An analysis of key factors affecting user acceptance of mobile payment

This paper aims to investigate the theoretical constructs involved in technological influence processes and cognitive influence processes and their influence on the acceptance of innovation especially in the mobile payment services context. We build the research model, referred to as the Mobile Payment Services Technology Acceptance Model (MPSTAM), based on an integration of Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), and Innovation Diffusion Theory (IDT). A questionnaire research is conducted to collect data and the structural equation modeling technique is used to evaluate the research model. Our findings show that (1) perceived usefulness, personal innovativeness and compatibility has direct positive influence on users' attitude towards this service, and compatibility is the most influential factors among the three; (2) perceived ease of use indirectly influences attitude by affecting perceived usefulness; (3) opportunity cost and perceived risks have direct negative effect on the acceptance of the service.

[1]  I. Ajzen,et al.  Intention, perceived control, and weight loss: an application of the theory of planned behavior. , 1985, Journal of personality and social psychology.

[2]  M. Fishbein An Investigation of the Relationships between Beliefs about an Object and the Attitude toward that Object , 1963 .

[3]  Dr. Hsin Kuang Chi,et al.  Applying Theory of Reasoned Action and Technology Acceptance Model to Investigate Purchase Behavior on Smartphone , 2011 .

[4]  Princely Ifinedo,et al.  Understanding information systems security policy compliance: An integration of the theory of planned behavior and the protection motivation theory , 2012, Comput. Secur..

[5]  Calum G. Turvey,et al.  Credit Risk Assessment and the Opportunity Costs of Loan Misclassification , 1997 .

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

[7]  Byoungsoo Kim,et al.  An empirical investigation of mobile data service continuance: Incorporating the theory of planned behavior into the expectation-confirmation model , 2010, Expert Syst. Appl..

[8]  Shin-Yuan Hung,et al.  Critical factors of WAP services adoption: an empirical study , 2003, Electron. Commer. Res. Appl..

[9]  Marianne Bradford,et al.  Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems , 2003, Int. J. Account. Inf. Syst..

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

[11]  A. Khalili,et al.  Gender differences in emotional intelligence among employees of small and medium enterprise: an empirical study , 2011 .

[12]  Ankit Kesharwani,et al.  The impact of trust and perceived risk on internet banking adoption in India : An extension of technology acceptance model , 2022 .

[13]  Geoffrey S. Hubona,et al.  The effects of gender and age on new technology implementation in a developing country: Testing the theory of planned behavior (TPB) , 2007, Inf. Technol. People.

[14]  John S. Gero,et al.  Computational Explorations of Compatibility and Innovation , 2007, IFIP CAI.

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

[16]  Su-Chao Chang,et al.  An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry , 2008, Int. J. Medical Informatics.

[17]  Thiagarajan Ravichandran,et al.  How to anticipate the Internet's global diffusion , 1998, CACM.

[18]  Dessislava A. Pachamanova,et al.  Back-propagation of user innovations: The open source compatibility edge , 2007 .

[19]  Kiseol Yang Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior , 2012 .

[20]  Abdelghani Echchabi Journal of Internet Banking and Commerce Online Banking Prospects in Morocco: an Extension of Technology Acceptance Model , 2022 .

[21]  Tao Zhou,et al.  Exploring Chinese users' acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory , 2009, Comput. Hum. Behav..

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