university for the
    real world
                 R




                        Strategic Management
                      Practices in Construction
                           Industry: A Study of
                        Indonesian Enterprises


                                    FINAL SEMINAR
                            MUHAMMAD SAPRI PAMULU
                                   BEng (Hons.), MEng (PM)




                     Presentation Outline
    1.     Introduction
    2.     Literature Review
    3.     Conceptual Model & Hypothesis
    4.     Research Methodology
    5.     Analysis and Results
    6.     Conclusions & Recommendations
Introduction - Background

• The construction       8.0%
                                                                     7.7%                   7.8%
  industry is one of     7.5%
  the key                7.0%
                                                    6.6%
  contributors to        6.5%
  most economies.
                         6.0%
  – The gross domestic          5.5%
                         5.5%
    product (GDP)
                         5.0%
  – Investment
                           00
                                01
                                     02
                                          03
                                               04
                                                     05
                                                           06
                                                                07
                                                                     08
                                                                          09
                                                                               10
                                                                                    11
                                                                                         12
  – Labour employed      20
                                20
                                     20
                                          20
                                               20
                                                    20
                                                         20
                                                              20
                                                                   20
                                                                        20
                                                                             20
                                                                                  20
                                                                                       20
        Introduction - Background

• The promising
  prospects but, many
  local construction
  firms have poor
  performance and
  low
  competitiveness.
Introduction - 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 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.
Research 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 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)
Research 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 Review

             Strategy Paradigms




  Competitive    Strategic    Resource-    Dynamic
                  Conflict     based      Capabilities
    Forces




 Strategy Paradigms (Teece et al. 1997)
 Strategy Paradigms (Teece et al. 1997)
Literature Review
    Processes
                                                 New Paths
                                                    and
                                                  Positions


     Positions                 Dynamic
     (assets)                 Capabilities



                                                Competitive
    Prior Paths
                                                Advantage



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




                   Research 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
Conceptual Model



Combination
                 +                   +
                       Competitive        Performance
  of Asset-            Advantage
 capabilities




    Conceptual Model
    Conceptual Model




            Research Hypothesis
                 H1
  Value of
   Asset-
 capabilities
combination
                                     H3
                       Competitive
                        Advantage         Performance
                 H2
Rareness of
   Asset-
 capabilities
combination
Research Hypothesis

                                       Competitive
                 A                      Advantage                              B




   Asset-                                      C’
Capabilities
Combination                                                                        Performance
 / Dynamic
Capabilities




          Research Methodology
                   Review of the
                                             Provision of theoretical
                    mainstream
 Stage 1                                     foundation and skeleton of the
                     Strategic
 Literature                                  model
                   Management
 Review              Theories

                            Provision of theoretical
                            foundation in the context of
                            Construction Industry
                       Dynamic             Identify Critical
                      Capabilities         variables in the           Conceptual
 Stage 2
 Model                Framework            model
 Development           (Assets &                                        Model
                      Capabilities)
                            Identify Critical variables and
                            interrelationships among
                            variables
                  Questionnaire
                      Survey                   Hypotheses
 Stage 3                                       Test
 Model           (Sampling, Design,
 Verification       & Construct)
                                               Conceptual Model Verification
Research 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 Methodology
   Sample Required
1. More than 84 cases (Kish, 1965)
2. More than 106 cases (Tabachnick and
   Fidell, 2007)

   Respondents
1. Contractors (AKI, GAPENSI, AKLI)
2. Consulting/Eng. Firms (INKINDO)
Research Methodology

Questionnaire Survey Construct *)
Questionnaire Survey Construct *)
       Research Construct                  Scale/Measurement item
Performance                              4 items: P1 – P4
Competitive Advantage                    3 items: CA1 – CA3
Value of Asset-Capabilities              6 items: V1 – V6
Rarity of Asset-Capabilities             3 items: R1 – R3
Environmental Hostility                  3 items: H1 – H3
Micro-foundation of dynamic              12 items: DC1 – DC12
   capabilities

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




                  Response Analysis
• Response Rate
     Number of Replies                    120
     Returned Undelivered                 75
     Total Number of Forms                503
       Sent
     Response Rate (%)                    28,04 %
                                            (delivered)
                                          23,86 % (of total)
Response Analysis
       Research Survey                   Author (year)            Response Rate
Strategic management in              Chinowsky, P.S., &           26.5% (106/400)
   construction                         Meredith, J.E (2000)

Changing strategic management        Price, A.D.F., Ganiev,       22.5% (45/200)
   practice within UK construction       B.V., & Newson, E.
   industry                              (2003)

Strategic analysis of large local    Cheah, C.Y.J, Kang, J. &     28.3% (85/300)
   construction firms in China          Chew, D.A.S (2007)

Strategic assets driving             Wetyavivorn,             25.1% (258/1027)
   organizational capabilities of      Charoenngam, &
   Thai construction firms             Teerajetgul, W. (2009)

Strategic management practices in Kazaz, A. & Ulubeyli, S.        37.4% (52/139)
   Turkish construction firms        (2009)




                       Response Analysis
  • Non-response Bias
     Table ANOVA Result: Significant Group Response
     Table ANOVA Result: Significant Group Response
       Item                Group                Mean           F-statistic
       Performance Early                           11.66         0.069+
                   Respondents
                           Late                    11.77
                           Respondents
       Employees           Early                    3.15         2.861+
                           Respondents
                           Late                     3.70
                           Respondents
          + p>0.05
           + p>0.05
Construct 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 Analysis

         Table Reliability & Validity Analysis
         Table Reliability & Validity Analysis

Construct                        Item   Reliability *) Validity **)
Performance                       4         .839           .773
Competitive Advantage             21        .936           .556
Value of Asset-Capabilities       42        .973           .525
Rareness of Asset-Capabilities    21        .955           .540
Environment Hostility             3         .734           .806
Dynamic Capability Processes      12        .872           .616

*) Alpha ;;N=120
 *) Alpha N=120
**) Min. Loading ;;N=120
 **) Min. Loading N=120
Results of Statistical Analysis

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

                  Technological     Complementar          Financial         Reputational
                  Assets and        y Assets and          Assets and        Assets and
                  Capabilities      Capabilities          Capabilities      Capabilities
                  (Model 1)         (Model 2)             (Model 3)         (Model 4)
Regression        Stage    Stage    Stage       Stage     Stage    Stage     Stage    Stage
Model               1        2        1           2         1        2         1        2
Environment (β)   -.11 ns -.07 ns   -.13   ns   -.05 ns   .02 ns   .09 ns   -.19*    -.01 ns
Value (β)                 .55***                .48***             .45***            .36***
Rarity (β)                .28*                  15+                .30**             .39***


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




             Results of Statistical Analysis

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

                  Structural        Institutional         Market Assets     Average Assets
                  Assets and        Assets and            and               and
                  Capabilities      Capabilities          Capabilities      Capabilities
                  (Model 5)         (Model 6)             (Model 7)         (Model 8)
Regression        Stage    Stage    Stage       Stage     Stage Stage       Stage    Stage
Model               1        2        1           2         1     2           1        2
Environment (β)   -.30*** -.17*     -.19*       -.05 ns   -.21*    -.02 ns -.20*     -.04 ns
Value (β)                 .41***                .49***             .47***            .25***
Rarity (β)                .19+                  .24*               .26*              .45**


  ns Not sig., +p<0.1, **p<0.05, **p<0.01, ***p<0.001
   ns Not sig., +p<0.1, p<0.05, **p<0.01, ***p<0.001
Results of Statistical Analysis
          Table Regression Results for Hypothesis 3
          Table Regression Results for Hypothesis 3

                    Technological      Complementar       Financial           Reputational
                    Assets and         y Assets and       Assets and          Assets and
                    Capabilities       Capabilities       Capabilities        Capabilities
                    (Model 1)          (Model 2)          (Model 3)           (Model 4)
Hierarchical        Stage     Stage Stage       Stage     Stage     Stage     Stage    Stage
Reg. Model            1         2     1           2         1         2         1        2
Environment (β)     -.30*** -.28** -.26**       -.22*     -.28**    -.30*** -.30*** -.23**
Competitive                   .19*              .28**               .32***             .33***
Advantage (β)




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




           Results of Statistical Analysis

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


                     Structural         Institutional      Market Assets      Average
                     Assets and         Assets and         and                Assets and
                     Capabilities       Capabilities       Capabilities       Capabilities
                     (Model 5)          (Model 6)          (Model 7)          (Model 8)
Hierarchical Reg.    Stage     Stage    Stage    Stage      Stage    Stage     Stage   Stage
Model                  1         2        1        2          1        2         1       2

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

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

  ns Not sig., +p<0.1, **p<0.05, **p<0.01, ***p<0.001
   ns Not sig., +p<0.1, p<0.05, **p<0.01, ***p<0.001
Results of Statistical Analysis
       Table Regression Results for Hypothesis 4
       Table Regression Results for Hypothesis 4

Mediated Relationships 1                     Sobel       Aroian     Goodman
Rareness of Reputational Asset-
capability combinations and                  1.75 +      1.72 +      1.77 +
Performance
Rareness of Market Asset-
capability combinations and                  2.45 *      2.40*       2.50 *
Performance
ns Not sig., +p<0.1, **p<0.05
 ns Not sig., +p<0.1, p<0.05




            Results of Statistical Analysis
      Table Regression Results for Hypothesis 5
      Table Regression Results for Hypothesis 5
 Mediated Relationships                         Sobel     Aroian     Goodman
 Transforming capability and
 Performance are mediated by                    2.66 *     2.62*      2.71 *
 reputational competitive advantage
 Transforming capability and
 Performance are mediated by                    1.74 +     1.69+      1.79 +
 institutional competitive advantage
 Transforming capability and
 Performance are mediated by                   2.69 **     2.65**     2.74**
 market competitive advantage
 Transforming capability and
 Performance are mediated by                    2.35 *     2.31 *     2.41 *
 average competitive advantage

   ns Not sig., +p<0.1, **p<0.05, **p<0.01
    ns Not sig., +p<0.1, p<0.05, **p<0.01
Summary of Results
                Hypotheses                      Findings
 1. The value of asset-capability combinations     Supported
    that an enterprise exploits will have positive
    relations to its competitive advantage
 2. The rarity of asset-capability combinations    Supported
    that an enterprise exploits will have positive
    relations to its competitive advantage
 3. An enterprise’s competitive advantage will     Supported
    have a positive correlation to its
    performance.




       Summary of Results (cont.)
               Hypotheses                       Findings
4. An enterprise’s competitive advantage will   Partially
   mediate the relationship between the value   Supported
   and rareness of the dynamic capability
   combinations and its performance.
5. An enterprise’s competitive advantage will   Partially
   mediate the relationship between the         Supported
   dynamic capability combinations and its
   performance
Discussion 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 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.
Discussion 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).




                  Conclusions
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.
Conclusions
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).




               Conclusions
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).
Contributions & 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 & 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.
Contributions & 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 & 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
Publication
• 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.




                      Publication
• 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.
Acknowledgements
• Supervisory Team
  – Professor Stephen Kajewski
  – Professor Martin Betts
• Scholarships providers
  – QUT
  – BEE




                 Questions?




                                 ?

Strategic management practices in construction

  • 1.
    university for the real world R Strategic Management Practices in Construction Industry: A Study of Indonesian Enterprises FINAL SEMINAR MUHAMMAD SAPRI PAMULU BEng (Hons.), MEng (PM) Presentation Outline 1. Introduction 2. Literature Review 3. Conceptual Model & Hypothesis 4. Research Methodology 5. Analysis and Results 6. Conclusions & Recommendations
  • 2.
    Introduction - Background •The construction 8.0% 7.7% 7.8% industry is one of 7.5% the key 7.0% 6.6% contributors to 6.5% most economies. 6.0% – The gross domestic 5.5% 5.5% product (GDP) 5.0% – Investment 00 01 02 03 04 05 06 07 08 09 10 11 12 – Labour employed 20 20 20 20 20 20 20 20 20 20 20 20 20 Introduction - Background • The promising prospects but, many local construction firms have poor performance and low competitiveness.
  • 3.
    Introduction - 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 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 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 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 Significance • Fillingthe 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 Review Strategy Paradigms Competitive Strategic Resource- Dynamic Conflict based Capabilities Forces Strategy Paradigms (Teece et al. 1997) Strategy Paradigms (Teece et al. 1997)
  • 6.
    Literature Review Processes New Paths and Positions Positions Dynamic (assets) Capabilities Competitive Prior Paths Advantage Dynamic Capabilities Framework (Teece et al. 1997, Teece 2007) Dynamic Capabilities Framework (Teece et al. 1997, Teece 2007) Research 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 Model Combination + + Competitive Performance of Asset- Advantage capabilities Conceptual Model Conceptual Model Research Hypothesis H1 Value of Asset- capabilities combination H3 Competitive Advantage Performance H2 Rareness of Asset- capabilities combination
  • 8.
    Research Hypothesis Competitive A Advantage B Asset- C’ Capabilities Combination Performance / Dynamic Capabilities Research Methodology Review of the Provision of theoretical mainstream Stage 1 foundation and skeleton of the Strategic Literature model Management Review Theories Provision of theoretical foundation in the context of Construction Industry Dynamic Identify Critical Capabilities variables in the Conceptual Stage 2 Model Framework model Development (Assets & Model Capabilities) Identify Critical variables and interrelationships among variables Questionnaire Survey Hypotheses Stage 3 Test Model (Sampling, Design, Verification & Construct) Conceptual Model Verification
  • 9.
    Research 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 Methodology Sample Required 1. More than 84 cases (Kish, 1965) 2. More than 106 cases (Tabachnick and Fidell, 2007) Respondents 1. Contractors (AKI, GAPENSI, AKLI) 2. Consulting/Eng. Firms (INKINDO)
  • 10.
    Research Methodology Questionnaire SurveyConstruct *) Questionnaire Survey Construct *) Research Construct Scale/Measurement item Performance 4 items: P1 – P4 Competitive Advantage 3 items: CA1 – CA3 Value of Asset-Capabilities 6 items: V1 – V6 Rarity of Asset-Capabilities 3 items: R1 – R3 Environmental Hostility 3 items: H1 – H3 Micro-foundation of dynamic 12 items: DC1 – DC12 capabilities *) English, Bahasa & Japanese version *) English, Bahasa & Japanese version Response Analysis • Response Rate Number of Replies 120 Returned Undelivered 75 Total Number of Forms 503 Sent Response Rate (%) 28,04 % (delivered) 23,86 % (of total)
  • 11.
    Response Analysis Research Survey Author (year) Response Rate Strategic management in Chinowsky, P.S., & 26.5% (106/400) construction Meredith, J.E (2000) Changing strategic management Price, A.D.F., Ganiev, 22.5% (45/200) practice within UK construction B.V., & Newson, E. industry (2003) Strategic analysis of large local Cheah, C.Y.J, Kang, J. & 28.3% (85/300) construction firms in China Chew, D.A.S (2007) Strategic assets driving Wetyavivorn, 25.1% (258/1027) organizational capabilities of Charoenngam, & Thai construction firms Teerajetgul, W. (2009) Strategic management practices in Kazaz, A. & Ulubeyli, S. 37.4% (52/139) Turkish construction firms (2009) Response Analysis • Non-response Bias Table ANOVA Result: Significant Group Response Table ANOVA Result: Significant Group Response Item Group Mean F-statistic Performance Early 11.66 0.069+ Respondents Late 11.77 Respondents Employees Early 3.15 2.861+ Respondents Late 3.70 Respondents + p>0.05 + p>0.05
  • 12.
    Construct 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 Analysis Table Reliability & Validity Analysis Table Reliability & Validity Analysis Construct Item Reliability *) Validity **) Performance 4 .839 .773 Competitive Advantage 21 .936 .556 Value of Asset-Capabilities 42 .973 .525 Rareness of Asset-Capabilities 21 .955 .540 Environment Hostility 3 .734 .806 Dynamic Capability Processes 12 .872 .616 *) Alpha ;;N=120 *) Alpha N=120 **) Min. Loading ;;N=120 **) Min. Loading N=120
  • 13.
    Results of StatisticalAnalysis Table Regression Results for Hypothesis 1 and 2 Table Regression Results for Hypothesis 1 and 2 Technological Complementar Financial Reputational Assets and y Assets and Assets and Assets and Capabilities Capabilities Capabilities Capabilities (Model 1) (Model 2) (Model 3) (Model 4) Regression Stage Stage Stage Stage Stage Stage Stage Stage Model 1 2 1 2 1 2 1 2 Environment (β) -.11 ns -.07 ns -.13 ns -.05 ns .02 ns .09 ns -.19* -.01 ns Value (β) .55*** .48*** .45*** .36*** Rarity (β) .28* 15+ .30** .39*** ns Not sig., +p<0.1, **p<0.05, **p<0.01, ***p<0.001 ns Not sig., +p<0.1, p<0.05, **p<0.01, ***p<0.001 Results of Statistical Analysis Table Regression Results for Hypothesis 1 and 2 (Cont.) Table Regression Results for Hypothesis 1 and 2 (Cont.) Structural Institutional Market Assets Average Assets Assets and Assets and and and Capabilities Capabilities Capabilities Capabilities (Model 5) (Model 6) (Model 7) (Model 8) Regression Stage Stage Stage Stage Stage Stage Stage Stage Model 1 2 1 2 1 2 1 2 Environment (β) -.30*** -.17* -.19* -.05 ns -.21* -.02 ns -.20* -.04 ns Value (β) .41*** .49*** .47*** .25*** Rarity (β) .19+ .24* .26* .45** ns Not sig., +p<0.1, **p<0.05, **p<0.01, ***p<0.001 ns Not sig., +p<0.1, p<0.05, **p<0.01, ***p<0.001
  • 14.
    Results of StatisticalAnalysis Table Regression Results for Hypothesis 3 Table Regression Results for Hypothesis 3 Technological Complementar Financial Reputational Assets and y Assets and Assets and Assets and Capabilities Capabilities Capabilities Capabilities (Model 1) (Model 2) (Model 3) (Model 4) Hierarchical Stage Stage Stage Stage Stage Stage Stage Stage Reg. Model 1 2 1 2 1 2 1 2 Environment (β) -.30*** -.28** -.26** -.22* -.28** -.30*** -.30*** -.23** Competitive .19* .28** .32*** .33*** Advantage (β) ns Not sig., +p<0.1, **p<0.05, **p<0.01, ***p<0.001 ns Not sig., +p<0.1, p<0.05, **p<0.01, ***p<0.001 Results of Statistical Analysis Table Regression Results for Hypothesis 3 (Cont.) Table Regression Results for Hypothesis 3 (Cont.) Structural Institutional Market Assets Average Assets and Assets and and Assets and Capabilities Capabilities Capabilities Capabilities (Model 5) (Model 6) (Model 7) (Model 8) Hierarchical Reg. Stage Stage Stage Stage Stage Stage Stage Stage Model 1 2 1 2 1 2 1 2 Environment (β) -.26** -.20* -.19* -.18* -.30*** -.23** -.30*** -.24** Competitive .27** .27*** .36*** .31*** Advantage (β) ns Not sig., +p<0.1, **p<0.05, **p<0.01, ***p<0.001 ns Not sig., +p<0.1, p<0.05, **p<0.01, ***p<0.001
  • 15.
    Results of StatisticalAnalysis Table Regression Results for Hypothesis 4 Table Regression Results for Hypothesis 4 Mediated Relationships 1 Sobel Aroian Goodman Rareness of Reputational Asset- capability combinations and 1.75 + 1.72 + 1.77 + Performance Rareness of Market Asset- capability combinations and 2.45 * 2.40* 2.50 * Performance ns Not sig., +p<0.1, **p<0.05 ns Not sig., +p<0.1, p<0.05 Results of Statistical Analysis Table Regression Results for Hypothesis 5 Table Regression Results for Hypothesis 5 Mediated Relationships Sobel Aroian Goodman Transforming capability and Performance are mediated by 2.66 * 2.62* 2.71 * reputational competitive advantage Transforming capability and Performance are mediated by 1.74 + 1.69+ 1.79 + institutional competitive advantage Transforming capability and Performance are mediated by 2.69 ** 2.65** 2.74** market competitive advantage Transforming capability and Performance are mediated by 2.35 * 2.31 * 2.41 * average competitive advantage ns Not sig., +p<0.1, **p<0.05, **p<0.01 ns Not sig., +p<0.1, p<0.05, **p<0.01
  • 16.
    Summary of Results Hypotheses Findings 1. The value of asset-capability combinations Supported that an enterprise exploits will have positive relations to its competitive advantage 2. The rarity of asset-capability combinations Supported that an enterprise exploits will have positive relations to its competitive advantage 3. An enterprise’s competitive advantage will Supported have a positive correlation to its performance. Summary of Results (cont.) Hypotheses Findings 4. An enterprise’s competitive advantage will Partially mediate the relationship between the value Supported and rareness of the dynamic capability combinations and its performance. 5. An enterprise’s competitive advantage will Partially mediate the relationship between the Supported dynamic capability combinations and its performance
  • 17.
    Discussion 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 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 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). Conclusions 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.
    Conclusions 2. The valueand 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). Conclusions 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 & 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 & 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 & 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 & 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.
    Publication • 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. Publication • 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.
    Acknowledgements • Supervisory Team – Professor Stephen Kajewski – Professor Martin Betts • Scholarships providers – QUT – BEE Questions? ?