hkca public policy research project fund 2009 – final report
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Policy changes to avoid boom and bust of the
construction cycle
thereby improving working opportunities and the quality of the
construction workforce
Ir KP Yim, Ir YM Fan, Ir Dr Linda Fan, Dr Paul Fox, Dr Vincent Ng
Funded by
Hong Kong Construction Association Funding Scheme
for the Public Policy Research/Project 2009
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Reported by
Association of Engineering Professionals in Society Ltd
and
Department of Building and Real Estate, The Hong Kong Polytechnic University
Funded by
Hong Kong Construction Association
March, 2011, Hong Kong
Copyright
All rights reserved. No part of the publication may be reproduced, stored in a retrieval system,
or transmitted in any form or by any means, electronic, mechanical, photocopy, recording orotherwise, without the prior written permission of the authors.
Disclaimer
While the authors and the publisher believe that the information and guidance given in thiswork are correct, all stakeholders must rely upon their own skill judgment when making use
of it. Neither the authors nor the publisher assume any liability to anyone for any loss or
damage caused by any error or omission in the work, whether such error or omission is the
result of negligence or any other cause. Any and all such liability is declaimed. Please note
that the comments of the study are only the views of the research team in their academic andprofessional pursuit and do not necessarily represent the opinion of the institutions orindividuals interviewed.
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Acknowledgements
We would like to express our deepest gratitude to all the interviewees who have
kindly spent their precious time for our interviews and provided us with most valuable
insights during the interviews with them during this study. They have offered their
help without hesitation and their expert knowledge in the subject matter is most
valuable to this research project. Without them, this project study simply could not be
accomplished.
Our sincere thanks are also to those who have made their effort to complete and return
to us the 145 questionnaire surveys. Their views, comments and suggestions
contributed significantly in guiding us to carry out the analysis, particularly in thechapters of the Conclusions and Recommendations.
We would like to thank the Association of Engineering Professionals in Society (AES)
who selected us to take up this project study, and have supported us throughout.
Last, but not least, we express our thanks to the Hong Kong Construction Association
(HKCA) who have generously given their financial support to enable the successful
commissioning and completion of this report.
KP Yim, YM Fan, Linda Fan, Paul Fox, Vincent Ng
The Research Team
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Table of ContentsPage
Foreword Ir Dr. the Hon Raymond C.T. Ho
Foreword Prof. Geoffrey Q.P. Shen
Acknowledgements
Table of Contents
Executive Summary
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Chapter 1 Introduction
1.1 The Project
1.2 Background to the Study
1.3 Project Objectives
1.4 Project Approach and Scope
1.5 Project Progress and Activities
1.6 Project Report
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Chapter 2 Review of Past Research Studies
2.1 Introduction
2.2 Definitions and Selection of Key Concepts
2.3 Factors that Cause Boom and Bust to the HK Construction Industry
2.4 Effect of the Bidding System on the Workforce Quality
2.5 Factors to improve workforce quality
2.6 Issues concerning the attractiveness of the industry
2.7 Summary of Literature Review
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Chapter 3 Methodology
3.1 Introduction
3.2 Project Objectives & Data Sources
3.3 Data Collection & Processing Methods
3.4 Independent, Dependent and Control Variables
3.5 Statistical Analytical Methods
3.6 Concluding Remarks
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Chapter 4 Macro-economic Data Analysis
4.1 Introduction4.2 Time Lag Analysis Visual Inspection
4.3 Time Lag Analysis Pearsons Correlation Coefficients
4.4 MRA & HRA Results
4.5 Summary of Findings
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Chapter 5 Questionnaire Survey Analysis
5.1 Introduction
5.2 Problems during Boom & Bust Times5.3 Personal Experience during Boom Times
5.4 Personal Experience during Bust Times
5.5. Summary of Findings
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Chapter 6 - Interview Data Analysis
6.1 Introduction
6.2 Capturing the Data from the Interviews
6.3 Analysis of the Responses
6.4 Summary of Interview Responses in Relation to the Study
Objectives
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Chapter 7 Discussion, including Forum Responses
7.1 Meeting with the Objectives
7.2 Scope of Improvements in Hong Kong Construction Industry
7.3 Labour Shortages
7.4 Ageing Workforce
7.5 Attract Young People to Join the Industry
7.6 Training
7.7 Avoid the Future Down Turn Period as Far as Possible
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Chapter 8 Conclusions and Recommendations8.1 Opportunities in Greater Pearl River Delta (GPRD)
8.2 To Strengthen and Provide the Training Facilities
8.3 Attracting Young People to Join the Industry
8.4 A Long Term Construction Planning Policy
8.5 Bust Doesnt Necessarily Come After the Boom
8.6 Recommendations
Reference
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Figures
Figure 2.1 Characteristics of Boom & Bust in the HKCI
Figure 2.2 Independent & Dependent Variables for Statistical Analysis
Figure 2.3 Independent by Broad and Detailed End-Users
Figure 4.1 Real Gross Value of Construction Works by Trade Construction
Sites (1983Q1 to 2010Q2)
Figure 4.2 Real Gross Value of Construction Works by Trade Construction
Sites (1984Q1 to 2010Q2)
Figure 4.3 Real Gross Value of Construction Works by Trade Locationsother than Sites (1983Q1 to 2010Q2)
Figure 4.4 Real Gross Value of Construction Works by Trade Locations
other than Sites (1984Q1 to 2010Q2)
Figure 4.5 Real Gross Value of Construction Works by Trade (1983Q1 to
2010Q2)
Figure 4.6 Real Gross Value of Construction Works by Trade (1984Q1 to
2010Q2)
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Figure 4.7 Real Gross Value of Construction Works by Broad End-Use
group Buildings (1983Q1 to 2010Q2)
Figure 4.8 Real Gross Value of Construction Works by Broad End-Use
group Buildings (1984Q1 to 2010Q2)
Figure 4.9 Real Gross Value of Construction Works by Broad End-Usegroup Structures (1983Q1 to 2010Q2)
Figure 4.10 Real Gross Value of Construction Works by Broad End-Use
group Structures (1984Q1 to 2010Q2)
Figure 4.11 Real Gross Value of Construction Works by Broad End-Use
Group (1983Q1 to 2010Q2)
Figure 4.12 Real Gross Value of Construction Works by Broad End-Use
Group (1984Q1 to 2010Q2)
Figure 4.13 General vs Construction Unemployment (1982Q1 to 2010Q2)
Figure 4.14 General vs Construction Unemployment (1983Q1 to 2010Q2)
Figure 4.15 General vs Construction Unemployment Rate (1982Q1 to
2010Q2)
Figure 4.16 Construction Employment in Construction Sites (Building vsCivil Engineering (1982Q2 to 2010Q2)
Figure 4.17 Construction Employment in Construction Sites (Building vs
Civil Engineering (1983Q2 to 2010Q2)
Figure 4.18 Construction Employment in Construction Sites (Public vs
Private Sector (1982Q2 to 2010Q2)
Figure 4.19 Construction Employment in Construction Sites (Public vs
Private Sector (1983Q2 to 2010Q2)
Figure 4.20 Real Wage Index of Construction Workers in Public Sector
(1985Q4 to 2010Q2)
Figure 4.21 Real Salary Index A of Construction Managerial & professional
Employees (1983Q2 to 2010Q2)
Figure 4.22 Real Salary Index B of Construction Managerial & professional
Employees (1983Q2 to 2010Q2)
Figure 4.23 Money Supply M1, M2, & M3, Hang Seng Index, Tael Gold,
GDP & GDP Construction (1982Q1 to 2010Q2) (Seasonally
Unadjusted)
Figure 4.24 Money Supply M1, M2, & M3, Hang Seng Index, Tael Gold,
GDP & GDP Construction (1982Q1 to 2010Q2) (Seasonally
Adjusted)
Figure 4.25 Consumer Price Index (1982Q1 to 2010Q2)
Figure 4.26 Tender Price Index (1982Q1 to 2010Q2)
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Tables
Table 4.1 Summary of Time Lag Relationships amongst GVCWs
Table 4.2 Summary of Time Lag Relationships amongst EmploymentTable 4.3 Summary of Time Lag Relationships amongst Wage/Salary
Indices
Table 4.4 Summary of Time Lag Relationships amongst Control Variables
Table 4.5 Summary of Stochastic Time Lag Relationships between
Dependent Variables and Control Variables
Table 4.6 Summary of Stochastic Time Lag Relationships between
Dependent Variables and Independent Variables
Table 4.7 Summary of Stochastic Time Lag Relationships between
Independent Variables and Control Variables
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Executive Summary
The excessive fluctuations imposed on the construction industry over many decades
have led to a culture of risk avoidance and in turn to a lack of stability in employmentrelations for manual workers, and consequential lack of training, lack of adequate
skills, lack of pride in ones occupation, poor image and lack of interest from
youngsters in joining the industry.
In Hong Kong the industry faces a huge increase in the construction workload coming
on stream over the next five years. A better understanding of these aspects and their
interrelationship can lead to measures which help the industry to be more stable, more
responsive, more efficient, more competitive, more attractive and more sustainable.
This leads us naturally to adopt the following objectives of the study.
The FOURobjectives of this Project identified for study are to:
Investigate and analyze the factors that cause boom and bust to the Hong Kongconstruction industry;
Assess the opportunities in improving the quality of the construction workforce inthe next decade in Hong Kong;
Investigate and analyze the effect of the volatile contract price fluctuation on thequality of the construction workforce and construction industry; and
Assess the present situation of the shortage of young people to join theconstruction industry, and to recommend ways of improvements in attracting them
to join the industry, in readiness for the major construction projects in Hong Kong
over the next decade
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4. Macro-economic Data AnalysisThe time lag analyses by visual inspection by referring to the graphs and by using the
Pearsons Correlation Coefficients. Then the multivariate Multiple RegressionAnalysis and Hierarchical Regression Analysis results together with the statistical
interpretations in relation to the phenomenon of the Hong Kong construction industry
for the past 30 years of boom and bust are analyzed and reported the details in
Chapter 4.
In analysis, the control variables are powerful in predicting the Employment and
Unemployment Indicators. The higher the GDP is, the lower the construction
unemployment and unemployment rate. At the same time, the greater the Money
Supply M2, the Hang Seng Index and Tael Gold Bar are, the lower the general and
construction unemployment. However, the greater the Money Supply M1 and M3 are,
the higher the construction unemployment and general unemployment respectively.Money Supply M1, M2 and M3 therefore do not exhibit salient time lag among them,
which is contradictory to common initiation.
The control variables are also powerful in predicting the Real Wage Index. The
greater the Construction GDP is, the higher the Real Wage Index of all major trade
workers. The greater the Money Supply M1 is, the higher the Real Wage Index of
most major trade workers. At the same time, the greater the Money Supply M2 is, the
higher the Real Wage Index of several major trade workers. However, the greater the
Money Supply M3, Hang Seng Index and Tael Gold Bar are, the lower the Real Wage
Index of all major trade workers. On the other hand, various construction spending
components are not as powerful as the control variables.
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5. Questionnaire Survey AnalysisChapter 5 reports the results of various statistical data analyses of the questionnaire
survey with 145 respondents of construction professionals. The primary data collectedpersonal attributes including the employment, management level and overseas
experience. The respondents have been asked views on 8 problems during boom and
bust times and 18 questions on personal experience during boom and bust times.
The employed construction professionals are more optimistic than the self-employed
ones when they faced the problems during boom and bust times. Both self-employed
and employed construction professionals have significantly different views to nearly
all problems they faced during boom and bust times except for the problems of
economic efficiency and work safety. The construction professionals working in
developer are the most optimistic when they faced problems whilst those working in
localized foreign contractor are the most pessimistic during boom and bust times.
The construction professionals at different management levels tend to be optimistic
towards certain problems during boom and bust times rather than being optimistic to
everything during boom and bust times. The junior management is the most
optimistic towards quality of work output, work performance reliability, reluctance to
invest in training and reluctance to innovate but the most pessimistic towards
economic efficiency, work safety, difficulties in recruiting young people and
reluctance to invest in business/organization. However, both middle and senior
management are neither the most optimistic nor the most pessimistic towards the
problems they faced during boom and bust times. The construction professionals with
moderate overseas work experience are the most optimistic when they faced problemswhilst those with well overseas work experience are the most pessimistic during boom
and bust times.
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6. Interview Data AnalysisThe interviewees opinions form a very significant part to this research study. The
respondents identified:
6.1 Nine factors that cause boom & bust in the Hong Kong construction industry
Governments total investment in public works per year (and this should notfluctuate too much year on year);
The HKCI should regulate itself based on a good understanding of industrycapacity and a long-term plan for workload. Law should be introduced if
necessary;
Maintenance work; Social needs of projects (new railways, hospitals, etc) given priority, then
other needs
Local manpower resources available (2 respondents mentioned this); Availability of training capacity in training institutions; Economic benefits of projects; Private sector demand should be included in picture; Better understanding of what we have already.
6.2 Six areas of opportunities in improving the quality of the workforce
The need for training Employment conditions needed to be improved Development of a professional culture at all levels was generally overlooked. Innovation was mentioned by about half of the stakeholders and revolved
around prefabrication / precast.
Globalisation was mentioned by about half of the stakeholders, and usually inthe context of importation of labour/professional skills.
Quality of Working Life (QWL) was mentioned by 3 stakeholders but only inpassing. They stressed that this was particularly acute because of the age
profile of the existing workforce, with many workers in their 50s likely to
retire in the next 10 years.
6.3 No possible linkages between volatile contract price fluctuation on the quality of
the construction workforce; and
6.4 Almost universal agreement that there is a shortage of young people to join the
construction industry, and this is a significant problem.
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7. Discussion, including Forum ResponsesThe synthesis is brought together in Chapter 7. This also incorporates further data
captured in our Industry Forum organized on 31 August 2010 by inviting the
construction stakeholders, academics, government officials and labour union
representatives to air their views and discussed the issues, where they responded toour interim findings as presented by all members of our research team.
The chapter aims to explore the scope for improvements in Hong Kong construction
industry, in particular, the phenomenon of the changes in the workload from boom to
bust and back again, are well-known, yet difficult for the industry to deal with on its
own. Key issues are highlighted in discussion, including labour shortages; ageing
workforce; attracting young people to join the construction industry; training; and
avoiding the future down turn period.
8. Conclusions and RecommendationsThe final chapter draws the threads of the whole study together. Chapter 8 addresses
the critical issues with a view to making recommendations on how to avoid the future
bust, to refrain from following the boom and bust cycle of the construction industry in
Hong Kong.
The Government should look into the issues and to even out and lengthen the
construction time of those infrastructure projects which do not fall into the critical
path of the long term strategic public works programme by:
Postponing those non-critical mega projects to smoothing the possible boom andbust cycle of the construction industry
Providing sufficient medium and small projects to ensure a smooth flow ofprovision of works for the local construction industry in a sustainable manner
The Hong Kong construction enterprises should use their competitive edge to take
advantage of the opportunities in the wake of the rapid recovery since the financial
crisis in 2008, by working out a strategically long term construction plan by:
Improving the training to meet the construction needs; Improving the employment conditions Improving unattractive image of the industry and raise the social status of the
construction workers
Improving the quality of working life.
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Chapter 1 Introduction
1.1 The Project - HKCA Funding Scheme for the Public Policy Research/Project
In December 2009 Hong Kong Construction Association (HKCA) awardedAssociation of Engineering Professionals in Society Ltd (AES) to carry out the projectstudy on Policy Changes to avoid boom and bust of construction cycle therebyimproving working opportunities and working quality of construction work force which is funded by the HKCA Funding Scheme for the Public PolicyResearch/Project 2009.
In March 2010 AES invited and requested the Department of the Building and RealEstate (BRE) of the Hong Kong Polytechnic University (HKPolyU) to form a
collaborative research team between the AESs experienced senior members and theBREs academic staff and research fellows.
The Research Team comprise five members, they are:
AES Members
Ir K. P. Yim
Ir Y. M. Fan
Academic Staff and Research Fellows of the Department of BRE, HKPolyU
Ir Dr. Linda C. N. Fan
Dr. Paul W. Fox
Dr. Vincent C.W. Ng
The Collaborative Research Team
During the forum discussion on 31-8-2010 at the Excelsior Hotel
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1.2 Background to the Study
The nature of construction industries worldwide is one based largely on projects thatare initiated by public sector and private sector clients. In market economies, such asHong Kong, the contracting side of the industry responds to the client stakeholder
needs, but has little control over how big and how fast the orders come in. It is widelyaccepted that if any place, Hong Kong being no exception, gets the supply ofconstruction projects wrong, too many or too few, either many projects will sufferdelays and/or extra expense, or the whole construction workforce experiences loss ofincome/skills. This, in turn, impacts the wider community. For example, after a boom
period the industry may have raised its costs to unacceptable levels for many clients.Likewise, quality and efficiency may deteriorate, leading to problems of costlymaintenance in later years. Whereas, after a bust period, the industry may have lostlarge numbers of skilled people and collectively the remaining survivors may nothave the capacity to respond to new demands. The community at large then willexperience excessive delays in the supply of new facilities and infrastructure, whichmay be essential to efficiency and competitiveness in other economic sectors. Thus amore stable provision of construction projects is a desirable condition that needs to beattained, and the government has more influence than most, in this respect. Thisresearch study seeks to address and tackle the problems arising from boom and bustin the industry workload: labour shortage on one hand, unemployment on the other;those needing training or re-training to cope with the construction supply boom;unstable construction prices, and measures to maintain and improve the quality ofconstruction deliverables under all constraints. All these factors underline the need tofocus on Hong Kong construction industrys working patterns, which should not be
prone to the sudden boom-and-bust of construction cycles. By means of adjustmentsto the supply of workload, the basic healthy conditions of the construction industry asa whole can be ensured sustainable over the medium term.
This research is important right now, as the industry faces a huge increase in theconstruction workload coming on stream over the next five years. Top-level policymakers within Government may not be aware of the consequences of the decisionsthey have made in this respect. At the same time, the excessive fluctuations imposedon the industry over many decades has led to a culture of risk avoidance and in turn toa lack of stability in employment relations for manual workers, and consequential lackof training, lack of adequate skills, lack of pride in ones occupation, poor image andlack of interest from youngsters in joining the industry. A better understanding ofthese aspects and their interrelationship can lead to measures which help the industryto be more stable, more responsive, more efficient, more competitive, more attractive,
and more sustainable. This leads us naturally to the objectives of the study.
This Project takes the opportunity to address the problems envisaged, and to focus onthe underlining factors so that the industry would not be prone to the sudden boom-and-bust of construction cycles. By these means, the basic conditions of theconstruction industry as a whole can be ensured sustainable at least over the mediumterm.
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1.3 Project Objectives
The following objectives have been identified for study:
(1)Investigate and analyze the factors that cause boom and bust to the Hong Kong
construction industry;
(2)Assess the opportunities in improving the quality of the construction workforce inthe next decade in Hong Kong;
(3)Investigate and analyze the effect of the volatile contract price fluctuation on thequality of the construction workforce and construction industry; and
It is noticeable that if population growth rates are declining, which is the case in HongKong, the percentage of the total population who are economically active tends toincrease because of a smaller proportion of persons below employment age. Thatupward influence is getting worse by the tendency for younger persons to delay entry
into the industrys work force and older persons to withdraw earlier. This Project alsostudied the objective of:
(4)Assessing the present situation of the shortage of young people to join theconstruction industry, and to recommend ways of improvements in attracting themto join the industry, in readiness for the major construction projects in Hong Kongover the next decade
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1.4 Project Approach and Scope
The research team first carried out a literature survey to understand the key conceptsrelevant to the problems perceived. This was followed by (a) capture of relevantmacro-economic statistical data for analysis; and (b) capture of opinions from selected
experienced construction stakeholders on issues relating to Hong Kong constructionenterprises. We elicited stakeholder views both through a questionnaire survey aswell as through interviews. Both of these sets of responses were captured, bearing inmind that most industry stakeholders anticipate the construction projects boom inHong Kong in the next decade, and are rightly concerned about how to avoid the bustfollowing the downturn, due to the change in economic circumstances or collapse ofsome favourable expectations. The study provides findings that address the criticalissues, identifying factors that trigger the upturns and downturns of the constructionindustry, and makes recommendations on how to avoid the future boom and bustcycle of the construction industry in Hong Kong. Our approach and scope is not somuch with the technical minutiae of statistics of numbers of people needed, but morewith the policies need to guide decisions by government and industry leaders for thefuture health and long-term sustainability of the industry.
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1.5 Project Progress and Activities
A series of regular research meetings were held in bi-weekly basis between Januaryand May 2010 to discuss items on how to start the research work for the project, howto identify, what are the objectives that can be mapped with the project scope, how to
describe and what are the project deliverables, how to set the project timeline and thekey milestones, what are the high level requirements and expectations, how to makethe practicable assumptions, what are the constraints and would there be any newchange requests that may modify the project scope. The following describes the
project scope.
On Thursday 31 August 2010 the research team briefed and presented the InterimReport on the Policy changes to avoid the boom and bust of construction cyclethereby improving working opportunities and working quality of construction work
forceto about 100 AES Members and their guests at the Excelsior Hotel, CausewayBay, Hong Kong. After the briefing and presentation, it was followed by the
discussion amongst the attendees. The forum was attended by the contractors,consultants, government officials, academia and labour union representatives. Theforum facilitated the exchange of views amongst the attendees and the guests. Thecomments and opinions collected in the forum discussion have been consolidated,addressed and incorporated in the Final Report of the project study.
On Monday 4 October 2010 AES held their Council Meeting at World Trade CentreClub, Causeway Bay, Hong Kong. Before their meeting, the research team briefedand presented the Interim Report to about 40 AES Council Members who did notattend the forum discussion before on 31 August 2010. The comments made andquestions raised have been addressed and incorporated in this Final Report.
The research team completed an Interim Report of the project study by end of October2010. A copy of the Interim Report was delivered to AES for their comments and fortheir subsequent submission for the attention of HKCA.
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1.6 The Project Report
The final Project Report consists of eight chapters.
Chapter 1 is the Introduction reported the collaborative Project funded by HongKong Construction Association.
Chapter 2 is the Review of Past Research Studies presented the key theoreticalconcepts and background to the research study.
Chapter 3 is the Methodology outlined the research approaches adopted forachieving the respective project objective including sampling, data collection, data
processing, independent and dependent variable construction, and data analysismethods.
Chapter 4 is the Macro-economic Data Analysis together with the statisticalinterpretations in relation to the phenomenon of the Hong Kong construction industryfor the past 30 years of boom and bust are reported.
Chapter 5 is the Questionnaire Survey Analysis reported the results of variousstatistical data analyses of the questionnaire survey with 145 respondents ofconstruction professionals.
Chapter 6 is the Interview Data Analysis consolidated the information obtained,analyzed the results and reported the findings of 9 interviews.
Chapter 7 is the Discussion, including Forum Responses. The synthesis of the
results of the various separate analyses is brought together in this chapter.
Chapter 8 is the Conclusions and Recommendations, which finally draws the threadsof the whole study together and examines its implications in the conclusions andrecommendations.
The supplementary information required for the carrying out the research study of thisproject, such as the survey questionnaires, samples, interview questions, interviewresult details, relevant statistical data and the references of the literature, are appendedat the end to form the overall Project Report.
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Chapter 2 Review of Past Research Studies
2.1 Introduction
This review covers the theoretical frameworks relevant to the objectives both fromstudies of overseas construction industries as well as studies in Hong Kong.Following on from this introduction, we set out the definitions we are using for thekey concepts. Wherever possible we make use of established definitions, but in thecase of the concepts of Boom and Bust we have found the existing definitionsneither sufficiently clear nor comprehensive. Thus we have developed our own, basedon our understanding of the way these terms are used in common usage, and weexplain the reasons why.
The subsequent sections of the review cover the four main objectives to establish:
Key factors that influence the industry workload;
Key factors that influence the quality of the workforce;
Possible linkages of the contract bidding system and the volatility of contractprices upon the quality of the workforce; and
Issues concerning the attractiveness of the industry to new recruits.
The final section summarises the review.
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2.2 Definitions and Selection of Key Concepts
In this study, we define the construction industryas comprising those organisationsinvolved in design, production, alteration, renovation, maintenance, facilitymanagement, demolition and re-cycling of building and civil engineering works,
including the supply of resources. It includes all internal and external stakeholderswho in some way or another promote the industrys policies, procedures, practicesand culture (Fox et al 2008).
There are many definitions ofBoom and Bust, but few of them convey the problemswhich arise at the peaks and troughs of the cycle. One definition that does indicatethese problems is: A type of cycle experienced by an economy characterized byalternating periods of economic growth and contraction. During booms an economy
will see an increase in its production and GDP. During busts an economy will see a
fall in production and an increase in unemployment. (Investorwords 2010)
Many of these definitions arise from studies of business cyclesand when applied tothe construction industry these, in turn, influence property cycles and constructioncycles. Our focus is on the latter concept and we thus interpret boom and bustin thiscontext. Since construction is a project based industry, this characteristic influencesthe way the process of boom and bust is experienced, and also how to respond to the
phenomenon.
Any investigation of the nature of boom and bust will lead to a complementaryconcept of industry capacity. As one of the pioneers in applying economic theory tothe construction industry, Hillebrandt (2000) refers to the capacity of the industry,
which she defines as the maximum output which is attainable by the industry,within the limits of conditions considered acceptable at the time. We take a slightlydifferent definition and consider that the capacity of the industry is something whichhas both maximum and minimum values. Thus Hillebrandts definition of maximumoutput we regard as the industry working at maximum capacity. We also recognise itcan be working at a lower level, or minimum capacity.How do we define these twolevels? In the case of maximum capacity, we agree with Hillebrandts assertion thatthe supply of resources is the ultimate determinant of capacity(Hillebrandt2000:191). She lists four factors which influence capacity:
the amount of a given resource in use to produce the current output of theindustry;
the amount of the resource lying idle awaiting the demand for its use from theconstruction industry;
the extent to which the resources will increase in the time span underconsideration
on the assumption of no change in intentions or policy,
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on the assumption of effort being directed to increasing of the resource and takinginto account the cost of increasing its availability;
the extent to which the resource can be saved by substitution of some otherresources and the cost of such substitution.
(Hillebrandt, 1975: 34)
At maximum capacity, the industry is already using all the key resources available toit, and there are no spare resources lying idle if demand further increases. At this point,any further increase in demand turns a sustainable healthy boom level to anunsustainable unhealthy boom, where the shortages of resources lead to a rapidincrease in costs as competing clients/projects bid up the prices to unhealthy levels(unsustainable levels). This is point c on the chart (Figure 2.1).
.
.
. .
( 2000: 191)
(, , )
Title: Characteristics of Boom & Bust in the HKCI
2013
a
b
c
Figure 2.1 Characteristics of Boom & Bust in the HKCI
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However, prior to this unhealthy level, we first identify normal conditions where theworkload is within the normal boundaries (shown as point a). Variations in theworkload arise through different mixes of work type, so that $1 million spent on newwork would produce a different demand for labour resources compared to the samemoney spent on maintenance work the latter requiring a higher labour input. We
also identify a level (shown as point b), where the demand has reached a pointwhere some resources are already stretched, or are not available, and the projectstakeholders can take remedial action by training extra workers, or purchasing newmachines from non-established sources or the design /methods of work can bechanged to avoid using the resource that is problematic. In this case, the wholeindustry can still function and provide service to its clients, but at greater cost, or withsome inconvenience. This level of demand we identify as the capacity earlywarning level. This is also the start of the boom phase, but it is still healthy becausethe industry overall can still meet its project goals, although there will be hot spotsof resource shortages appearing.
Thus we define the start of a boom as the point when the demand exceeds the earlywarning level of capacity and available resources. Beyond this point, there are many
problems arising within this boom phase, including:
Shortages of various resources of labour, materials, and plant;
Associated increased costs;
Project delays;
Increase in unqualified /untrained / inexperienced / imported labour;
Loss of efficiency;
Increase in accident rate;
Reduction in training (people cannot afford the time to attend training);
Lowering of quality of output (as people rush to complete work);
Lower quality of working life (QWL) as people work long hours;
Increased stress and other heavy workload problems;
Insufficient training capacity.
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Likewise, at times of industry workload being lower than its minimum capacity itenters a bust phase, with the following associated problems:
Unemployment and /or under-employment;
Loss of trained and experienced people (both temporary and permanent loss);
Loss of income for labour;
Insufficient profit for businesses to be viable (sustainable);
Loss of training (too little income to pay trainees, or for self-employed to taketime off seeking for work);
Loss of skills through insufficient use;
Lowering of morale in industry, lowering of motivation;
Lowering of image of industry to newcomers, especially youngsters who see nojob security for a career choice in the industry;
Lowering of recruitment to industry.
The construction workforce includes the whole variety of people engaged in theindustry, whether they use manual, technical or professional skills directly on site, or
prior to site work in design, research & development, or after site operations inmaintenance and management of constructed facilities. The term constructionworkforce is used interchangeably with the term construction labour, or simply
labour.Within this definition, when referring to manual workers, we class them asskilled labourers/workers, semi-skilled labourers/workers or unskilled/generalworkers.
When we refer to working opportunities, we mean the opportunity to engage in workfull-time or part-time and paid directly as employees or paid as self-employedcontract staff/workers for a package of work duties. The definition is intended toinclude all types of employment conditions.
The quality of the construction workforce is already defined by the government in
terms of the qualifications held by industry participants. Each member of the industrypossesses certificates of training completed and educational attainment both in generaleducation level achieved as well as specialist education in construction orconstruction-related subjects. A more comprehensive view of quality may not relyonly on levels of achievement by individuals. It might be more broadly defined byconsidering the breadth of experience of individuals as well as how they relate withinteams (Clarke 1992, GB DETR 1998, HK CIRC 2001), such as
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Work experience outside of Hong Kong;
Work experience outside of the construction industry ; having a sense of ethics inwhat and how they do their work ;
Belonging to a network of similar people through membership of an association
/institute which fosters their sense of belonging, of contributing to the commongood, of leading change within their field of experience, and of being accountableto their peers ;
Flexibility to adapt to change, creativity leading to innovation, and motivation toimprove their knowledge and skills ; and
Willingness to work with others as members of a team towards common goals.
In construction, the individual works on many different projects throughout a working
career. Thus, the ability to work together with strangers in teams in unfamiliarsurroundings is part of the normal pattern. The set of skills needed for efficiency,safety, quality, team work, flexibility, adaptability and integrity, even for an unskilledlabourer, require aptitudes of a far higher level than those needed in manufacturingindustry, where the tasks are simpler, safer, and in a fixed location every day withcontrolled climate and familiar layout. Whilst these additional measures of quality ofthe workforce are important, for the purposes of this study, we will rely more on theeasily obtainable measures of education / training attained through recognizedcertificates.
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2.3 Factors that Cause Boom and Bust to the HK Construction Industry
The literature relating to bust and boom of construction cycles is well established andextends over at least 4 decades. Some of the earliest studies were those of theUniversity of London University College when a group of economists led by
Professor Turin attempted to view the behaviour of whole construction industry usingeconomic theory (Turin 1975). Hillebrandt was one of the economists recruited byTurin when the Unit for Building Economics was set up, and she later publishedseveral seminal texts which helped readers to understand the issues that the UKconstruction industry faced (Hillebrandt, 1984, 1985; Hillebrandt et al1995). These
principles were found to be applicable to the construction industry in many othercountries as well, and we can thus recognise that these are applicable to Hong Kong.She asserts that all demand is affected, though in different degree, by the ups anddown of the economic cycle and by actions of government, either directly as a client
of the industry, or by the way in which it runs the economy. (Hillebrandt 2000:5)
A recent study by Wong (2006) looked at manpower planning in depth. He drew uponthe work of Agapiou (1996) who had completed a doctoral study ten years earlier,
based on the UK construction industry. Wong investigated manpower demandforecasting both from an industry level as well as at project level, using Hong Kongdata. At the industry level, he recognised that existing forecasts were unsatisfactoryand that too little research had been done in this area. He compared four differentapproaches: Time-Series projection; Bottom-up; Top-down; and Labour MarketAnalysis. Of these he found that a Top-down approach was both good in staticsituations where a snapshot at a single point in time was needed, and also excellent indynamic situations where changes over time took place. Thus, overall, a Top-downapproach was best. Based upon economic theory, it has advantages of reliability, andthe ability to deal with what if scenarios. The key variables used for this type ofanalysis include macroeconomic ones such as GDP, sectoral output, unemploymentrate, productivity, interest rate, and wages.
Given the prominent role of the government, we have decided to use variables fromgovernment statistics to analyse the demand and response to demand. Figure 2.2shows the key variables that we have included.
The mainIndependent variableis the Gross Volume of Construction Works (GVCW)which includes demand arising from both public and private sector clients. Figure 2.3shows the various ways in which this overall amount of investment in buildings andfacilities is further sub-divided into various sectors, either according to work onConstruction Sites/ Other locations; or by Building/Civil engineering. Referringagain to Figure 2.2, it also shows how the government may influence demand throughdirect investment (GVCW) as well as through indirect means. The indirect variablesare indicated asModeratingor Control variableson the chart, and include such itemsas:
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Money supply M2;
Money supply M3;
Best Lending Rate;
Hang Seng Index;
The Consumer Price Index (CPI); and
The Tender Price Index (TPI).
Finally, concerning theDependent variablesthese include:
Employment / Unemployment (as well as Importation of Workers); and
Salaries & Daily Wages, (further subdivided according to Skilled/UnskilledWorkers, and Short/Long Organisation Tenure).
/
&
()
()
2
3
Controlvariables
Independent & Dependent Variables for Statistical Analysis
Time Lag of
x months. Influencedby Control Variables
Figure 2.2 Independent & Dependent Variables for Statistical Analysis
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Independent Variables by Broad & Detailed End-users
&
&
&
GVCW for Construction Siteby Broad Trade Group
By Broad End-userGroup
By Detailed End-userGroup
Figure 2.3 Independent by Broad and Detailed End-Users
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2.4 Effect of the Bidding System on the Workforce Quality
In Hong Kong, the dominant procurement system for building work in both publicand private sectors is through competitive tender (Drew 1994:35; Oo 2007:41). TheHK CIRC Report (2001: 1) identified the shortcomings in the industrys operations
and quality of its products as follows:
Construction activities are labour-intensive, dangerous and polluting;
Built products are seldom defect-free;
Construction costs are comparatively high;
The industry is very fragmented and is hindered by an adversarial culture;
Many industry participants adopt a short-term view on business development,with little interest in enhancing their long-term competitiveness;
There is a tendency to award contracts to the lowest bidders and deliveryprogrammes are often unrealistically compressed;
Accountability is undermined by non-value-adding multi-layered subcontractingand lax supervision;
An inadequately trained workforce also impairs the industrys ability to adopt newtechnologies and to cope with new challenges.
The Grove Report (Grove 2000) also observed that some clauses regarding ground
conditions in the Government General Conditions of Contract for public sector workplaced unreasonable risks onto Main Contractors such that it deterred genuine andresponsible contractors whilst allowing weaker but more gambler-oriented contractorsto obtain contracts. The effect is that the winning tenderer will either be the
gambler or the low guesser. Frequently this will be the thinly financed, low asset
contractor who has little to lose. It is not in Government's interest to attract this
calibre of contractor, nor to discourage highly competent, conservative contractors.(Grove Report Para. 12.10).
Chiang et al (2001) found a contrast between the civil engineering sector and buildingsector of the HKCI in terms of the competitiveness. Whilst the former sector required
technological and capital resources which imposed a strong barrier to entry to themarket, the private building sector was very easy to enter, as it needed only lowtechnology using traditional methods. Consequently the latter sector
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competed intensely on cost reduction rather than technology improvement,leading to poor construction safety and product quality. Generally profit margins
are razor thin, and are only squeezed through the exploitation of lower layer
subcontractors. Competitiveness based on cost reduction is not sustainable, as it
creates no enduring competitive edge. The authors concluded that the government,
being both a major client and a regulator, could be more active in promoting theoverall competitiveness of indigenous local contractors in Hong Kong. Although thestabilization of construction demand can motivate local contractors to improve quality,the implication is that international contractors in complex projects could only growmore competitive. The authors warn that the industry must not become too dependenton government initiatives, so from a policy perspective, this is a fine point of balance.
A very recent paper (Chiang and Cheng 2010) adds further to this discussion byarguing that the interim payment mechanism has induced a low barrier to entry andhelped perpetuate the vicious circle of labour intensiveness of buildingconstruction, exploitation of labour-only subcontracting, proliferation of small
subcontractors and intense rivalry between firms.
Our interpretation of this part of the review is that such conditions, in attracting andencouraging the gambler attitude, only increase the competitive nature of the businessenvironment, and make it difficult to sustain a strong profitable business. This in turnaffects the funds available for long term planning, investment in improvement of the
business, and the recruitment, retention of staff, and adequacy of salaries/wages/employment packages, staff development and training. In other words, the realities ofthe overly-competitive bidding system lead to the poor quality of the workforce.
Finally, we highlight that too much emphasis on measures to stabilise the overallindustry workload may lead to neglect of more important policies. Wong et al(2010)argued that the industry needs to have a comprehensive strategic plan to develop theindustry in a sustainable manner. Four key strategic directions were identified:
(1) Formulation of an industry-specific long-term vision and policy;
(2) Development of favourable factor conditions and resources;
(3) Fostering of a best (better) practice culture; and
(4) Enhancement of technical competencies.
Each of these strategies links to the development of the quality of the workforce. Inturn, this highlights the need for improved levels of training, and thus the need forlong-term stable employment conditions.
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2.5 Factors to improve workforce quality
Dainty et al (2005) studied the skills crisis in the UK construction industry, and firstreviewed the existing theoretical foundations of the topic, noting that the sectorslabour market is based on the concepts of informality and flexibility. During their
own qualitative data collection, they found 3 key themes of significance in theindustry-wide labour market characteristics. These are: Skills requirements andimpacts- every employer interviewed believed there to be a skills crisis with too fewskilled workers, and a low level of skills.
Overall, 10 distinct issues were found through interviews with contracting firms,including
Client demands and expectations;
Impact of new technology and work practices;
The ageing workforce;
Geographical mobility;
Remuneration and reward;
Self-employment and the impact of labour market regulation;
Workforce quality;
Specific skill requirements;
Multi-skilled workers; and
Supervisory, professional and management skills.
Recruitment and retention issueswere seen as a huge problem by most employers.Strategies to deal with it included six areas:
Advertising;
Agency recruitment;
Self-employment and informal recruitment practices;
Image of the industry;
Workforce diversification; and
Employee turnover and retention.
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Training and qualifications were seen as doubtful in value by two thirds ofrespondents. Others were committed to training and its benefits. Six areas werehighlighted:
New entrant trainees;
The qualification and training structure;
Training provision and availability;
Training and developing the existing workforce;
Government-sponsored training schemes; and
Funding for training.
Overall, Dainty et als conclusions are that the calculations of numbers of skillsneeded are a starting point for identifying skills shortages. However, the crucialconcern was that the quality of skills available is a more urgent focus. A tendency to
blame clients and avoid responsibility was observed, but a different mindset bymanagement was needed to solve the problems. This, together with bettercoordination between training providers, employers, and regulatory bodies wouldaddress the skill needs and provide a basis to lobby for policy changes. Many of theissues faced in Dainty et als study are common to the Hong Kong situation. This,we assert, is arising from the similarities in the structural, institutional and culturalcharacteristics between the two construction industries.
The lack of quality of skills available in sufficient numbers which Dainty et al havehighlighted points to the need to provide a structured framework for various levels ofskills. Such a National Qualifications Framework (NFQ) are found in a number ofcountries / administrative region, including the UK and Hong Kong. Young (2003)discusses these at length and recognises their importance, whilst giving examples ofhow difficult it has been to implement them successfully. The impasse motivated himto explore some of the deeper social, political and economic issues in his paper.
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The Government of HKSAR, through the Vocational Training Council (VTC) haveimplemented such a framework in Hong Kong, as from 2004. The new QualificationsFramework (QF) covers qualifications of academic, vocational and continuingeducation and training, and is intended to meet the following needs:
Better equip and improve the Hong Kong society to face change;
Ensure Quality Assurance of training programmes;
Ensure relevance of training programmes;
Provide a platform for arranging and ordering various programmes andqualifications to ensure their standard and quality; and thus
Enable individuals to pursue further studies for their own career development.
Given the lack of quality of skills which Dainty et al have highlighted, it would seemobvious that the QF should provide a ready solution. However, despite the rollout ofthe QF framework since 6 years, the only construction- related area of application isin property management. Otherwise, the construction industry has not adopted QF,and has no plans to do so.
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2.6 Issues concerning the attractiveness of the industry
The final area of focus of this study concerns, perhaps, the most important issuefacing construction industry employers. Although it is presented here as a separateissue, its very nature links it with all the previous research objectives. It is not only a
major concern of the Hong Kong construction industry, but it is of significance tonational construction industries worldwide. It is not just one issue, but a multi-dimensional, multi-related set of issues.
In terms of its common nature worldwide, the poor attractiveness of the constructionindustry starts with a simple understanding that beauty is in the eye of the beholder.It is a view from the outside, looking in, and by this, we mean the image that theindustry presents to the outside world. In order to understand the nature of the imageof the industry, the International Labour Office (ILO) of the United Nationsconducted a survey and published their results in 2001 (ILO 2001). Thecharacteristics of informalityandflexibilityare mentioned in the conclusion, and, like
Dainty et al, remind us again of the often casual employment relationship betweenemployer and worker. The paper asserts that the construction industry in mostcountries is fragmented and employment terms have become based more onoutsourcing. This raises concerns about job security, health, safety as well as skillformation. The image of the industry has suffered to the point where it is oftendifficult to attract new recruits, while the shortage of skills is threatening the quality
of the products and possibly also, in the long term, the quantity of employment.
The big issue facing the sector is how to raise the image of the industry and make
construction more attractive to young people. This is not just a question of finding a
good public relations consultant. There are real issues here that have to be
addressed.(ILO 2001:43)
In the eyes of the ILO, the way forward is seen through three main courses of action:
(1)Continuation and Enhancement of the Subcontracting System
Subcontracting is seen as essential to enabling the flexibility needed to cope withthe way workload demands are received. However, the employment relationshipneeds to be more stable and permanent to ensure proper protection of labour rights
and access to training enjoyed by permanent employees in other sectors.
(2)Highlight priority areas for action including:
New role for trade unions and other pressure groups;
Extension of social security to all, including insurance cover for sickness orunemployment, and retirement benefits;
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Promotion of health and safety;
Training & skill formation through training the trainers the creation of aclass of master craftsmen, and opportunities for lifelong learning and a career
path;
Skills testing and certification.
(3)Use levers for change, by dealing with pressures from consumers,environmentalists, and other groups. The construction industry must solve its own
problems and not be too dependent on government or other stakeholders. Thepublic sector clients can do much to promote desirable change.
Apart from job security, safety and health issues, other areas concerning the
attractiveness of the industry to potential new recruits relate to the conditions of theworkplace in terms of stress, burnout, and work-life balance. Research has looked atthese concepts for over twenty years in general terms (Altroni & Paxon 1988; White& Keith 1990) looking at working hours, shift work and effects on the quality andstability of marital relations. Some studies in construction industries overseas have
been completed over the past ten years (Lingard & Francis 2002, 2004; Lingard et al2007; Lingard et al 2008; Walker et al 2001). Australian experience shows thatconstruction industry workers work long and irregular hours, and as a resultexperience a higher level or work-to-family conflict and burnout than office-basedworkers (Lingard et al 2008). Studies in Hong Kong confirm that similar negativefactors make the industry an unattractive place to work. For example, Ip (2009:110)related three reasons why both workers and prospective entrants disliked the industry:
(The) industry downturn had led to low wages and unemployment. Stressinduced by job instability and lowered income had led a few experienced
interviewees to consider leaving the industry for good;
Low occupational status and harsh work conditions including omnipresent danger,a rough,, confrontational culture, and long work hours deter youngsters from
entering the trade. Youth with a low educational attainment prefer to enter other
service industries which may offer career advancement options despite lower pay,
and
Lack of foreseeable, future growth in local industry and clear career advancement
paths also contribute to low worker morale.
The final kiss of death view on the industrys attractiveness is captured in Ipsstatement: During interviews, workers of all cohorts overwhelmingly concurred thatthey would not encourage their children to enter the industry.
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2.7 Summary of Literature Review
The review has covered all the key concepts that we consider important to the studyobjectives. We have needed to derive our own definitions of some concepts, such asBoom and Bust, and whilst we would prefer to use existing definitions, we found
that some of them did not fully describe what we observe in the real world. Thereview is not an in-depth and exhaustive exercise, but we have tried to keep it brief,relevant and up-to-date.
The problems being experienced by the Hong Kong construction industry are notunique. There are similar examples from many industries around the world, both fromdeveloping and developed countries. However, it is clear that there are not manyexamples of successful solutions to the problems commonly experienced. Despite thisknowledge, there are several pointers as to where possible solutions may lie.
The data collection and analysis that we describe in the following chapters should beinterpreted in the light of the framework we have discovered through this review.
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Chapter 3 Methodology
3.1 Introduction
The section outlines the research approaches adopted for achieving the respectiveproject objective including the sampling, data collection, data processing, independentand dependent variable construction, and data analysis methods. In order to achieve arigorous verification of the project objectives, both primary and secondary datasources are delineated with robust statistical analyses to be performed upon each dataset. With a view to the different algorithms of the data sets, specific data processingmethods are also detailed so as to show how the elements of practicability, reliabilityand validity of the research methodology are triangulated and balanced. Furthermore,common and well-known robust statistical analytical methods are also detailed andtailor-made to the processed data sets so that the statistical interpretations and
inferences are able to be generalized and easily understood by the public at large.
The first part of this section details the data sources for the research approachesadopted for each project objective. The second part defines the independent anddependent variables and delineates the data processing methods. The third part relatesthe statistical analytical methods to each project objective. The fourth part provides asummary of this section.
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3.2 Project Objectives & Data Sources
Both primary and secondary data sources are collected for the following projectobjectives:
(1)Factors causing boom and bust to the Hong Kong construction industry
(2)Quality improvement of the construction workforce in the next decade in HongKong
3.2.1 Primary Data Sources Questionnaire Survey
Primary data sources from the questionnaire survey with respondents targeted atconstruction professionals are used. The questionnaire is attached in Appendix B,which comprises the following questions:
(1)Personal information Question No. 1 to 3 about the employment status,management level and overseas work experience
(2)Problems during boom and bust times Question No. 4 and 5 define the problemsencountered by the organizational unit where the respondents are situated asfollows:
a) Unit economic efficiency
b) Unit work safety
c) Unit quality of work output
d) Unit work performance reliability
e) Reluctance to invest in training
f) Difficulties in recruiting young people
g) Reluctance to invest in business or organization
h) Reluctance to innovate
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(3)Personal experience during boom and bust times Question 6 and 7 define thepersonal experience of the respondents as follows:
a) I changed employer
b) I changed projectc) My role on projects changed
d) My colleagues changed frequently
e) Change in my work reliability
f) Change in my workload and work hours
g) Change in quality of my work output
h) Change in my remuneration package
i) My personal development opportunities
j) Change in my training opportunities
k) Change in my safety and health risk
l) Change in my work experience
m)My enjoyment, fulfilment and meaningfulness of work
n) Change in a sense of pride in my work
o) My work-life balance
p) My stress experienced
q) Change in my ethical behaviour at work
r) Change in my commitment to lifelong learning
3.2.2 Secondary Data Sources Marco-economic Indicators
In addition to the primary sources from the questionnaire survey, which serves thepurpose of a cross-sectional snapshot of the attitudes and experiences of therespondents for the time being, secondary data sources from various government
publications are gathered and processed in order to reflect the long-term picture andrepetitive and abrupt phenomenon for the past 30 years of the Hong Kongconstruction industry.
The secondary data sources are summarized in Appendix C, which comprises thefollowing data sets:
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(1)Gross Value of Construction Works (GVCW) reported in the Quarterly Survey ofConstruction Output from 1983Q1 to 2010Q2, which includes the followingcategories (See Appendix C1 for details):
a) Construction Sites vs. Locations other than Sites
b) Private Sector vs. Public Sector
c) General Trades vs. Special Trades
d) Buildings vs. Structures & Facilities
(2)Employment Indicators and Salary Indices reported in the Hong Kong MonthlyDigest of Statistics, which includes the following categories (See Appendix C2 fordetails):
a) General Unemployment & General Unemployment Rate (1983Q1 to 2010Q2)1
b) Unemployment & Unemployment Rate in Construction Sites (1998Q3 to 2010Q2)
c) Number of Establishments, Persons Engaged & Vacancies in Construction Sites(1983Q1 to 2010Q2)2
d) Average Daily Wages of Workers Engaged in Public Sector Construction Projectsas Reported by Main Contractors (1985Q1 to 2010Q2)
e) Salary Index for Managerial and Professional Employees in Building &Construction (1983Q2 to 2010Q2)3
f) Nominal Salary Index A and B by Occupational Group by Occupation (1983Q2 to2010Q2)4
(3)Financial Indicators & Inflationary Factors reported in the Hong Kong MonthlyDigest of Statistics, which includes the following categories:
1 Data prior to 1983Q1 neglected in order to align with the availability of the GVCW data sets from 1983Q1to 2010Q2.
2 Ibid.
3 Data became available since 1983Q2 on a yearly basis.
4 Ibid.
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a) Money Supply M1, M2 and M3 (1983Q1 to 2010Q2)5
b) Best Lending Rate (BLR) (1983Q1 to 2010Q2)6
c) HIBOR (1984Q4 to 2010Q2)
d) Hang Seng Index (1983Q1 to 2010Q2)7
e) Tael Gold Bar (1983Q1 to 2010Q2)8
f) Gross Domestic Products (1994Q2 to 2010Q2)
g) Construction Industry GDP (2001Q2 to 2010Q2)
h) Composite CPI (1990Q3 to 2010Q2)
i) CPI(A) to (C) (1983Q1 to 2010Q2)9
(4)Tender Price Index published by various construction cost consultants andgovernment departments, which includes the following indices:
a) RLB Tender Price Index (1983Q1 to 2010Q2)10
b) DLS Tender Price Index (1983Q1 to 2010Q2)11
c) ASD Tender Price Index (1983Q1 to 2010Q2)12
d) Housing Department Tender Price Index (1983Q1 to 2010Q2)13
e) Highways Department Tender Price Index (1996Q1 to 2010Q2)
f) CEDD Tender Price Index (1996Q1 to 2010Q2)
5 Data prior to 1983Q1 neglected in order to align with the availability of the GVCW data sets from 1983Q1to 2010Q2.
6 Ibid.
7 Ibid.
8 Ibid.
9 Ibid.
10 Ibid.
11 Ibid.
12 Ibid.
13 Ibid.
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3.3 Data Collection & Processing Methods
3.3.1 Questionnaire Survey
The survey using the questionnaire in Appendix B is conducted by distributing thequestionnaire through various arenas including invitation by emails, HKCA webpage,etc., through HKCA corporate members to their employees, etc. With the thankfulhelp of the respondents, 145 returned questionnaires are usable. Most of thequestionnaires are fully completed whilst the partially completed questionnaires areused to the extent where the particular questions are fully completed in order tomaximize the datasets.
The datasets from the completed questions are denoted as categorical variables forQuestion No. 1a and 1b, continuous variables on a 3-point Likert Scale for Question
No. 4 and a 5-point Likert Scale for Question No. 6 and 7. Neither decomposition norcombination is performed upon the datasets.
3.3.2 Macro-economic Indicators
Since the GVCWs are only available from 1983Q1 onwards, all indicators and indiceswith different base years are converted to 1983Q1 prices in general. Inflationaryfactors including various Consumer Price Indices and Tender Price Indices areconverted to 1983Q1 prices as follows:
(1)Consumer Price Indices
a) The base year of the CPI(A), CPI(B) and CPI(C) is fixed at 1983Q1.
b) Since the Composite CPI is only available from 1990Q3 and CPI(A), CPI(B)and CPI(C) comprise 90% of the Composite CPI, the Composite CPI from1983Q1 to 1990Q2 are constructed by using 50% CPI(A), 30% CPI(B) and10% CPI(C), with base year fixed at 1983Q1.
(2)Tender Price Indices
a) The base year of the RLB, DLS, ASD and Housing Department TPI is fixed at1983Q1.
b) Since the Highways Department and CEDD TPI from 1996Q1 onwards, theTPI from 1983Q1 to 1995Q4 are constructed by following the geometric trendof the ASD TPI, which is the most relevant comparable for the time being.
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c) A new TPI, Private Sector TPI, is constructed by averaging the RLB and DLSTPI, which account for almost 90% market share of the construction costconsultancy in the private sector.
d) A new TPI, Public Sector TPI, is constructed by averaging the ASD, Housing
Department, Highways Department and CEDD TPI, which account for over90% GVCW in the public sector.
e) A new TPI, Public/Private Sector TPI, is constructed by applying the GVCWproportions of the public and private sector in construction sites in combiningthe Private Sector TPI and Public Sector TPI.
(3)Various GVCWs are converted to 1983Q1 prices by using the corresponding newTPI as follows:
a) Construction Sites Private Sector GVCW is deflated by the Private SectorTPI.
b) Construction Sites Public Sector GVCW is deflated by the Public Sector TPI
c) Locations other than Sites General Trades and Special Trades GVCWsdeflated by the Public/Private Sector TPI.
d) Construction Sites Buildings GVCW is deflated by the Public/Private SectorTPI
e) Construction Sites Structures & Facilities GVCW is deflated by the PublicSector TPI
Public Sector Average Daily Wages of Works are converted to the Nominal WageIndices with base year at 1983Q1. Real Wage Indices are constructed by deflating the
Nominal Wage Indices by the CPI(B). The base year of the Nominal Salary Index Aand B is fixed at 1983Q1. Real Salary Index A and B are constructed by deflating the
Nominal Salary Index A and B by the CPI(C). Financial Indicators are not deflatedbecause they are conventionally assumed to be the prime drivers of inflationaryfactors.
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3.4 Independent, Dependent and Control Variables
After processing the macro-economic indicators in Section 3.3.2, each indicator isclassified either as Independent Variable, Dependent Variable and Control Variablefor subsequent robust statistical analyses. Since the project objective is to investigate
the factors that are affecting boom and bust in the Hong Kong construction industryand the boom and bust are best reflected by the wage and salary levels andemployment and unemployment status, the Dependent Variables therefore include:
(1) General Unemployment and General Unemployment Rate
(2) Construction Unemployment and Construction Unemployment Rate
(3) Employment in Construction Sites
(4) Public vs. Private Sector
(5) Building vs. Civil Engineering
(6) Real Wage Indices
(7) Real Salary Indices
Various GVCWs are initiatively assumed to be the prime drivers of these DependentVariables and are therefore taken to be the Independent Variables:
(8) Construction Sites Private Sector GVCW
(9) Construction Sites Public Sector GVCW
(10) Locations other than Sites General Trades GVCW
(11) Locations other than Sites Special Trades GVCW
(12) Construction Sites Buildings Residential Projects GVCW
(13) Construction Sites Buildings Commercial Projects GVCW
(14) Construction Sites Buildings Industrial & Storage Projects GVCW
(15) Construction Sites Buildings Service Projects GVCW
(16) Construction Sites Structures & Facilities Transport Projects GVCW
(17) Construction Sites Structures & Facilities Utilities & Plant ProjectsGVCW
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(18) Construction Sites Structures & Facilities Environment Projects GVCW
(19) Construction Sites Structures & Facilities Sports & Recreation ProjectsGVCW
Other than the Independent Variables driving the boom and bust times of the HongKong construction industry, certain Control Variables are inserted in order to reflectthe effect of the macro-economic environment:
(20) BLR and HIBOR
(21) Money Supply M3 (naturally logged)
(22) Hang Seng Index (naturally logged)
(23) Tael Gold Bar (naturally logged)
(24) GDP and Construction GDP (naturally logged)
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3.5 Statistical Analytical Methods
3.5.1 Time Series Analysis & Time Lag Analysis
In order to align with the format of the GVCW datasets, all variables are convertedfrom either monthly or yearly basis to quarterly basis by using geometric means.However, there may be seasonal effects impacting the time series of the 27-yeardatasets. With a view to eliminating the possible seasonal effects, the Pearsons
Method is applied to the time series of the Independent, Dependent and ControlVariables so that the seasonally adjusted variables are used for subsequent statisticalanalyses.
Graphs are produced for the visual inspection of the time lag relationships betweenvarious GVCWs, Real Wage Indices and Real Salary Indices. Other than the visual
inspection, the Pearsons Correlation Coefficientsare also used for indicating thesetime lag relationships in a robust manner. A time lag from 16 quarters lead to 16quarters lag is used to investigate the time lag relationships. The exact time lag
between any two variables is indicated by the maximum Pearsons CorrelationCoefficients among the 37 time lag scenarios. However, since there may be certainsituations where the coefficient value continuously goes up or goes down across the37 time lag scenarios, no time lag relationship is concluded between any two variablesif this situation is encountered.
3.5.2 Multivariate MRA & HRA
Both multivariate Multiple Regression Analysis (MRA) and Hierarchical RegressionAnalysis (HRA) are used for testing the impact of each Independent Variable andControl Variable on the Dependent Variables. Both modeling approachesprovideregression analysis for multiple Dependent Variables by one or more IndependentVariables. In particular, HRA is a multi-stage strategy that investigates variablesoccurring at multi-levels of analysis. Null hypotheses about the effects of theIndependent Variables on the means of various groupings of a joint distribution of theDependent Variables are tested with tests of significance using Fishers F-distribution.Each set of the Independent Variables is included in the regression equation atdifferent level of analysis. At Model 1 analysis, the Control Variables are includedinto the regression equation:
+=i
CiCik XY with2
CR (1)
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where kY is the kth Dependent Variable, is the intercept, Ci is the coefficient for
the Control Variables. Independent Variables are included in the regression equationat Model 2 analysis:
++=i i
DiDiCicik XXY with2
1CDR (2)
where Di is the partial regression coefficient for the Independent Variables. The
contribution to the prediction power of Model 2 regression equation by the addition of
Independent Variables is the difference between 21CDR and2
CR , i.e.22
1
2
CCDD RRR = .
Change in F-Statistics and R2 values in Model 2 against Model 1 helps show the
effects of the set of the Independent Variables. Partial regression coefficientis usedto show the effect of each Independent Variable. An Independent Variable is
considered as significant if the value of goes to the predicted direction and
significant at 0.05 level.
3.6 Concluding Remarks
After processing the datasets of the secondary data sources by using the time seriesanalysis, graphs are produced in Chapter 4 for the time lag analyses by visualinspection and Pearsons Correlation Coefficients and statistical relationships betweenthe Independent, Dependent and Control Variables are investigated by eitherMRAor
HRA. Questionnaire survey results are studied by using either MRA or HRA inChapter 5. Data analysis of nine interviews of nine leading persons in the construction
industry is presented in Chapter 6.
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Chapter 4 Macro-economic Data Analysis
4.1 Introduction
The section reports the time lag analyses by visual inspection and PearsonsCorrelation Coefficients amongst pairs of the macro-economic indicators and themultivariate Multiple Regression Analysis (MRA) and Hierarchical Regression
Analysis (HRA) for the groups of the Dependent Variables, i.e. employment andunemployment situations, and Real Wage Indices and Real Salary Indices, and theIndependent Variables, i.e. various GVCWs, and the Control Variables. The first partof this section briefs the time lag analysis by visual inspection by referring to thegraphs produced for the seasonally unadjusted datasets of the macro-economicindicators. Graphs are also produced for the seasonally adjusted datasets in order toshow the smoothing effects of the Pearsons Method. The second part details the time
lag analysis from another angle by using the Pearsons Correlation Coefficients. Thethird part reports theMRAandHRAresults together with the statistical interpretationsin relation to the phenomenon of the Hong Kong construction industry for the past 30years of boom and bust. The fourth part provides a summary of this section.
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4.2 Time Lag Analysis Visual Inspection
Subsequent to the classification of the macro-economic indicators into theIndependent Variables, Dependent Variables and Control Variables in Section 3.4, atime lag among pairs of each group of variables exists and this section is delegated to
the visual inspection of such time lag relationships. As a usual tool for visualinspection for this purpose, graphs for each of the following subgroups of variablesare produced with certain annotations in order to indicate the time lag from the
perspective of visual inspection:
(1)Independent Variables (Seasonally Unadjusted & Adjusted Time Series)
GVCW Construction Sites Public Sector vs. Private Sector
GVCW Locations other than Sites General Trades vs. Special Trades
GVCW Construction Sites Buildings Residential, Commercial, Industrial& Storage vs. Service
GVCW Construction Sites Structures & Facilities Transport, Utilities &Plant, Environment vs. Sports & Recreation
(2)Dependent Variables (Seasonally Adjusted Time Series)
Unemployment - General and Construction
Unemployment Rate - General and Construction
Construction Employment in Construction Sites
Real Wage Index
Real Salary Index A
Real Salary Index B
(3)Control Variables (Seasonally Unadjusted & Adjusted Time Series)
Money Supply M1, M2 and M3
Hang Seng Index
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