Moderating effects of Job Relevance and Experience on mobile wireless technology acceptance: Adoption of a smartphone by individuals

My study extended TAM to include individuals' intention to use mobile wireless technology (MWT). It added two new constructs, Perceived Cost Savings and Company's Willingness to Fund, and two causal relationships, Job Relevance and Experience, as moderating effects. The 286 sets of data collected in an online survey were tested against the model using SEM. Results supported my new model: the new constructs and variables accounted for 62.7% of the variance found in an individual's behavioral intention to use MWT. The path coefficients between the constructs ranged from 0.26 to 0.85 also supporting the model.

[1]  A. Parasuraman,et al.  Technology Readiness Index (Tri) , 2000 .

[2]  Thompson S. H. Teo,et al.  Intrinsic and extrinsic motivation in Internet usage , 1999 .

[3]  Per E. Pedersen,et al.  Adoption of Mobile Internet Services: An Exploratory Study of Mobile Commerce Early Adopters , 2005, J. Organ. Comput. Electron. Commer..

[4]  Anol Bhattacherjee,et al.  Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model , 2006, MIS Q..

[5]  M.H.P. Kleijnen,et al.  Consumer acceptance of wireless finance , 2004 .

[6]  P. A. Dabholkar Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality , 1996 .

[7]  Izak Benbasat,et al.  Electronic Data Interchange and Small Organizations: Adoption and Impact of Technology , 1995, MIS Q..

[8]  Y. Iwasaki,et al.  Examining Rival Models of Leisure Coping Mechanisms , 2003 .

[9]  Terry Anthony Byrd,et al.  PDA usage in healthcare professionals: testing an extended technology acceptance model , 2003, Int. J. Mob. Commun..

[10]  E. Carmines,et al.  Analyzing models with unobserved variables: analysis of covariance structures , 1981 .

[11]  Mun Y. Yi,et al.  Understanding information technology acceptance by individual professionals: Toward an integrative view , 2006, Inf. Manag..

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

[13]  D. Leonard-Barton,et al.  Managerial influence in the implementation of new technology , 1988 .

[14]  Vincent S. Lai,et al.  Prediction of Internet and World Wide Web usage at work: a test of an extended Triandis model , 2000, Decis. Support Syst..

[15]  S. Howard,et al.  A Field Study of Perceptions and Use of Mobile Telephones by 16 to 22 Year Olds , 2002 .

[16]  Jen-Her Wu,et al.  What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model , 2005, Inf. Manag..

[17]  Leysia Palen,et al.  Mobile telephony in a connected life , 2002, CACM.

[18]  M. Browne,et al.  Alternative Ways of Assessing Model Fit , 1992 .

[19]  Dennis F. Galletta,et al.  A model of end-user computing policy: Context, process, content and compliance , 1992, Inf. Manag..

[20]  Dale Goodhue,et al.  Understanding user evaluations of information systems , 1995 .

[21]  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.

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

[23]  E. Rogers,et al.  Diffusion of Innovations , 1964 .

[24]  Patrick Y. K. Chau,et al.  An Empirical Assessment of a Modified Technology Acceptance Model , 1996, J. Manag. Inf. Syst..

[25]  James E. Yao,et al.  Exploring Factors Associated with Wireless Internet via Mobile Technology Acceptance in Mainland China , 2014, Communications of the IIMA.