Adoption of public WiFi using UTAUT2: An exploration in an emerging economy

Abstract The dependence on information technology has evidently increased over the past decade. With the increased internet use and the need for accessing information on the go, the use of wireless internet has also been on the higher side. This need for always staying connected to the web has opened avenues for the usage of public internet services. The current study thus investigates the adoption of these public WiFi by the consumers. The study adopts the conceptual model of UTAUT2 which uses various variables to explain the acceptance of technology. The analysis uses the data procured from 257 respondents through a structured questionnaire which collects data surrounding model variables along with the demographics of the users. Variables including Facilitating Condition, Performance Expectancy, Effort Expectancy, Social Influence, Hedonic Motivation, Trust, Individual Characteristics, Business Intention and Usage are considered to be influencing the acceptance of public WiFi technology. The statistical analysis of the responses has been done by conducting tests on reliability and validity. The regression analysis and path analysis lead to the findings which may be useful by various stakeholders for decision making surrounding the promotion of their services in the sector.

[1]  N. Selwyn Digital division or digital decision? A study of non-users and low-users of computers , 2006 .

[2]  Joseph S. Valacich,et al.  Technology Adoption by Groups: A Valence Perspective , 2005, J. Assoc. Inf. Syst..

[3]  Chang Liu,et al.  Technology acceptance model for wireless Internet , 2003, Internet Res..

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

[5]  Joseph S. Valacich,et al.  An Alternative to Methodological Individualism: A Non-Reductionist Approach to Studying Technology Adoption by Groups , 2010, MIS Q..

[6]  Arpan Kumar Kar,et al.  Critical Success Factors to Establish 5G Network in Smart Cities: Inputs for Security and Privacy , 2017, J. Glob. Inf. Manag..

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

[8]  John D. Villasenor,et al.  Bringing the Wireless Internet to Mobile Devices , 2001, Computer.

[9]  Naveen Donthu,et al.  Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics , 2006 .

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

[11]  June Lu,et al.  Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology , 2005, J. Strateg. Inf. Syst..

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

[13]  R. Rice,et al.  Comparing internet and mobile phone usage: digital divides of usage, adoption, and dropouts , 2003 .

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

[15]  J. Cooper,et al.  The digital divide: the special case of gender , 2006, J. Comput. Assist. Learn..

[16]  Blair H. Sheppard,et al.  The Theory of Reasoned Action: A Meta-Analysis of Past Research with Recommendations for Modifications and Future Research , 1988 .

[17]  A. Bandura Human agency in social cognitive theory. , 1989, The American psychologist.

[18]  Matthew K. O. Lee,et al.  Information Instruments for Creating Awareness in IT Innovations: An Exploratory Study of Organizational Adoption Intentions of ValuNet , 2001, Electron. Mark..

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