Factors influencing consumers’ adoption of electronic shopping: findings from a meta-analysis

Abstract

E-commerce has significantly reshaped consumers’ shopping processes and habits. The need to understand the key drivers of online shopping adoption has received a noticeable attention and fueled a rich strand of studies. The purpose of this research is to summarize this growing volume of evidence through the first comprehensive meta-analysis on the antecedent factors of e-commerce acceptance, to derive actionable insights for managers and researchers. The study draws upon the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), which have been broadly validated in e-commerce literature, and integrates them with relevant constructs that support the integration of cross-disciplinary studies in the online shopping environment. Three dependent variables (attitude toward online shopping, purchase intention, purchase behavior) and eighteen antecedent factors classified into four categories (perceived channel characteristics, website characteristics, social influence, consumer characteristics) are included in the proposed framework. 1,710 effect sizes across 183 studies on a total sample size of 671,689 shoppers are synthetized. The study explicitly clarified several key contributions to the understanding of the dynamics of adoption of online shopping. Results suggest that all subsets of predictors are strongly related to attitude and purchase intention while a reduced number of antecedent factors displays a significant impact on purchase behavior. Meta-analytic structural equation modeling is used to test the theoretical framework that adds to the understanding of the dominant drivers of adoption. Furthermore, moderator analysis is carried out. Implications for online shopping research and practice, and an agenda for future research are finally presented.