Year: 2026
Type: article
Abstract: HRMARS - This study employs bibliometric methods to examine the intellectual landscape of post-COVID firm innovation research from 2020 to 2026. Based on 4,264 documents published in 624 sources, the study integrates analysis with science-mapping techniques, including Bradford’s Law, keyword co-occurrence networks, thematic mapping, trend-topic analysis, and so on. The analysis is organized around three questions: the characterization of the database and its main publication sources; the current thematic configuration and conceptual structure of the field; and the patterns of thematic evolution that inform prospective research directions. In order to provide a clear understanding of topic clusters and their relationships, the study uses a systematic procedure for collecting data and keyword integration. The study offers a systematic review of how Post-COVID innovation research has been structured across fields and how its topic attention has changed over time by combining network-based clustering with centrality–density positions and dynamic topic movements. The findings are intended to support conceptual boundaries and agenda framing for further empirical research.
Authors: Jiang Zongyu, Rohaida Basiruddin
Institution: University of Technology Malaysia
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7136314042
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