Predicting Fintech Adoption: Evidence from an Emerging Market

Abstract

The examination of the mobile payment system or fintech research has been insufficient with regard to the perspective of Dhaka’s residents, who reside in the capital of Bangladesh, a country experiencing a growing economy. Prior to making a final decision on adopting fintech, a value-based adoption model (VAM) analysis can be conducted to evaluate the perceived net worth. Hence, the objective of this research is to quantify client acceptance by developing and verifying the VAM model, which integrates both emotional and functional values. We employed the purposive sampling technique, along with power analysis, to carry out a cross-sectional and quantitative survey. Furthermore, the online questionnaire yielded a grand total of 248 valid responses. Subsequently, data analysis, model validity assessment and hypothesis testing were conducted using measurement and structural models. The combined analysis of the benefit and sacrifice questions accurately predicted 44.4% and 52.6% of the emotional and functional scores, respectively, in relation to the intention to adopt. Additionally, there was a variance of 72.6% and 68% in these predictions. Furthermore, 7 out of the 11 hypotheses yielded significant results, with usefulness being identified as the most reliable predictor of perceived values. The determining elements for user approval were the utility and the ease of disregarding technological intricacy and expenses. Consequently, these data can assist service providers in creating top-notch payment systems that fulfil both the practical and emotional desires of consumers. This study enhanced the current body of knowledge by incorporating emotionally and functionally perceived values into VAM. Our investigation revealed that utility elements strongly predict perceived values, but sacrifice aspects were not shown to be significant.