Cash rich to cashless market: Segmentation and profiling of Fintech-led-Mobile payment users

Abstract

Considering the growing prominence of the Fintech-led-Mobile-Payment (FMP) platform, it has become imperative for practitioners and academicians to look beyond technology adoption to understand causal relationships. Building on the premise, previous literature primarily examined the causal relationships to describe the phenomenon of evolving digital payment technology in a varied context. However, limited studies explored user classification and profiling with some exceptions, principally stressing upon barely online and mobile-based banking segmentation contexts.Grounded in analyzing user taxonomy based on benefits-trust-behavioral linkage model from the purview of an emerging mobile-based digital payment market, this research aims to identify and test an a-priori approach to market segmentation of FMP platform users and profiling them based on perceived benefits, behavioral, and socio-demographic characterization. To analyze the model of users' classification, 550 valid online responses were received and employed a blended analytical approach of multivariate techniques (CFA, cluster analysis, discriminant function analysis) along with the bivariate technique of the Chi-square test for clustering procedures followed by resulting clusters' validation and their profiling. The three distinct segments are identified as ‘The Fintech Dubious,’ ‘The Cash Conservatives, ‘and ‘The Fintech Enthusiasts.’ The study also advances the current theoretical understanding of the trust based modified version of UTAUT with the associative framework of ‘perceived benefits-attitude, and intention’ by adding two additional cognitive constructs of perceived trust and perceived price value along with added socio-demographics (usage frequency and geographical area). Lastly, this timely study offers several unflinching implications for the practitioners of strategic marketing and policymakers for encouraging FMP usage.