Technological unemployment anxiety in the post-digital ecosystem: A bibliometric analysis

Abstract

Rapid advances in automation, artificial intelligence, and Industry 4.0 technologies have intensified concerns about job displacement and reshaped employment relations globally. While technological unemployment has been widely examined, its psychological dimen sion—technological unemployment anxiety—remains fragmented and relatively under explored in the literature. This study conducts a bibliometric analysis of 930 articles pub lished between 2001 and 2025 and indexed in the Web of Science database to map the intellectual structure and thematic evolution of research on technology-related employ ment, including anxiety-related dimensions. Using keyword co-occurrence, collaboration mapping, and thematic clustering, this study identifies a gradual shift from macro-level economic discussions toward micro-level concerns, including job insecurity perceptions, employability expectations, and worker well-being. The findings indicate that post-pan demic digital acceleration has intensified individualized forms of workplace anxiety within contemporary workplaces. The novelty of this study lies in explicitly positioning technological unemployment anxiety as a distinct analytical construct, rather than a sec ondary outcome of technological change, thereby extending existing bibliometric re search. The results offer insights for scholars and provide practical implications for poli cymakers and organizational actors seeking to address technology-driven anxiety in the emerging post-digital ecosystem.