1

university for therealworld R

Strategic Management Practices in Construction

Industry: A Study of Indonesian Enterprises

Strategic Management Practices in Construction

Industry: A Study of Indonesian Enterprises

FINAL SEMINARMUHAMMAD SAPRI PAMULU

BEng (Hons.), MEng (PM)

Presentation OutlinePresentation Outline

1. Introduction2. Literature Review3. Conceptual Model & Hypothesis4. Research Methodology5. Analysis and Results6. Conclusions & Recommendations

2

Introduction - BackgroundIntroduction - Background

• The construction industry is one of the key contributors to most economies. – The gross domestic

product (GDP)– Investment – Labour employed

7.8%

5.5%

6.6%

7.7%

5.0%

5.5%

6.0%

6.5%

7.0%

7.5%

8.0%

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Introduction - BackgroundIntroduction - Background

• The promising prospects but, many local construction firms have poor performance and low competitiveness.

3

Introduction - BackgroundIntroduction - Background

• Strategic management research related to the Indonesian construction industry remain scarce. This has potentially become one of the factors hampering efforts to guide Indonesian construction enterprises.

Research ObjectivesResearch Objectives

• Major aims is to construct a conceptual model to enable Indonesian construction enterprises to develop sound long-term corporate strategy that generates competitive advantage and superior performance.

4

Research ObjectivesResearch Objectives

Specific objectives:• Explore a number of strategic factors and their

characteristics and inter-relationships that may potentially affect the competitive advantage and the performance of a firm.

• Construct a conceptual model that captures the linkages with specific factors, competitive advantage and performance

• Verify the characteristics and inter-relationships of the factors and setting within the conceptual model based on survey feedback.

Research ScopeResearch Scope

• Specific focus on exploring the “Dynamic Capabilities Framework” (Teece et al. 1997; Teece 2007).

• Limited to those Indonesian construction enterprises belonging to the first-class qualification (Grade 6-7)

5

Research SignificanceResearch Significance

• Filling the gap between theoretical construct and practical evidence of dynamic capabilities framework within the construction industrial context

• Introduces the framework for Indonesian construction firms which has never adopted previously by others.

Literature ReviewLiterature Review

Strategy Paradigms

Competitive Forces

Resource-based

Strategic Conflict

DynamicCapabilities

Strategy Paradigms (Teece et al. 1997)Strategy Paradigms (Teece et al. 1997)

6

Literature ReviewLiterature Review

Competitive Advantage

New Paths and

Positions

Dynamic Capabilities

Prior Paths

Positions (assets)

Processes

Dynamic Capabilities Framework (Teece et al. 1997, Teece 2007)Dynamic Capabilities Framework (Teece et al. 1997, Teece 2007)

Research GapResearch Gap

Strategy Research in Construction:• Static vs. Dynamic Approach• Single vs. Integrated Approach• The standard vs. Multi-stage models• Specific vs. All asset/capabilities• Competitive advantage = Organisational

Performance• Construction Industry in Developing

countries

7

Conceptual ModelConceptual Model

Combination of Asset-

capabilities

Competitive Advantage

Performance+ +

Conceptual Model Conceptual Model

Research HypothesisResearch Hypothesis

Value of Asset-

capabilities combination

Competitive Advantage Performance

H3

H1

Rareness of Asset-

capabilities combination

H2

8

Research HypothesisResearch Hypothesis

Competitive Advantage

Performance

Asset-Capabilities Combination / Dynamic

Capabilities

C’

A B

Research MethodologyResearch Methodology

Conceptual Model Verification

Conceptual Model

Dynamic Capabilities Framework

(Assets & Capabilities)

Questionnaire Survey

(Sampling, Design, & Construct)

Stage 3Model Verification

Hypotheses Test

Identify Critical variables and interrelationships among variables

Identify Critical variables in the model

Provision of theoretical foundation in the context of Construction Industry

Provision of theoretical foundation and skeleton of the model

Review of the mainstream

Strategic Management

Theories

Stage 1Literature Review

Stage 2Model Development

9

Research MethodologyResearch Methodology

Why Survey?• The type of research question (Yin 2003).• 70% of empirical studies on dynamic capabilities

used surveys and case-based data sources (Arend and Bromiley, 2009)

• Data Access to private firms• Limited time resources (Cross Section)

Research MethodologyResearch Methodology

Sample Required1. More than 84 cases (Kish, 1965)2. More than 106 cases (Tabachnick and

Fidell, 2007)

Respondents1. Contractors (AKI, GAPENSI, AKLI)2. Consulting/Eng. Firms (INKINDO)

10

Research MethodologyResearch Methodology

12 items: DC1 – DC12 Micro-foundation of dynamic capabilities

3 items: H1 – H3Environmental Hostility

3 items: R1 – R3Rarity of Asset-Capabilities

6 items: V1 – V6 Value of Asset-Capabilities

3 items: CA1 – CA3Competitive Advantage

4 items: P1 – P4Performance

Scale/Measurement itemResearch Construct

Questionnaire Survey Construct *)Questionnaire Survey Construct *)

*) English, Bahasa & Japanese version*) English, Bahasa & Japanese version

Response AnalysisResponse Analysis

• Response Rate

23,86 % (of total)

28,04 %(delivered)

Response Rate (%)

503Total Number of Forms Sent

75Returned Undelivered

120Number of Replies

11

Response AnalysisResponse Analysis

37.4% (52/139)Kazaz, A. & Ulubeyli, S. (2009)

Strategic management practices in Turkish construction firms

25.1% (258/1027)Wetyavivorn, Charoenngam, & Teerajetgul, W. (2009)

Strategic assets driving organizational capabilities of Thai construction firms

28.3% (85/300)Cheah, C.Y.J, Kang, J. & Chew, D.A.S (2007)

Strategic analysis of large local construction firms in China

22.5% (45/200)Price, A.D.F., Ganiev, B.V., & Newson, E. (2003)

Changing strategic management practice within UK construction industry

26.5% (106/400)Chinowsky, P.S., & Meredith, J.E (2000)

Strategic management in construction

Response RateAuthor (year)Research Survey

Response AnalysisResponse Analysis

• Non-response BiasTable ANOVA Result: Significant Group ResponseTable ANOVA Result: Significant Group Response

3.70Late Respondents

2.861+3.15Early Respondents

Employees

11.77Late Respondents

0.069+11.66Early Respondents

PerformanceF-statisticMeanGroupItem

+ p>0.05+ p>0.05

12

Construct AnalysisConstruct Analysis

The item scales are suitably reliable and valid.

• All Alpha coefficients are above the 0.7 threshold (Nunnaly, 1978).

• All loading coefficients are above the 0.5 cut-off (Tosi et al. 1973).

Construct AnalysisConstruct Analysis

Table Reliability & Validity Analysis Table Reliability & Validity Analysis

.616.87212Dynamic Capability Processes

.806.7343Environment Hostility

.540.95521Rareness of Asset-Capabilities

.525.97342Value of Asset-Capabilities

.556 .936 21 Competitive Advantage

.773.839 4PerformanceValidity **)Reliability *)ItemConstruct

*) Alpha ; N=120

**) Min. Loading ; N=120

*) Alpha ; N=120

**) Min. Loading ; N=120

13

Results of Statistical AnalysisResults of Statistical Analysis

Table Regression Results for Hypothesis 1 and 2Table Regression Results for Hypothesis 1 and 2

.39***.30**15+.28*Rarity (β)

.36***.45***.48***.55***Value (β)

-.01 ns-.19*.09 ns.02 ns-.05 ns-.13 ns-.07 ns-.11 nsEnvironment (β)

Stage 2

Stage 1

Stage 2

Stage 1

Stage 2

Stage 1

Stage 2

Stage 1

Regression Model

Reputational Assets and Capabilities (Model 4)

Financial Assets and Capabilities (Model 3)

Complementary Assets and Capabilities (Model 2)

Technological Assets and Capabilities(Model 1)

ns Not sig., +p<0.1, * p<0.05, **p<0.01, ***p<0.001ns Not sig., +p<0.1, * p<0.05, **p<0.01, ***p<0.001

Results of Statistical AnalysisResults of Statistical Analysis

.45**.26*.24*.19+Rarity (β)

.25***.47***.49***.41***Value (β)

-.04 ns-.20*-.02 ns-.21*-.05 ns-.19*-.17*-.30***Environment (β)

Stage 2

Stage 1

Stage 2

Stage 1

Stage 2

Stage 1

Stage 2

Stage 1

Regression Model

Average Assets and Capabilities (Model 8)

Market Assets and Capabilities (Model 7)

Institutional Assets and Capabilities (Model 6)

Structural Assets and Capabilities (Model 5)

Table Regression Results for Hypothesis 1 and 2 (Cont.)Table Regression Results for Hypothesis 1 and 2 (Cont.)

ns Not sig., +p<0.1, * p<0.05, **p<0.01, ***p<0.001ns Not sig., +p<0.1, * p<0.05, **p<0.01, ***p<0.001

14

Results of Statistical AnalysisResults of Statistical Analysis

.33***.32***.28**.19*Competitive Advantage (β)

-.23**-.30***-.30***-.28**-.22*-.26**-.28**-.30***Environment (β)

Stage 2

Stage 1

Stage 2

Stage 1

Stage 2

Stage 1

Stage 2

Stage 1

Hierarchical Reg. Model

Reputational Assets and Capabilities (Model 4)

Financial Assets and Capabilities (Model 3)

Complementary Assets and Capabilities (Model 2)

Technological Assets and Capabilities(Model 1)

Table Regression Results for Hypothesis 3 Table Regression Results for Hypothesis 3

ns Not sig., +p<0.1, * p<0.05, **p<0.01, ***p<0.001ns Not sig., +p<0.1, * p<0.05, **p<0.01, ***p<0.001

Results of Statistical AnalysisResults of Statistical Analysis

.31***.36***.27***.27**Competitive Advantage (β)

-.24**-.30***-.23**-.30***-.18*-.19*-.20*-.26**Environment (β)

Stage 2

Stage 1

Stage 2

Stage 1

Stage 2

Stage 1

Stage 2

Stage 1

Hierarchical Reg. Model

Average Assets and Capabilities (Model 8)

Market Assets and Capabilities (Model 7)

Institutional Assets and Capabilities (Model 6)

Structural Assets and Capabilities (Model 5)

Table Regression Results for Hypothesis 3 (Cont.)Table Regression Results for Hypothesis 3 (Cont.)

ns Not sig., +p<0.1, * p<0.05, **p<0.01, ***p<0.001ns Not sig., +p<0.1, * p<0.05, **p<0.01, ***p<0.001

15

Results of Statistical AnalysisResults of Statistical Analysis

2.50 *2.40*2.45 *Rareness of Market Asset-capability combinations and Performance

1.77 +1.72 +1.75 +Rareness of Reputational Asset-capability combinations and Performance

GoodmanAroianSobelMediated Relationships 1

Table Regression Results for Hypothesis 4 Table Regression Results for Hypothesis 4

ns Not sig., +p<0.1, * p<0.05ns Not sig., +p<0.1, * p<0.05

Results of Statistical AnalysisResults of Statistical Analysis

2.41 *2.31 *2.35 *Transforming capability and Performance are mediated by average competitive advantage

2.74**2.65**2.69 **Transforming capability and Performance are mediated by market competitive advantage

1.79 +1.69+1.74 +Transforming capability and Performance are mediated by institutional competitive advantage

2.71 *2.62*2.66 *Transforming capability and Performance are mediated by reputational competitive advantage

GoodmanAroianSobelMediated Relationships

Table Regression Results for Hypothesis 5 Table Regression Results for Hypothesis 5

ns Not sig., +p<0.1, * p<0.05, **p<0.01ns Not sig., +p<0.1, * p<0.05, **p<0.01

16

Summary of ResultsSummary of Results

Supported3. An enterprise’s competitive advantage will have a positive correlation to its performance.

Supported2. The rarity of asset-capability combinations that an enterprise exploits will have positive relations to its competitive advantage

Supported1. The value of asset-capability combinations that an enterprise exploits will have positive relations to its competitive advantage

FindingsHypotheses

Summary of Results (cont.)Summary of Results (cont.)

Partially Supported

5. An enterprise’s competitive advantage will mediate the relationship between the dynamic capability combinations and its performance

Partially Supported

4. An enterprise’s competitive advantage will mediate the relationship between the value and rareness of the dynamic capability combinations and its performance.

FindingsHypotheses

17

Discussion of ResultsDiscussion of Results

Model Evaluation – H1/H2

• All regression models fully support hypotheses 1 and 2 : all asset-capability combinations fully exhibit the characteristics of value and rarity

• All value variables contribute more to the competitive advantage than rarity variables (except in the reputational model)

• Reputational model records the largest contributor of rarity, the technological model contributes the highest value

Discussion of ResultsDiscussion of Results

Model Evaluation – H3

• Market and reputational asset-capability combinations are major contributors in determining the competitive advantage and performance of Indonesian construction enterprises

• The technological advantage model is the lowest contributors to the performance.

18

Discussion of ResultsDiscussion of Results

Model Evaluation – H4 / H5

• Competitive advantage fully plays it mediation role in the relationship between characteristics of asset-capabilities combination and performance of the firm.

• The results affirm previous studies that competitive advantage and performance are two distinct construct (Tang and Liou’s 2009; Grahovac & Miller 2009; O’Shannassy 2008; Newbert 2007).

ConclusionsConclusions

1. This study provides empirical evidence in support of the notion that a competitive advantage via the implementation of dynamic capability framework is an important way by the construction enterprise in improving its organisational performance.

19

ConclusionsConclusions

2. The value and rarity characteristics of asset-capability combinations contribute to the competitive advantage of the Indonesian construction enterprises, and that such an advantage, sequentially contribute to its organisational performance (Hypotheses 1,2,3).

ConclusionsConclusions

3. This study offers practical evidence of positively direct relationship between characteristics of the enterprises’ asset-capability, dynamic capability, competitive advantage, and its mediating effect on organisational performance (Hypothesis 4 & 5).

20

Contributions & ImplicationsContributions & Implications

• For academics, this study fills an important gap in the empirical literature.

• Hence, the present findings reinforce the dynamic capabilities framework’s recognition as a rigorous theory of strategic management.

Contributions & ImplicationsContributions & Implications

• For practitioners, this study’s finding that a competitive advantage stems from the combination of valuable and rare assets and capabilities may inform the way in which managers make decisions to alter their firms’ asset/capability bases.

21

Contributions & ImplicationsContributions & Implications

• This study suggest that importance knowledge asset as micro-foundation for dynamic capabilities.

• To sustain competitive advantage, it is important that managers develop and/or renewal dynamic capabilities by focusing on elements of knowledge assets through learning process.

Limitations & RecommendationsLimitations & Recommendations

• Cross sectional -> Longitudinal studies

• Single respondents and method -> Multiple respondents and methods

• Large firms sample and level -> different company size and level of analysis

• Indonesia focus –> different emerging countries

22

PublicationPublication

• Publication– Conference Paper (Published)

• Pamulu, M. S, S. Kajewski and M. Betts (2009) Financial management effectiveness of Indonesia's construction state-owned enterprises. In: Infrastructure Research Theme Postgraduate Student Conference 2009, 26 March 2009, Queensland University of Technology, Brisbane.

• Pamulu, Muhammad Sapri and Kajewski, Stephen L. and Betts, Martin (2008) Financial ratio analysis of Indonesian construction firms. In: Fourth International Conference on Global Research in Business & Economics, December 27-30, 2008, Bangkok, Thailand.

• Pamulu, Muhammad Sapri and Kajewski, Stephen L. and Betts, Martin (2007) Evaluating financial ratios in construction industry : a case study of Indonesian firms. In: 1st International Conference of European Asian Civil Engineering Forum (EACEF), 26 - 27 September 2007, Jakarta, Indonesia.

PublicationPublication

• Publication– Book Part (Published)

• Pamulu, M. S, S. Kajewski and M. Betts (2007) Management of Information Technology. In Indonesian Construction Firms, in Construction: Industry, Management and Engineering. Ed. M. Abduh, 73-83. Bandung: ITB Press. ISBN 979-3507-98-5

– Journal Paper (in progress)• Pamulu, M. S, S. Kajewski and M. Betts (2010) Dynamic

capabilities framework in construction: A Study of Indonesian Enterprises.

• Pamulu, M. S, S. Kajewski and M. Betts (2011) Micro-foundations of dynamic capabilities: A Study of Indonesian Construction Firms.

23

AcknowledgementsAcknowledgements

• Supervisory Team– Professor Stephen Kajewski– Professor Martin Betts

• Scholarships providers– QUT– BEE

Questions?Questions?

?