Why Are Egyptian Mobile Banking Users Dissatisfied? An Exploratory Text Mining Analysis
DOI:
https://doi.org/10.56830/IJAMS07202502Keywords:
Mobile Banking Applications, Service Quality Dimensions, Text Mining Approach, Latent Dirichlet Allocation (LDA), Online Customer Reviews (OCR)Abstract
This research aims to explore the main mobile banking service quality dimensions that lead to shaping customer dissatisfaction in the Egyptian banking sector. This research was conducted on the top ten Mobile banking applications in Egypt, according to Statista (2023). Data were collected from Google Play Store as reviews covering the period from January 2020 to May 2024 were extracted from the mobile banking application's URL using Python code applied on Google Colab. Topic modeling was used to explore the main dimensions causing dissatisfaction by applying the Latent Dirichlet Allocation (LDA) method through Orange data mining software, analyzing 4,634 negative user reviews to uncover the latent dimensions of mobile banking service quality. The findings support that the main dissatisfiers were ranked from highest to lowest importance: customer support, login problems, faulty updates, and security. The implications of this study are to support the improvement of mobile banking services and help banks develop more effective digital marketing strategies that fix the main customer dissatisfaction factors, and deliver high-quality services based on the findings, which can serve as a competitive advantage for banks. This study contributes to the literature by understanding mobile banking dimensions in the Egyptian market depending on analyzing thousands of real customer reviews and ranking their importance according to their MTP in the corpus.
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