Strategic management practices in construction

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It is an empirical study of strategic management practices in the construction industry. It examines the dynamic capabilities paradigm within the context of the Indonesian construction industry. The characteristics of asset-capability combinations were found to be significant determinants of the competitive advantage of the Indonesian construction enterprises, and that such advantage sequentially contributes to organizational performance. In doing so, this study fills an important gap in the empirical literature and reinforces the dynamic capabilities framework’s recognition as a rigorous theory of strategic management. As the dynamic capabilities framework can work in the context of Indonesia, it suggests that the framework has potential applicability in other emerging and developing countries

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Strategic management practices in construction

  1. 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. 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. 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. 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. 5. 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)
  6. 6. Literature Review Processes New Paths and Positions Positions Dynamic (assets) Capabilities Competitive Prior Paths AdvantageDynamic 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. 7. Conceptual ModelCombination + + Competitive Performance of Asset- Advantage capabilities Conceptual Model Conceptual Model Research Hypothesis H1 Value of Asset- capabilitiescombination H3 Competitive Advantage Performance H2Rareness of Asset- capabilitiescombination
  8. 8. Research Hypothesis Competitive A Advantage B Asset- C’CapabilitiesCombination Performance / DynamicCapabilities 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. 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 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. 10. Research MethodologyQuestionnaire Survey Construct *)Questionnaire Survey Construct *) Research Construct Scale/Measurement itemPerformance 4 items: P1 – P4Competitive Advantage 3 items: CA1 – CA3Value of Asset-Capabilities 6 items: V1 – V6Rarity of Asset-Capabilities 3 items: R1 – R3Environmental Hostility 3 items: H1 – H3Micro-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. 11. Response Analysis Research Survey Author (year) Response RateStrategic 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. 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 AnalysisConstruct Item Reliability *) Validity **)Performance 4 .839 .773Competitive Advantage 21 .936 .556Value of Asset-Capabilities 42 .973 .525Rareness of Asset-Capabilities 21 .955 .540Environment Hostility 3 .734 .806Dynamic Capability Processes 12 .872 .616*) Alpha ;;N=120 *) Alpha N=120**) Min. Loading ;;N=120 **) Min. Loading N=120
  13. 13. 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 StageModel 1 2 1 2 1 2 1 2Environment (β) -.11 ns -.07 ns -.13 ns -.05 ns .02 ns .09 ns -.19* -.01 nsValue (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 AnalysisTable 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 StageModel 1 2 1 2 1 2 1 2Environment (β) -.30*** -.17* -.19* -.05 ns -.21* -.02 ns -.20* -.04 nsValue (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. 14. 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 StageReg. Model 1 2 1 2 1 2 1 2Environment (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 StageModel 1 2 1 2 1 2 1 2Environment (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. 15. Results of Statistical Analysis Table Regression Results for Hypothesis 4 Table Regression Results for Hypothesis 4Mediated Relationships 1 Sobel Aroian GoodmanRareness of Reputational Asset-capability combinations and 1.75 + 1.72 + 1.77 +PerformanceRareness of Market Asset-capability combinations and 2.45 * 2.40* 2.50 *Performancens 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. 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 Findings4. 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. 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. 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). Conclusions1. 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. 19. Conclusions2. 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). Conclusions3. 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. 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. 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. 22. Publication• Publication – Conference Paper (Published) • Pamulu, M. S, S. Kajewski and M. Betts (2009) Financial management effectiveness of Indonesias 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. 23. Acknowledgements• Supervisory Team – Professor Stephen Kajewski – Professor Martin Betts• Scholarships providers – QUT – BEE Questions? ?

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