Understanding the Adoption of Smart Wearable Devices to Assist Healthcare in China

With the development and advancement of information communication technology, smart wearable devices are playing a more and more important role in peoples’ daily lives. This study aims to investigate the adoption of smart wearable devices to assist healthcare in China. Based on the previous technology diffusion theories (e.g., TAM, IDT), a research model with ten research hypotheses was proposed in this research. The research model was empirically tested with a sample of 180 users of smart wearable devices in China. The results indicated that seven of the ten research hypotheses were significantly supported. The most significant determinant for users’ attitude towards smart wearable devices was trust. However, personal characteristics did not have a significant positive impact on both users’ attitude and behavior intention to use smart wearable devices.

[1]  Naresh K. Malhotra,et al.  Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research , 2006, Manag. Sci..

[2]  Robin Wright,et al.  Wearable Technology: If the Tech Fits, Wear It , 2014 .

[3]  Hans van der Heijden,et al.  Factors influencing the usage of websites: the case of a generic portal in The Netherlands , 2003, Inf. Manag..

[4]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[5]  Jacob Paroush,et al.  Economic aspects of diffusion models , 1982 .

[6]  Jan Marco Leimeister,et al.  Reaching into patients’ homes – participatory designed AAL services , 2011, Electron. Mark..

[7]  Keng Siau,et al.  Developing an instrument to measure the adoption of mobile services , 2011 .

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

[9]  John Krogstie,et al.  The Effect of Flow Experience and Social Norms on the Adoption of Mobile Games in China , 2016, Int. J. Mob. Hum. Comput. Interact..

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

[11]  Jean-Yves Fourniols,et al.  Smart wearable systems: Current status and future challenges , 2012, Artif. Intell. Medicine.

[12]  Paul A. Pavlou,et al.  Predicting E-Services Adoption: A Perceived Risk Facets Perspective , 2002, Int. J. Hum. Comput. Stud..

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

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

[15]  John P. Robinson,et al.  CHAPTER 1 – Criteria for Scale Selection and Evaluation , 1991 .

[16]  Venkatesh,et al.  A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes. , 2000, Organizational behavior and human decision processes.

[17]  Richard A. Johnson,et al.  Applying the Technology Acceptance Model to the WWW , 2000 .

[18]  Keng Siau,et al.  Adoption of mobile information services: An empirical study , 2014, Mob. Inf. Syst..

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

[20]  J. Wareham,et al.  A Smart City Initiative: the Case of Barcelona , 2012, Journal of the Knowledge Economy.

[21]  Naveen Donthu,et al.  The Internet Shopper , 1999 .

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

[23]  Yiwen Gao,et al.  An empirical study of wearable technology acceptance in healthcare , 2015, Ind. Manag. Data Syst..

[24]  Shang Gao,et al.  An empirical examination of users’ adoption of mobile advertising in China , 2016 .

[25]  John Krogstie,et al.  Lifestyles and Mobile Services Adoption in China , 2014, Int. J. E Bus. Res..

[26]  Richard P. Bagozzi,et al.  Specification, evaluation, and interpretation of structural equation models , 2012 .

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

[28]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[29]  John Krogstie,et al.  The Adoption of Smartphones Among Older Adults in China , 2015, ICISO.

[30]  Dong-Hee Shin,et al.  An acceptance model for smart watches: Implications for the adoption of future wearable technology , 2015, Internet Res..

[31]  J. Kolodinsky,et al.  The adoption of electronic banking technologies by US consumers , 2004 .

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

[33]  Paul A. Pavlou,et al.  Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model , 2003, Int. J. Electron. Commer..

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

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

[36]  David Gefen,et al.  TAM or Just Plain Habit: A Look at Experienced Online Shoppers , 2003, J. Organ. End User Comput..