Factors that influence the decision to adopt software upgrades in Australian small and medium sized businesses A dissertation submitted by David Roberts, B App Sc., Dip Ed, Grad Dip IT, MSc For the award of Doctor of Philosophy July 2009
i Abstract Despite the substantial contribution to the software industry by small and medium sized businesses purchasing software package upgrades, to date there has been minimal research on the topic. Most businesses rely on packaged software for administrative and many core business functions. The practitioner press reports that managers experience frustration due to the frequency of software upgrade releases. After reviewing the diffusion of innovation literature, factors thought to influence the likelihood to purchase software upgrades were identified: business characteristics, innovativeness, relative advantage, external influences, complexity of purchase decision, and compatibility. A mixture of qualitative and quantitative methods was used to further explore the factors that influence the decision to upgrade software in small and medium sized Australian businesses. The responses to ten in-depth interviews were used to develop a questionnaire which was mailed to a five thousand small and medium sized Australian businesses. A number of factors were identified through exploratory factor analysis and these were further examined using structural equation modelling to determine which factors contributed significantly to the decision to upgrade software. The analysis concluded that innovativeness of the decision maker, the perceived lack of control in the upgrade decision and the complexity of the upgrade decision had a small but significant influence on the likelihood to upgrade software. i
iii Certification of the Dissertation I certify that the ideas, interviews, survey work, results, analyses and conclusions reported in this dissertation are entirely my own effort, except where otherwise acknowledged. I also certify that the work is original and has not been previously submitted for any other award. Signature of candidate Date ENDORSEMENT Signature of supervisor Date Signature of supervisor Date iii
iv Acknowledgements I wish to express my sincere appreciation to those who have advised and assisted throughout this investigation. Due to staff changes I have experienced a number of supervisorial changes. To my early supervisors, Professor Angèle Cavaye, Professor Andy Koronios, and Dr Meredith Lawley, I want to express my thanks for assisting and advising me at the beginning of my investigation. A special thanks is extended to my principal supervisor Professor Mark Toleman from whom assistance, guidance and advice were always willingly given. I wish to also thank my assistant supervisor Associate Professor Aileen Cater-Steel for her encouragement, assistance, and advice. I am very thankful that both of you were able to help me finalize the thesis. I must also acknowledge my colleagues who have helped at various stages in the research, and also thank the participants who willingly participated in the interviews and surveys. Finally, thanks are also extended to my wife Carolyn, and three children Cameron, Stuart, and Fiona for their support, encouragement, understanding, and tolerance throughout the years. iv
Table of contents Abstract... i Certification of the Dissertation... iii Acknowledgements... iv Table of contents... v List of Figures... ix List of Tables... xi List of Appendices... xiii 1 Introduction... 1 1.1 Research problem and aim... 1 1.2 Background to the research... 2 1.3 Significance of the research... 4 1.4 Methodology... 6 1.5 Data analysis... 7 1.6 Contribution of the research... 7 1.6.1 Contributions to academic research... 7 1.6.2 Contributions to Small Business Practice... 7 1.7 Limitations of the research... 8 1.8 Outline of the dissertation... 8 2 Literature review... 10 2.1 Introduction... 10 2.2 Diffusion of innovations... 12 2.3 Adoption of information technology in small business... 14 2.4 Organisational buying behaviour... 15 2.5 Adoption of software upgrades... 16 2.5.1 Hidden costs of software upgrades... 16 2.5.2 Benefits of software upgrades... 17 2.5.3 Pressure to upgrade software... 17 2.5.4 Investment analysis... 17 2.6 Research question... 18 2.7 Factors identified from the literature... 19 2.7.1 Innovativeness... 19 2.7.2 Business impact... 19 2.7.3 Organisational characteristics... 20 2.7.4 Prior experience... 20 2.7.5 Educational level... 20 2.7.6 Relative advantage... 21 2.7.7 Compatibility... 21 2.7.8 Past behaviour... 21 2.7.9 Information... 21 2.7.9 External influences... 21 2.7.10 Complexity... 22 v
2.8 Preliminary model... 23 2.9 Conclusion... 23 3 Methodology... 24 3.1 Introduction... 24 3.2 Research philosophy... 24 3.3 Sequential exploratory methodology... 25 3.4 Qualitative study... 26 3.5 Protocols used in the interviews... 27 3.6 Quantitative study... 29 3.7 Development of the survey... 29 3.7.1 Prepare the draft questionnaire... 31 3.7.2 Question content... 32 3.7.3 Question wording... 32 3.7.4 Response format... 33 3.7.5 Structure and layout... 34 3.7.6 Pre-test and revise questionnaire... 35 3.7.7 Assess reliability and validity of questionnaire... 35 3.7.8 Sampling strategy... 35 3.7.9 Data analysis... 36 3.8 Ethical considerations... 37 3.9 Conclusions... 37 4 The qualitative study... 39 4.1 Introduction... 39 4.2 Profile of businesses used in the interviews... 39 4.3 Topics explored... 40 4.3.1 Why do you upgrade?... 41 4.3.2 Business upgrade policy... 41 4.3.3 Cost-benefit analysis... 41 4.3.4 Advice on the upgrade decision... 42 4.3.5 Test before purchase... 42 4.3.6 Adopter type... 43 4.3.7 Utilization... 43 4.3.8 Views about ever increasing features... 43 4.3.9 Upgrade problems encountered... 44 4.3.10 Concluding interview comments... 44 4.4 Conclusion... 44 5 Pilot Study... 45 5.1 Introduction... 45 5.2 Factors... 46 5.3.1 Innovativeness of the manager... 46 5.3.2 Business impact... 46 5.3.3 Organisational characteristics... 47 5.3.4 Prior experience... 47 vi
5.3.5 Educational level... 47 5.3.6 Relative advantage... 47 5.3.7 Compatibility... 48 5.3.8 Past behaviour... 48 5.3.9 Information... 48 5.3.10 External influences... 48 5.3.11 Complexity... 49 5.4 Survey... 49 5.4.1 Survey design... 50 5.4.2 Survey response and demographics... 50 5.4.3 Business and manager characteristics... 50 5.4.4 Likelihood of upgrade purchase... 51 5.4.5 Innovativeness of manager... 51 5.4.6 Complexity of purchase decision... 52 5.4.7 Analysis of perceptions regarding the software upgrade purchase. 52 5.4.8 Revised research model... 57 5.5 Discussion... 57 5.6 Conclusion... 58 6 Data analysis and discussion of the full scale study... 59 6.1 Introduction... 59 6.2 Sample size... 60 6.3 Sample response and representativeness... 61 6.4 Non-response bias... 61 6.5 Response characteristics... 61 6.6 Constructing composite variables for use in structural equation models... 64 6.6.1 Splitting the dataset... 65 6.6.2 Determining the factors... 65 6.6.3 Modelling the factors... 73 6.6.4 Desired fit statistics... 74 6.6.5 Congeneric model for Gains... 75 6.6.6 Congeneric model for Control... 79 6.6.7 Congeneric model for Complexity... 79 6.6.8 Congeneric model for Impact... 80 6.6.9 Congeneric model for Efficiencies... 80 6.6.10 Congeneric model for Informed... 80 6.6.11 Congeneric model for Innovate... 81 6.6.12 Summary of exploratory constructs... 82 6.7 Hypotheses... 83 6.8 Multiple regression analysis... 84 6.9 Alternative models... 85 6.9.1 Alternative model 1... 85 6.9.2 Alternative model 2... 86 6.9.3 Alternative model 3... 87 6.10 Analysis of confirmation models... 88 vii
6.10.1 Confirmatory congeneric model for Gains... 89 6.10.2 Confirmatory congeneric model for Complexity... 89 6.10.3 Confirmatory congeneric model for Efficiency... 90 6.10.4 Confirmatory congeneric model for Impact... 90 6.10.5 Confirmatory congeneric model for Control... 91 6.10.6 Confirmatory congeneric model for Informed... 91 6.10.7 Confirmatory congeneric model for Innovate... 92 6.11 Reliabilities for the congeneric models... 92 6.11.1 Reject alternative model 3... 93 6.11.2 Other possibilities... 93 6.12 A new model.....95 6.13 Comments from survey respondents.....99 6.14 Conclusions... 100 7 Conclusions and implications... 100 7.1 Introduction... 100 7.2 Outline of the thesis... 100 7.3 Conclusions... 102 7.4 Limitations... 103 7.3 Recommendations for further research... 105 List of references... 106 viii
List of figures Figure 1.1 Australia's ICT services trade balance,... 2 Figure 1.2 IT spending per 100 population in 2007... 3 Figure 2.1 Outline of chapter 2... 11 Figure 2.2 Areas of literature relevant to a study on upgrades of office software in Australian small and medium business... 12 Figure 2.3 Adopter categorization on the basis of innovativeness... 13 Figure 2.4 S-shaped adopter distribution curve... 13 Figure 2.5 Organisational buying behaviour... 15 Figure 2.6 Preliminary model of potential factors influencing decision to upgrade software... 23 Figure 3.1 Outline of chapter 3... 24 Figure 3.2 Sequential Exploratory Design... 26 Figure 3.3 Guidelines used in item construction... 30 Figure 3.4 Questionnaire design process... 31 Figure 3.5 Question wording guidelines... 34 Figure 4.1 Outline of chapter 4... 39 Figure 5.1 Outline of chapter 5... 45 Figure 5.2 Potential factors identified in the literature review... 46 Figure 5.3 Scree plot... 53 Figure 5.4 Scree plot after items removed... 54 Figure 6.1 Outline of chapter 6... 59 Figure 6.2 Process followed within the exploratory and confirmatory analysis... 60 Figure 6.3 Scree Plot... 66 Figure 6.4 Scree plot after some items were removed... 68 Figure 6.5 Gains congeneric model... 76 Figure 6.6 Revised Gains Congeneric Model... 77 Figure 6.7 Model 1... 86 Figure 6.8 Model 2.... 87 Figure 6.9 Model 3.... 88 Figure 6.10 Model 4 a revised Model 3... 94 Figure 6.11 Model 5 a modification to model 4... 95 Figure 6.12 Model 6 using 3 observed variables for Innovate... 96 Figure 6.13 Model 7 with the exploratory data... 97 Figure 6.14 Model 7 with the confirmatory data... 98 Figure 7.1 Structure of chapter seven... 100 ix
Figure D.1 Control congeneric model exploratory data... 150 Figure D.2 Complexity congeneric model exploratory data... 151 Figure D.3 Impact congeneric model exploratory data... 152 Figure D.4 Efficiencies congeneric model exploratory data... 153 Figure D.5 Informed congeneric model exploratory data... 154 Figure D.6 Innovate congeneric model exploratory data... 155 Figure E.1 Gains congeneric model confirmatory data... 157 Figure E.2 Control congeneric model confirmatory data... 158 Figure E.3 Complexity congeneric model confirmatory data... 159 Figure E.4 Impact congeneric model confirmatory data... 160 Figure E.5 Efficiencies congeneric model confirmatory data... 161 Figure E.6 Informed congeneric model confirmatory data... 162 Figure E.7 Innovate congeneric model confirmatory data... 163 x
List of tables Table 1.1 IT industry competitiveness index: Overall scores and ranks... 3 Table 4.1 Profile of businesses participating in the interviews... 40 Table 5.1 Likelihood of software upgrade... 51 Table 5.2 Innovativeness in regards purchase of software upgrade for most important software... 52 Table 5.3 Factors extracted 1... 54 Table 5.4 Factor 1... 55 Table 5.5 Factor 2... 55 Table 5.6 Factor 3... 56 Table 5.7 Factor 4... 56 Table 5.8 Factor 5... 56 Table 5.9 Factor 6... 57 Table5.10 Regression model... 57 Table 6.1 Position title... 61 Table 6.2 Purchasing role in software upgrades... 62 Table 6.3 Highest level of education... 62 Table 6.4 Years respondent has personally been using computers... 62 Table 6.5 Number of years the business had computers... 62 Table 6.6 Full time computer specialist employee... 63 Table 6.7 Age of the business... 63 Table 6.8 Number of full time employees... 63 Table 6.9 Scope of the business... 64 Table 6.10 Industry type... 64 Table 6.11 Annual turnover... 64 Table 6.12 Rotated Component Matrix... 66 Table 6.13 Rotated factor loadings after the removal of items loading onto more than one factor... 68 Table 6.14 Rotated factor loadings with the confirmatory data i2 removed 69 Table 6.15 Factors extracted in the Exploratory and Confirmatory data... 71 Table 6.16 Factor 1... 72 Table 6.17 Factor 2... 72 Table 6.18 Factor 3... 72 Table 6.19 Factor 4... 72 Table 6.20 Factor 5... 72 Table 6.21 Factor 6... 73 Table 6.22 Desired fit statistics... 75 Table 6.23 Gains reliability (r c ), loading (λ) and error (θ)... 78 Table 6.24 Factor score weights for Gains... 78 Table 6.25 Innovate (hardware)... 81 Table 6.26 Innovate (most important software)... 81 Table 6.27 Innovate (word processor)... 82 xi
Table 6.28 Construct items, loadings, reliability, and error for the exploratory data... 83 Table 6.29 Multiple regression model summary... 84 Table 6.30 Collinearity statistics for the latent variables... 85 Table 6.31 Measures of fit for the Gains measurement model... 89 Table 6.32 Measures of fit for the Complexity measurement model... 89 Table 6.33 Measures of fit for the Efficiency measurement model... 90 Table 6.34 Measures of fit for the Impact measurement model... 91 Table 6.35 Measures of fit for the Lack of Control measurement model... 91 Table 6.36 Measures of fit for the Informed measurement model... 92 Table 6.37 Measures of fit for the Innovativeness measurement model... 92 Table 6.38 Construct items, loadings, reliability, and error for the confirmatory data... 93 Table A.1 Important issues... 122 Table A.2 Decision... 123 Table A.3 Justification... 124 Table A.4 Decision maker... 125 Table A.5 Negatives... 126 Table A.6 Managing the upgrade... 127 Table A.7 Information sources... 128 Table A.8 Testing before buying?... 129 Table A.9 Adopter type... 130 Table A.10 Training... 131 Table A.11 Value of IT... 132 Table A.12 Utilization... 133 Table A.13 Dealing with upgrade problems... 134 Table A.14 Excessive features... 135 Table A.15 Upgrade problems... 136 Table A.16 Other issues... 137 xii
List of Appendices Appendix A Interview notes... 121 Appendix B Software Upgrade Adoption Survey... 138 Appendix C Script to calculate reliability for congeneric models... 147 Appendix D Exploratory congeneric models... 149 Appendix E Confirmatory congeneric models... 156 Appendix F Comments from survey respondents... 164 xiii