International Journal on Customer Relations

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

A Study on Consumers’ Adoption Intention for Digital Wallets in India


Affiliations
1 Indian Institute of Social Welfare & Business Management, Management House, College Square West, Kolkata, West Bengal, India
     

   Subscribe/Renew Journal


The purpose of the present research study is to find out whether customer demographics influence adoption intention for e-wallets in India and to identify the parameters that are most important in predicting consumers’ adoption intention and whether the market can be segmented into different customer groups. The regression model showed an impressive amount of variance explained for adoption intention (R2=81.7%) and cluster analysis helped to reveal three different customer segments with their different set of criteria. The above findings will help digital wallet companies to have a better and clear understanding of factors that influence the adoption decision of Indian consumers concentrating particularly on the parameters that influence end-users to adopt their services.

Keywords

E-Wallet, Adoption Intention, Regression, Cluster, Anova.
Subscription Login to verify subscription
User
Notifications
Font Size


  • Abubakar, F. M., & Ahmad, H. B. (2013). The moderating effect of technology awareness on the relationship between UTAUT constructs and behavioural intention to use technology: A conceptual paper. Australian Journal of Business and Management Research, 3(2), 14-23.

  • Al-Maghrabi, T., & Dennis, C. (2011). What drives consumers’ continuance intention to e-shopping?: conceptual framework and managerial implications in the case of Saudi Arabia. International Journal of Retail Distribution Management, 39(12), 899-926.

  • Amoroso, D. L., & Hunsinger, D. S. (2009). Analysis of the factors that influence online purchasing. Journal of Information Systems Applied Research, 2(1).

  • Amoroso, D., & Watanabe, R. (2011). 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).

  • Battacherjee. (2000). Acceptance of e-commerce services: The case of electronic brokerages. IEEE Transactions on Systems, Man and Cybernetics, 30, 411-420.

  • Bhatt, T. (2007). Exploring factors influencing the adoption of mobile commerce. Journal of Internet Banking and Commerce, 12(3).

  • Chen, Y., Lou, H., & Luo, W. (2002). Distance learning technology adoption: A motivation perspective. The Journal of Computer Information Systems, 42(2), 38-43.

  • Cheong, J. H., Park, M. C., & Hwang, J. H. (2004). Mobile payment adoption in Korea: Switching from credit card. Ph.D. dissertation, School of Business, Information and Communications University, Daejon, Korea, 2004.

  • Chong, A. Y. L., Chan, F. T. S., & Ooi, K. B. (2012). Predicting consumer decisions to adopt mobile commerce. Decision Support Systems, 53.

  • Clarke III, I. (2001). Emerging value propositions for m-commerce. Journal of Business Strategies, 25(2).

  • David, G., & Detmar, S. W. (2004). Consumer Trust in B2C e-commerce and the importance of Social Presence: Experiments in e-products & e-services. Omega: The International Journal of Management Science, 32, 407-424.

  • Deng, Z., Lu, Y., Deng, S., & Zhang, J. (2010). Exploring user adoption of mobile banking: An empirical study in China. International Journal of Information Technology and Management, 9(3).

  • Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A Perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4).

  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An Introduction to theory and research. Reading, MA: Addison-Wesley.

  • Garrity, J., & Kurd, J. (2015). The future of the mobile wallet: Barriers and opportunities for the next stage of the mobile payment revolution. An independent research conducted by CMB’s self-funded Consumer Pulse Project.

  • Gefen, D., & Straub, D. W. (1997). Gender Differences in the perception and use of e-mail: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389-400.

  • Gitau, L., & David, N. (2014). Analysis of determinants of m-commerce adoption by online consumers. International Journal of Business, Humanities and Technology, 4(3).

  • Heijden, H. V. D., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: Contributions from technology and trust perspectives. European Journal of Information Systems, 12, 41-48.

  • Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: the case of computers. J. Appl. Psvchol., 72, 307-313.

  • Hong, S. J., Thong, J. Y. L., & Tam, K. Y. (2006). Understanding continued information technology usage behaviour: A comparison of three models in the context of mobile internet. Decision Support Systems, 42, 1819-1834.

  • Jaw, C. (2011). The determinants of the adoption of online payment services: Integrating customer experiences and perceptions into the technology acceptance model. International Journal of Arts & Sciences, 4(22), 255-271.

  • Joubert, J., & Belle, J. P. V. (2013). The role of trust and risk in mobile commerce adoption within South Africa. International Journal of Business, Humanities and Technology, 3(2).

  • Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barriers and repurchase intentions in services. Journal of Retailing, 76(2), 259-275.

  • Kallamarthodi, G., & Vaithiyanathan, M. (2011). Empirical assessment of a modified technology acceptance model in emerging economy: An assessment from the perspective of Indian consumers. International Conference on E-business, Management and Economics, 25.

  • Kassim, N., & Abdullah, N. A. (2010). The effect of perceived service quality dimensions on customer satisfaction, trust, and loyalty in e-commerce settings: A cross cultural analysis. Asia Pacific Journal of Marketing and Logistics, 22(3), 351-371.

  • Kesharwani, A., & Bisht, S. S. (2012). The impact of trust and perceived risk on internet banking adoption in India: An extension of technology acceptance model. International Journal of Bank Marketing, 30(4), 303-322.

  • Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: An empirical investigation. Decision Support Systems, 43(1), 111-126. Retrieved from http://dx.doi.org/10.1016/j.dss.2005.05.009

  • Kurnia, S., Smith., S. P., & Lee, H. (2006). Consumers’ perception of mobile internet in Australia. The e-business Review, 5(1), 19-32.

  • Lah, N. S. C., Hussin, A. R. C., Dahlan, H. M. (2013). Improving B2C e-commerce trust through social presence factors. Journal of Information Systems Research and Innovation, 3, 44-53.

  • Lee, I., Choi, B., Kim, J., & Hong, S. J. (2007). Culture-technology fit: Effects of cultural characteristics on the post-adoption beliefs of mobile internet users. International Journal of Electronic Commerce, 11(4), 11-51.

  • Lee, T. M. (2005). The impact of perceptions of interactivity on customer trust and transaction intentions in mobile commerce. Journal of Electronic Commerce Research, 6(3).

  • Lim, Y. J., Osman, A., Salahuddin, S. N., Romle, A. R., & Abdullah, S. (2016). Factors influencing online shopping behaviour: The mediating role of purchase intention. Procedia Economics and Finance, 35, 401-410.

  • Lin, H. H., & Wang, Y. S. (2006). An examination of the determinants of customer loyalty in mobile commerce contexts. Information & Managementm, 43, 271-282.

  • Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems, 49, 222-234.

  • Madan, K., & Yadav, R. (2016). An exploration of factors affecting m-commerce adoption in India. Advances in Economics and Business Management, 3(1), 1-6.

  • Mallat, N. (2007). Exploring consumer adoption of mobile payments: A qualitative study. The Journal of Strategic Information Systems, 16(4).

  • Mallat, N., Rossi, M., & Tuunainen, V. K. (2004). Mobile banking services. Communications of the ACM, 47(5), 42-46.

  • Mashagba, F. F. A., Mashagba, E. F. A., & Nassar, M. O. (2013). Exploring technological factors affecting the adoption of m-commerce in Jordan. Australian Journal of Basic and Applied Sciences, 7(6), 395-400.

  • Mirella, K., Martin, W., & De, R. K. (2003). Consumer acceptance of wireless finance. Journal of Financial Services Marketing, 8(3), 206-217.

  • Nguyen, T. N., Cao, T. K., Dang, P. L., & Nguyen, H. A. (2016). Predicting consumer intention to use mobile payment services: Empirical evidence from Vietnam. International Journal of Marketing Studies, 8(1).

  • Nyshadham, E. A. (2000). Privacy policies of air travel web sites: A survey and analysis. DOI: 10.1016/S0969-6997(00)00007-7

  • Okazaki, S., Li, H., & Hirose, M. (2009). Consumer privacy concerns and preference for degree of regulatory control. Journal of Advertising, 38(4), 63-77.

  • Padashetty, D., & Kishore, K. S. V. (2013). An empirical study on consumer adoption of mobile payments in Bangalore city: A case study. International Refereed Research Journal, 1(1).

  • Parveen, F., & Sulaiman, A. (2008). Technology complexity, personal innovativeness and intention to use wireless internet using mobile devices in Malaysia. International Review of Business Research Papers, 4(5), 1-10.

  • 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), 69-103.

  • Pavlou, P. A., Liang, H., & Xue, Y. (2006). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. Under 2nd Round of Review in MIS Quarterly.

  • Pederson, P. E. (2005). Adoption of mobile internet services: An exploratory study of mobile commerce early adopters. Journal of Organisational Computing and Electronic Commerce, 15(3).

  • Qingfei, M., Shaobo, J., & Gang, Q. (2008). Mobile commerce user acceptance study in China: A revised UTAUT model. Tsinghua Science and Technology, 13(3), 257-264.

  • Rathore, H. M. (2016). Adoption of digital wallet by consumers. BVIMSR’s Journal of Management Research, 8(1).

  • Sadi, A. H. M. S., & Noordin, M. F. (2011). Factors influencing the adoption of M-commerce: An exploratory Analysis. Proceedings of the 2011 International Conference on Industrial Engineering and Operations Management, Kuala Lumpur, Malaysia, January 22-24, 2011.

  • Saibaba, S., & Naryana Murthy, T. (2013). Factors influencing the behavioural intention to adopt internet banking: An empirical study in India. Journal of Arts, Science & Commerce, 4(1), 77-91.

  • San, M. H., & Herrero A. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management 33, 341-350.

  • Shah, M. U., Fatimee, S., & Sajjad, M. (2014). Mobile commerce adoption: An empirical analysis of the factors affecting consumer intention to use mobile commerce. Journal of Basic Application of Scientific Research, 4(4), 80-88.

  • Siau, K., & Shen, Z. (2003). Building customer trust in mobile commerce. Communications of The ACM, 46(4).

  • Song, S. (2010). Factors that Influence Consumer’s Adoption Behaviour in M-Commerce”, Thesis submitted to the Faculty of Purdue University in Partial Fulfilment of the Requirements for the Degree of Master of Science.

  • Sudarshan, J., & Eze, U. C. (2012). Analysing the intention to use mobile coupon & the moderating effects of price consciousness and gender. International Journal of e-Business Research, 8(1), 54-75.

  • Suh, B., & Han, I. (2003). The impact of customer trust and perception of security control on the acceptance of electronic commerce. International Journal of Electronic Commerce, 7(3), 135-161.

  • Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: a test of competing models. Information Systems Research, 6, 144-176.

  • Tang, J. E., & Chiang, C. (2009). Towards an understanding of the behavioral intention to use mobile knowledge management. Wseas Transactions on Information Science and Applications, 6(9).

  • Thakur & Srivastava (2013). Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research, 24(3), 369-392.

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

  • Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behaviour. MIS Quarterly, 24(1), 115-139.

  • 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.

  • Webster, J., & Martocchio, J. J. (1992). Microcomputer playfulness: Development of a measure with workplace implications. MIS Quarterly, 16, 201-226.

  • Wu, W., & Ke, C. (2015). An online shopping behaviour model integrating personality traits, perceived risk and technology acceptance. Social Behaviour and Personality, 43(1), 85-98.

  • Yiu, C. S., Grant, K., & Edgar, D. (2007). Factors affecting the adoption of internet banking in Hong Kong - implications for the banking sector. International Journal of Information Management, 27(5), 336-351.

  • http://www.thehindu.com/news/cities/mumbai/business/with-220mn-users-india-is-now-worlds-secondbiggest-smartphone-market/article8186543.ece


Abstract Views: 956

PDF Views: 2




  • A Study on Consumers’ Adoption Intention for Digital Wallets in India

Abstract Views: 956  |  PDF Views: 2

Authors

Satadruti Chakraborty
Indian Institute of Social Welfare & Business Management, Management House, College Square West, Kolkata, West Bengal, India
Dipa Mitra
Indian Institute of Social Welfare & Business Management, Management House, College Square West, Kolkata, West Bengal, India

Abstract


The purpose of the present research study is to find out whether customer demographics influence adoption intention for e-wallets in India and to identify the parameters that are most important in predicting consumers’ adoption intention and whether the market can be segmented into different customer groups. The regression model showed an impressive amount of variance explained for adoption intention (R2=81.7%) and cluster analysis helped to reveal three different customer segments with their different set of criteria. The above findings will help digital wallet companies to have a better and clear understanding of factors that influence the adoption decision of Indian consumers concentrating particularly on the parameters that influence end-users to adopt their services.

Keywords


E-Wallet, Adoption Intention, Regression, Cluster, Anova.

References