ENTERPRISE 2.0: AN EXTENDED TECHNOLOGY ACCEPTANCE MODEL PREVIEW. James M. Kurz. THOMAS RICHARDS, PhD, Faculty Mentor and Chair

Transcription

1 ENTERPRISE 2.0: AN EXTENDED TECHNOLOGY ACCEPTANCE MODEL by James M. Kurz THOMAS RICHARDS, PhD, Faculty Mentor and Chair RICHARD YELLEN, PhD, Committee Member HARRY STEUDEL, PhD, Committee Member William A. Reed, PhD, Dean, School of Business & Technology A Dissertation Presented in Partial Fulfillment Of the Requirements for the Degree Doctor of Philosophy Capella University December 2012

2 UMI Number: All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. UMI Published by ProQuest LLC (2013). Copyright in the Dissertation held by the Author. Microform Edition ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code ProQuest LLC. 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, MI

3 James M. Kurz, 2012

4 Abstract The amount of information that people produce is changing, especially as social networking becomes more commonplace and globalization inefficiencies continue to swamp enterprise. Companies are rising to the challenge to create a collaborative approach for information management, but according to many leading technology advisory firms, they have not leveraged these same efficiencies internally. Empowering the social networking collaborative while using Enterprise 2.0 (E2.0) social networks / media technologies as a transformational force for a company s relationship to its employees seems to be untapped. There are many studies that attempt to construct models that provide a management tool to leverage the belief-attitude-intention-behavior relationship in testing new technology acceptance. This study utilized technology acceptance model (TAM) constructs to examine the relationships among the self-reported outcomes for perceived trust, perceived usefulness, perceived ease of use, attitude, perceived enjoyment, subjective norms, self-efficacy, facilitating conditions, perceived behavioral control, behavioral intention to use, and actual use in enterprise collaboration by adopting E2.0 technologies to communicate and interact within social networking communities at work. The data were analyzed using regression analysis and structured equation modeling. Results demonstrate that the model e2.0tam can be a helpful tool to understand user acceptance of E2.0 technologies when used to mitigate adoption barriers. This research s findings suggests there is a positive correlation between the use of these technologies and perceived usefulness, perceived ease of use, perceived trust, attitude, self-efficacy, facilitating conditions and perceived behavioral control, behavioral intention to use, use behavior, while perceived enjoyment and subjective norms were not.

5 Dedication This is dedicated to my wife, Patricia, whose inspiration, patience, and love helped me to stay focused and finish this endeavor. Thank you for your understanding when I had to work on my paper. You made this all possible. This is dedicated to my children, Michelle and James, and granddaughter, Kasia, for giving me the motivation and strength to pursue this goal. Most important, it is dedicated in loving memory of my mother, Helen, and father, William Kurz, who nurtured me to be the person I am. To all of my family and friends, thank you for your support. iii

6 Acknowledgements I would like to acknowledge my adviser, Dr. Thomas Richards, for his guidance during this research project. I would like also to acknowledge my dissertation committee, Dr. Richard Yellen and Dr. Harry Steudel, for their insightful comments and suggestions. I would like to acknowledge my daughter, Michelle, who was there with me word for word as my proofreader, editor, sounding board, and idea generator, but mostly for her love and encouragement. I would like to extend my appreciation and gratitude to the entire staff and faculty at Capella University. Thank you to everyone who has made this possible. iv

7 Table of Contents Acknowledgements List of Tables List of Figures iv viii x CHAPTER 1. INTRODUCTION 1 The Introduction 1 Background of the Study 4 Statement of the Problem 6 Purpose of the Study 9 Rationale 10 Research Question and Model 10 Significance of the Study 15 Definitions of Terms 15 Assumptions and Limitations 19 Nature of the Study 20 Organization for the Remainder of the Study 23 CHAPTER 2. LITERATURE REVIEW 24 Enterprise Technology Acceptance Model 39 CHAPTER 3. METHODOLOGY 63 Introduction 63 Research Question and Hypothesis 65 Behavioral Intent 68 Decomposition of Attitude 68 v

8 Perceived Usefulness 70 Perceived Ease of Use 70 Perceived Trust 71 Perceived Enjoyment 71 Subjective Norms 72 Decomposition of Perceived Behavioral Control 72 Methodology and Design 74 Population and Sampling 76 Design of Study 78 Instrumentation 79 Field and Pilot Tests 80 Construct Measurements 81 Reliability 87 Validity 89 Data Collection Procedures 91 Sampling Technique and Recruitment 92 Sample Size 92 Data Analysis Plans 93 Ethical Consideration 96 CHAPTER 4. RESEARCH RESULTS 97 Introduction 97 Data Collection Procedures 98 Data Analysis 99 Summary 116 vi

9 CHAPTER 5. DISCUSSION, IMPLICATIONS, RECOMMENDATIONS & CONCLUSION 120 Discussion of Results 120 Research Question 130 Implications 130 Recommendation for Further Study 131 Conclusion 132 REFERENCES 135 APPENDIX A FINAL MEASUREMENT SCALES FOR PU & PEU 158 APPENDIX B THE ENTERPRISE 2.0 USER ACCEPTANCE SURVEY E2.0UAS159 APPENDIX C E2.0TAM OPERATIONAL CONSTRUCT 166 APPENDIX D REGRESSION SCATTERPLOTS 169 vii

10 List of Tables Table 1. Usage 82 Table 2. Perceived Usefulness 82 Table 3. Perceived Ease of Use 83 Table 4. Perceived Trust 83 Table 5. Attitude 84 Table 6. Perceived Enjoyment 84 Table 7. Subjective Norms 85 Table 8. Self-Efficacy 85 Table 9. Facilitating Condition 86 Table 10. Perceived Behavioral Control 86 Table 11. Behavioral Intention 87 Table 12. Cronbach Alpha scale reliabilities 88 Table 13. Construct Validity Using Factor Analysis 90 Table 14. Model Fit for Each Good-Fitting CFA 103 Table 15. Standardized Factor Loadings for Each Subscale and Cronbach Alphas 103 Table 16. Mean, Standard Deviations, Skewness, and Kurtosis for Each Item 104 Table 17. Full Correlation Matrix Among Variables 105 Table 18. Overall Model Fit and the Revision 107 Table 19. Results for Behavior Intent Predicting Usage 109 Table 20. Attitude, Perceived Enjoyment, Social Norms, and Perceived Behavior Control Predicting Behavior Intent 111 viii

11 Table 21. Perceived Ease of Use, Perceived Usefulness, and Perceived Trust Predicting Attitude 112 Table 22. Perceived Ease of Use Predicting Perceived Usefulness 113 Table 23. Self-Efficacy and Facilitating Control Predicting Perceived Behavior Control 115 Table 24. Summary of Hypotheses 115 Table 25. Regression Model Equations 117 ix

12 List of Figures Figure 1. Growth in the big five social networks 2 Figure 2. Gartner Hype Cycle: Emerging Technologies 7 Figure 3. Technology Acceptance Model 11 Figure 4. Enterprise 2.0 Technology Acceptance Model (e2.0tam) Research Model 11 Figure 5. E2.0TAM Research Model. Extended Technology Acceptance Model 66 Figure 6. e2.0tam Construct Measurement Model 79 Figure 7. Full proposed model demonstrating poor model fit 106 Figure 8. Behavioral intent predicting usage with standardized regression weight 110 Figure 10. Perceived ease of use, perceived usefulness, and perceived trust predicting attitude with standardized regression weights. 112 Figure 11. Perceived ease of use predicting perceived usefulness with standardized regression weights 113 Figure 12. Self-efficacy and facilitating control predicting perceived behavior control with standardized regression weights 114 Figure 13. Hypothesis support model 116 Figure D1. Normality plot for the first regression 169 Figure D2. Homoscedasticity plot for first regression 170 Figure D3. Normality plot for second regression 171 Figure D4. Homoscedasticity plot for second regression 172 Figure D5. Normality plot for third regression 173 Figure D6. Homoscedasticity plot for third 174 Figure D7. Normality plot for fourth regression 175 x

13 Figure D8. Homoscedasticity plot for fourth regression 176 Figure D9. Normality plot for fifth regression 177 Figure D10. Homoscedasticity plot for fifth regression 178 xi

14 CHAPTER 1. INTRODUCTION The Introduction The amount of information that people produce is changing, especially as social networking becomes more commonplace and globalization inefficiencies continue to swamp enterprise (Friedman, 2006). Companies are rising to the information management challenge, collaborating with partners or customers utilizing Web 2.0 technologies, but, according to many leading technology advisory firms, including Forrester Research, McKinsey & Company, Cutter Consortium, Gartner Group, and others, they have not leveraged these same efficiencies internally (McAfee, 2010). DiNucci (1999) originally coined the term Web 2.0 in her 1999 article, Fragmented Future. However, it wasn t until 2006, in his blog, that O Reilly (2006b) provided this short definition: Web 2.0 is the business revolution in the computer industry caused by the move to the Internet as a platform, and an attempt to understand the rules for success on that new platform. Chief among these rules is this: Build applications that harness network effects to get better the more people use them. (para. 1) The Web 2.0 social networking platform supports user collaboration. These users, who are located in different places, come together to: share knowledge, interact and communicate on common interests, needs, or goals (Brandtzæg, 2007; Pettenati & Ranieri, 2006). Most people have become familiar with Web 2.0, based on the exponential growth of emergent social software platforms such as Facebook, Myspace, LinkedIn, Plato, and Twitter (see Figure 1). 1

15 Figure 1. Growth in the big five social networks. Adapted from Social Networks: Facebook Takes Over Top Spot, Twitter Climbs, A. Kazeniac, 2009, Retrieved from Copyright 2012 Compete Pulse. Adapted with permission. Organizations are adapting these same technologies, as McAfee (2010) has seen. McAfee coined the term Enterprise 2.0 (E2.0) to describe this transition as the use of emergent social software platforms by organizations in pursuit of their goals (p. 73). Therefore, organizational groups or communities shared goals can be addressed using these new collaborative tools. However, E2.0 use as a transformational force for a company s employee relationships seems to be untapped and these new technologies workplace acceptance is unknown. How individuals adopt and use new technologies is an enduring question since simply rolling out a new technology does not inherently translate into individuals using the technology (Hirschheim, 2007). F. D. Davis (1986), in a doctoral dissertation, first addressed the need for a management tool to leverage the belief-attitude-intentionbehavior relationship in testing new technology acceptance. F. D. Davis leveraged the Fishbein and Ajzen (1975) theory, which stated, The beliefs about an object provide the basis for the formation of attitude toward the object, and we have shown that attitudes are 2

16 usually measured by assessing a person s beliefs (p. 138). The ensuing technology acceptance model (TAM) specified the causal relationships among system design features, perceived usefulness, perceived ease of use, attitude toward using, and usage behavior (F. D. Davis, 1986). After F. D. Davis, Bagozzi and Warshaw s further enhancements of TAM was found to be a practical tool for early user acceptance and could be used to help practitioners identify and evaluate enhanced user acceptance strategies (F. D. Davis, 1989; F. D. Davis, Bagozzi, & Warshaw, 1989; Bagozzi, F. D. Davis, & Warshaw, 1992). The TAM has become one of the most prominent research tools in investigating the causes of technology acceptance (Chau, 1996). Over time, the TAM has been developed and extended within different populations and various technology systems (Agarwal & Prasad, 2000; An, 2005; Chau & Hu, 2001; Cheung & Huang, 2005; Drennan, Kennedy, & Pisarki, 2005; Hong, Thong, Wong, & Tam, 2002; Lu, Yu, Liu, & Yao, 2003; Moon & Kim, 2001; Riemenschneider, Harrison, & Mykytyn, 2003; Venkatesh, 2000; Venkatesh & F. D. Davis, 2000; Venkatesh & Morris, 2000). According to Lucas, Swanson, and Zmud (2007), TAM has in fact come to occupy a central position in research focused on individual adoption of Information Technology [IT] innovations (p. 206). Since E2.0 is a recent IT innovation, its adoption can also be examined by extending TAM in congruence with those successful studies mentioned throughout this study. The extended model was called E2.0 Technology Acceptance Model (e2.0tam). This study used e2.0tam to examine the explanatory capability for E2.0 adoption. This research study examined the self-reported outcomes for perceived trust (PT), perceived usefulness (PU), perceived ease of use (PEU), attitude (A), perceived enjoyment (PE), 3

17 subjective norms (SN), self-efficacy (SE), facilitating conditions (FC), perceived behavioral control (PBC), behavioral intention to use (BI), and use behavior (U) in the belief-attitude-intention-behavior relationship in enterprise collaboration by adopting E2.0 social networks / media technologies. The setting was an online survey of working adults within their enterprise environment. This researcher s focus was the adoption of E2.0 social networks / media technologies to communicate and interact within social networking communities at work. Overall, this research project added to the existing body of knowledge while uncovering the causal relationships or forces (trends) that influence the adoption of a new technology that can be used to predict a stated outcome. The goal was to create a management tool that management could use not only to predict the adoption of the new E2.0 social networks / media technologies, but to provide a list of determinant(s) that can be further studied to help improve the rate of successful adoptions. This might be a way to gage usability in a corporate environment and has the potential to help improve the success of adopting E2.0 social networks / media technologies. Background of the Study Information Systems (IS) or Information Technology (IT) is an applied discipline similar to engineering and as such uses, redefines, and potentially redevelops the theories in other disciplines (Baskerville & Myers, 2002). This presents a variety of seminal works, which broadly encompass computer science, organizational behavior, organizational theory, and cognitive psychology (Vessey, Ramesh, & Glass, 2002). The authors found, [Information Systems] researchers [should] use the theories derived in those reference disciplines to develop their own theories to provide the [Information 4

18 Systems] field with new understanding (p. 166). As such, this study leverages theories, such as theory of reasoned action (TRA) and TAM that were rooted in the behavioral science discipline. Fishbein and Ajzen (1975) developed the TRA, which identified the main detriments to the attitudes toward new technology as being the perceived ease of use and perceived usefulness of technology. The TRA model indicates that a person s attitude toward a behavior represents the person s beliefs about the behavior and subsequently its use; while F. D. Davis s (1989) TAM determined that use is modeled as a direct function of intention thereby extending Fishbein and Ajzen s TRA to address ease of use and usefulness. Behavioral elements from TRA and TAM indicate that a person acts limitlessly when the act is intended (Bagozzi et al., 1992; F. D. Davis et al., 1989). Bagozzi et al. (1992) state: Due to having doubt in their own ability to learn to use new technology, users tend to judge the outcome of difficult learning tasks in technology even before trying to learn to use the new technology or trying just a few times. These judgments may negatively influence the implementation and usage of new technology which can skew the results of what was actually learned and how the new technology is being used. (p. 665) This research paper by Venkatesh and F. D. Davis (2000) extended the original TAM version that F. D. Davis developed to include perceived trust, perceived usefulness, perceived ease of use, attitude, perceived enjoyment, subjective norms, self-efficacy, facilitating conditions, perceived behavioral control, behavioral intention to use, and use behavior in the belief-attitude-intention-behavior relationship in enterprise collaboration 5

19 by adopting E2.0 social networks / media technologies. This helped explain perceived usefulness and behavioral intention to use in terms of the cognitive social influence for the instrumental process. Further explanation of these extended determinants can be found in the literature review. Consistent with most typical IT management research, this effort utilized quantitative data analysis methodologies. This research uses e2.0tam to examine the causal relationships associated with the adoption of E2.0 social networks / media technologies. Statement of the Problem The problem this study examined was that the use of E2.0 social networks / media technologies as a transformational force for a company s employee relationships is untapped and workplace acceptance of these new technologies is unknown (McAfee, 2010). This shows a potential gap in literature and an area for workplace improvement. Because of globalization, there has been a move from the way people worked together in the traditional workplace, and toward those who embrace teleworking, collaboration of virtual teamwork, changes in customer and partner relationships, and an increasing presence of project outworkers and consultants (Friedman, 2006). As worker demographics change, the baton must be passed to the next generation. There are 77 million baby boomers born between 1946 and 1964 who are near retirement, and 81 million Generation Y or Millennials, born from 1977 to 1997, who are entering the workforce (Tapscott & Williams, 2008). These young workers are adept at technology and Web 2.0 (Web 2.0) social media, and they expect the same technologies at work that they use in their personal lives, while those exiting have a great deal of intellectual capital 6

20 they could share (Salkowitz, 2008). In addition, many workers are currently active and effective participants in popularized consumer-based Web 2.0, and they expect consumer-based tools to be available in their companies (McAfee, 2010). Consumer social networking application products and services have dramatically been impacted as a result of this shift. Their popularity, as represented in Figure 1, shows the tremendous annual growth rate (May 2009 to May 2010) of regular visitors to the big five social network sites. Figure 2. Gartner Hype Cycle: Emerging Technologies. Emerging technologies offers a snapshot of the relative maturity of technologies, IT methodologies and management disciplines highlighting overhyped areas against those that are high impact while estimating how long technologies and trends will take to reach maturity. This graphic represents Gartner s historical analysis and was published by Gartner, Inc. as part of the larger research document and should be evaluated in the context of the entire document. The Gartner document; Gartner's Hype Cycle Special Report for 2009, J. Fenn, M. Raskino & B. Gammage, 2009; is available upon request from arch Copyright 2009 Gartner, Inc. Adapted with permission. Gartner Fellow Jackie Fenn said, Companies need to establish how to incorporate consumer technologies in a secure and effective manner for employee productivity and also how to transform them into business value for the enterprise (as cited in Pettey & Goasduff, 2006, para. 16). Even though vendors have rushed to 7

21 capitalize on the Web 2.0 social networking phenomenon, with the expectation of encouraging and enhancing business collaboration, many businesses are still struggling with how best to replicate the success of the Web 2.0 consumer and social Web sites within their enterprises (Havenstein, 2007; Lynch, 2009; Taft, 2007). This study was pertinent because, based on Gartner s Hype Cycle (see Figure 2) the emerging technologies coming within next 5 years include the adoption of social software, Web 2.0, and corporate blogging, which are all facets of E2.0, as explained in the literature review. These collaborative technologies dubbed, Web 2.0, have been encapsulated into E2.0 to help move these concepts into enterprise. However, enterprise has many opportunities for change in the face of challenges that should be taken into account to successfully implement social applications and services (Efta, 2012). Oliver Young, a Forrester analyst, believes that successful social computing solutions adoption and deployment are dependent on people s collective embrace, their associations, the way they collaborate, their communication practices, and their business processes (Efta, 2012; Lynch, 2008b). Globalization and outsourcing have exacerbated the situation by requiring the need for virtual teams to collaborate beyond traditional colocations (Carmel, 1999). Studies have identified that trust between virtual teams and well-defined processes positively influence their proficiency and satisfaction (Edwards & Sridhar, 2005). E2.0 social networks / media technologies introduction offers collaborative support for active stakeholder participation (Decker, Ras, Resh, Jaubert, & Rieth, 2007). While enterprise is adopting E2.0 social networks / media technologies, the rate of adoption has been slow 8

22 (Coleman, 2009) and as with any new technology, the adoption and sustainable use has been found to be dependent on its acceptance among those who use it (F. D. Davis, 1989). This research is relevant because it addresses the problem currently facing enterprise leaders. Employing the social networking collaborative at work, while using E2.0 social networks / media technologies, has not been studied in depth in this area, as identified in the comprehensive literature review. While most of the focus of this field has been on external facing or consumer-based social computing (Cha, 2009; Gefen & Straub, 2003; Gefen, Karahanna, & Straub, 2003; Hsu & Lin, 2008; Lin, 2006; Ridings, Gefen & Arinze, 2002; Shin & Kim, 2008) or academia (Baker-Eveleth, Stone & Pendegraft, 2007; Ngai, Poon, & Chan, 2007; Usluel & Mazman, 2009), few address enterprise s internal facing concerns (Lin, 2006; Shen & Eder, 2009), and even fewer focus on internal enterprise concerns (DiMicco et al., 2008). This study focused internally, with emphasis on E2.0 social networks / media technologies adoption while leveraging theories such as TRA and TAM, which are rooted in behavioral science. This research was important because it closes the gap in the literature regarding new technology adoption for a different area of IT that combines IS and Web 2.0 technologies within the business enterprise. Purpose of the Study The study s purpose was to analyze and establish the explanatory and predictive capability of the belief-attitude-intention-behavior relationship combined with the extended TAM for the social networking collaborative while using E2.0 social networks / media technologies. These determinants were primarily obtained using an online survey 9

23 that used e2.0tam, a new extended technology acceptance model. Based on previous studies and as documented in the literature review, the results of this survey could be used by industry to improve the expected user acceptance for technology projects in general and E2.0 social networking collaboration projects in particular. This study added to the body of management knowledge by testing an extended technology acceptance model in industry and helps fill the void in the existing research on industry s E2.0 social networks / media technologies use. Rationale Several studies focused on Web 2.0 and there were significant studies in IT that relate usefulness and ease of use. However, there were no significant studies that analyzed and explained the relationship of perceived trust, perceived usefulness, perceived ease of use, attitude, perceived enjoyment, subjective norms, self-efficacy, facilitating conditions and perceived behavioral control of Web 2.0 within E2.0. The TAM applied these variables to IT cases and the TAM was shown to be an appropriate tool to measure the technology acceptance since it was vetted by testing in both voluntary and mandatory settings (F. D. Davis, 1989; Venkatesh & F. D. Davis, 2000). These studies have been evaluated as part of this study s literature search and methodology assessment. This study s results added the application of the TAM to a different area of IT that combines IS and Web 2.0 technologies within E2.0. Research Question and Model This study attempted to extend the original TAM to identify the determinants associated with an organization s acceptance and usage behavior of E2.0 social networks / media technologies, used for collaboration in enterprise virtual communities, by 10

24 providing an answer to the following research question: Does the e2.0tam increase the explanatory and predictive power of TAM when using E2.0 social networks / media technologies to communicate and interact within organizational social networking communities? Overall, the intent of this research project was to uncover causal relationships or forces (trends) that influence the whole system that can be used to predict a stated outcome. Through the investigation of the determinants previously stated, this research study analyzed and explained the use of the belief-attitude-intention-behavior relationship in enterprise collaboration when adopting E2.0 social networks / media technologies. F. D. Davis et al. (1989) TAM was the basis for the modified model illustrated in Figure 3. Figure 3. Technology Acceptance Model. Based on the research to follow the e2tam model was proposed in Figure 4. Figure 4. Enterprise 2.0 Technology Acceptance Model (e2.0tam) Research Model. 11