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Development of E-banking channels and market share in developing countries

Author

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  • Ali Nazaritehrani

    (University of Science and Culture)

  • Behzad Mashali

    (University of Science and Culture)

Abstract

There is fierce global competition within the banking industry. Therefore, banks endeavor to grow and strive to increase their market share. We analyzed the effect of developing innovative channels of presenting bank services on banks’ market share. The statistical population of this research was Shahr bank’s central headquarter and its branches in Tehran, Iran. We developed questionnaires for gathering the data. The validity and reliability of the scales were tested by EFA, CFA, experts’ opinion, and Cronbach’s alpha. We used linear regression to assess the impact of innovative channels, including internet banking, automatic teller machines (ATMs), mobile banking, telephone banking (TB), and point of sales (POS) on banks’ market share. The results indicated that some of these channels, including internet banking, POS, and TB, positively affect a bank’s market share. The effect of two other platforms, including mobile banking and ATM development, on banks’ market share was rejected. The findings of this study expand our understanding of how bank managers can improve their market share by developing innovative e-banking channels.

Suggested Citation

  • Ali Nazaritehrani & Behzad Mashali, 2020. "Development of E-banking channels and market share in developing countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
  • Handle: RePEc:spr:fininn:v:6:y:2020:i:1:d:10.1186_s40854-020-0171-z
    DOI: 10.1186/s40854-020-0171-z
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    4. Chang, Yung-Chi & Enkhjargal, Uguumur & Huang, Chen-I & Lin, Wen-Ling & Ho, Chi-Ming, 2020. "Factors Affecting the Internet Banking Adoption," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 54(3), pages 117-131.
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    7. Jin, Chenglu & Chen, Rongda & Cheng, Diandian & Mo, Sitian & Yang, Ke, 2020. "The dependency measures of commercial bank risks: Using an optimal copula selection method based on non-parametric kernel density," Finance Research Letters, Elsevier, vol. 37(C).
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