Coded corpus for "Human–AI Complementarity at Work: A Systematic Review of Trust, Attitudes, and Employee Outcomes" (174 studies, 2019–2025)

This dataset is the complete data-extraction and coding sheet underpinning a PRISMA 2020 systematic literature review of artificial intelligence (AI) in the workplace. From a systematic search and screening of the peer-reviewed literature, 174 articles published between 2019 and 2025 were included and coded. For every included study the sheet records its bibliographic details (title, authors, year, country, and source journal), its methodological orientation, a concise statement of its key conclusions, the open codes generated during thematic analysis, and the broad theme under which it was classified. Together these fields reproduce the descriptive analyses reported in the review — the year-wise, method-wise, and geographic distributions of the corpus — and its thematic synthesis across five themes, and they allow other researchers to trace each claim in the article back to its underlying sources, re-analyse the corpus, or extend the review. The data are derived entirely from already-published scholarly articles and contain no human-participant or personal information.本数据集为一项针对职场人工智能（AI）的PRISMA 2020系统文献综述提供完整的数据提取与编码表支撑。本研究通过对同行评议文献开展系统性检索与筛选，最终纳入并编码了2019年至2025年间发表的174篇文献。针对每一篇纳入的文献，该编码表均记录了其题录信息（包括标题、作者、发表年份、发表国家及来源期刊）、研究方法取向、核心结论的简明表述、主题分析过程中生成的开放编码，以及该文献所属的大类主题。上述所有字段可复现该综述中报告的描述性分析结果——即该文献集的年度、方法学及地域分布情况——以及其基于五大主题的主题综合结果；同时可供其他研究者将文中的每一项主张追溯至其原始来源，对该文献集开展二次分析，或对该综述进行拓展延伸。本数据集所有数据均来自已发表的学术文献，未包含任何人类受试者相关信息或个人隐私数据。