Factors influencing digital payment behavior: a meta-analysis

Purpose This study aims to identify and consolidate the most effective predictors of individuals' intention to use digital payments and their actual adoption by synthesizing findings across various digital payment technologies, including digital banking, mobile/digital wallets and QR code-based payments. Design/methodology/approach A meta-analysis was conducted on 41 empirical studies comprising 141 relationships. OpenMEE software was used to statistically synthesize the data and evaluate the predictive strength of different behavioral variables across the three main types of digital payment services. Findings Attitude, compatibility, habit, hedonic motivation, performance expectancy and trust emerged as the most effective predictors of behavioral intention to use digital payments. Website design was also identified as a promising factor. Behavioral intention was the strongest predictor of actual adoption, while habit significantly influenced the continued use of digital payments. The analysis reveals both shared and distinct factors across digital banking, mobile/digital wallets and QR code services. Originality/value This study fills a significant gap in the literature by empirically comparing key adoption drivers across different digital payment technologies using meta-analytic techniques. It offers a comprehensive and evidence-based understanding of the most influential factors, supporting practitioners and policymakers in enhancing digital payment strategies and financial inclusion initiatives.