Factors Affecting the Intention to Use E-Wallets during the COVID-19 Pandemic
Abstract
The COVID-19 pandemic has reshaped the lifestyle of Malaysians. The government has introduced various incentives to encourage contactless transactions. Malaysia has also expe- rienced a spike in e-wallet transactions during the COVID-19 pandemic. However, there is no consensus on the reasons behind the rapid increase in the usage of e-wallets. This study aims to fill a knowledge gap by incorporating government support, the perceived risk, and social influence as the potential factors affecting the use of e-wallets. Survey data were collated from 598 respondents using Google Forms and analyzed using covariance-based structural equation modeling (CB-SEM). The findings confirm that perceived usefulness, government support, the perceived risk, and social influence are positively related to the attitude toward the usage of e-wallets. This attitude is also positively related with the user’s intention of using the wallets. The outcomes of this study may assist policymakers to devise effective strategies that are able to capture the users’ intentions to use e-wallets during the COVID-19 pandemic. This study also recommends that the government increases the incentives to speed up the formation of a cash- less society. The related organizations should also enhance public awareness on the usefulness of e-wallets in preventing virus transmission.
Keywords
DOI: 10.22146/gamaijb.64708
References
Aji, H. M., Berakon, I., & Husin, M. M. (2020). COVID-19 and e-wallet usage intention: a multigroup analysis between Indonesia and Malaysia. Cogent Business and Management, 7, 1–16.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.
Al-Emran, M., & Teo, T. (2020). Do knowledge acquisition and knowledge sharing really affect e-learning adoption? An empirical study. Education and Information Technologies, 25(2), 1983–1998.
Alsamydai, M. J. (2014). Adaptation of the technology acceptance model (TAM) to the use of mobile banking services. International Review of Management and Business Research, 3(4), 2039–2051.
Belanche, D., Flavián, M., & Pérez-Rueda, A. (2020). Mobile apps use and WOM in the food delivery sector: the role of planned behavior, perceived security and customer lifestyle compatibility. Sustainability, 12(4275), 1–21.
Becker, T. B. Randall, M., Riegel, D. C. (1995). The multidimensional view of commitment and the theory of reasoned action: a comparative evaluation. Journal of Management, 21(4), 617-638.
Bettman, J. R. (1979). Memory factors in consumer choice: a review. Journal of Marketing, 43(2), 37-53.
Borneo, P.O. (2021). Boost records strong increase in GTV post-MCO. Retrieved 5 January, from https://www.theborneopost.com/2020/08/31/boost-records-strong-increase-in-gtv-post mco.
Cheng, A. Y., Hamid, N. R. A., & Cheng, E. H. (2013). Risk perception of the E-payment systems: a young adult perspective. WSEAS Transactions on Information Science and Applications, 1(10), 26–35.
Cheong, A. (2020). Government to provide RM50 digital incentive for E-wallet users, matched with additional RM50 vouchers. Retrieved 5 January, from https://ringgitplus.com/en/blog/e-wallet/government-to-provide-rm50-digital-incentive-for-e-wallet-users-matched-with-additional-rm50-vouchers.html.
Chua, C. J., Lim, C. S., & Khin, A. A. (2020). Consumers' behavioural intention to accept of the mobile wallet in Malaysia. Journal of Southwest Jiaotong University, 55(1), 1–13.
Claudia, B. A., Patel, V. K., & Wanzenried, G. (2014). A comparative study of CB-SEM and PLS-SEM for theory development in family firm research. Journal of Family Business Strategy, 5, 116-128.
Crespo, A. H., Del Bosque, I. R., & Sanchez, M. M. G. D. L. S. (2009). The influence of perceived risk on Internet shopping behavior: A multidimensional perspective. Journal of Risk Research, 12(2), 259–277.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Do, N. B., & Do, H. N. T. (2020). An investigation of generation Z's intention to use electronic wallet in Vietnam. Journal of Distribution Science, 18(10), 89–99.
Elie-dit-cosaque, C., Pallud, J., & Kalika, M. (2012). The influence of individual, contextual, and social factors on perceived behavioral control of information technology: a field theory approach. Journal of Management Information Systems, 28(3), 201-234.
Elkheshin, S., & Saleeb, N. (2020). Assessing the adoption of E-government using TAM model: case of Egypt. International Journal of Managing Information Technology, 12(1), 1–14.
Fayad, R., & Paper, D. (2015). The technology acceptance model E-commerce extension: a conceptual framework. Procedia Economics and Finance, 26, 1000–1006.
Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International Journal of Human Computer Studies, 59, 451–474.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Gbongli, K., Xu, Y., & Komi, M. A. (2019). Extended technology acceptance model to predict mobile-based money acceptance and sustainability: a multi-analytical structural equation modeling and neural network approach. Sustainability, 11(3639), 1-33.
Gupta, V. (2017). A study on consumer adoption of mobile wallet. International Journal of Trade &Commerce, 6(1), 57–70.
Hair, J. F. J., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate Data Analysis (7th ed.). Pearson Prentice Hall.
Hair, J. F., Celsi, M., Money, A., & Samouel, P., & Page, M. (2011). Essentials of business research methods (2nd ed.). Armonk, NY: ME Sharpe.
Hair, J. F., Hult, G. T. M. Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: Sage.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
Howard, J. A., & Sheth, J. N. (1969). The Theory of Buyer Behavior. John Wiley & Sons.
Hwang, J., & Choi, J. K. (2018). An investigation of passengers' psychological benefits from green brands in an environmentally friendly airline context: the moderating role of gender. Sustainability, 10(80), 1–17.
Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information and Management, 48, 1–8.
Jaradat, M. I. R. (2013). Applying the technology acceptance model to the introduction of mobile voting. International Journal of Mobile Learning and Organisation, 7(1), 29–47.
Karim, M. W., Haque, A., Ulfy, M. A., Hossain, M. A., & Anis, M. Z. (2020). Factors influencing the use of E-wallet as a payment method among Malaysian young adults. Journal of International Business and Management, 3(2), 1–12.
Kelman, H. C. (1958). Compliance, identification, and internalization: three processes of attitude change. Journal of Conflict Resolution, 2, 51-60.
Khairul, M. D. A., Khidzir, N. Z., Ismail, A. R., & Abdullah, F. A. (2018). Validity and reliability of instrument to measure social media skills among small and medium entrepreneurs at Pengkalan Datu River. International Journal of Development and Sustainability, 7(3), 1026–1037.
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents. Decision Support Systems, 44, 544–564.
Lee, M. C. (2009). Factors influencing the adoption of internet banking: an integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8, 130–141.
Lee, H. J., Cho, H. J., Xu, W., & Fairhurst, A. (2010). The influence of consumer traits and demographics on intention to use retail self-service checkouts. Marketing Intelligence & Planning, 28(1), 46-58.
Leiva, F. M., Climent, C. S., & Cabanillas, L. F. (2017). Determinants of intention to use the mobile banking apps: an extension of the classic TAM model. Spanish Journal of Marketing - ESIC, 21(1), 25–38.
Lian, J. W., & Yen, D. C. (2014). Online shopping drivers and barriers for older adults: age and gender differences. Computers in Human Behavior, 37, 133–143.
Liu, G.-S., & Tai, P. T. (2016). A Study of Factors Affecting the Intention to Use Mobile Payment Services in Vietnam. Economics World, 4(6), 249–273.
Lwoga, E. T., & Lwoga, N. B. (2017). User acceptance of mobile payment: the effects of user-centric security, system characteristics and gender. Electronic Journal of Information Systems in Developing Countries, 81(3), 1–24.
Marangunic, N., & Granic, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal Access in the Information Society, 14, 81-95.
Mitchell, V. W. (1992). Understanding consumers' behavior: can perceived risk theory help?. Management Decision, 30(3), 26-31.
Mohamad, M., Afthanorhan, A., Awang, Z., & Mohammad, M. (2019). Comparison between CB-SEM and PLS-SEM: testing and confirming the Maqasid Syariah quality of life measurement model. The Journal of Social Sciences Research, 5(3), 608-614.
Nag, A. K., & Gilitwala, B. (2019). E-Wallet- factors affecting its intention to use. International Journal of Recent Technology and Engineering, 8(4), 3411–3415.
Nguyen, H. T., Dang, T. V., Nguyen, V. V., & Nguyen, T. T. (2020). Determinants of e-government service adoption: an empirical study for business registration in Southeast Vietnam. Journal of Asian Public Policy, 12(1), 1–16.
Nortajuddin, A. (2020). E-wallet adoption on the rise in ASEAN. Retrieved 5 January, fromhttps://theaseanpost.com/article/e-wallet-adoption-rise asean.
Pal, R., & Bhadada, S. K. (2020). Cash, currency and COVID-19. Postgraduate Medical Journal, 96(1137), 427–428.
Pertiwi, D., Suprapto, W., & Pratama, E. (2020). Perceived usage of E-wallet among the Y generation in Surabaya based on technology acceptance model. Jurnal Teknik Industri, 22(1), 17–24.
Ramayah, T., Lee, J. W. C., & Julie, B. C. I. (2011). Network collaboration and performance in the tourism sector. Service Business, 5(4), 411–428.
Saleh, A. N. (2019). Extend of TAM model with technology anxiety and self-efficacy to accept course websites at University Canada West. International Journal of Information Technology and Language Studies, 3(2), 1–7.
Saxena, S. (2018). Role of perceived risks in adopting mobile government (m-government) services in India. Foresight, 20(2), 190-205.
Sharma, S. K. (2019). Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling. Information Systems Frontiers, 21(4), 815–827.
Sharon, A. (2020). Malaysia govt hands out RM450 million. Retrieved 5 January, fromhttps://opengovasia.com/malaysia-govt-hands-out-rm450-million-to-boost-etransactions.
Shankar, A., & Datta, B. (2018). Factors affecting mobile payment adoption intention: an Indian perspective. Global Business Review, 19, 72-89.
Subaramaniam, K., Kolandaisamy, R., Jalil, A. Bin, & Kolandaisamy, I. (2020). The impact of E-Wallets for current generation. Journal of Advanced Research in Dynamical and Control Systems, 12(1), 751–759.
Sugianto, D. K. (2017). The moderating effect of age, income, gender, expertise, loyalty program, and critical incident on the influence of customer satisfaction towards customer loyalty in airline industry: a case of PT. X. iBuss Management, 5(1), 70-83.
Tan, J. (2020). RM30 e-Tunai rakyat E-wallet initiative : what you need to know. Retrieved 5 January, fromhttps://ringgitplus.com/en/blog/e-wallet/rm30-e-tunai-rakyat-e-wallet-initiative-what-you-need-to-know.
Tan, O. K., Fatinsyakila, A. A., Ong, C. H., Goh, C. F., Lim, K. Y., Mohd, S. I. B. S., & Choi, S. L. (2020). E-wallet acceptance among undergraduates in Malaysia. Test Engineering and Management, 83, 12990–12998.
Tao, D., Yuan, J., Shao, F., Li, D., Zhou, Q., & Qu, X. (2018). Factors affecting consumer acceptance of an online health information portal among youth internet users. CIN: Computers, Informatics, Nursing, 36(11), 530-539.
Taufan, A., &, & Yuwono, R, T. (2018). Analysis of factors that affect intention to use e-Wallet through the technology acceptance model approach (Case Study : GO-PAY ). International Journal of Science and Research, 8(7), 413–419.
Teo, T., & Zhou, M. (2014). Explaining the intention to use technology among university students: a structural equation modeling approach. Journal of Computing in Higher Education, 26, 124-142.
To, A. T., & Trinh, T. H. M. (2021). Understanding behavioral intention to use mobile wallets in Vietnam: extending the TAM model with trust and enjoyment. Cogent Business and Management, 8(1), 1-14.
Tsai, H., & Bagozzi, R. (2014). Contribution behavior in virtual communities: cognitive, emotional, and social influences. MIS Quarterly, 38(1), 143-163.
Undale, S., Kulkarni, A., & Patil, H. (2020). Perceived eWallet security: impact of COVID-19 pandemic. Vilakshan - XIMB Journal of Management, 1–16.
Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: integrating the technology acceptance model (TAM) and task technology fit (TIF) model. Computer Human Behavior, 67, 221-232.
Yang, Y., & Tan, Z. (2019). Investigating the influence of consumer behavior and governmental policy on the diffusion of electric vehicles in Beijing, China. Sustainability, 11(6967), 1-20.
Yeoh, A. (2020). ePenjana: remember to claim your RM50 e-wallet credit before 24 September. Retrieved 5 January, from https://www.thestar.com.my/tech/tech-news/2020/09/03.
Zhang, L., Fan, Y., Zhang, W., & Zhang, S. (2019). Extending the theory of planned behavior to explain the effects of cognitive factors across different kinds of green products. Sustainability, 11(4222), 1–17.
Zhang, X., Prybutok, V. R., & Strutton, D. (2007). Modeling influences on impulse purchasing behaviors during online marketing transactions. Journal of Marketing Theory and Practice, 15(1), 79-89.
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