Continuous intention to use e-wallets in Indonesia: The impact of e-wallets features
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Author(s)Arief Prima JohanLink to ORCID Index: https://orcid.org/0000-0002-4026-2094
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Niki LukviarmanLink to ORCID Index: https://orcid.org/0000-0003-1430-6601
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Rahmat Eka PutraLink to ORCID Index: https://orcid.org/0000-0003-0745-4462
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DOIhttp://dx.doi.org/10.21511/im.18(4).2022.07
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Article InfoVolume 18 2022, Issue #4, pp. 74-85
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Increased use of e-wallets in Indonesia has resulted in high competition among providers. Hence, companies must act to retain customers and impose continuous utilization of their services. This study aimed to investigate the determinants of continuous intention to use the preferred e-wallet in Indonesia. The framework was drawn from the technology continuance theory (TCT) with modifications to fit the e-wallet settings. This study assessed the effect of e-wallet features on continuous intention to use, with attitudes and satisfaction as intervening factors. Data were collected from the general population in Indonesia who uses e-wallets and possesses at least two accounts on different platforms. A total of 948 samples were generated using a web-based self-administrated survey. The data were analyzed using AMOS-SEM by assessing construct validity and reliability, as well as measurement and structural models. The analysis confirms the effect of attitudes and satisfaction on continuous intention. The findings also highlighted the positive impact of service compatibility and merchant networks on attitudes and satisfaction and the positive impact of perceived security toward satisfaction. Unexpected results revealed a strong and direct impact of value of reward programs and merchant networks toward continuance intentions. This study concludes that the modifications of TCT into the e-wallet settings can predict users’ post-adoption behavior.
Acknowledgment
This study is fully funded by the Directorate General of Higher Education of Indonesia with grant number 104/E4.1/AK.04.PT/2021; LPPM: T/37/UN.16.17/PT.01.03/PD UPT- Soshum/2021.
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JEL Classification (Paper profile tab)M31, G23
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References42
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Tables5
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Figures2
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- Figure 1. Research framework
- Figure 2. Final structural model
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- Table 1. Respondents’ profiles
- Table 2. CFA and structural model fit
- Table 3. Quality construct and correlation
- Table 4. Hypotheses testing
- Table A1. Items and factor loading
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- Abdul-Halim, N. A., Vafaei-Zadeh, A., Hanifah, H., Teoh, A. P., & Nawaser, K. (2022). Understanding the determinants of e-wallet continuance usage intention in Malaysia. Quality and Quantity, 56(5), 3413-3439.
- Al-Emran, M., Arpaci, I., & Salloum, S. A. (2020). An empirical examination of continuous intention to use m-learning: An integrated model. Education and Information Technologies, 25(4), 2899-2918.
- Bank Indonesia. (2021). Bersinergi Membangun Optimisme Pemulihan Ekonomi. In Laporan Perekonomian Indonesia 2020.
- Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370.
- Bounie, D., François, A., & Van Hove, L. (2016). Consumer Payment Preferences, Network Externalities, and Merchant Card Acceptance: An Empirical Investigation. Review of Industrial Organization, 51(3), 257-290.
- Chawla, D., & Joshi, H. (2019). Consumer attitude and intention to adopt mobile wallet in India – An empirical study. International Journal of Bank Marketing, 37(7), 1590-1618.
- Chin, W. W. (2010). How to Write Up and Report PLS Analyses. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of Partial Least Squares: Concepts, Methods and Applications (pp. 655-690). Springer.
- Daragmeh, A., Sági, J., & Zéman, Z. (2021). Continuous intention to use e-wallet in the context of the covid-19 pandemic: Integrating the health belief model (HBM) and technology continuous theory (TCT). Journal of Open Innovation: Technology, Market, and Complexity, 7(2), 132.
- Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.
- Enck, W., Ongtang, M., & McDaniel, P. (2009). On lightweight mobile phone application certification. Proceedings of the ACM Conference on Computer and Communications Security (pp. 235-245).
- Flavián, C., Guinalíu, M., & Gurrea, R. (2006). The role played by perceived usability, satisfaction and consumer trust on website loyalty. Information & Management, 43(1), 1-14.
- Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388.
- GSMA. (2021). The Mobile Economy 2021.
- Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis (7th ed.). Pearson Education Limited.
- Ipsos. (2020). The evolution of the digital wallet: driving the next wave of growth.
- Jenkins, B. (2008). Developing Mobile Money Ecosystems. IFC and the Harvard Kennedy School.
- Jiang, Y., Wang, X., & Yuen, K. F. (2021). Augmented reality shopping application usage: The influence of attitude, value, and characteristics of innovation. Journal of Retailing and Consumer Services, 63, 102720.
- Khan, A., & Khan, S. (2022). Purchasing grocery online in a nonmetro city: Investigating the role of convenience, security, and variety. Journal of Public Affairs, 22(2), e2497.
- Kleijnen, M., de Ruyter, K., & Wetzels, M. (2007). An assessment of value creation in mobile service delivery and the moderating role of time consciousness. Journal of Retailing, 83(1), 33-46.
- Kuester, M., & Benkenstein, M. (2014). Turning dissatisfied into satisfied customers: How referral reward programs affect the referrer׳s attitude and loyalty toward the recommended service provider. Journal of Retailing and Consumer Services, 21(6), 897-904.
- Kumar, A., Adlakaha, A., & Mukherjee, K. (2018). The effect of perceived security and grievance redressal on continuance intention to use M-wallets in a developing country. International Journal of Bank Marketing, 36(7), 1170-1189.
- Lee, S. M., & Lee, D. H. (2020). Healthcare wearable devices: an analysis of key factors for continuous use intention. Service Business, 14(4), 503-531.
- Li, F., Lu, H., Hou, M., Cui, K., & Darbandi, M. (2021). Customer satisfaction with bank services: The role of cloud services, security, e-learning and service quality. Technology in Society, 64, 101487.
- Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309-320.
- Nesset, E., Bergem, O., Nervik, B., Schiøll Sørlie, E., & Helgesen, Ø. (2021). Building chain loyalty in grocery retailing by means of loyalty programs – A study of ‘the Norwegian case’. Journal of Retailing and Consumer Services, 60, 102450.
- O’Brien, L., & Jones, C. (1995). Do Rewards Really Create Loyalty? Harvard Business Review, 73(3), 75-82.
- Ozturk, A. B., Bilgihan, A., Nusair, K., & Okumus, F. (2016). What keeps the mobile hotel booking users loyal? Investigating the roles of self-efficacy, compatibility, perceived ease of use, and perceived convenience. International Journal of Information Management, 36(6), 1350-1359.
- Pal, A., De’, R., Herath, T., & Rao, H. R. (2019). A review of contextual factors affecting mobile payment adoption and use. Journal of Banking and Financial Technology, 3(1), 43-57.
- Pal, A., Herath, T., De’, R., & Rao, H. R. (2020). Contextual facilitators and barriers influencing the continued use of mobile payment services in a developing country: insights from adopters in India. Information Technology for Development, 26(2), 394-420.
- Phuong, N. N. D., Ngoc, N., Luan, L. T., Van Dong, V., & Le Nhat Khanh, N. (2020). Examining customers’ continuance intentions towards e-wallet usage: The emergence of mobile payment acceptance in Vietnam. Journal of Asian Finance, Economics and Business, 7(9), 505-516.
- Rahi, S., Khan, M. M., & Alghizzawi, M. (2021). Extension of technology continuance theory (TCT) with task technology fit (TTF) in the context of Internet banking user continuance intention. International Journal of Quality and Reliability Management, 38(4), 986-1004.
- Sebetci, Ö. (2018). Enhancing end-user satisfaction through technology compatibility: An assessment on health information system. Health Policy and Technology, 7(3), 265-274.
- Shaw, N., Eschenbrenner, B., & Brand, B. M. (2022). Towards a Mobile App Diffusion of Innovations model: A multinational study of mobile wallet adoption. Journal of Retailing and Consumer Services, 64, 102768.
- Singh, N., Sinha, N., & Liébana-Cabanillas, F. J. (2020). Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use and social influence. International Journal of Information Management, 50, 191-205.
- Tanford, S. (2013). The impact of tier level on attitudinal and behavioral loyalty of hotel reward program members. International Journal of Hospitality Management, 34, 285-294.
- Teng, S., & Khong, K. W. (2021). Examining actual consumer usage of E-wallet: A case study of big data analytics. Computers in Human Behavior, 121, 106778.
- Tsai, Y.-T., & Tiwasing, P. (2021). Customers’ intention to adopt smart lockers in last-mile delivery service: A multi-theory perspective. Journal of Retailing and Consumer Services, 61, 102514.
- Van Noort, G., Kerkhof, P., & Fennis, B. M. (2008). The persuasiveness of online safety cues: The impact of prevention focus compatibility of Web content on consumers’ risk perceptions, attitudes, and intentions. Journal of Interactive Marketing, 22(4), 58-72.
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425-478.
- Venkatesh, V., & Balla, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Science, 39(2), 273-315.
- Verma, P. (2020). The effect of presentation, product availability and ease upon transaction reliability for online food delivery aggregator applications–moderated mediated model. Journal of Foodservice Business Research, 23(4), 285-304.
- Zhou, T. (2015). The effect of network externality on mobile social network site continuance. Program: electronic library and information systems, 49(3), 289-304.
