Methodological Review: The Technology Acceptance Model: Its past and its future in health care

A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects

Integrating TTF and UTAUT to explain mobile banking user adoption

Understanding information technology acceptance by individual professionals: toward an integrative view

This paper presents a qualitative study on consumer adoption of mobile payments. The findings suggest that the relative advantage of mobile payments is different from that specified in adoption theories and include independence of time and place, availability, possibilities for remote payments, and queue avoidance. Furthermore, the adoption of mobile payments was found to be dynamic, depending on certain situational factors such as a lack of other payment methods or urgency. Several other barriers to adoption were also identified, including premium pricing, complexity, a lack of critical mass, and perceived risks. The findings provide foundation for an enhanced theory on mobile payment adoption and for the practical development of mobile payment services.

/pdf/exploring-consumer-adoption-of-mobile-payments-a-qualitative-200aushzb6.pdf

Exploring consumer adoption of mobile payments - A qualitative study

http://mail.im.tku.edu.tw/~myday/teaching/992/SEC/S/992SEC_T4_Paper_20110520_What%20drives%20mobile%20commerce.pdf

What drives mobile commerce? An empirical evaluation of the revised technology acceptance model

Mobile computing acceptance factors in the healthcare industry: a structural equation model.

Falling in love with online games: The uses and gratifications perspective

The proliferation of mobile communication and computing technologies in supporting highly specialized tasks and services in health care has made it increasingly important to understand the factors essential to technology acceptance by health care professionals. This paper presents a conceptual model to examine what determines medical professionals acceptance of mobile healthcare systems. The structural equation modeling technique was used to evaluate the causal model and confirmatory factor analysis was performed to test the reliability and validity of the measurement model. The results indicate that compatibility and computer self-efficacy (CSE) have significant direct effect on behavioral intent, whereas technical support and training have strong indirect impact on behavioral intent through the mediator of CSE. Among these, the compatibility has the most significant contribution to behavioral intent. Yet, the hypothesis for management support effect on behavioral intention to use is not supported.

/pdf/what-drives-mobile-health-care-an-empirical-evaluation-of-30iuwa6b1d.pdf

Shu-Ching Wang

Papers

What drives mobile commerce? An empirical evaluation of the revised technology acceptance model

Mobile computing acceptance factors in the healthcare industry: a structural equation model.

Falling in love with online games: The uses and gratifications perspective

What Drives Mobile Health Care? An Empirical Evaluation of Technology Acceptance

Proactive privacy practices in transition: Toward ubiquitous services