Navigating Digital Inequality: Examining Factors Affecting Rural Customers’ Internet Banking Adoption in Post-COVID Bangladesh

  • Mohammad Abu Sayed Toyon Estonian Business School


As the world continues to navigate the new normal brought about by the COVID-19 pandemic, one issue that has come to the forefront is digital inequality. In Bangladesh, where a significant portion of the population resides in rural areas, the adoption of internet banking has been hindered by various factors. However, understanding these factors is crucial, especially now that digital transactions have become more important. This study aims to understand the factors influencing the adoption of internet banking services among rural customers in Bangladesh. To acquire data, a questionnaire was administered to 443 rural bank customers in the district of Barisal. The Exploratory Factor Analysis (EFA) revealed three primary factors: trust compatibility, service benefit, and access to consumer education. In addition, the research sought to determine if the identified factors, particularly access to consumer education, varied according to the occupation and income level of rural consumers. Using exhaustive Chi-squared Automatic Interaction Detection (CHAID) analysis, the findings revealed that access to consumer education differs significantly by occupation level, with business and service holders being more likely than farmers to have access to consumer education. This research contributes to the literature by providing insights into the adoption of internet banking by rural customers and informing policymakers about the special needs of this demographic.


Alhujran, O. (2009). Determinants of e-government services adoption in developing countries: A field survey and a case study. University of Wollongong.

Ashraf, M. M., Mia, M. A., & Hasan, N. (2014). Factors affecting mobile internet usages in Bangladesh. Bangladesh Journal of MIS, 6(2), 17-35.

Babar, Z. M. (2017). Digital divide: Concepts and reality in Bangladesh. Journal of Business, 2(2), 24-33.

BBS. (2022). Population and housing census 2022: Preliminary report. Bangladesh Bureau of Statistics (BBS).

Dasu, T., & Johnson, T. (2003). Exploratory data mining and data cleaning. John Wiley & Sons.

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

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

Dijk, J. v., & Hacker, K. (2003). The digital divide as a complex and dynamic phenomenon. The Information Society, 19(4), 315-326.

Field, A. (2009). Discovering statistics using SPSS (and sex and drugs and rock ‘n’ roll). SAGE Publications Ltd.

Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90.

Harun, M. A. (2023). Customers’ choice of the bank during the Covid-19 pandemic: The moderating effect of different banks in Bangladesh. South Asian Journal of Marketing, 4(1), 33-50.

Hertzum, M., Jørgensen, N., & Nørgaard, M. (2004). Usable security and e-banking: Ease of use vis-à-vis security. Australasian Journal of Information Systems, 11, 52-65.

Islam, M. N., & Inan, T. T. (2021). Exploring the fundamental factors of digital inequality in Bangladesh. SAGE Open, 11(2).

IWS. (2023, January 15). Internet World Stats.

Jaruwachirathanakul, B., & Fink, D. (2005). Internet banking adoption strategies for a developing country: The case of Thailand. Internet Research, 15(3), 295-311.

Kim, J. Y., Altinkemer, K., & Bisi, A. (2012). Yield management of workforce for IT service providers. Decision Support Systems, 53(1), 23-33.

Macevičiūtė, E., & Wilson, T. D. (2018). Digital means for reducing digital inequality: literature review. Informing Science: The International Journal of an Emerging Transdiscipline, 21, 269-287.

Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. The Academy of Management Review, 20(3), 709-734.

Milanovic, M., & Stamenkovic, M. (2016). CHAID decision tree: Methodological frame and application. Economic Themes, 54(4), 563-586.

Mugenda, O., & Mugenda, A. G. (2003). Research methods, quantitative and qualitative approaches. Act Press.

Ndubisi, N. O., & Sinti, Q. (2006). Consumers attitudes system’s characteristics an internet banking adoption in Malaysia. Management Research News, 29(1/2), 16-27.

Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the Technology Acceptance Model. International Journal of Electronic Commerce, 7(3), 101-134.

Rahman, M. F. (2023, January 15). Internet banking transactions surge in November. The Daily Star:

Rosbo, S. D. (2023). Bangladesh telecoms market report: Telecoms, mobile and broadband - statistics and analyses. Paul Budde Communication Pty Ltd.

Saha, S. (2013, October 6). Bangladesh: A bright spot in m-banking. The Daily Star.

Samaneh, B., & Mohammadi, S. (2009). An efficient model to improve customer acceptance of mobile banking. Proceedings of the World Congress on Engineering and Computer Science 2009 Vol II (pp. 1-4). WCECS.

Sathye, M. (1999). Adoption of internet banking by Australian consumers: An empirical investigation. International Journal of Bank Marketing, 17(7), 324-334.

Stern, M. J., Adams, A. E., & Elsasser, S. (2009). Digital inequality and place: The effects of technological diffusion on internet proficiency and usage across rural, suburban, and urban counties. Sociological Inquiry, 79(4), 391-417.

Suh, B., & Han, I. (2002). Effect of trust on customers’ acceptance of internet banking. Electronic Commerce Research and Applications, 1(3/4), 247-263.

Sukkar, A. A., & Hasan, H. (2005). Toward a model for the acceptance of internet banking in developing countries. Information Technology for Development, 11(4), 381-398.

Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.

Wang, Y.‐S., Wang, Y.‐M., Lin, H.‐H., & Tang, T.‐I. (2003). Determinants of user acceptance of internet banking: An empirical study. International Journal of Service Industry Management, 14(5), 501-519.

Yousafzai, S. Y., Foxall, G. R., & Pallister, J. G. (2007). Technology acceptance: A meta-analysis of the TAM: Part 2. Journal of Modelling in Management, 2(3), 281-304.
How to Cite
TOYON, Mohammad Abu Sayed. Navigating Digital Inequality: Examining Factors Affecting Rural Customers’ Internet Banking Adoption in Post-COVID Bangladesh. International Journal of Business and Technology Management, [S.l.], v. 5, n. 1, p. 501-513, apr. 2023. ISSN 2682-7646. Available at: <>. Date accessed: 29 sep. 2023.