Impact of Perceived Severity and Susceptibility of Covid-19 Pandemic on m-Payment Continuance Intention: Using Technology Continuance Theory

  • Kin Leong Tang Universiti Tunku Abdul Rahman
  • Pei Meng Tan Universiti Tunku Abdul Rahman
  • Chun Lam Fong Universiti Tunku Abdul Rahman
Keywords: m-payment, continuance intention, perceived susceptibility, perceived severity, satisfaction


The purpose of this study is to look at the effect of customers' perceptions of COVID-19 susceptibility and severity on their m-payment confirmation, which leads to satisfaction and hence a continuance intention to use m-payment. An online questionnaire was used to conduct a survey on m-payment users to investigate the variables impacting their intention to continue using m-payment. Only experienced m-payment users were qualified to participate in this survey, and thus a purposive sampling technique was used. The data was collected between September and October 2021, and the sample includes 184 valid responses for empirical data analysis. The results show that all hypotheses are found to be significant. Perceived susceptibility and severity have a positive impact on confirmation and, in turn, user satisfaction. It is also found that attitude and satisfaction have an association with continuance intention. From the theoretical perspective, it provides a better understanding of the impact of perceived susceptibility and perceived severity on continuance intention of m-payment. At the practical level, the findings give a deeper insight into the influence of antecedent factors on m-payment continuance intention and its ability to retain users. This study regards perceived susceptibility and perceived severity as critical factors in user confirmation of the benefit of m-payment as the financial technology alternative to maintain social distance and to prevent the spread of the SARS-COV-2 virus during the pandemic. Perceived susceptibility and perceived severity were incorporated into the Technology Continuance Theory (TCT) to expand the knowledge of the impact of COVID-19 pandemic on m-payment continuance intention.


Download data is not yet available.


Alghamdi, M., & Basahel, S. (2021). COVID-19 and continuance intention to use mobile payment technology: A moderated mediation model. International Journal of Human Potentials Management, 3(2).

Amoroso, D. L., Ackaradejruangsri, P., & Lim, R. A. (2017). The impact of inertia as mediator and antecedent on consumer loyalty and continuance intention. International Journal of Customer Relationship Marketing and Management, 8(2), 1–20.

Azman, N. H. (2021). iPay88 e-wallet transactions grew 6-fold in 2020.

Cao, X., Yu, L., Liu, Z., Gong, M., & Adeel, L. (2018). Understanding mobile payment users’ continuance intention: a trust transfer perspective. Internet Research, 28(2), 456–476.

Chen, X., Carpenter, D., Li, X., Chen, C. C., & Hung, S. Y. (2018). Why do individuals continue using mobile payments – A qualitative study in China. Proceedings of the Annual Hawaii International Conference on System Sciences, 2018-Janua(January), 1452–1461.

Chen, X., & Li, S. (2017). Understanding continuance intention of mobile payment services: An empirical study. Journal of Computer Information Systems, 57(4), 287–298.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(July), 155–159.

Coronavirus (COVID-19) latest insights. (2022).

Dahlberg, T., Guo, J., & Ondrus, J. (2015). A critical review of mobile payment research. Electronic Commerce Research and Applications, 14(5), 265–284.

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).

Deng, S., Wang, W., Xie, P., Chao, Y., & Zhu, J. (2020). Perceived severity of COVID-19 and post-pandemic consumption willingness: The roles of boredom and sensation-seeking. Frontiers in Psychology, 11.

DigitalEdge. (2022). E-Wallet: Digital payments pivotal to Malaysia’s financial services industry.

Franque, F. B., Oliveira, T., & Tam, C. (2021). Understanding the factors of mobile payment continuance intention: empirical test in an African context. Heliyon, 7(8), e07807.

Han, M., Wu, J., Wang, Y., & Hong, M. (2018). A model and empirical study on the user’s continuance intention in online China brand communities based on customer-perceived benefits. Journal of Open Innovation: Technology, Market, and Complexity, 4(4), 1–20.

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.

Hepola, J., Leppäniemi, M., & Karjaluoto, H. (2020). Is it all about consumer engagement? Explaining continuance intention for utilitarian and hedonic service consumption. Journal of Retailing and Consumer Services, 57, 102232.

Hong, C., Choi, H. (Hailey), Choi, E.-K. (Cindy), & Joung, H.-W. (David). (2021). Factors affecting customer intention to use online food delivery services before and during the COVID-19 pandemic. Journal of Hospitality and Tourism Management, 48, 509–518.

Humbani, M., & Wiese, M. (2019). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing.

Ifinedo, P. (2018). Determinants of students’ continuance intention to use blogs to learn: an empirical investigation. Behaviour and Information Technology, 37(4), 381–392.

Jaiswal, D., & Thaichon, P. (2022). Mobile wallets adoption : pre- and post-adoption dynamics of mobile wallets usage.

Japan Coronavirus map and case Ccount. (2022).

Jordan, P. J., & Troth, A. C. (2020). Common method bias in applied settings: The dilemma of researching in organizations. Australian Journal of Management, 45(1), 3–14.

Khayer, A., & Bao, Y. (2019). The continuance usage intention of Alipay. The Bottom Line, 32(3), 211–229.

Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of E-Collaboration, 11(4), 1–10.

Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227–261.

Luo, Y., Cheng, Y., Sui, M., & Napoli, C. (2021). The moderating effects of perceived severity on the generational gap in preventive behaviors during the COVID-19 pandemic in the U.S.

Memon, M. A., Ting, H., Cheah, J.-H., Ramayah, T., Chuah, F., & Cham, T. H. (2020). Sample size for survey research: Review and recommendations. Journal of Applied Structural Equation Modeling, 4(2), i–xx.

Ministry of Health Malaysia. (2022). COVIDNOW in Malaysia - COVIDNOW.

Omicron BA.5 variant likely to cause spike in cases, Khairy says. (2022).

PR Newswire. (2022). Malaysia prepaid card and digital wallet markets report 2022: Malaysian banks are collaborating with digital payment service providers to enter the prepaid market.

Puriwat, W., & Tripopsakul, S. (2021). Explaining an adoption and continuance intention to use contactless payment technologies: During the covid-19 pandemic. Emerging Science Journal, 5(1), 85–95.

Raman, P., & Aashish, K. (2021). To continue or not to continue: a structural analysis of antecedents of mobile payment systems in India. International Journal of Bank Marketing, 39(2), 242–271.

Sreelakshmi, C. C., & Prathap, S. K. (2020). Continuance adoption of mobile-based payments in Covid-19 context: An integrated framework of health belief model and expectation confirmation model. International Journal of Pervasive Computing and Communications, 16(4), 351–369.

Statista. (2021). Malaysia: mobile payment users 2025.

Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1), 243–257.

Tamara, D., Widjaja, C., Elista, F., & Yassar, S. (2021). Millenials endorse environment factors as continuance intention of the mobile payment technology during Covid-19 in Indonesia. Journal of Research in Business, Economics, and Education, 3(4).

Tan, J. (2020). Mastercard: Malaysia has highest mobile wallet usage in Southeast Asia.

Tang, K. L., Aik, N. C., & Choong, W. L. (2021). A modified UTAUT in the context of m-payment usage intention in Malaysia. Journal of Applied Structural Equation Modeling, 5(1), 40–59.

Tehseen, S., Ramayah, T., & Sajilan, S. (2017). Testing and controlling for Common Method Variance: A review of available methods. Journal of Management Sciences, 4(2), 142–168.

Thach, L., Riewe, S., & Camillo, A. (2021). Generational cohort theory and wine: analyzing how gen Z differs from other American wine consuming generations. International Journal of Wine Business Research, 33(1), 1–27.

Types of payment systems. (n.d.). Retrieved April 29, 2022, from

Warkentin, M., Johnston, A. C., Shropshire, J., & Barnett, W. D. (2016). Continuance of protective security behavior: A longitudinal study. Decision Support Systems, 92.

Weng, G. S., Zailani, S., Iranmanesh, M., & Hyun, S. S. (2017). Mobile taxi booking application service’s continuance usage intention by users. Transportation Research Part D: Transport and Environment, 57.

Zhao, Yang, Ni, Q., & Zhou, R. (2018). What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age. International Journal of Information Management, 43(August), 342–350.

Zhao, Yuyang, & Bacao, F. (2020). A comprehensive model integrating UTAUT and ECM with espoused cultural values for investigating users’ continuance intention of using mobile payment. ACM International Conference Proceeding Series, September, 155–161.

How to Cite
Tang, K. L., Tan, P. M., & Fong, C. L. (2022). Impact of Perceived Severity and Susceptibility of Covid-19 Pandemic on m-Payment Continuance Intention: Using Technology Continuance Theory. The Journal of Management Theory and Practice (JMTP), 3(3), 1-9.
Marketing & Management