Factors that influence the decision to adopt software upgrades in Australian small and medium sized businesses. A dissertation submitted by

Transcription

1 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

2 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

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4 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

5 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

6 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 Research problem and aim Background to the research Significance of the research Methodology Data analysis Contribution of the research Contributions to academic research Contributions to Small Business Practice Limitations of the research Outline of the dissertation Literature review Introduction Diffusion of innovations Adoption of information technology in small business Organisational buying behaviour Adoption of software upgrades Hidden costs of software upgrades Benefits of software upgrades Pressure to upgrade software Investment analysis Research question Factors identified from the literature Innovativeness Business impact Organisational characteristics Prior experience Educational level Relative advantage Compatibility Past behaviour Information External influences Complexity v

7 2.8 Preliminary model Conclusion Methodology Introduction Research philosophy Sequential exploratory methodology Qualitative study Protocols used in the interviews Quantitative study Development of the survey Prepare the draft questionnaire Question content Question wording Response format Structure and layout Pre-test and revise questionnaire Assess reliability and validity of questionnaire Sampling strategy Data analysis Ethical considerations Conclusions The qualitative study Introduction Profile of businesses used in the interviews Topics explored Why do you upgrade? Business upgrade policy Cost-benefit analysis Advice on the upgrade decision Test before purchase Adopter type Utilization Views about ever increasing features Upgrade problems encountered Concluding interview comments Conclusion Pilot Study Introduction Factors Innovativeness of the manager Business impact Organisational characteristics Prior experience vi

8 5.3.5 Educational level Relative advantage Compatibility Past behaviour Information External influences Complexity Survey Survey design Survey response and demographics Business and manager characteristics Likelihood of upgrade purchase Innovativeness of manager Complexity of purchase decision Analysis of perceptions regarding the software upgrade purchase Revised research model Discussion Conclusion Data analysis and discussion of the full scale study Introduction Sample size Sample response and representativeness Non-response bias Response characteristics Constructing composite variables for use in structural equation models Splitting the dataset Determining the factors Modelling the factors Desired fit statistics Congeneric model for Gains Congeneric model for Control Congeneric model for Complexity Congeneric model for Impact Congeneric model for Efficiencies Congeneric model for Informed Congeneric model for Innovate Summary of exploratory constructs Hypotheses Multiple regression analysis Alternative models Alternative model Alternative model Alternative model Analysis of confirmation models vii

9 Confirmatory congeneric model for Gains Confirmatory congeneric model for Complexity Confirmatory congeneric model for Efficiency Confirmatory congeneric model for Impact Confirmatory congeneric model for Control Confirmatory congeneric model for Informed Confirmatory congeneric model for Innovate Reliabilities for the congeneric models Reject alternative model Other possibilities A new model Comments from survey respondents Conclusions Conclusions and implications Introduction Outline of the thesis Conclusions Limitations Recommendations for further research List of references viii

10 List of figures Figure 1.1 Australia's ICT services trade balance,... 2 Figure 1.2 IT spending per 100 population in Figure 2.1 Outline of chapter Figure 2.2 Areas of literature relevant to a study on upgrades of office software in Australian small and medium business Figure 2.3 Adopter categorization on the basis of innovativeness Figure 2.4 S-shaped adopter distribution curve Figure 2.5 Organisational buying behaviour Figure 2.6 Preliminary model of potential factors influencing decision to upgrade software Figure 3.1 Outline of chapter Figure 3.2 Sequential Exploratory Design Figure 3.3 Guidelines used in item construction Figure 3.4 Questionnaire design process Figure 3.5 Question wording guidelines Figure 4.1 Outline of chapter Figure 5.1 Outline of chapter Figure 5.2 Potential factors identified in the literature review Figure 5.3 Scree plot Figure 5.4 Scree plot after items removed Figure 6.1 Outline of chapter Figure 6.2 Process followed within the exploratory and confirmatory analysis Figure 6.3 Scree Plot Figure 6.4 Scree plot after some items were removed Figure 6.5 Gains congeneric model Figure 6.6 Revised Gains Congeneric Model Figure 6.7 Model Figure 6.8 Model Figure 6.9 Model Figure 6.10 Model 4 a revised Model Figure 6.11 Model 5 a modification to model Figure 6.12 Model 6 using 3 observed variables for Innovate Figure 6.13 Model 7 with the exploratory data Figure 6.14 Model 7 with the confirmatory data Figure 7.1 Structure of chapter seven ix

11 Figure D.1 Control congeneric model exploratory data Figure D.2 Complexity congeneric model exploratory data Figure D.3 Impact congeneric model exploratory data Figure D.4 Efficiencies congeneric model exploratory data Figure D.5 Informed congeneric model exploratory data Figure D.6 Innovate congeneric model exploratory data Figure E.1 Gains congeneric model confirmatory data Figure E.2 Control congeneric model confirmatory data Figure E.3 Complexity congeneric model confirmatory data Figure E.4 Impact congeneric model confirmatory data Figure E.5 Efficiencies congeneric model confirmatory data Figure E.6 Informed congeneric model confirmatory data Figure E.7 Innovate congeneric model confirmatory data x

12 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 Table 5.1 Likelihood of software upgrade Table 5.2 Innovativeness in regards purchase of software upgrade for most important software Table 5.3 Factors extracted Table 5.4 Factor Table 5.5 Factor Table 5.6 Factor Table 5.7 Factor Table 5.8 Factor Table 5.9 Factor Table5.10 Regression model Table 6.1 Position title Table 6.2 Purchasing role in software upgrades Table 6.3 Highest level of education Table 6.4 Years respondent has personally been using computers Table 6.5 Number of years the business had computers Table 6.6 Full time computer specialist employee Table 6.7 Age of the business Table 6.8 Number of full time employees Table 6.9 Scope of the business Table 6.10 Industry type Table 6.11 Annual turnover Table 6.12 Rotated Component Matrix Table 6.13 Rotated factor loadings after the removal of items loading onto more than one factor Table 6.14 Rotated factor loadings with the confirmatory data i2 removed 69 Table 6.15 Factors extracted in the Exploratory and Confirmatory data Table 6.16 Factor Table 6.17 Factor Table 6.18 Factor Table 6.19 Factor Table 6.20 Factor Table 6.21 Factor Table 6.22 Desired fit statistics Table 6.23 Gains reliability (r c ), loading (λ) and error (θ) Table 6.24 Factor score weights for Gains Table 6.25 Innovate (hardware) Table 6.26 Innovate (most important software) Table 6.27 Innovate (word processor) xi

13 Table 6.28 Construct items, loadings, reliability, and error for the exploratory data Table 6.29 Multiple regression model summary Table 6.30 Collinearity statistics for the latent variables Table 6.31 Measures of fit for the Gains measurement model Table 6.32 Measures of fit for the Complexity measurement model Table 6.33 Measures of fit for the Efficiency measurement model Table 6.34 Measures of fit for the Impact measurement model Table 6.35 Measures of fit for the Lack of Control measurement model Table 6.36 Measures of fit for the Informed measurement model Table 6.37 Measures of fit for the Innovativeness measurement model Table 6.38 Construct items, loadings, reliability, and error for the confirmatory data Table A.1 Important issues Table A.2 Decision Table A.3 Justification Table A.4 Decision maker Table A.5 Negatives Table A.6 Managing the upgrade Table A.7 Information sources Table A.8 Testing before buying? Table A.9 Adopter type Table A.10 Training Table A.11 Value of IT Table A.12 Utilization Table A.13 Dealing with upgrade problems Table A.14 Excessive features Table A.15 Upgrade problems Table A.16 Other issues xii

14 List of Appendices Appendix A Interview notes Appendix B Software Upgrade Adoption Survey Appendix C Script to calculate reliability for congeneric models Appendix D Exploratory congeneric models Appendix E Confirmatory congeneric models Appendix F Comments from survey respondents xiii