Privacy concerns in e‐commerce: A multilevel meta‐analysis

Abstract Whilst the rapid advancement of technology in the 21st century has facilitated the online collection, storage, retrieval, manipulation, and transmission of individuals' personal information, it has also led to a concomitant rise in privacy concerns amongst e‐commerce users. Although privacy concerns have received considerable attention in the e‐commerce literature, to date, empirical research has tended to report somewhat erratic and inconsistent findings in the context of consumer privacy. Accordingly, the relationships between the antecedents, privacy concerns, and the outcome variables in e‐commerce contexts remains unclear. To remedy such deficiencies in the literature, this study adopts the meta‐analytic approach to gather and make sense of the inconsistent and mixed empirical findings reported in the literature. The findings show that risk perceptions trigger privacy concerns while benefit perceptions, familiarity, reputation, privacy policy, and trust mitigate privacy concerns which in turn affect customer attitude and usage of e‐commerce platforms. To investigate the possible reasons for inconsistent findings, we performed a moderation analysis which suggests that methodological moderators, that is, type of article, research methods, and sample type; and contextual moderators, i.e. country where the study was carried out, and gender dominance in a sample set, can cause inconsistencies in the findings. Theoretically, this meta‐analysis contributes to the Antecedents; Privacy Concerns; Outcome variables (APCO) Model, and the literature on consumer privacy in the context of e‐commerce. Practically, the findings provide guidelines to e‐commerce businesses to effectively address customers' privacy concerns.