网上银行对埃塞俄比亚商业银行底线的影响

Prof. (Dr.) Krishna Gadasandula , Mr. Belaynew Ayalew, Dr. Nageswara Rao Thadvuai, Dr. Anitha Lourdu James, Dr. Mohamed Zaheeruddin
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引用次数: 0

摘要

目的:研究电子银行业务如何影响埃塞俄比亚商业银行的底线是本研究的主要动机。研究的总体目标是分析一系列变量对埃塞俄比亚商业银行业务的影响,这些变量包括自动取款机的使用、销售点借记卡的接受程度、手机银行和网上银行、银行规模以及管理效率。 研究方法:在 2018-2022 年期间,本研究以九家商业银行为主要分析单位。我们精心挑选了这九家商业银行,因为它们在研究期间提供了完整的数据和信息。在调查中,我们使用了一种特殊类型的数据,即面板数据。自动取款机(ATM)、手机银行、销售点(POS)、借记卡(DC)和网上银行(IB)等电子银行服务以及银行规模和管理效率作为本研究的补充控制指标。本研究使用了描述性和推论性统计方法来帮助实现研究目标。平均值、方差和标准差是本研究描述性分析中使用的一些中心倾向指标。计量经济学分析中使用了静态面板数据模型。这些模型包括集合普通最小二乘法(POLS)、固定效应和随机效应模型。 分析结果根据固定效应模型,以资产回报率(ROA)衡量的商业银行业绩受移动银行业务对数和管理效率的负面影响。ROA 受银行规模和网络银行业务普及率对数的正向显著影响。因此,商业银行可以通过重新评估其某些电子银行产品,特别是移动银行业务来获益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Effect of Online Banking on Ethiopia's Commercial Banks' Bottom Lines
Purpose: Examining how electronic banking affects the bottom lines of Ethiopia's commercial banks was the primary motivation for this research. The study's overarching goal is to analyse the effect on commercial banking in Ethiopia of a number of variables including ATM usage, debit card acceptance at points of sale, mobile and internet banking, bank size, and management effectiveness. Methodology: Over the course of 2018–2022, this study focused on nine commercial banks as its primary unit of analysis. These nine commercial banks were chosen with care since they provided complete data and information during the study period. In our investigation, we used a special type of data called panel data. Separate electronic banking services such as ATMs, mobile banking, point of sale (POS), debit cards (DC), and internet banking (IB), as well as bank size and managerial efficiency, serve as supplementary controls in this investigation. Both descriptive and inferential statistics were used to help the study reach its goal. Mean, variance, and standard deviation are some of the central tendency measures that have been used in the study's descriptive analysis. Static panel data models were used for the econometric analysis in this work. These included the pooled ordinary least squares (POLS), fixed effect, and random effect models. Results: Commercial banks' performance, as measured by return on asset (ROA), is negatively impacted by the logarithm of mobile banking and management efficiency, according to the fixed effect model. ROA is positively and significantly impacted by bank size and the logarithmic prevalence of internet banking. For this reason, commercial banks could benefit from revaluating certain of their electronic banking offerings, especially mobile banking.
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