Uncovering the Inhibitors of Digital Payment Adoption: A BWM-TOPSIS Study with Sensitivity Analysis

This study focuses on the inhibitors of the Digital Payment Platform (DPP) that prevent the user from adopting the payment platform. The objective of the study is to find out the most important criteria (inhibitors) that influence the user decision regarding the DPP adoption and also find out the most influential DPP apps that have greater inhibitors. We have used Multi-criteria Decision Making (MCDM) techniques such as the Best-worst Method (BWM), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Sensitivity Analysis to assess the reliability of inhibitors present in Digital Payment Platforms (DPPs). The finding of this study shows that privacy concerns are one of the most important inhibitors which become a barrier in the adoption of DPPs. While we used the TOPSIS method to analyze the alternative apps, which showed that Instagram Pay is the platform where the user faces the highest inhibitors which refrain the user from adopting it. Contrary to it, sensitivity analysis with five criteria with five DPPs revealed that WhatsApp Pay is one of the platforms which has the most consistent impact of inhibitor and hence users avoid using this app. The implication of the study highlights the critical area of adoption and focuses on the payment app which has greater inhibitors. We have to reduce the inhibitors from the respective apps for the wider adoption of DPPs.