Identifying key determinants of e-banking during COVID-19 in Bangladesh – Case Study on Chattogram city

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Over the past two years, e-banking services became very popular and safe transaction processes in the context of COVID-19 in Bangladesh. The purpose of this study is to analyze how the pandemic has affected Bangladesh’s e-banking system. Using stratified random sampling in a randomized block design, a questionnaire was developed that registered participants’ responses on a five-point Likert scale to examine the current state of e-banking during the COVID-19 pandemic (January-February 2022). Survey response data from 200 respondents in the commercial port city of Chattogram, Bangladesh, were delivered and returned via e-mail and hand-to-hand delivery, to enable the researcher to learn users’ opinions and e-banking satisfaction levels. To test the hypotheses, the study applied the Kolmogorov-Smirnov test, the Shapiro-Wilk test, Spearman’s rho correlation coefficient, the Mann-Whitney U test, and the Kruskal-Wallis H test. The study found that e-banking infrastructure facility, customer e-banking awareness, and the e-banking security service facility were important determinants in increasing bank e-service quality. The e-banking infrastructure and security services facility impressed younger users more than older customers (mean performance: 3.21 and 2.85 vs. 2.48 and 2.16, respectively). Educational qualifications did not affect perceptions of bank e-service quality, the e-banking infrastructure facility, customer e-banking professional knowledge, customer e-banking awareness, and the e-banking security service facility. Customers reported more fascination with private banks than with government-owned banks regarding bank e-service quality, e-banking infrastructure facilities, and customer e-banking awareness (mean performance: 3.51, 3.17, and 4.19 vs. 2.97, 2.29, and 3.65, respectively). Moreover, income level affected customers’ e-banking professional knowledge.

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    • Table 1. Descriptive statistics and normality test
    • Table 2. Spearman’s rho correlation coefficient test
    • Table 3. Mann-Whitney test for gender
    • Table 4. Kruskal-Wallis test for age group
    • Table 5. Kruskal-Wallis test for education
    • Table 6. Mann-Whitney test for government-owned and private banks
    • Table 7. Kruskal-Wallis test for income level
    • Conceptualization
      Md. Shahnur Azad Chowdhury, Engg Md. Shahidul Islam, Manjurul Alam Mazumder, Sayma Hoque, Habib Ullah
    • Formal Analysis
      Md. Shahnur Azad Chowdhury, Manjurul Alam Mazumder
    • Funding acquisition
      Md. Shahnur Azad Chowdhury, Engg Md. Shahidul Islam, Sayma Hoque
    • Resources
      Md. Shahnur Azad Chowdhury, Sayma Hoque, Habib Ullah
    • Supervision
      Md. Shahnur Azad Chowdhury
    • Writing – original draft
      Md. Shahnur Azad Chowdhury, Engg Md. Shahidul Islam, Manjurul Alam Mazumder
    • Writing – review & editing
      Md. Shahnur Azad Chowdhury, Manjurul Alam Mazumder
    • Methodology
      Engg Md. Shahidul Islam
    • Software
      Engg Md. Shahidul Islam, Manjurul Alam Mazumder
    • Validation
      Engg Md. Shahidul Islam, Sayma Hoque, Habib Ullah
    • Data curation
      Manjurul Alam Mazumder
    • Visualization
      Sayma Hoque, Habib Ullah
    • Project administration
      Habib Ullah