Abstract
The use of mobile payment (m-payment) is growing exponentially in developing countries. A small number of investigations have been undertaken on what makes people continue to use m-payment in an African context. We combine the task technology fit (TTF) model, expectation-confirmation model (ECM), and trust dimension to explain the influence of continuance use of m-payment. We collected 384 valid questionnaire responses from Mozambique. The results show that the relevant constructs to explain continuance intention are use, individual performance, overall trust, and the moderation role of satisfaction.
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Afshan, S., & Sharif, A. (2016). Acceptance of mobile banking framework in Pakistan. Telematics and Informatics, 33(2), 370–387. https://doi.org/10.1016/j.tele.2015.09.005
Aiken, L. S., West, S. G., & Reno, R. R. (1991). Multiple regression: Testing and interpreting interactions. Sage.
Albashrawi, M., & Motiwalla, L. (2019). Privacy and personalization in continued usage intention of mobile banking: An integrative perspective. Information Systems Frontiers, 21(5), 1031–1043. https://doi.org/10.1007/s10796-017-9814-7
Alraimi, K. M., Zo, H., & Ciganek, A. P. (2015). Understanding the MOOCs continuance: The role of openness and reputation. Computers and Education, 80, 28–38. https://doi.org/10.1016/j.compedu.2014.08.006
APWG. (2021). Phishing Activity Trends Report 3rd Quarter 2021 (Issue November). https://docs.apwg.org/reports/apwg_trends_report_q3_2021.pdf
Batista, C., & Vicente, P. C. (2014). Introducing mobile money in rural Mozambique: Initial evidence from a field experiment. Nova Africa, 1301.https://doi.org/10.2139/ssrn.2384561
Batista, C., & Vicente, P. C. (2018). Improving access to savings through mobile money: Experimental evidence from smallholder farmers in Mozambique. Nova Africa, 1705.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921
Bhattacherjee, A., & Lin, C.-P. (2014). A unified model of IT continuance: Three complementary perspectives and crossover effects. European Journal of Information Systems, 24(4), 1–10. https://doi.org/10.1057/ejis.2013.36
Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185–216. https://doi.org/10.1177/135910457000100301
Carillo, K., Scornavacca, E., & Za, S. (2017). The role of media dependency in predicting continuance intention to use ubiquitous media systems. Information and Management, 54(3), 317–335. https://doi.org/10.1016/j.im.2016.09.002
Chang, I.-C., Liu, C.-C., & Chen, K. (2014). The effects of hedonic/utilitarian expectations and social influence on continuance intention to play online games. Internet Research, 24(1), 21–45. https://doi.org/10.1108/IntR-02-2012-0025
Chang, Y. P., & Zhu, D. H. (2012). The role of perceived social capital and flow experience in building users’ continuance intention to social networking sites in China. Computers in Human Behavior, 28(3), 995–1001. https://doi.org/10.1016/j.chb.2012.01.001
Chen, S. C., & Dhillon, G. S. (2003). Interpreting Dimensions of Consumer Trust in E-commerce. Information Technology and Management, 4, 303–318. https://doi.org/10.1023/a:1022962631249
Chen, Shih Chih, Yen, D. C., & Hwang, M. I. (2012). Factors influencing the continuance intention to the usage of Web 2.0: An empirical study. Computers in Human Behavior, 28(3), 933–941. https://doi.org/10.1016/j.chb.2011.12.014
Chen, X., & Li, S. (2017). Understanding continuance intention of mobile payment services: An empirical study. Journal of Computer Information Systems, 57(4), 287–298. https://doi.org/10.1080/08874417.2016.1180649
Chinn, W. W. (1998). The partial least squares approach to structural equation modelling. Modern Methods for Business Research, 295(2), 295–336.
Cho, J. (2016). The impact of post-adoption beliefs on the continued use of health apps. International Journal of Medical Informatics, 87, 75–83. https://doi.org/10.1016/j.ijmedinf.2015.12.016
Côrte-Real, N., Ruivo, P., & Oliveira, T. (2020). Leveraging internet of things and big data analytics initiatives in European and American firms: Is data quality a way to extract business value? Information and Management, 57(1). https://doi.org/10.1016/j.im.2019.01.003
YMandy, Dang, Gavin, Zhang Y., Brown, S. A., & Chen, H. (2020). Examining the impacts of mental workload and task-technology fit on user acceptance of the social media search system. Information Systems Frontiers, 22(3), 697–718. https://doi.org/10.1007/s10796-018-9879-y
Davison, R. M., & Martinsons, M. G. (2016). Context is king! Considering particularism in research design and reporting. Journal of Information Technology, 31(3), 241–249. https://doi.org/10.1057/jit.2015.19
DeLone, W. H., & Mclean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems / Spring, 19(4), 9–30. https://doi.org/10.1073/pnas.0914199107
Fan, J., Shao, M., Li, Y., & Huang, X. (2018a). Understanding users’ attitude toward mobile payment use: A comparative study between China and the USA. Industrial Management & Data Systems, 118(3), 524–540.
Fan, J., Shao, M., Li, Y., & Huang, X. (2018b). Understanding users’ attitude toward mobile payment use. Industrial Management & Data Systems, 118(3), 524–540. https://doi.org/10.1108/IMDS-06-2017-0268
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Franque, F. B., Oliveira, T., Tam, C., de Santini, F., & O. (2020). A meta-analysis of the quantitative studies in continuance intention to use an information system. Internet Research, 31(1), 123–158. https://doi.org/10.1108/INTR-03-2019-0103
Gao, L., & Waechter, K. A. (2015). Examining the role of initial trust in user adoption of mobile payment services: An empirical investigation. Information Systems Frontiers, 19, 1–24. https://doi.org/10.1007/s10796-015-9611-0
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. https://doi.org/10.1016/j.chb.2015.07.014
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in Online Shopping: An Integrated Mode. MIS Quarterly, 27(1), 51–90. https://doi.org/10.1017/CBO9781107415324.004
Gong, X., Lee, M. K. O., Liu, Z., & Zheng, X. (2020). Examining the role of tie strength in users’ continuance intention of second-generation mobile instant messaging services. Information Systems Frontiers, 22(1), 149–170. https://doi.org/10.1007/s10796-018-9852-9
Goodhue, D. L., & Thompson, R. (1995). Task-Technology Fit and Individual Performance. MIS Quaterly, 19(2), 213. https://doi.org/10.2307/249689
Götz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach. In Handbook of Partial Least Squares (pp. 691–711). Springer. https://doi.org/10.1007/978-3-540-32827-8_30
Hair Jr., J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A Primer on partial least squares structural equation modeling (PLS-SEM) (2° Edition). Sage Publications.
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. https://doi.org/10.1007/s11747-014-0403-8
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014
Humbani, M., & Wiese, M. (2018). A cashless society for all: Determining consumers’ readiness to adopt mobile payment services. Journal of African Business, 19(3), 409–429. https://doi.org/10.1080/15228916.2017.1396792
Humbani, M., & Wiese, M. (2019). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing, 37(2), 646–664. https://doi.org/10.1108/IJBM-03-2018-0072
Idemudia, E. C., Raisinghani, M. S., & Samuel-Ojo, O. (2018). The contributing factors of continuance usage of social media: An empirical analysis. Information Systems Frontiers, 20(6), 1267–1280. https://doi.org/10.1007/s10796-016-9721-3
INE. (2019). Resultados definitivos do VI recenseamento geral da população e habitação 2017. Instituto Nacional de Estatística (INE). http://www.ine.gov.mz/
Jack, W., & Suri, T. (2011). Mobile money: The economics of M-PESA.
Khalilzadeh, J., Ozturk, A. B., & Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460–474. https://doi.org/10.1016/j.chb.2017.01.001
Koksal, M. H. (2016). The intentions of Lebanese consumers to adopt mobile banking. International Journal of Bank Marketing, 34(3), 327–346. https://doi.org/10.1108/IJBM-03-2015-0025
Koloseni, D., & Mandari, H. (2017). Why mobile money users keep increasing? investigating the continuance usage of mobile money services in Tanzania. 26(2), 117–145.
Kujala, S., Mugge, R., & Miron-Shatz, T. (2017). The role of expectations in service evaluation: A longitudinal study of a proximity mobile payment service. International Journal of Human Computer Studies, 98, 51–61. https://doi.org/10.1016/j.ijhcs.2016.09.011
Larsen, T. J., Sørebø, A. M., & Sørebø, Ø. (2009). The role of task-technology fit as users’ motivation to continue information system use. Computers in Human Behavior, 25(3), 778–784. https://doi.org/10.1016/j.chb.2009.02.006
Lee, J. K., Park, J., Gregor, S., & Yoon, V. (2021). Axiomatic theories and improving the relevance of information systems research. Information Systems Journal, 32(1), 147–171. https://doi.org/10.1287/isre.2020.0958
Liébana-cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2018). A global approach to the analysis of user behavior in mobile payment systems in the new electronic environment. Service Business, 12(1), 25–64. https://doi.org/10.1007/s11628-017-0336-7
Liébana-Cabanillas, F., Singh, N., Kalinic, Z., & Carvajal-Trujillo, E. (2021). Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: A multi-analytical approach. Information Technology and Management, 22(2), 133–161. https://doi.org/10.1007/s10799-021-00328-6
Lu, J., Wei, J., Yu, C., & Liu, C. (2017). How do post-usage factors and espoused cultural values impact mobile payment continuation? Behaviour & Information Technology, 36(2), 140–164. https://doi.org/10.1080/0144929X.2016.1208773
Makina, D. (2017). Introduction to the financial services in Africa special issue. African Journal of Economic and Management Studies, 8(1), 2–7. https://doi.org/10.1108/AJEMS-03-2017-149
Mouakket, S. (2015). Factors influencing continuance intention to use social network sites: The Facebook case. Computers in Human Behavior, 53, 102–110. https://doi.org/10.1016/j.chb.2015.06.045
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43, 157–169. https://doi.org/10.1016/j.jretconser.2018.03.017
Odoom, R., & Kosiba, J. P. (2020). Mobile money usage and continuance intention among micro enterprises in an emerging market – the mediating role of agent credibility. Journal of Systems and Information Technology, 22(4), 97–117. https://doi.org/10.1108/JSIT-03-2019-0062
Oliveira, T., Alhinho, M., Rita, P., & Dhillon, G. (2017). Modelling and testing consumer trust dimensions in e-commerce. Computers in Human Behavior, 71, 153–164. https://doi.org/10.1016/j.chb.2017.01.050
Oliveira, T., Faria, M., Thomas, M. A., & Popovič, A. (2014). Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM. International Journal of Information Management, 34(5), 689–703. https://doi.org/10.1016/j.ijinfomgt.2014.06.004
Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior, 61, 404–414. https://doi.org/10.1016/j.chb.2016.03.030
Ouyang, Y., Tang, C., Rong, W., Zhang, L., Yin, C., & Xiong, Z. (2017). Task-technology fit aware expectation-confirmation model towards understanding of MOOCs continued usage. 50th Hawaii International Conference on System Sciences, 174–183.
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. https://doi.org/10.1080/02681102.2019.1701969
Palvia, P. (2009). The role of trust in e-commerce relational exchange: A unified model. Information and Management, 46(4), 213–220. https://doi.org/10.1016/j.im.2009.02.003
Park, M., Jun, J., & Park, H. (2017). Understanding mobile payment service continuous use intention: An expectation - Confirmation model and inertia. Quality Innovation Prosperity, 21(3), 78–94. https://doi.org/10.12776/QIP.V21I3.983
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
Rahi, S., Khan, M. M., & Alghizzawi, M. (2020). 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, ahead-of-p(ahead-of-print). https://doi.org/10.1108/IJQRM-03-2020-0074
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. https://doi.org/10.1108/IJBM-04-2020-0167
Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS. http://www.smartpls.com
Ryans, A. B. (1974). Estimating consumer preferences for a new durable brand in an established product class. Journal of Marketing Research, 11(4), 434–443. https://doi.org/10.2307/3151290
Shao, Z., Zhang, L., Li, X., & Guo, Y. (2019). Antecedents of trust and continuance intention in mobile payment platforms: The moderating effect of gender. Electronic Commerce Research and Applications, 33(11), 100823. https://doi.org/10.1016/j.elerap.2018.100823
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. https://doi.org/10.1016/j.ijinfomgt.2019.05.022
Sinha, M., Majra, H., Hutchins, J., & Saxena, R. (2019). Mobile payments in India: The privacy factor. International Journal of Bank Marketing, 37(1), 192–209. https://doi.org/10.1108/IJBM-05-2017-0099
Susanto, A., Chang, Y., & Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services. Industrial Management & Data Systems, 116(3), 508–525. https://doi.org/10.1108/imds-05-2015-0195
Talwar, S., Dhir, A., Khalil, A., Mohan, G., & Islam, A. K. M. N. (2020). Point of adoption and beyond. Initial trust and mobile-payment continuation intention. Journal of Retailing and Consumer Services, 55, 102086. https://doi.org/10.1016/j.jretconser.2020.102086
Tam, C., Loureiro, A., & Oliveira, T. (2019). The individual performance outcome behind e-commerce: Integrating information systems success and overall trust. Internet Research, 30(2), 439–462. https://doi.org/10.1108/INTR-06-2018-0262
Tam, C., & Oliveira, T. (2016a). Performance impact of mobile banking: Using the task-technology fit (TTF) approach. International Journal of Bank Marketing, 34(4), 434–457. https://doi.org/10.1108/IJBM-11-2014-0169
Tam, C., & Oliveira, T. (2016b). Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective. Computers in Human Behavior, 61, 233–244. https://doi.org/10.1016/j.chb.2016.03.016
Tam, C., & Oliveira, T. (2019). Does culture influence m-banking use and individual performance? Information & Management, 56(3), 356–363. https://doi.org/10.1016/j.im.2018.07.009
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. https://doi.org/10.1007/s10796-018-9864-5
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. https://doi.org/10.1016/j.chb.2021.106778
Verkijika, S. F. (2020). An affective response model for understanding the acceptance of mobile payment systems. Electronic Commerce Research and Applications, 39(08), 100905. https://doi.org/10.1016/j.elerap.2019.100905
Vodafone Group. (2016). M-Pesa - The world’s most successful money transfer service. https://www.vodafone.com/what-we-do/services/m-pesa
Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. https://doi.org/10.1016/j.chb.2016.10.028
Yu, L., Cao, X., Liu, Z., Gong, M., & Adeel, L. (2018). Understanding mobile payment users’ continuance intention: A trust transfer perspective. Internet Research, 28(2), 456–476. https://doi.org/10.1108/IntR-11-2016-0359
Zhou, T. (2011). The effect of initial trust on user adoption of mobile payment. Information Development, 27(4), 290–300. https://doi.org/10.1177/0266666911424075
Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085–1091. https://doi.org/10.1016/j.dss.2012.10.034
Zhou, T. (2014). Understanding the determinants of mobile payment continuance usage. Industrial Management & Data Systems, 114(6), 936–948. https://doi.org/10.1108/IMDS-02-2014-0068
Zhou, T. (2015). An empirical examination of users’ switch from online payment to mobile payment. International Journal of Technology and Human Interaction, 11(1), 55–66. https://doi.org/10.4018/ijthi.2015010104
Zhou, T., & Li, H. (2014). Understanding mobile SNS continuance usage in China from the perspectives of social influence and privacy concern. Computers in Human Behavior, 37, 283–289. https://doi.org/10.1016/j.chb.2014.05.008
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Franque, F.B., Oliveira, T. & Tam, C. Continuance Intention of Mobile Payment: TTF Model with Trust in an African Context. Inf Syst Front 25, 775–793 (2023). https://doi.org/10.1007/s10796-022-10263-8
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DOI: https://doi.org/10.1007/s10796-022-10263-8