Adaptive IT Capability and its Impact on the Competitiveness of Firms: A Dynamic Capability Perspective A thesis submitted in fulfilment of the requirement for the degree of Doctor of Philosophy Jörg-René Paschke Master of Business School of Business Information Technology Business College RMIT University March 2009 II DECLARATION I certify that except where due acknowledgement has been made, the work is that of the author alone; the work has not been submitted previously, in whole or in part, to qualify for any other academic award; the content of this thesis is the result of work which has been carried out since the official commencement date of the approved research program; any editorial work, paid or unpaid, carried out by a third party is acknowledged; and, ethics procedures and guidelines have been followed. Signed: Jörg-René Paschke 30. March 2009 III ACKNOWLEDGEMENTS Many people have contributed to my thinking, and provided outstanding support in the completion of this thesis, which deserves recognition. I have been most fortunate to be guided by a supportive supervisor team.
A special word of thanks goes to my senior supervisor Associate Professor Alemayehu Molla, not only for sharing his knowledge and expertise with me, but also for his guidance, tireless mentoring and for being a great source of motivation. It was a privilege and great pleasure to be supervised and constantly challenged by such an outstanding academic and research supervisor in the final two years of my candidature. His guidance, motivation and advice enabled me to constantly improve my work on all levels and made this dissertation possible. I am also highly grateful to my second supervisor Professor Bill Martin, for his patience, moral support, advice and financial support through the International Postgraduate Research Scholarship (IPRS), which made this research possible.
Special thanks for his commitment and time in the final stages of this project. I also want to recognise and thank RMIT University, especially Professor Brian Corbitt, for the financial support for publishing papers, attending conferences and providing other resources. Additional thanks go to Dr. John Byrne as my senior supervisor in the first two years of my PhD.
Furthermore, I would like to thank Professor Kosmas Smyrnios, Dr Zijad Pita and Dr Siddhi Pittayachawan for offering me their time and advice on statistical interpretations, as well as Julia Farrell for editorial support. To the 250 CIOs and CEOs go my thanks for taking the time and patience to complete the online questionnaire. Further, thanks go to the fourteen academics on my panel of experts for providing feedback for my questionnaire in the instrument development process. In addition I thank the two CIOs of my pilot study for their time and the opportunity to interview them.
Their comments gave me added insights and improved the research instrument. I must not forget all my research colleagues and my friends for helping me through this difficult journey. Their precious advice and constant cheering were of great support. Special thanks to Dr Ahmad Abarehsi, Timothy James, Kevin Leung, as well as Stefan Briel and Stefanie Grewe.
Finally, I would like to thank my parents Dr Jörg-Volker Paschke and Sieglinde Paschke as well as my sister Silvia Paschke for their motivation, support and, foremost, for believing in me. IV TABLE OF CONTENT DECLARATION. III TABLE OF CONTENT .IV LIST OF FIGURES.IX LIST OF TABLES. XV GLOSSARY OF TERMS.
Research Questions and Objectives. Research Method and Assumptions. Findings of this Study. Contribution of this Study.
Organisation of Thesis. PERSPECTIVES ON COMPETITIVE ADVANTAGE. The Concepts of Competitive Advantage, Firm Performance and Sustained Competitive Advantage. Competitive Advantage and Strategic Management.
Different perspectives on competitive advantage in strategic management. Competitive advantage in the industrial organisations perspective. The Resource-Based View of Competitive Advantage. Overview of competitive advantage from the resource-based view.
Concepts and terminology in the resource-based view. Resources and competitive advantage. Capabilities and competitive advantage. Competences and competitive advantage.
Summary of competitive advantage from the resource-based view. The Dynamic Capability Perspective on Competitive Advantage. The concept and building of dynamic capabilities. The dynamic capability perspective as an improvement on the resource- based view to explain competitive advantage.
PERSPECTIVES ON IT AND COMPETITIVE ADVANTAGE. Overview of Perspectives on IT and Competitive Advantage. Economic Perspective on IT and Firm Performance. Strategic Perspective on IT and Firm Performance.
The Resource-Based View of IT and Competitive Advantage. Overview of the resource-based view of IT and competitive advantage. IT resource complementarities and competitive advantage. IT intangibles and competitive advantage.
Dynamic Capabilities Perspective on IT and Competitive Advantage. A THEORETICAL FRAMEWORK OF ADAPTIVE IT CAPABILITY AND COMPETITIVE ADVANTAGE FROM THE DYNAMIC CAPABILITY PERSPECTIVE. The Research Model. Adaptive IT Capability and Competitive Advantage.
Adaptive IT capability. IT Support for Core Competences, Adaptive IT Capability and Competitive Advantage. IT support for core competences and competitive advantage: The direct hypothesis. IT support for core competences and competitive advantage: The indirect hypothesis.
Relationship between IT support for core competences. IT Capabilities and Adaptive IT Capability. IT infrastructure capability. IT personnel capability.
IT management capability. Overview of data collection methods. Possible methods of inquiry for data collection. Step 1: Specify the domain of constructs.
Step 2: Generate a sample of items. Step 3: Panel of experts survey. Step 4: Pilot study and instrument finetuning. Respondents selection criteria.
DATA ANALYSIS I: DATA CLEANING. Data Examination and Preparation. Data screening and cleaning. Missing value analysis.
Test for normality. Outliers and Multicollinearity. Estimating non-response bias. Profile of Respondents.
INSTRUMENT VALIDATION AND MEASUREMENT MODEL. Assessing Construct Validity through Exploratory Factor Analysis. Overview of factor analysis. Exploratory factor analysis.
Assessing Construct Validity through Confirmatory Factor Analysis. Developing the measurement model in SEM. Statistical criteria for assessing the validity of measurement models. Measurement Model for the IT Infrastructure Capability Construct.
One factor, congeneric measurement models for IT infrastructure capability variables. Full measurement model for IT infrastructure capability construct. IT infrastructure capability as a second order construct. Measurement Model for IT Personnel Capability Construct.
One factor, congeneric measurement models for IT personnel capability construct. Full measurement model of the IT personnel capability construct. IT personnel capability as a second order construct. Measurement Model for IT Management Capability.
Measurement Model of the IT Support for Core Competences Constructs. IT support for market competence. IT support for operational competence. Measurement Model of the Adaptive IT Capability Construct.
Measurement Model for Competitive Advantage. Full CFA Measurement Model. RESEARCH FINDINGS AND DISCUSSION. Overview of IT capabilities and IT support for core competences among Australian organisations.
Adaptive IT capability. IT support for core competences. Summary of descriptive findings. Structural Model and Hypothesis Testing.
Adaptive IT capability and competitive advantage. IT support for core competences, adaptive IT capability and competitive advantage. IT capabilities, IT support for core competences and adaptive IT capability. SUMMARY AND CONCLUSION.
Research Questions Revisited. Is adaptive IT capability a source of competitive advantage?. Is adaptive IT capability mediating the effect of IT support for core competences (market and operational) on competitive advantage?. Which factors influence adaptive IT capability?.
Contributions of this Study. Limitations and Further Study. Final Concluding Remarks. 217 IX LIST OF FIGURES Figure 1-1: Overview of Thesis Structure .11 Figure 2-1: Classification of the Resource Based View Concepts utilized in this Study .24 Figure 4-1: Overview of the Research Model .53 Figure 4-2: Research Model and Hypotheses .55 Figure 6-1: Job Profile of Respondents .109 Figure 7-1: Proposed One Factor, Congeneric Model of IT Integration.132 Figure 7-2: One Factor, Parallel Model of IT Connectivity.135 Figure 7-3: One Factor, Parallel Model of IT Compatibility.136 Figure 7-4: Proposed One Factor, Congeneric Model of IT Modularity .137 Figure 7-5: Final One Factor, Parallel Model of IT Modularity .138 Figure 7-6: Measurement Model of IT Infrastructure Capability Construct .139 Figure 7-7: One Factor Parallel Model of Broad IT Knowledge .143 Figure 7-8: One Factor Parallel Model for Business Knowledge .144 Figure 7-9: Full Measurement Model for IT Personnel Capability .146 Figure 7-10: IT Personnel Capability as a Second Order Construct.148 Figure 7-11: One Factor Congeneric Model of IT Management Capability .149 Figure 7-12: One Factor Congeneric Model of IT Support for Market Competence .150 Figure 7-13: Final One Factor Measurement Model for IT Support for Market Competence .151 Figure 7-14: Proposed One Factor Congeneric Model of IT Support for Operational Competence.152 Figure 7-15: Final One Factor Congeneric Model for IT Support for Operational Competence .154 Figure 7-16: Proposed One Factor Congeneric Model for Adaptive IT Capability .155 X Figure 7-17: Final One Factor Congeneric Measurement Model for Adaptive IT Capability .158 Figure 7-18: One Factor Proposed Model of Competitive Advantage .159 Figure 7-19: Proposed Full CFA Measurement Model .162 Figure 7-20: Final Full CFA Measurement Model.165 Figure 7-21: Re-estimated IT infrastructure capability measurement model .168 Figure 8-1: Overview of IT Constructs among Australian Organisations.171 Figure 8-2: The Effect of Company size .172 Figure 8-3: Adaptive IT Capability .174 Figure 8-4: IT Support for Core Competences .175 Figure 8-5: IT Infrastructure Capability .176 Figure 8-6: IT Personnel Capability .177 Figure 8-7: IT Management Capability .178 Figure 8-8: Full Research model .181 Figure 8-9: Research Model and Hypotheses .184 Figure 9-1: Research Model Revisited .204 XI LIST OF TABLES Table 2-1: Perspectives on Competitive Advantage.18 Table 3-1: Perspectives on IT and Competitive Advantage.37 Table 3-2: Research on Resource-Based View of IT and Competitive Advantage .43 Table 4-1: Constructs of the Research Model .54 Table 4-2: IT Infrastructure Capability Dimensions.65 Table 5-1: Generated Items for IT Infrastructure Capability .79 Table 5-2: Generated Items for IT Personnel Capability .79 Table 5-3: Generated Items for IT Management Capability.81 Table 5-4: Generated Items for IT support for Core Competences .83 Table 5-5: Generated Items for Adaptive IT Capability.85 Table 5-6: Generated Items for Competitive Advantage .86 Table 5-7: Inter-Judge Reliability .87 Table 5-8: Instrument Improvements after Panel of Experts Survey .88 Table 5-9: Changes to Instrument after Pilot Study.90 Table 5-10: Comparison of Sampling Frames from Previous Studies.91 Table 5-11: Comparison of Sample Sizes from Previous Studies .94 Table 5-12: Respondents Selection Criteria .96 Table 6-1: Overview of Data Examination and Preparation.100 Table 6-2: Deleted Items Due to ‘User-Missing’ Data.102 Table 6-3: Independent Sample t-test for ‘System-Missing’ Data.103 Table 6-4: Results of Normal Distribution Test .105 Table 6-5: Independent Sample t-test for Non-Response Bias .108 Table 6-6: Industry and Size Profiles of Survey Respondents .109 Table 6-7: Summary of Data Preparation .110 Table 7-1: Item Deletion Due to Low Reliability.115 XII Table 7-2: Final Item Reliability Score I .116 Table 7-3: Final Reliability score II.117 Table 7-4: KMO and Bartlett's Test .120 Table 7-5: Initial Results of Explorative Factor Analysis.121 Table 7-6: Item Deletions after Exploratory Factor Analysis.122 Table 7-7: Results of Exploratory Factor Analysis I.123 Table 7-8: Results of Exploratory Factor Analysis II.124 Table 7-9: Summary of Key Issues in SEM Model Development .127 Table 7-10: Summary of Goodness of Fit Indices .128 Table 7-11: Goodness of Fit Measures .129 Table 7-12: Statistics for Proposed One Factor, Congeneric Measurement Model of IT Integration .132 Table 7-13: Respecification Statistics for IT Integration Model.133 Table 7-14: Statistics for One Factor, Parallel Model of IT Connectivity .135 Table 7-15: Statistics for One Factor, Parallel Model of IT Compatibility .136 Table 7-16: Statistics for Proposed One Factor, Congeneric Model of IT Modularity .137 Table 7-17: Statistics for Final One Factor, Parallel Model of IT Modularity.138 Table 7-18: Statistics for Measurement Model of IT Infrastructure Capability .139 Table 7-19: Discriminant Validity of IT Infrastructure Capability Construct.140 Table 7-20: Statistics for Second Order Confirmatory Factor Analysis Measurement model of IT Infrastructure Capability.142 Table 7-21: Statistics for One Factor Parallel Model of Broad IT Knowledge.143 Table 7-22: Respecification of Statistics for Broad IT Knowledge .