Understanding the continuance use of social network sites: a computer self-efficacy perspective

Based on social cognitive theory and the balanced thinking–feelings model, this study proposes a research model to examine the different roles of general computer self-efficacy (CSE) and specific CSE. The research model was tested with a survey of university students in Singapore in the Facebook context. It is found that while general CSE affects continuance intention through both cognition and affection, specific CSE mainly affects continuance intention through cognition. It is also found that general computer experience affects general CSE only and specific computer experience affects specific CSE only.

[1]  Xianggui Qu,et al.  Multivariate Data Analysis , 2007, Technometrics.

[2]  Marilyn E. Gist,et al.  Self-Efficacy: A Theoretical Analysis of Its Determinants and Malleability , 1992 .

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

[4]  T. Busch Gender Differences in Self-Efficacy and Attitudes toward Computers , 1995 .

[5]  Shahriar Akter,et al.  Modelling the impact of mHealth service quality on satisfaction, continuance and quality of life , 2013 .

[6]  Muris Cicic,et al.  Understanding determinants of information systems users’ behaviour: a comparison of two models in the context of integrated accounting and budgeting software , 2013 .

[7]  Chao-Min Chiu,et al.  Predicting electronic service continuance with a decomposed theory of planned behaviour , 2004, Behav. Inf. Technol..

[8]  Bassam Hasan,et al.  Delineating the effects of general and system-specific computer self-efficacy beliefs on IS acceptance , 2006, Inf. Manag..

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

[10]  William R. King,et al.  A meta-analysis of the technology acceptance model , 2006, Inf. Manag..

[11]  Deborah Compeau,et al.  Computer Self-Efficacy: Development of a Measure and Initial Test , 1995, MIS Q..

[12]  R. Reisenzein Pleasure-Arousal Theory and the Intensity of Emotions , 1994 .

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

[14]  Nancy E. Betz,et al.  The Relationship of Career-Related Self-Efficacy Expectations to Perceived Career Options in College Women and Men. , 1981 .

[15]  R. Oliver,et al.  Assessing the Dimensionality and Structure of the Consumption Experience: Evaluation, Feeling, and Satisfaction , 1993 .

[16]  A. Bandura Self-efficacy mechanism in human agency , 2024, Psihologìâ ì suspìlʹstvo.

[17]  A. Bandura Social Foundations of Thought and Action: A Social Cognitive Theory , 1985 .

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

[19]  R. W. Stone,et al.  Computer self-efficacy and outcome expectancy: the effects on the end-user's job satisfaction , 1995, CPRS.

[20]  Izak Benbasat,et al.  Quo vadis TAM? , 2007, J. Assoc. Inf. Syst..

[21]  Moez Limayem,et al.  Predicting the continued use of Internet-based learning technologies: the role of habit , 2011, Behav. Inf. Technol..

[22]  Deborah Compeau,et al.  Application of Social Cognitive Theory to Training for Computer Skills , 1995, Inf. Syst. Res..

[23]  Heshan Sun,et al.  A Longitudinal Study of Herd Behavior in the Adoption and Continued Use of Technology , 2013, MIS Q..

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

[25]  Anol Bhattacherjee,et al.  Understanding Post-Adoption Behavior in the Context of Online Services , 1998, Inf. Syst. Res..

[26]  Jeung-tai Eddie Tang,et al.  Blog learning: effects of users' usefulness and efficiency towards continuance intention , 2014, Behav. Inf. Technol..

[27]  R. Lazarus Emotion and Adaptation , 1991 .

[28]  Hsi-Peng Lu,et al.  Experience differences and continuance intention of blog sharing , 2012, Behav. Inf. Technol..

[29]  Ya-Yueh Shih,et al.  The effect of computer self-efficacy on enterprise resource planning usage , 2006, Behav. Inf. Technol..

[30]  Chia-Chi Chang,et al.  Effects of individuals' locus of control and computer self-efficacy on their e-learning acceptance in high-tech companies , 2014, Behav. Inf. Technol..

[31]  B. Whitley Gender Differences in Computer-Related Attitudes and Behavior: A Meta-Analysis , 1997 .

[32]  Richard D. Johnson,et al.  The Evolving Nature of the Computer Self-Efficacy Construct: An Empirical Investigation of Measurement Construction, Validity, Reliability and Stability Over Time , 2007, J. Assoc. Inf. Syst..

[33]  W. Mischel,et al.  A cognitive-affective system theory of personality: reconceptualizing situations, dispositions, dynamics, and invariance in personality structure. , 1995, Psychological review.

[34]  Anne Beaudry,et al.  The Other Side of Acceptance: Studying the Direct and Indirect Effects of Emotions on Information Technology Use , 2010, MIS Q..

[35]  Chao-Min Chiu,et al.  Understanding e-learning continuance intention: An extension of the Technology Acceptance Model , 2006, Int. J. Hum. Comput. Stud..

[36]  J. Solomon,et al.  On the other side. , 1996, RN.

[37]  James T. C. Teng,et al.  Extended conceptualisation of perceived usefulness: empirical test in the context of information system use continuance , 2012, Behav. Inf. Technol..

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

[39]  Marilyn E. Gist,et al.  EFFECTS OF ALTERNATIVE TRAINING METHODS ON SELF-EFFICACY AND PERFORMANCE IN COMPUTER SOFTWARE TRAINING , 1989 .

[40]  Catherine Dwyer,et al.  Task Technology Fit, The Social Technical Gap and Social Networking Sites , 2007, AMCIS.

[41]  R. W. Stone,et al.  A Structural Equation Model Of End-User Satisfaction With A Computer-Based Medical Information System , 1994 .

[42]  Chao-Min Chiu,et al.  Internet self-efficacy and electronic service acceptance , 2004, Decis. Support Syst..

[43]  Hui-Tzu Min,et al.  Understanding continuance intention of knowledge creation using extended expectation–confirmation theory: an empirical study of Taiwan and China online communities , 2010, Behav. Inf. Technol..

[44]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[45]  Venkateshviswanath,et al.  A Theoretical Extension of the Technology Acceptance Model , 2000 .

[46]  M. Csíkszentmihályi Beyond boredom and anxiety , 1975 .

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

[48]  Matthew K. O. Lee,et al.  Predicting continuance in online communities: model development and empirical test , 2010, Behav. Inf. Technol..

[49]  Richard D. Johnson,et al.  The Multilevel and Multifaceted Character of Computer Self-Efficacy: Toward Clarification of the Construct and an Integrative Framework for Research , 1998, Inf. Syst. Res..

[50]  A. Bandura Self-efficacy: toward a unifying theory of behavioral change. , 1977, Psychological review.

[51]  R. Kelly Rainer,et al.  Explicating Computer Self-Efficacy Relationships: Generality and the Overstated Case of Specificity Matching , 2008, J. Organ. End User Comput..

[52]  D. Cicchetti Emotion and Adaptation , 1993 .

[53]  Magid Igbaria,et al.  The effects of self-efficacy on computer usage , 1995 .

[54]  Kar Yan Tam,et al.  The Effects of Post-Adoption Beliefs on the Expectation-Confirmation Model for Information Technology Continuance , 2006, Int. J. Hum. Comput. Stud..

[55]  Wen-Lung Shiau,et al.  Continuance intention of blog users: the impact of perceived enjoyment, habit, user involvement and blogging time , 2013, Behav. Inf. Technol..

[56]  Saeid Nahavandi,et al.  The impact of self-efficacy and perceived system efficacy on effectiveness of virtual training systems , 2014, Behav. Inf. Technol..

[57]  Nian-Shing Chen,et al.  Understanding e-learning continuance intention: a negative critical incidents perspective , 2011, Behav. Inf. Technol..

[58]  J. Russell A circumplex model of affect. , 1980 .

[59]  Mark E. McMurtrey,et al.  Introducing task-based general computer self-efficacy: An empirical comparison of three general self-efficacy instruments , 2007, Interact. Comput..

[60]  Chin-Chung Tsai,et al.  Information searching strategies in web-based science learning: the role of internet self-efficacy , 2003 .

[61]  Qingxiong Ma,et al.  The Role of Internet Self-Efficacy in the Acceptance of Web-Based Electronic Medical Records , 2005, J. Organ. End User Comput..

[62]  Songpol Kulviwat,et al.  The Role of Self-Efficacy in Predicting Technology Acceptance , 2015 .

[63]  Joseph J. Martocchio,et al.  Microcomputer playfulness: development of a measure with workplace implications , 1992 .

[64]  Dennis L. Hoffman,et al.  Marketing in Hypermedia Computer-Mediated Environments : Conceptual Foundations 1 ) , 1998 .

[65]  Marko Sarstedt,et al.  PLS-SEM: Indeed a Silver Bullet , 2011 .

[66]  Hee-Woong Kim,et al.  A balanced thinking-feelings model of information systems continuance , 2007, Int. J. Hum. Comput. Stud..

[67]  Robert E. Umbaugh AUBREY G. CHERNICK , 1992 .

[68]  Petter Bae Brandtzæg,et al.  User loyalty and online communities: why members of online communities are not faithful , 2008, INTETAIN '08.

[69]  R. Frank Falk,et al.  A Primer for Soft Modeling , 1992 .

[70]  Mun Y. Yi,et al.  Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model , 2003, Int. J. Hum. Comput. Stud..

[71]  Terence A. Oliva,et al.  Play as a Consumption Experience: The Roles of Emotions, Performance, and Personality in the Enjoyment of Games , 1984 .

[72]  Fred D. Davis,et al.  Modeling the Determinants of Perceived Ease of Use , 1994, ICIS.

[73]  Thomas Hill,et al.  Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers. , 1987 .

[74]  Tao Zhou,et al.  An empirical examination of users' post-adoption behaviour of mobile services , 2011, Behav. Inf. Technol..

[75]  Yi-Fen Chen,et al.  See you on Facebook: exploring influences on Facebook continuous usage , 2014, Behav. Inf. Technol..

[76]  J. Rossiter,et al.  Store atmosphere: an environmental psychology approach , 1982 .

[77]  Deanna S. Kempf Attitude formation from product trial: Distinct roles of cognition and affect for hedonic and functional products , 1999 .

[78]  A. Bandura Self-Efficacy: The Exercise of Control , 1997, Journal of Cognitive Psychotherapy.

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

[80]  R. Kelly Rainer,et al.  The Influence of Individual Differences on Skill in End-User Computing , 1992, J. Manag. Inf. Syst..

[81]  Barbara S. Chaparro,et al.  Trick or Tweet: How Usable is Twitter for First-Time Users? , 2009 .

[82]  Vallabh Sambamurthy,et al.  Research Report: The Evolving Relationship Between General and Specific Computer Self-Efficacy - An Empirical Assessment , 2000, Inf. Syst. Res..

[83]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[84]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

[85]  Kar Yan Tam,et al.  Understanding Continued Information Technology Usage Behavior: A Comparison of Three Models in the Context of Mobile Internet , 2006, Decis. Support Syst..