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.

中文翻译：

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电子商务中的隐私问题：多层次元分析

21 世纪科技的飞速发展促进了个人个人信息的在线收集、存储、检索、操作和传输，但也导致电子商务用户对隐私的担忧随之增加。尽管隐私问题在电子商务文献中受到了相当大的关注，但迄今为止，实证研究倾向于报告在消费者隐私方面有些不稳定和不一致的发现。因此，电子商务环境中的前因、隐私问题和结果变量之间的关系仍不清楚。为了弥补文献中的这些缺陷，本研究采用元分析方法来收集和理解文献中报告的不一致和混合的实证结果。研究结果表明，风险感知引发隐私担忧，而利益感知、熟悉度、声誉、隐私政策和信任减轻了隐私担忧，进而影响了客户对电子商务平台的态度和使用。为了调查结果不一致的可能原因，我们进行了调节分析，该分析表明方法调节因素，即文章类型、研究方法和样本类型；和背景调节者，即进行研究的国家，以及样本集中的性别优势，可能导致研究结果的不一致。从理论上讲，这种元分析有助于前因；隐私问题；结果变量 (APCO) 模型，以及电子商务背景下有关消费者隐私的文献。几乎，