The Influence Of Perceived Risk On Conumers’ Intention To Buy Online: A Meta-Analysis Of Empirical Results

When buying online consumers fear for the security of their financial data and the privacy of their personal information. These two fears summed up gives researchers the perceived risk of an online transaction. The influence of perceived risk on consumers’ intention to buy online has been studied in various models, ranging from having an insignificant influence to having a strong and direct influence. Faced with these confusing results from previous empirical researches, we wonder why there are such differences among reported results. Is perceived risk a strong predictable of the consumers’ intention to buy online? Should it be considered a significant impact variable when modelling online consumer behaviour? We answer these research questions by conducting a meta-analysis on previous empirical findings. We first conduct a search for academic articles that have included perceived risk in their explanatory and predictive models of online consumer behaviour. The search was carried out using ScienceDirect international database and Google search engine. The selection of articles to be included in the study was based on some defined inclusion criteria. All included models had to be based on an empirical research and had to report the correlation coefficient between perceived risk and intention to buy online. We selected 11independent studies for inclusion in our meta-analysis. We report the findings from the mean effect sizes using a comparison between three methods: simple mean method, sample size-adjusted mean and Fisher r to Z transformation. Both limitations of this analysis and managerial implications are discussed.