et al.,

2013), which are not left to the forces of demand (client) and supply (consultant) as it pertains in

other consulting nomenclature like management consultancy. Component 4 contain only

fluctuations in professional tariff of fees with eigenvalue of .910 with respondent ranking its

impact as RII= 0.61. The ranking by respondents revealed that no matter the severity of this

challenge in other jurisdiction, it is a mediocre issue as far as the scope of this study is concerned

because, in practical terms authorities do not interfere in to the gauging of consultancy fees in

Ghana.

A Generic Framework for Pricing QS Consultancy Services

Having examined the pricing issues empirically through the development of sub frameworks

above, it is now time to develop the generic (all-embracing) framework that will reflect the

realities of pricing quantity surveying services. This generic (all-embracing) framework

metamorphosed from figure 6.5.1.3a; figure 6.5.2.3; and figure 6.5.4.2a respectively is

demonstrated in figure 6.6 below.

232

Administration and management

Overheads

Profits

Office management

Reimbursements and Payments

Client QS Consultant

Figure 6.6: A framework for pricing quantity surveying consultancy services

Supply

Supply

Pricing

Strategies

Pricing Catalyst

-Pricing risks

-Taxes

-Input prices

Demand

Value

-Intrinsic

nature of

clients

-Client’s

affordability

-Social

influence

Just Price

Pricing

Management

Pricing

Objectives

Clie

nt E

xp

ec

ta

tio

n

Outcome

-Robust price level

-Image

-Success

-Failure

Pricing S

pine

Client-Consultant Relationship

233

CHAPTER SEVEN

CONCLUSION AND RECOMMENDATIONS

7.1 INTRODUCTION

This research study commenced with the target of extensively delving into the dynamics of

quantity surveying consultancy services pricing. It has become necessary to engage in this

important venture because of the absolute lack of a generic framework for pricing the services

rendered by professional quantity surveyors for their clients as pertaining to other corporate

establishments like manufacturing companies. The six chapters undertaken hitherto the

commencement of this chapter have concentrated on theoretical framework for the research;

literature and conceptual milieu of the research agenda; the methodological dimensions including

philosophical underpinnings of the research; and analysis and discussion of results leading to the

development of framework for pricing.

This chapter ties the knot on the research endeavor by addressing only the main points

throughout the study. It commences by reviewing the objectives of the research study; findings;

recommendations; and limitations of the research. The curtain to this research journey so far

would be drawn on future research agenda emanating from this research.

7.2 REVIEW OF RESEARCH OBJECTIVES

The main aim of this research was to explore Quantity Surveying (QS) practice in Ghana, and to

develop a generic framework for pricing QS professional consulting services in Ghana. To

achieve this novel aim of the research, four key specific research objectives were set to

effectively drive the agenda as follows:

234

Objective 1: To conduct a critical literature review on quantity surveying and consulting

practice

Critical issues concerning the consultancy services pricing environment of the quantity surveying

profession were reviewed to identify the trends in practice. The review was also necessitated by

the need to be abreast with the current quantity surveying and research environment to take

sound decisions concerning what should be investigated. The review aided in the identification

of the knowledge gap and research gap as far as this research is at stake. The review of extant

literature concentrated on key issues notably general consultancy practice; quantity surveying

practice; and a theoretical framework on pricing and its allied concepts which are needed in the

development of a robust pricing framework. The theoretical framework culminated in to the

postulation of key hypothesis in which the dependent variables (DV) were pricing, price

robustness and price levels and several independent variables (IV) (refer to chapter two for more

details). The literature review revealed a gap in research as far as the pricing of quantity

surveying consultancy services are concerned. This lacuna in knowledge and research in quantity

surveying practice alone but in other consulting practices. Similarly, the literature also unfolded

a scarcity of research conducted on quantity surveying practice in Ghana.

Objective 2: To explore the potential challenges confronting Quantity Surveying (QS)

consultancy in Ghana

Challenges confronting corporate organizations would affect their business transactions

culminating into weak pricing strategies which can cause the collapse of business entities if they

are not able to recover the cost of operation among others in the provision of goods and services.

Quantity surveying practice is no exception as far as challenges confronting business entities are

235

concerned. This study explored the challenges confronting quantity surveying consultancy

practice and found changing nature of clients’ demand; impact of competition; complexity of

modern construction projects and slow response to information and communication technology

revolution as the general challenges confronting quantity surveying consultancy practice. On

pricing challenges, the study revealed exposure to risks; and decrease in project value by

inflation. However, price-related challenges are perceived to be moderately significant in the

pricing of quantity surveying consultancy services except in the cases of market forces. This

therefore implies that the general challenges are the most severe challenges confronting quantity

surveying practice. Risk of various dimensions posing as challenges to quantity surveying

consultancy services pricing identified by the study have been categorized as directly related to

the activities of the consulting firm include financial risk; market related risk; and technological

risk. Indirect risk which are risks occurring at the various stages of the project implementation

were identified by the study as financial risk; legal risk; political risk; and regulatory risk. Using

the factor analysis, these risks were further classified as corporate internal risk; corporate

external risk; and location risk (political risk and force majeure).

Objective 3: To establish the key determinants (indicators) in pricing QS consultancy service

practice

The study also sought to identify the key determinants of quantity surveying consultancy

services pricing. The study unfolded the key determinants as demand for quantity surveying

services; taxes and inflation; amount of cost incurred in service provision; various forms of risks

as identified in objective 2 above; inflation; effects of input market; service cost management;

value; social influence (media and pressure groups); pricing strategies adopted; profit; and

duration of service provision.

236

Objective 4: To develop a generic framework for pricing QS consultancy services based on the

identified indicators

In achieving the above objective which is the grand agenda of this study, the researcher

combined the results and discussion conducted using statistical tools: relative importance index,

chi-square test of hypothesis to ascertain the relationship between the dependent variables and

independent variables; and the factor analysis to identify the underlying common factors among

these pricing variables. The discussions led to the development of the generic framework

depicted in figure 7.1 below.

237

Administration and management

Overheads

Profits

Office management

Reimbursements and Payments

Client QS Consultant

Figure 7.1: A generic framework for pricing quantity surveying consultancy services

Pricing Catalyst

-Pricing risks

-Taxes

-Input prices

Just Price

Value

-Intrinsic

nature of

clients

-Client’s

affordability

-Social

influence

Pricing

Management

Outcome

-Robust price level

-Image

-Success

-Failure

Pricing S

pine

Clie

nt E

xp

ec

ta

tio

n

Pricing

Strategies

Pricing

Objectives

Demand Supply

Supply Client-Consultant Relationship

238

7.3 FINDINGS

In addition to the findings under the review of research objectives above, other findings

identified by the research study which are crucial to the pricing of quantity surveying

consultancy services include:

indirect risks associated with projects are significant pricing variables that can change the

levels of consultancy services pricing;

financial risk is both direct and indirect consultancy services pricing risk of major

proportion;

when cost of consultancy services is high all components of consultancy services pricing

will be proportionally high except profit and contingencies;

the dominance of capitalism has weakened the power of professional bodies in price

determination and control leading to haggling between demand (client) and supply

(consultant) to set consultancy services price levels hence price-related challenges are

deemed to be moderately significant in the pricing of quantity surveying consultancy

services except in the case of market forces;

traditional QS consultancy services are the most significantly priced while the non-

traditional services remain the less priced;

QS consultancy price levels and robustness are affected by risk and tax liabilities of the

consultancy entities;

corporate external risks are not directly related to the core activities of the QS

consultancy firms but they have the potential to affect QS consultancy services pricing;

239

social influence affect the value system of the client through media advertising,

marketing and the actions of consumer protection groups will exert pressure on price

setters;

intrinsic values of clients have the potential of influencing the affordability of QS

consultancy services; and

QS consultancy price levels and robustness are affected by risk and tax liabilities of the

consultancy entities.

7.3.1 Special Relationships Identified

The tripartite discussion of the results involving the three main statistical tools employed for this

research study in section 6.5 of chapter six culminating into the above generic framework for

quantity surveying consultancy services pricing has led to the creation of key relationships

among some of the variables involved in the study by other variables equally involved in the

study. These relationships were discovered during the development of the various subclass

frameworks and include the following:

1. A relationship has been created between profitability and pricing strategies. This means

that the type of pricing strategy adopted by the quantity surveying consultant would

determine the level of profit to be enjoyed from services rendered to clients;

2. There is a relationship between pricing objectivity and pricing strategy. This implies that

the objective of pricing would determine the pricing strategy to be adopted;

3. Time taken to render service to clients has a bearing on business management and

service cost management. This means that the cost of service provision is proportional to

the duration of the service provision; however, adoption of appropriate business

240

management practices would determine whether higher or minimal service cost would be

incurred; and

4. Production of timely reports is related to business management, service cost

management, technical and financial capabilities.

7.4 CONTRIBUTION TO KNOWLEDGE

The relevance of a research is measured in terms of its contribution. All over the world higher

education institutions set their parameters for contribution to knowledge. Thus what counts as a

contribution to knowledge may slightly differ from institution to institution but there are

commonalities among these parameters for determining contribution to knowledge by a research

work. For instance, Gray (2011) identified five criteria for determination of contribution to

knowledge as:

literature review to demonstrate what counts as knowledge in the area of discourse and

establishing what is currently known in the area of research study;

development of frameworks (models);

publications;

contributions to methodology; and

formulas.

Within this study, extensive literature review had been conducted covering the key areas of

general consultancy; quantity surveying practice; and a theoretical framework of the general

pricing milieu. These reviews demonstrated that much work has not been done in the areas of

quantity surveying practice in Ghana especially in terms of research which is entirely focus on

241

QS services pricing. The review revealed that even though QS practitioners publish papers in

Ghana, they rather focus mostly on other areas such as project management which are not their

core areas of operation. This research also contributed to knowledge by publication of papers in

international journals of repute. It is estimated that this research study has the potential of

yielding more than three academic publications.

The generic framework for pricing consultancy services contributes to knowledge in diverse

ways by the combination of the various facets of pricing dynamics into a simpler, manageable,

and comprehensive entity for price setters of consultancy services and others alike. The key

findings of the research regarding value emphasized the need for ensuring value in pricing QS

services which hitherto pricing knowledge transmission has not been robust. This is very

significant in the case of knowledge transmission to provide value pricing in consultancy

services provision to clients especially in the arena of quantity surveying. The pricing catalysts

comprising pricing risks, taxes and input prices have added to the dimension of pricing

consultancy services especially in terms of potential risks that can alter the robustness and level

of consultancy services pricing. A pricing knowledge in area of the identified pricing catalysts by

this research provides solid foundation for understanding pricing situations faster. This leads to

quick analysis of consulting engagements to price effectively. In addition, this study identified

special pricing relationships among key pricing variables of profitability and pricing strategy;

pricing objectivity and pricing strategy; and the concept of consultancy duration and its bearing

on business and service cost management. The knowledge of these special pricing relationships

improves the knowledge base of consultancy services price setters. The systematic manner of

developing the generic framework through the development of subclass pricing frameworks has

242

added to the understanding of consultancy services pricing phenomenon that pricing within the

QS consultancy practice should be systematic and methodical.

7.5 RECOMMENDATIONS FOR PRACTITIONERS

In view of the findings of this research, it is appropriate to recommend vital issues for

consideration by consultancy practitioners and other stakeholders as far as consulting practice is

concerned. These recommendations include the following:

it is important for price setters in the consulting industry to envisage the risks in relation

to consulting engagements for which they are employed to provide services;

the low ranking of various taxes except VAT/NHIL means non-payment of taxes or tax evasion

by consultants dealing with private sector clients as a result of the inability of the tax authorities

to locate consultants to fulfill this statutory obligation due to improper planning and layout of

offices. This finding is a pearl for the tax authorities to dwell on in expanding their tax net to

mobilize more revenue for government coffers for development;

it is equally important for consulting entities to take due cognizance of inflation and its

causes that will affect consultancy services pricing;

competition in the non-traditional service sectors of QS practice is not intensive hence

innovative QS practitioners venturing into facilities management; oil and gas and other

non-traditional services of quantity surveying have the opportunity of making substantial

profit; and have the prospect of enjoying some significant monopoly for some

considerable period of time;

practically, clients are interested in the duration of service delivery, the consultant can

only meet this expectation by deploying experience in sound business management to

243

ensure value for money thereby meeting timelines, cost and quality expectations of

clients;

the objective of the firm determines the pricing strategy to be adopted in setting prices

hence QS consultancy practitioners must be mindful of their roles and bear in mind that

setting price for clients will either affect their image and ultimately their success in

consultancy business; and

the impact of market forces on QS consultancy services pricing is much higher than other

challenges. It is therefore vital for practitioners to be very wary of the market.

7.6 FUTURE RESEARCH AGENDA

This study has its own shortcomings as it cannot cover all aspects of the consultancy services

pricing agenda. It is therefore appropriate to turn these shortcomings into future research to be

undertaken; these future researches as far as this study is concerned evolved from the analysis

and discussion of the research results (see for instance chapter six) include:

a further research agenda to explore the in-depth dynamics of pricing objectives with

much emphasis on their influence on price levels will be a novel research undertaking;

it is therefore necessary to determine the parameters for the ascertainment of value of

services provided by QS consultants to their clients, this phenomenon has not been

addressed by this study hence a research agenda to determine the parameters for value of

services will be novel and apt;

Similarly, a study to determine the willingness to afford or pay (WTP) by clients for

consultancy services will be a step in the right direction;

244

having established the evidence of these variables (demand, cost, competition and profit)

as the fundamentals of pricing, it is novel that a further research at advanced level be

conducted in an in-depth manner on the dynamics of each of these variables in

influencing consultancy services pricing;

it is important to explore the nature of consultancy financial risks, to establish its true

level of influence and other associated encumbrances in pricing;

this study has not critically examine the key aspects of value pricing, it will be necessary

to conduct a future study to explore the dynamics of value pricing as far as QS

consultancy services pricing is at stake; and

a further empirical study on the relationship between economic development and demand

for consultancy services would be a novelty to undertake at a higher level of research.

7.7 CONCLUSIONS

It is important to examine the various aspects of the generic framework developed from this

research work viz-a-viz the circumstances surrounding a particular consulting engagement

during service delivery to clients. It should be noted that the utilization of this framework is

subject to the manipulation of the quantity surveying services price setter since practitioners

would operate under different ambiance all the time. In short, the framework should be used in

relation to the circumstances of the consultancy service price setter.

The adoption of this framework for practice has the potential of providing consultancy

practitioners the opportunity to estimate realistic prices based on the nature of their service

delivery. The generic framework also provides an opportunity for reflections on consultancy

245

engagements in order to engage in the right caliber of practices that would inure to the

profitability and sustenance of consultancy firms.

246

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APPENDICES

APPENDIX 1: QUESTIONNAIRE

This research is a Postgraduate level research entitled “A Generic Framework for Consultancy Service

Pricing: The Case of Quantity Surveying Practice (QSP)” and intends to identify the challenges

confronting QSP; to establish the key determinants of pricing QS consultancy services; and to establish a

framework for pricing QS consultancy services. Please , kindly respond to the questions by

ticking(√) the appropriate box for each item. Please note that all information provided will be

strictly treated as confidential as this work is for academic purposes.

Firm Status

1. What is the status of your firm?

A. Enterprise / sole proprietorship [ ]

B. Private Limited company [ ]

C. Partnership / Joint venture [ ]

D. Other (Please specify) ……………………………………………………… [ ]

Years of Experience

2. How long has the firm been in existence?

[ ] under 10 years [ ] 11 – 20 years [ ] 21 – 30 years [ ] over 30 years

Rate of work acquisition

3. How frequent do you render consultancy services to clients?

[ ] Not frequent [ ] moderately frequent [ ] frequent [ ] very frequent

Sectors of operation

4. Which of the following sectors do you render services frequently? Use the key: 1= Not frequent 2=

Less frequent 3= Moderately frequent 4= Frequent 5= Very frequent.

Sectors 1 2 3 4 5

Building construction

Civil and structural engineering

Mechanical building and engineering services

Petro-chemical

Mineral extraction

Urban planning

Concept of Price and Value

5. How significant does your pricing decisions depend on the following factors? Use the key 1= Not

significant 2= Less significant 3= Moderately significant 4= Significant 5= Very significant

E. PRICE AND VALUE 1 2 3 4 5

Value of a product or service

Affordability

F. JUST PRICE

271

The Government

Media action

Pressure Group

Seller’s profit

Customer’s intrinsic value

Customer’s affordability

G. IMPORTANCE, OBJECTIVES AND GOALS OF PRICING

(ROLE OF THE FIRM)

Firm’s objectivity

Firm’s failure

Firm’s success

Firm’s image

H. PRICING STRATEGIES

Cost

Profit

Demand

Competition

Project Pricing (Consultancy Pricing)

6. How will the following influence your consultancy services pricing decisions? Use the key 1= Not

significantly 2= Less significantly 3= Moderately significantly 4= Significantly 5= Very significantly.

B. PRICING PARAMETERS/ CRITERIA

1

2

3

4

5

Time taken to solve the problem

Materials used on the project

Good financial control system

Record of past project costs

Accurate forecast of future cost

Production of timely reports

C. BID PRICE SUCCESS IS DEPENDENT ON

Financial capacity

Technical capacity

Firm’s experience

Duration to render the service

Firm’s reputation

Business development

Overhead and profit

Concept of Risk

7. To what extent does the following affect your pricing decision? Use the scale: 1= Not significant 2=

Less significant 3= Moderately significant 4= Significant 5= Very significant

B. PRICE AND RISK

1

2

3

4

5

Associated business risk

Financial risk

Market related risk

Logistical and infrastructural risk

272

Managerial and operational risk

Technological risk

Organizational and societal risk

C. RISKS AT VARIOUS STAGES OF PROJECTS AFFECTING

CONSULTANCY PRICE LEVELS

Financial risk

Legal risk

Regulatory risk

Political risk

Force majeure risks

Concept of Taxation and inflation

8. How significant would the following influence your pricing decisions? Use the key: 1=Not significant

2=Less significant 3= Moderately significant 4= Significant 5= Very significant

A. TAXATION

1

2

3

4

5

Personal income tax

VAT/ NHIL

Corporate tax

Profit tax

Local rates

Property tax

B. INFLATION

Input prices

Inflation

C. INFLATIONARY CAUSES AFFECTING CHANGE IN

CONSULTANCY PRICE LEVELS

Production shortfall

Effects of input market

Government policies

International trade and trade barriers

Quantity Surveying Consultancy Services Pricing Components

9. How significant are the following quantity surveying consultancy pricing components in your price

build-up? Use the key: 1= Not significant 2=Less significant 3=moderately significant 4= Significant

5=Very significant.

A. Pricing Components 1 2 3 4 5

Consultant staff remuneration

Travel and transport

Mobilization and demobilization

Staff allowances

Communications

Office rent

Supplies and equipment

Training programmes

Report preparation

Insurance

Contingencies

273

Taxes and duties

Profits

Challenges confronting quantity surveying consultancy practice (Odeyinka, 2006; Eke, 2006; cartlidge,

2002; Cruywagen and Snyman, 2005)

10. How would you rate the following challenges confronting quantity surveying consultancy practice?

Use the scale: 1= Not Severe 2=Less severe 3=Moderately severe 4=Severe 5= Very severe.

A. GENERAL CHALLENGES 1 2 3 4 5

Slow response to changing contractual arrangements

Challenge of appropriate response to emerging services

Slow response to information and communication technology revolution

Inability to integrate applied research outputs into practice

Changing nature of clients’ demand

Impact of competition

Complexity of modern construction projects

B. PRICING/FEES CHALLENGES

Reducing fees to loss-making territory

Exposure to risks

Decrease in project value

Fluctuation in professional tariff of fees

Quantity surveying consultancy services (Seeley, 1997; Olatunde, 2006)

11. What would you say about the rate at which you provide the following quantity surveying consultancy

services to clients? Use the key: 1= Not frequent 2= Less frequent 3= Moderately frequent 4= Frequent

5= Very frequent

A. TRADITIONAL SERVICES (SEELEY, 1997) 1 2 3 4 5

Preliminary cost advice

Cost planning and cost checking

Advice on contracting methods

Advice on construction procurement systems

Valuation of construction work

Preparing tender documents

Negotiating contract prices

Participating in contract administration

Preparing cash flow forecasts

Cost control of projects

Value management

Interim valuations and payments

Financial statements

Valuation of variations

Final account preparation and agreement

Project management

Claims preparation

Arbitrations and disputes resolution

B. NON-TRADITIONAL(EMERGING) SERVICES (OLATUNDE,

2006)

274

Oil and gas

Management of capital expenditure

Procurement management

Construction management

Rail network

Cost and business planning

Procurement and supply chain management

Commercial management

Facilities management of stations

Risk and value management

Whole life cycle cost management

Power sector

Cost planning and budgeting

Program management

Construction management

Expertise in maintenance programme

Advice on procurement strategy

Contract administration

Project management

Development and facilities management

275

APPENDIX 2: Random Number Table used for sample selection

1 2 3 4 5 6 7 8 9 10

1 8450 6992 6563 0340 2649 6933 9446 6182 2601 7800 2 5952 1443 7100 8444 3904 0159 1849 2601 9763 9058 3 5711 6779 9388 9668 4167 1423 2744 4622 2179 8503 4 2681 8047 0494 7853 8411 5406 8127 9577 8530 2350 5 0739 3114 3997 3482 3226 2216 6874 0620 8521 2938 6 8985 2463 5054 3448 6357 0187 6342 4740 4064 5068 7 7644 9339 8375 4583 7715 6355 6827 2055 9328 3287 8 6277 6631 8797 3693 6370 1436 1599 6267 2758 0323 9 6355 7590 7628 9054 0022 4241 7499 3430 3644 6576

10 7828 0589 3075 1954 5972 2266 0055 1097 9706 9009 11 6026 4546 4119 1554 4895 3123 9849 2094 5062 6711 12 8416 1972 9345 1593 2943 2379 5062 4829 5952 8292 13 1433 8823 7706 5273 6160 2161 5510 8617 7894 0175 14 0622 4884 8113 4447 5735 6347 7280 2301 2330 0693 15 4104 7164 1184 3964 2119 6968 0469 3827 0845 8400 16 4272 4979 1471 0942 9573 4283 1557 0161 3957 2516 17 1225 4171 3433 8700 0042 5884 2508 3250 1520 6366 18 7442 6575 1927 7267 7182 3960 4341 0350 1126 5945 19 4911 9007 3048 0319 0916 3002 1466 4421 7246 7662 20 3143 7402 4486 0909 1858 7961 1211 6296 5545 4588 21 8055 9294 2578 0426 4322 6925 2487 5677 9491 4301 22 9240 5260 7134 8001 0140 3394 8437 4066 2855 0933 23 7923 8630 3654 2638 2868 1059 0903 3114 6351 8261 24 0020 5104 4344 3324 9214 6615 5926 7012 9052 9205 25 3312 5923 5469 9171 4877 5392 3394 5077 3750 5637 26 3466 4193 5330 4680 0456 5891 3175 5733 5678 0956 27 1677 1694 1697 8921 2520 2811 3597 1355 9605 3637 28 3846 6283 0969 0051 5857 1043 1671 2013 8955 7706 29 8084 2327 0550 7231 1087 4830 9742 5654 5458 8290 30 2715 2247 4504 1374 9236 7340 1773 0693 2749 1335 31 6537 5815 9312 1460 6593 7678 4312 7537 9360 7195 32 4263 8931 1642 6694 1925 2661 1274 7346 8234 3159 33 7468 4077 6691 3961 7640 2355 9938 8485 9398 8364 34 4884 3324 3690 7433 1245 0523 4483 5933 5634 0512 35 7222 7299 1346 8937 0933 1569 5562 3735 2982 5966 36 5040 0820 8606 4006 4743 6343 4873 1002 4757 1075 37 2980 4860 5694 1501 5791 9414 7246 1283 9766 7427 38 8660 5480 7436 9745 8869 3307 4916 6543 9830 6099 39 7627 4959 6417 3542 1877 0370 5464 9590 5184 7379 40 1890 7664 7144 3523 8465 0385 8174 4740 3654 5543 41 3175 2580 3919 7436 0796 1018 5565 1142 4577 0457 42 7616 9338 6304 0283 6502 9085 5443 1531 9724 4140 43 5223 4525 0895 9930 0050 2201 5270 6447 1850 2070 44 9384 9794 8418 0374 4119 2075 0067 4535 7769 4719 45 5862 9165 5302 9789 5771 9670 7523 9280 2604 0212 46 9450 9307 6597 7183 5243 8854 6735 2415 0364 3096

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