Exploring customer intentions to adopt mobile banking services: evidence from a developing country

  • Received March 9, 2020;
    Accepted April 27, 2020;
    Published May 19, 2020
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/bbs.15(2).2020.10
  • Article Info
    Volume 15 2020, Issue #2, pp. 105-116
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This work is licensed under a Creative Commons Attribution 4.0 International License

As the number of smart phone users and the popularity of Internet among people are growing day by day in Bangladesh, it became necessary for Bangladeshi local banks to provide mobile banking services to their customers. Therefore, this study seeks to identify the crucial and determining factors that may affect the intention of customers to use mobile banking services. The sample size in this study is 91, in which majority are the students of Business Studies. All respondents have mobile banking at the time of the survey. The samples in the study were mainly drawn from the private university students (i.e. Business Administration students) and faculty members, and some bank officers participated as sample respondents in this study. A non-probability random sampling method is applied, and a 5% significance level is used to accept the hypotheses. Cronbach alpha (α) of 0.7 and above is considered to measure the reliability of the item wise variables. This study examines six variables (perceived usefulness, perceived ease of use, trust, security, perceived privacy, and technology competency) to analyze their impact on the behavioral intention of banking customers to use mobile banking services. Three variables, namely perceived usefulness, security, and technology competency, are found to be significant predictors of customers’ intent to use mobile banking in Bangladesh. For analytical purposes, SPSS version 23.0 is used to test hypotheses. The paper also provides significant implications for bank managers to increase the adoption of mobile banking for their sustainability.

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    • Figure 1. Conceptual framework of the study
    • Table 1. References to the sources of accepted questionnaires
    • Table 2. Item wise of the Cronbach Alpha (α) value
    • Table 3. Sample characteristics
    • Table 4. Results of the coefficient value (regression analysis)
    • Conceptualization
      Ayeasha Akhter, Ahmed Al Asheq
    • Formal Analysis
      Ayeasha Akhter, Ahmed Al Asheq, Md. Uzzal Hossain, Md. Mobarak Karim
    • Funding acquisition
      Ayeasha Akhter, Md. Uzzal Hossain, Md. Mobarak Karim
    • Methodology
      Ayeasha Akhter, Ahmed Al Asheq, Md. Uzzal Hossain
    • Project administration
      Ayeasha Akhter, Md. Uzzal Hossain, Md. Mobarak Karim
    • Resources
      Ayeasha Akhter, Md. Uzzal Hossain, Md. Mobarak Karim
    • Validation
      Ayeasha Akhter, Ahmed Al Asheq, Md. Mobarak Karim
    • Visualization
      Ayeasha Akhter, Md. Uzzal Hossain, Md. Mobarak Karim
    • Writing – original draft
      Ayeasha Akhter, Ahmed Al Asheq
    • Writing – review & editing
      Ayeasha Akhter, Ahmed Al Asheq, Md. Uzzal Hossain
    • Software
      Ahmed Al Asheq, Md. Uzzal Hossain, Md. Mobarak Karim
    • Supervision
      Ahmed Al Asheq, Md. Uzzal Hossain
    • Data curation
      Md. Uzzal Hossain, Md. Mobarak Karim