Information technology adoption and continuance: A longitudinal study of individuals' behavioral intentions

Extant research on information technology (IT) adoption and continuance has not adequately modeled the times of adoption by individuals. This study argues that individuals adopt an innovation at different times and are likely to be influenced by different factors over time. The theoretical models are empirically validated using data gathered at three points in time through surveys of 132 users of a new innovation. The results indicate that the innovation attributes and individual characteristics influence individuals' intentions to adopt the innovation during the early stage, and the innovation attributes and contextual factors impact the individuals' intentions during the later stage.

[1]  Kai Lung Hui,et al.  Identifying early adopters of new IT products: A case of Windows 95 , 1998, Inf. Manag..

[2]  F. Bass.  A new product growth model for consumer durables , 1976 .

[3]  Charles Chowa,et al.  Information System Success: Individual and Organizational Determinants , 2006, Manag. Sci..

[4]  Frank M. Bass,et al.  A New Product Growth for Model Consumer Durables , 2004, Manag. Sci..

[5]  O. Kwon,et al.  User acceptance of context-aware services: self-efficacy, user innovativeness and perceived sensitivity on contextual pressure , 2007, Behav. Inf. Technol..

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

[7]  Yuan Sun,et al.  Extending technology usage to work settings: The role of perceived work compatibility in ERP implementation , 2009, Inf. Manag..

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

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

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

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

[12]  L. G. Tornatzky,et al.  Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings , 1982, IEEE Transactions on Engineering Management.

[13]  I. Ajzen.  The theory of planned behavior , 1991 .

[14]  이훈,et al.  지각된 유용성(Perceived Usefulness)의 영향분석 , 2004 .

[15]  Manju K. Ahuja,et al.  Early and Late Adopters of IT Innovations: Extensions to Innovation Diffusion Theory , 1998 .

[16]  Jijie Wang,et al.  Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT , 2007, Inf. Manag..

[17]  Rolph E. Anderson,et al.  Multivariate Data Analysis: Text and Readings , 1979 .

[18]  Shih-Chieh Fang,et al.  Early versus potential adopters: Exploring the antecedents of use intention in the context of retail service innovations , 2010 .

[19]  Paul Jen-Hwa Hu,et al.  Examining technology acceptance by school teachers: a longitudinal study , 2003, Inf. Manag..

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

[21]  Younghwa Lee,et al.  The Technology Acceptance Model: Past, Present, and Future , 2003, Commun. Assoc. Inf. Syst..

[22]  James C. Wetherbe,et al.  The Adoption of Spreadsheet Software: Testing Innovation Diffusion Theory in the Context of End-User Computing , 1990, Inf. Syst. Res..

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

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

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

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

[27]  R. Rosenfeld.  Belief , 2012, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[28]  Ritu Agarwal,et al.  A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology , 1998, Inf. Syst. Res..

[29]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[30]  Тараса Шевченка,et al.  Quo vadis? , 2013, Clinical chemistry.

[31]  J. Nunnally.  Psychometric Theory (2nd ed), New York: McGraw-Hill. , 1978 .

[32]  R. Burt.  Social Contagion and Innovation: Cohesion versus Structural Equivalence , 1987, American Journal of Sociology.

[33]  Gordon B. Davis,et al.  Testing the Determinants of Microcomputer Usage via a Structural Equation Model , 1995, J. Manag. Inf. Syst..

[34]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.