Navigating the Gap: Exploring Low Adoption of Financial Mobile Apps in Rural Areas of Developing Countries and Enhancing User Experience
Year: 2024
Type: article
Abstract: This study investigates the factors contributing to the low adoption of financial mobile applications among rural populations in Bangladesh. Through a survey including almost 300 respondents from diverse backgrounds, the research identifies significant barriers such as low literacy rates and exceedingly intricate app designs. It focuses on popular platforms such as Bkash, Nagad, Rocket, and UPAY, looks at usage patterns, and makes suggestions to make the platforms more accessible and easier to use, especially for older adults and less literate customers. The proposed solutions leverage state-of-the-art technologies such as artificial intelligence, natural language processing, and notions of human-computer interaction to enhance user experiences. The proposed solution demonstrates a significant improvement in the performance of the financial app compared to the conventional method, as indicated by a t-score of approximately -6.47 and a p-value of 0.000115. Even though financial mobile apps have improved access to effective money management and revolutionized global financial ecosystems, Bangladesh's rural areas are still disproportionately represented in this digital revolution. This study offers focused solutions that support inclusivity, especially for excluded groups, and aims to address the root causes of poor adoption. Through overcoming these obstacles, the study advances the more general objective of promoting economic growth and financial independence in Bangladesh's rural areas. The results underscore the significance of user-centered design and focused interventions in closing the digital gap and optimizing the influence of mobile financial technologies on international initiatives for financial inclusion.
Authors: Naimul Haque, Kaniz Fatiha, Tasfia Tasneem Annesha
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6893020661
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