Decoding digital payment apps adoption in India: insights from Best-Worst method and Chi-square automatic interaction detector

Abstract

Purpose The purpose of this paper is to identify and evaluate the criteria which the consumers of Tier 1 and Tier 2 cities in India deem important for adoption of a digital payment app (DPA). Additionally, it provides a framework to discern high and low adopters of DPAs. Design/methodology/approach This research used a mixed-method approach by integrating the Best-Worst Method to assess the importance of adoption criteria and Chi-Square Automatic Interaction Detector method to classify consumers based on adoption behavior as high or low adopter of DPAs. Findings Trust emerged as the most important adoption criterion in both Tier 1 and Tier 2 cities, while customer service and integration with other apps and services ranked lowest in Tier 1 and Tier 2 cities, respectively. Tier 1 consumers showed a preference for non-banking apps, whereas Tier 2 users favored banking apps. Practical implications The findings provide actionable insights for fintech managers to develop segment specific strategies to enhance both adoption and long-term engagement with DPAs. Originality/value Departing from traditional frameworks like the technology acceptance model and statistical models like structural equation modeling, as per the best knowledge of the authors, this study is the first to use a data-driven approach, integrating the Best-Worst Method and Chi-square automatic interaction detector to capture the preferences and adoption patterns of DPA users.