South Asian Journal of Management

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Do Perceived Risk and Trust affect Consumer Adoption of Mobile Payments? A Study of Indian Consumers


Affiliations
1 ISBR Business School, No. 107, Near Infosys, Behind BSNL Telephone Exchange, Electronic City Phase I, Bengaluru 560100, India
2 Dayananda Sagar Institute of Engineering, Hosur Main Road, Kudlu Gate, Hongasandra Village, Begur Hobli, Bengaluru 560068, India
     

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India has over one billion mobile users of mobile phones of which a very meagre proportion are active users of mobile payment services. As seen from technology adoption literature, trust issues and risk perception were probable hindrances in consumer adoption of mobile payments. To understand this further, the structural associations between predictor variables trust, perceived monetary risk, perceived privacy risk, perceived security risk on the dependent variables behavioral intention and attitude towards adoption of mobile payment services were explored. Exploratory factor analysis, confirmatory factor analysis and structural equation modeling was conducted using Lavaan package in R studio (version 0.99.879). The SEM output revealed that four out of twelve hypothesized associations were statistically significant. Trust emerged as a significant predictor with strong association on consumer attitude towards adoption of mobile payments.

Keywords

Mobile Payment, Perceived Risk, Structural Equation Modeling, Trust.
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  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.

  • Akturan, U., & Tezcan, N. (2012). Mobile banking adoption of the youth market: Perceptions and intentions. Marketing Intelligence & Planning, 30(4), 444-459.

  • Alkhunaizan, A., & Love, D. S. (2012). What drives mobile commerce? An empirical evaluation of the revised UTAUT model. International Journal of Management and Marketing Academy, 2(1), 82-99.

  • Amoroso, D. L., & Magnier-Watanabe, R. (2012). Building a Research Model for Mobile Wallet Consumer Adoption: The Case of Mobile Suica in Japan. Journal of Theoretical and Applied Electronic Commerce Research, 7(1), 94-110.

  • Apanasevic, T., Markendahl, J., & Arvidsson, N. (2016). Stakeholders’ expectations of mobile payment in retail:lessons from Sweden. International Journal of Bank Marketing, 34(1), 37-61.

  • Arvidsson, N. (2014). Consumer attitudes on mobile payment services - results from a proof of concept test. International Journal of Bank Marketing, 32(2), 150-170.

  • Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.

  • Benamati, J., Fuller, M., Serva, M., & Baroudi, J. (2010). Clarifying the integration of trust and TAM in e-commerce environments: implications for systems design and management. IEEE Transactions on Engineering Management, 57(3), 380-473.

  • Bentler, P. M., & Chou, C.-P. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238.

  • Brown, I., Cajee, Z., Davi, D., & Stroebel, S. (2003). Cell phone banking: predictors of adoption in South Africa—an exploratory study. International Journal of Information Management, 23, 381-394.

  • Chauhan, S. (2015). Acceptance of mobile money by poor citizens of India: integrating trust into the technology acceptance model. info, 17(3), 58-68.

  • Cheong, J. H., & Park, M.-C. (2005). Mobile internet acceptance in Korea. Internet Research, 15(2), 125-140.

  • Cruz, P., Neto, L. B., Mun˜oz-Gallego, P., & Laukkanen, T. (2010). Mobile banking rollout in emerging markets: evidence from Brazil. International Journal of Bank Marketing, 28(5), 342-371.

  • Dahlberg, T., & Öörni, A. (2007). Understanding Changes in Consumer Payment Habits - Do Mobile Payments and Electronic Invoices Attract Consumers? (pp.50, 50). Hawaii: 40th Annual Hawaii International Conference on System Sciences, 2007. HICSS 2007. doi:10.1109/HICSS.2007.580

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982-1002.

  • Donner, J., & Tellez, C. A. (2008). Mobile banking and economic development: Linking adoption, impact, and use . Asian Journal of Communication, 18(4), 318-332.

  • Evans, D. S., & Pirchio, A. (2015, March). An Empirical Examination of Why Mobile Money Schemes Ignite in Some Developing Countries but Flounder in Most. University of Chicago Coase-Sandor Institute for Law & Economics Research Paper No. 723. Retrieved from http://ssrn.com/abstract=2578312 or http:// dx.doi.org/10.2139/ssrn.2578312

  • Featherman, M. S., & Pavlou, P. A. (2003). Predicting E-Services Adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451-525.

  • Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. MA: Addison-Wesley, Reading, MA.

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

  • Gerrard, P., Cunningham, J. B., & Devlin, J. F. (2006). Why consumers are not using internet banking: a qualitative study. Journal of Services Marketing, 20(3), 160-8.

  • Goeke, L., & Pousttchi, K. (2010). A scenario-based analysis of mobile payment acceptance. The Ninth International Conference on Mobile Business/Ninth Global Mobility Roundtable, (pp. 371-378). Athens .

  • Gu, J.-C., Lee, S.-C., & Suh, Y.-H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616.

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

  • Koening-Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers’ take up of mobile banking services. International Journal of Bank Marketing, 28(5), 410-432.

  • Kwon, H. S., & Chidambaram, L. (2000). A test of the technology acceptance model: the case of cellular. Proceedings of the 33rd Annual Hawaii International (pp. p. 7–pp). Hawaii: System Sciences, 2000.

  • Laforet, S., & Li, X. (2005). Consumers’ attitudes towards online and mobile banking in China. International Journal of Bank Marketing, 23(5), 362-380.

  • Liébana-Cabanillas, F., Ramos de Luna, I., & Montoro-Ríos, F. J. (2015). User behaviour in QR mobile payment system: the QR Payment Acceptance Model. Technology Analysis & Strategic Management, DOI: 10.1080/09537325.2015.1047757.

  • Maheshwari, R. (2016, February 17). Paytm scraps transaction fee for offline merchants. Retrieved September 21, 2016, from http://economictimes.indiatimes.com: http://economictimes.indiatimes.com/small-biz/startups/paytm-scraps-transaction-fee-for-offline-merchants/articleshow/51017672.cms

  • Mallat, N. (2007). Exploring consumer adoption of mobile payments – a qualitative study. The Journal of Strategic Information Systems, 16, 413-432.

  • Phonthanukitithaworn, C., Sellitto, C., & Fong, M. W. (2016). An investigation of mobile payment (m-payment) services in Thailand. Asia-Pacific Journal of Business Administration, 8(1), 37-54.

  • Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model.Internet Research, 14(3), 224-35.

  • Püschel, J., Mazzon, J. A., & C. Hernandez, J. M. (2010). Mobile banking: proposition of an integrated adoption intention framework. International Journal of Bank Marketing, 28(5), 389-409.

  • Rogers, E. M. (1995). Diffusion of Innovations. Free Press.

  • Slade, E., Dwivedi, Y., Piercy, N., & Williams, M. (2015). Modeling consumers’ adoption intentions of remote mobile payments in the UK: Extending UTAUT with innovativeness, risk and trust. Psychology & Marketing, 32(8).

  • Taylor, E. (2016). Mobile payment technologies in retail: a review of potential benefits and risks. International Journal of Retail & Distribution Management, 44(2), 159-177.

  • Tang, L.-L., & T.H, H. N. (2013). Common cuses of trust satisfaction and TAM in online shopping : an integrated model. Journal of Quality, 20(5), 483-501.

  • Thakur, R., & Srivastava, M. (2014). Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research, 24(3), 369-392.

  • Unnikrishnan, R., & Jagannathan, L. (2017). Adoption of mobile payment services in Bangalore urban - A structural equation modelling based approach. Journal of Contemporary Research in Management, 12(4), 1-20

  • Venkatesh, V., Morris, M., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information: 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), 157-178.

  • Wei, T. T., Marthandan, G., Yee-Loong, C., Ooi, K.-B., & Arumugam, S. (2009). What drives Malaysian m-commerce adoption? An empirical analysis. Industrial Management & Data Systems, 109(3), 370-388.

  • Wessels, L., & Drennan, J. (2010). An investigation of consumer acceptance of Mbanking. International Journal of Bank Marketing, 28(7), 547-568.

  • Yang, Y., Liu, Y., Li, H., & Yu, B. (2015). Understanding perceived risks in mobile payment acceptance. Industrial Management & Data Systems, 115(2), 253-269.

  • Yousafzai, S. Y., Pallister, J. G., & Foxall, G. R. (2003). A proposed model of e-trust for electronic banking. Technovation, 23, 847-860.

  • Zhou, T. (2011). An empirical examination of initial trust in mobile banking. Internet Research, 21(5), 527-540.

  • Zhou, T. (2014). Understanding the determinants of mobile payment continuance usage. Industrial Management & Data Systems, 114(6), 936-948.


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  • Do Perceived Risk and Trust affect Consumer Adoption of Mobile Payments? A Study of Indian Consumers

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Authors

Roshny Unnikrishnan
ISBR Business School, No. 107, Near Infosys, Behind BSNL Telephone Exchange, Electronic City Phase I, Bengaluru 560100, India
Lakshmi Jagannathan
Dayananda Sagar Institute of Engineering, Hosur Main Road, Kudlu Gate, Hongasandra Village, Begur Hobli, Bengaluru 560068, India

Abstract


India has over one billion mobile users of mobile phones of which a very meagre proportion are active users of mobile payment services. As seen from technology adoption literature, trust issues and risk perception were probable hindrances in consumer adoption of mobile payments. To understand this further, the structural associations between predictor variables trust, perceived monetary risk, perceived privacy risk, perceived security risk on the dependent variables behavioral intention and attitude towards adoption of mobile payment services were explored. Exploratory factor analysis, confirmatory factor analysis and structural equation modeling was conducted using Lavaan package in R studio (version 0.99.879). The SEM output revealed that four out of twelve hypothesized associations were statistically significant. Trust emerged as a significant predictor with strong association on consumer attitude towards adoption of mobile payments.

Keywords


Mobile Payment, Perceived Risk, Structural Equation Modeling, Trust.

References