Abstract:
This study evaluates the cost-benefit performance of EasyPaisa, a prominent mobile payment platform in Pakistan, from the perspective of consumers engaged in informal and semi-formal supply chains. Recognizing the growing role of mobile finance in digitally transforming economic transactions, the research adopts a method approach to explore the quantitative indicators. Quantitative data were collected via a structured questionnaire from 118 active users. A theoretical cost-benefit framework, grounded in behavioral economics, was employed to examine the influence of perceived costs (e.g., service charges, security risks) and perceived benefits (e.g., convenience, transaction speed, user empowerment) on overall user perception. Reliability testing confirmed strong internal consistency (Cronbach’s α > 0.77), and statistical analysis using SPSS revealed that perceived benefits had a significant positive effect on overall perception (β = 0.690, p < 0.001), whereas perceived costs exerted a moderate negative influence (β = –0.274, p < 0.001), explaining over 61% of the total variance. The study concludes that EasyPaisa offers net positive utility to most users, particularly in terms of convenience and accessibility, yet its long-term sustainability in low-income segments may be threatened by fee sensitivity and inconsistent support mechanisms. Based on the findings, the study proposes strategic recommendations including: introducing tiered pricing structures, expanding multilingual UI support, enhancing human-centered customer service, and promoting financial literacy programs in underserved regions. This research adds to the growing conversation around mobile financial services in emerging economies by offering a well-rounded evaluation framework that considers both practical financial factors and the real-world experiences of users. The insights and model developed here could be useful for platform providers, policymakers, and development organizations working to improve digital access and streamline payments in complex supply chains.
