South Asian Journal of Management

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Mobile Wallet Adoption in India:Impact of Trust and Information Sharing


Affiliations
1 Rajagiri Business School, Rajagiri Valley, Kochi 682039, Kerala, India
     

   Subscribe/Renew Journal


This paper aims to explore how trust and information sharing influence consumer intention to use mobile wallets for making payments. An extended technology acceptance model incorporating the constructs is empirically tested through an online survey involving a vignette using the mobile wallet. Structural equation modeling using partial least squares approach has been performed to analyze the data collected from the survey conducted among 240 postgraduate students of a university in Kerala, who represent the tech savvy young population, using a structured questionnaire. Though the importance of perceived usefulness and perceived ease of use is validated, the results of the study provide conclusive evidence that trust is a stronger driver of mobile wallet adoption, suggesting the need to build consumer trust to drive mobile wallet adoption. The study also confirms the positive influence of trust on consumer willingness to share information which is crucial for co-creation of service.

Keywords

Information Sharing, Mobile Wallet, Perceived Ease of Use, Perceived Usefulness, Trust.
User
Subscription Login to verify subscription
Notifications
Font Size

  • Andreev, P., Duane, A., & O’Reilly, P. (2011). Conceptualizing Consumer Perceptions of Making M-Payments Using Smart Phones in Ireland. In Chiasson M., Henfridsson O., Karsten H., & DeGross, J. I. (Eds.). Researching the Future in Information Systems. IFIP Advances in Information and Communication Technology (109-12). Berlin, Heidelberg: Springer.

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.

  • Chan, K. W., Kin, C. Y., & Lam, S. S. K. (2010). Is customer participation in value creation a double-edged sword? Evidence from professional financial services across cultures. Journal of Marketing, 74(3), 48-64.

  • Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14, 189-217.

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35, 982-1003.

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to use Computers in the Workplace. Journal of Applied Social Psychology, 22, 1111-1132.

  • Dillon, A., & Morris, M. G. (1996). User acceptance of information technology: Theories and models. Annual Review of Information Science and Technology, 31, 3-32.

  • Duane, A., O’Reilly, P., & Andreev, P. (2014). Realising m-payments: Modelling consumers’ willingness to m-pay using smart phones. Behavior & Information Technology, 33(4), 318-334.

  • Friedman, B., Khan, P. H. & Howe, D. C. (2000). Trust Online, Communications of the ACM, 43 (12), 34-40.

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.

  • Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90.

  • Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural Equation Modeling and Regression: Guidelines for Research Practice. Communications of the Association for Information Systems, 4(7), 1-70.

  • Grabner-Kräuter, S. (2002). The Role of Consumers’ Trust in Online-Shopping. Journal of Business Ethics, 39(1-2), 43-50.

  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate Data Analysis. Upper Saddle River, NJ: Prentice Hall.

  • Handrich, M., & Heidenreich, S. (2013). The willingness of a customer to cocreate innovative, technology-based services: Conceptualization and measurement. International Journal of Innovation Management, 17(4), 61-97.

  • Handrich, M., & Heidenreich, S. (2014). Adoption of technology based services: the role of customers’ willingness to co-create. Journal of Service Management, 26(1), 44-71.

  • Hoyer, W. D., Chandy, R., Dorotic, M., Krafft, M., & Singh, S. S. (2010). Consumer cocreation in new product development. Journal of Service Research, 13(3), 283-296.

  • Ketkar, S., Kock, N., Parente, R., & Verville, J. (2012). The impact of individualism on buyer-supplier relationship norms, trust and market performance: An analysis of data from Brazil and the U.S.A. International Business Review, 21(5), 782–793.

  • Kim, D., Ferrin, D. & Rao, H. (2009). Trust and satisfaction, two stepping stones for successful e-Commerce relationships: A longitudinal exploration. Information Systems Research, 20(2), 237-257.

  • Kock, N., & Lynn, G. S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546-580.

  • McKnight, D.H. & Chervany, N. L. (2002). What Trust Means in E-Commerce Customer Relationships: An Interdisciplinary Conceptual Typology. International Journal of Electronic Commerce, 6(2), 35-60.

  • Nunnally, J. C., & Bernstein, I. H. (1994) Psychometric Theory. New York: McGrawHill.

  • Ostrom, A.L., Bitner, M. J., Brown, S.W., Burkhard, K.A., Goul, M., Smith-Daniels, V., Demirkan, H., & Rabinovich, E. (2010). Moving forward and making a difference: Research priorities for the science of service. Journal of Service Research, 13(1), 4-36.

  • Park, Y., & Chen, J. V. (2007). Acceptance and adoption of the innovative use of smartphone. Industrial Management & Data Systems, 107(9), 1349-1365.

  • Pavlou, P. A. (2003). Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model. International Journal of Electronic Commerce, 7(3), 101-134.

  • Petrovic, O., Ksela, M., Fallenbock M., & Kittl, C. (2003). Trust in the network economy, New York, NY: Wien: Springer-Verlag Wien (2).

  • Rogers, E. M. (1995). Diffusion of Innovations. New York, NY: Free Press.

  • Rosenthal, R., & Rosnow, R. L. (1991). Essentials of Behavioral Research: Methods and Data Analysis. New York, NY: McGraw-Hill.

  • Rust, R. T., & Chung, T. S. (2006), “Marketing models of service and relationships”, Marketing Science, 25(6), 560-580.

  • Setterstrom, A. J., Pearson, J. M., & Orwig, R. A. (2013). Web-enabled wireless technology: An exploratory study of adoption and continued use intention. Behavior & Information Technology, 32(11), 1139-1154.

  • Shaw, N. (2014). The mediating influence of trust in the adoption of the mobile wallet. Journal of Retailing and Consumer Services, 21(4), 449-459.

  • Tornatzky, L., & Fleischer, M. (1990). The Process of Technology Innovation. Massachusetts, MA: Lexington Books.

  • Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.

  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.

  • Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1). 157-78.

  • Wei, T.W., Marthandan, G., Chong, A.Y. L., Ooi, K. B., & Arumugam, S. (2009). What drives Malaysian mcommerce adoption? An empirical analysis. Industrial Management & Data Systems, 109(3), 370-388.

  • Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information Management, 42, 719-729.

  • Yi, Y., & Gong, T. (2013). Customer value co-creation behavior: scale development and validation. Journal of Business Research, 66(9), 1279-1284.

  • Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22.


Abstract Views: 160

PDF Views: 0




  • Mobile Wallet Adoption in India:Impact of Trust and Information Sharing

Abstract Views: 160  |  PDF Views: 0

Authors

Neetha J. Eappen
Rajagiri Business School, Rajagiri Valley, Kochi 682039, Kerala, India

Abstract


This paper aims to explore how trust and information sharing influence consumer intention to use mobile wallets for making payments. An extended technology acceptance model incorporating the constructs is empirically tested through an online survey involving a vignette using the mobile wallet. Structural equation modeling using partial least squares approach has been performed to analyze the data collected from the survey conducted among 240 postgraduate students of a university in Kerala, who represent the tech savvy young population, using a structured questionnaire. Though the importance of perceived usefulness and perceived ease of use is validated, the results of the study provide conclusive evidence that trust is a stronger driver of mobile wallet adoption, suggesting the need to build consumer trust to drive mobile wallet adoption. The study also confirms the positive influence of trust on consumer willingness to share information which is crucial for co-creation of service.

Keywords


Information Sharing, Mobile Wallet, Perceived Ease of Use, Perceived Usefulness, Trust.

References