The Moderating Effect of Gender on Continuance Intention Toward Mobile Wallet Services in India

Authors

  •   T. Thirumal Reddy Faculty - Marketing, Siva Sivani Institute of Management, NH-7, Kompally, Secunderabad - 500 014, Telangana
  •   B. Madhusudhana Rao Professor, School of Management Studies, Vignan's University (VFSTR), Vadlamudi - 522 213, Guntur District, Andhra Pradesh

DOI:

https://doi.org/10.17010/ijom/2019/v49/i4/142976

Keywords:

Mobile Wallet

, Satisfaction, Continued Usage, Perceived Ease of Use, Confirmation

Paper Submission Date

, May 19, 2018, Paper sent back for Revision, February 6, 2019, Paper Acceptance Date, February 25, 2019

Abstract

With the rapid development of mobile technologies in the last decade, there are many benefits offered to both businesses and individuals, including evolution of an innovative payment method, that is, mobile wallet services. The rapid diffusion of 4G technologies, growth in mobile Internet users, increasing trend of shopping through smartphones, and government's demonetization policy in 2016 resulted in widespread usage of mobile wallet services in India. In this context, this study aimed at understanding the factors influencing the mobile wallet customers' satisfaction and motivations behind the continued usage of a specific service provider. Further, the study attempted to identify the differences in behavioural characteristics of mobile wallet users based on their gender. A conceptual model was developed to measure the impact of three significant variables, that is, perceived usefulness, perceived ease of use, and confirmation on the post-adoption behaviour of mobile wallet customers. The data were collected from 325 mobile wallet customers through a popular online survey website. The analysis of data using structural equation modeling provided certain important insights, including the positive and strong influence of perceived ease of use on both satisfaction and continuance intention, and satisfaction was found to be the key factor that motivated mobile wallet users to continue using a particular mobile wallet application. Finally, the moderating effect of gender on the hypothesized relationships proposed in the model was empirically supported.

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Published

2019-04-02

How to Cite

Reddy, T. T., & Rao, B. M. (2019). The Moderating Effect of Gender on Continuance Intention Toward Mobile Wallet Services in India. Indian Journal of Marketing, 49(4), 48–62. https://doi.org/10.17010/ijom/2019/v49/i4/142976

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Articles

References

Alshare, K., & Mousa, A. (2014). The moderating effect of espoused cultural dimensions on consumer's intention to use mobile payment devices. In Proceedings of the 35th International Conference on Information Systems, Auckland. Retrieved from https://pdfs.semanticscholar.org/b09b/ae6059c7a50995686cb6abae4fcc338bfb58.pdf

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103 (3), 411 - 423.

Aparna, R. R., Ostwal, T., Baliga, T. B., & Sreekumar, N. (2015). Overview of digital wallets in India. International Journal of Advanced Research in Computer Science, 6 (8), 28 - 31.

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.

Aydin, G., & Burnaz, S. (2016). Adoption of mobile payment systems: A study on mobile wallets. Journal of Business Economics and Finance, 5 (1), 73 - 92.

Banerjee, N., Dutta, A., & Dasgupta, T. (2010). A study on customers' attitude towards online shopping - An Indian perspective. Indian Journal of Marketing, 40 (11), 36 - 42.

Bhattacherjee, A. (2001). Understanding information systems continuance : An expectation - confirmation model. MIS Quarterly, 25 (3), 351 - 370.

Bitner, M. J. (1990). Evaluating service encounters: The effects of physical surroundings and employee responses. The Journal of Marketing, 54 (2), 69 - 82.

Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological Methods & Research, 17 (3), 303 - 316.

Byrne, B. M. (2001). Structural equation modeling: Perspectives on the present and the future. International Journal of Testing, 1 (3 - 4), 327 - 334.

Chong, A. Y. - L. (2013). Understanding mobile commerce continuance intentions: an empirical analysis of Chinese consumers. Journal of Computer Information Systems, 53 (4), 22 - 30.

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

eMarketer. (2017). Mobile wallet spending worldwide, 2016 & 2017 (trillions and % change). Retrieved from https://www.emarketer.com/Chart/Mobile-Wallet-Spending-Worldwide-2016-2017-trillions-change/204668

Gao, L., Waechter, K. A., & Bai, X. (2015). Understanding consumers' continuance intention towards mobile purchase: A theoretical framework and empirical study - A case of China. Computers in Human Behavior, 53, 249 - 262.

Gupta, A., Madan, P., & Gupta, S. (2012). Factors influencing B2C m - commerce satisfaction and trust towards m - commerce service providers. Journal of Pure and Applied Science & Technology, 2 (1), 59 - 65.

Hampshire, C. (2017). A mixed methods empirical exploration of UK consumer perceptions of trust, risk and usefulness of mobile payments. International Journal of Bank Marketing, 35 (3), 354 - 369.

Hong, S., Thong, J. Y., & Tam, K. Y. (2006). Understanding continued information technology usage behavior: A comparison of three models in the context of mobile internet. Decision Support Systems, 42 (3), 1819 - 1834.

Hsu, C. L., & Lin, J. C. C. (2015). What drives purchase intention for paid mobile apps ? - An expectation confirmation model with perceived value. Electronic Commerce Research and Applications, 14 (1), 46 - 57.

Kapoor, K., Dwivedi, Y. K., & Williams, M. D. (2013, June). Role of innovation attributes in explaining the adoption intention for the interbank mobile payment service in an Indian context. In International Working Conference on Transfer and Diffusion of IT (pp. 203 - 220). Springer, Berlin, Heidelberg.

Kotler, P., & Armstrong, G. (2010). Principles of marketing. USA : Pearson Education.

Koundinya, C. (2017). Online shopping behavior : Demographics' influence on online travel. Indian Journal of Marketing, 47(6), 7-21. doi:10.17010/ijom/2017/v47/i6/115366

Kumar, A. A., Nayak, D. V., & Shekhar, V. (2018). Knowledge outlook of Indian consumers towards BHIM app. Indian Journal of Marketing, 48 (3), 7 - 16. doi:10.17010/ijom/2018/v48/i3/121979

Kuo, Y. F., Wu, C. M., & Deng, W. J. (2009). The relationships among service quality, perceived value, customer satisfaction, and post - purchase intention in mobile value-added services. Computers in Human Behavior, 25 (4), 887 - 896.

Kurup, A. J., & Jain, P. (2018). Effect of e-loyalty cues on repurchase behavioural intentions among online shoppers. Indian Journal of Marketing, 48 (11), 7 - 22. doi:10.17010/ijom/2018/v48/i11/137982

Madan, K., & Yadav, R. (2016). Behavioural intention to adopt mobile wallet : A developing country perspective. Journal of Indian Business Research, 8 (3), 227 - 244.

Marinkovic, V., & Kalinic, Z. (2017). Antecedents of customer satisfaction in mobile commerce: Exploring the moderating effect of customization. Online Information Review, 41 (2), 138 - 154.

Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2017). Understanding the intention to use mobile shopping applications and its influence on price sensitivity. Journal of Retailing and Consumer Services, 37, 8 - 22.

Oghuma, A. P., Libaque - Saenz, C. F., Wong, S. F., & Chang, Y. (2016). An expectation - confirmation model of continuance intention to use mobile instant messaging. Telematics and Informatics, 33(1), 34 - 47.

Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460 - 469.

Pal, D., Vanijja, V., & Papasratorn, B. (2015). An empirical analysis towards the adoption of NFC mobile payment system by the end user. Procedia Computer Science, 69, 13 - 25.

Park, E., & Kim, K. J. (2013). User acceptance of long-term evolution (LTE) services : An application of extended technology acceptance model. Program, 47 (2), 188 - 205.

Rathore, H. S. (2016). Adoption of digital wallet by consumers. BVIMSR's Journal of Management Research, 8 (1), 69 - 75.

Reichheld, F. F., & Sasser Jr., W. E. (1990). Zero defections: Quality comes to services. Harvard Business Review, 68 (5), 105-111.

Shin, D. H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25 (6), 1343 - 1354.

Singh, A., Panackal, N., Bommireddipalli, R. T., & Sharma, A. (2016). Understanding youngsters' buying behavior in e-retail: A conceptual framework. Indian Journal of Marketing, 46 (10), 53 - 62. doi:10.17010/ijom/2016/v46/i10/102857

Statista. (2016). Global mobile payment transaction volume from 2015 to 2019 (in billion US dollars). Retrieved from www.statista.com/statistics/226530/mobile-payment-transaction-volume-forecast

Susanto, A., Chang, Y., & Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services : An extension to the expectation - confirmation model. Industrial Management & Data Systems, 116(3), 508 - 525.

Upadhyay, P., & Jahanyan, S. (2016). Analyzing user perspective on the factors affecting use intention of mobile based transfer payment. Internet Research, 26 (1), 38 - 56.

Yang, S., Lu, Y., Gupta, S., Cao, Y., & Zhang, R. (2012). Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computers in Human Behavior, 28 (1), 129 - 142.

Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54 (2), 1085 - 1091.