Nonadopters of Online Social Network Services: Is It Easy to Have Fun Yet?

Although online social network services (OSNS), e.g., Facebook, Twitter, MySpace, LinkedIn, are enjoying rampant popularity, a subsection of the population (i.e., nonadopters) continues to forgo using them. Our study is one of the first to focus exclusively on what might motivate nonadopters to accept a widely adopted IT. By considering nonadopters’ inertia within the context of early stages of innovation diffusion and incorporating status quo bias theory into well-established technology acceptance model (TAM) relationships, this study uncovers the finding that people who report that they do not use OSNS would use them if they thought OSNS were easier and more enjoyable to use, and if they were persuaded by others to use them. Our findings suggest these nonadopters do not see the usefulness of OSNS, risks of sharing personal information publically, or the perceived amount of effort in using OSNS as factors that influence potential acceptance and use of the technology. This study contributes to research by offering an integrated theoretical framework that updates TAM with status quo bias theory to study nonadopters and offers IS practice guidelines for OSNS providers to attract nonadopters to accept and use the technology.

[1]  P. M. Podsakoff,et al.  Self-Reports in Organizational Research: Problems and Prospects , 1986 .

[2]  J. Brown,et al.  Knowledge and Organization: A Social-Practice Perspective , 2001 .

[3]  S. Ram A Model of Innovation Resistance , 1987 .

[4]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[5]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[6]  Detmar W. Straub,et al.  Structural Equation Modeling and Regression: Guidelines for Research Practice , 2000, Commun. Assoc. Inf. Syst..

[7]  A. Lenhart,et al.  Teens, privacy and online social networks: How teens manage their online identities and personal information in the age of MySpace , 2007 .

[8]  Elena Karahanna,et al.  Reconceptualizing Compatability Beliefs in Technology Acceptance Research , 2006, MIS Q..

[9]  Laku Chidambaram,et al.  A test of the technology acceptance model: the case of cellular telephone adoption , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[10]  Wynne W. Chin The partial least squares approach for structural equation modeling. , 1998 .

[11]  Detmar W. Straub,et al.  Trust and TAM in Online Shopping: An Integrated Model , 2003, MIS Q..

[12]  Atreyi Kankanhalli,et al.  Investigating user resistance to information systems implementation: a status quo bias perspective , 2009 .

[13]  Susan Folkman,et al.  Making the case for coping. , 1992 .

[14]  Tao Hu,et al.  Why People Continue to Use Social Networking Services: Developing a Comprehensive Model , 2008, ICIS.

[15]  Viswanath Venkatesh,et al.  User acceptance of information technology : a unified view , 1998 .

[16]  Tamara Dinev,et al.  An Extended Privacy Calculus Model for E-Commerce Transactions , 2006, Inf. Syst. Res..

[17]  Per E. Pedersen,et al.  Explaining intention to use mobile chat services: moderating effects of gender , 2005 .

[18]  Richard,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace , 2022 .

[19]  S. Deshpande,et al.  Task Characteristics and the Experience of Optimal Flow in Human—Computer Interaction , 1994 .

[20]  Detmar W. Straub,et al.  Validating Instruments in MIS Research , 1989, MIS Q..

[21]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[22]  S. Ram,et al.  Consumer Resistance to Innovations: The Marketing Problem and its solutions , 1989 .

[23]  S. Ghoshal,et al.  Social Capital, Intellectual Capital, and the Organizational Advantage , 1998 .

[24]  Hans van der Heijden,et al.  User Acceptance of Hedonic Information Systems , 2004, MIS Q..

[25]  Houston H. Carr,et al.  Threats to Information Systems: Today's Reality, Yesterday's Understanding , 1992, MIS Q..

[26]  Danah Boyd,et al.  Social Network Sites: Definition, History, and Scholarship , 2007, J. Comput. Mediat. Commun..

[27]  Heshan Sun,et al.  Causal Relationships between Perceived Enjoyment and Perceived Ease of Use: An Alternative Approach , 2006, J. Assoc. Inf. Syst..

[28]  E. Hirschman,et al.  Hedonic Consumption: Emerging Concepts, Methods and Propositions , 1982 .

[29]  Corey M. Angst,et al.  Reconceptualizing Compatibility Beliefs in Technology Acceptance , 2006 .

[30]  Anne Beaudry,et al.  Understanding User Responses to Information Technology: A Coping Model of User Adaption , 2005, MIS Q..

[31]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[32]  Detmar W. Straub,et al.  A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And Annotated Example , 2005, Commun. Assoc. Inf. Syst..

[33]  Fiona Fui-Hoon Nah,et al.  UNDERSTANDING ATTRIBUTES OF HIGHLY COMPETENT INFORMATION SYSTEM USERS: A QUALITATIVE APPROACH , 2007 .

[34]  Terry L. Childers,et al.  HEDONIC AND UTILITARIAN MOTIVATIONS FOR ONLINE RETAIL SHOPPING BEHAVIOR , 2001 .

[35]  William Samuelson,et al.  Status quo bias in decision making , 1988 .

[36]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[37]  Anne P. Massey,et al.  Usability of Online Services: The Role of Technology Readiness and Context , 2007, Decis. Sci..

[38]  E. Hirschman,et al.  The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun , 1982 .

[39]  Elena Karahanna,et al.  Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage , 2000, MIS Q..

[40]  Andrew B. Whinston,et al.  Research Issues in Social computing , 2007, J. Assoc. Inf. Syst..

[41]  S. O'Donohoe,et al.  Groundswell: Winning in a World Transformed by Social Technologies , 2008 .

[42]  Elena Karahanna,et al.  Reconceptualizing Compatibility Beliefs , 2006 .

[43]  Albert L. Lederer,et al.  A Meta-Analysis of the Role of Environment-Based Voluntariness in Information Technology Acceptance , 2009, MIS Q..

[44]  Hsiu-Fen Lin,et al.  Antecedents of Virtual Community Satisfaction and Loyalty: An Empirical Test of Competing Theories , 2008, Cyberpsychology Behav. Soc. Netw..

[45]  Gilbert A. Churchill A Paradigm for Developing Better Measures of Marketing Constructs , 1979 .

[46]  Ellen Weave,et al.  Groundswell: Winning in a World Transformed by Social Technologies , 2010 .

[47]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[48]  Atreyi Kankanhalli,et al.  Contributing Knowledge to Electronic Knowledge Repositories: An Empirical Investigation , 2005, MIS Q..

[49]  S. Folkman,et al.  Stress, appraisal, and coping , 1974 .

[50]  D. DavisFred,et al.  User Acceptance of Computer Technology , 1989 .

[51]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[52]  Viswanath Venkatesh,et al.  Technology Acceptance Model 3 and a Research Agenda on Interventions , 2008, Decis. Sci..

[53]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

[54]  Detmar W. Straub,et al.  Validation in Information Systems Research: A State-of-the-Art Assessment , 2001, MIS Q..

[55]  J. Moskowitz,et al.  Positive affect and the other side of coping. , 2000, The American psychologist.

[56]  Ravi Thambusamy,et al.  Socially Exchanging Privacy for Pleasure: hedonic Use of Computer-Mediated Social Networks , 2010, ICIS.

[57]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[58]  Elena Karahanna,et al.  Shackled to the Status Quo: The Inhibiting Effects of Incumbent System Habit, Switching Costs, and Inertia on New System Acceptance , 2012, MIS Q..

[59]  Detmar W. Straub,et al.  Validation Guidelines for IS Positivist Research , 2004, Commun. Assoc. Inf. Syst..

[60]  Wynne W. Chin,et al.  A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic - Mail Emotion/Adoption Study , 2003, Inf. Syst. Res..

[61]  Fred D. Davis,et al.  Dead Or Alive? The Development, Trajectory And Future Of Technology Adoption Research , 2007, J. Assoc. Inf. Syst..

[62]  Fred D. Davis,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1 , 1992 .

[63]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[64]  Thomas F. Stafford,et al.  Determining Uses and Gratifications for the Internet , 2004, Decis. Sci..

[65]  E. Rogers,et al.  Diffusion of Innovations, 5th Edition , 2003 .

[66]  Eric Abrahamson Managerial Fads and Fashions: The Diffusion and Rejection of Innovations , 1991 .

[67]  Kenneth P. Uhl,et al.  How Are Laggards Different? An Empirical Inquiry , 1970 .

[68]  Sung S. Kim,et al.  Out of Dedication or Constraint? A Dual Model of Post-Adoption Phenomena and its Empirical Test in the Context of Online Services , 2009, MIS Q..

[69]  David Gefen,et al.  Structural Equation Modeling Techniques and Regression: Guidelines for Research Practice , 2000 .

[70]  Young-Gul Kim,et al.  Extending the TAM for a World-Wide-Web context , 2000, Inf. Manag..

[71]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[72]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[73]  Rhoda C. Joseph To Adopt or Not to Adopt - That is the Question , 2005, AMCIS.

[74]  Paul A. Pavlou,et al.  Understanding and Mitigating Uncertainty in Online Exchange Relationships: A Principal-Agent Perspective , 2007, MIS Q..

[75]  Christine T. Kydd,et al.  Individual characteristics associated with World Wide Web use: an empirical study of playfulness and motivation , 1997, DATB.