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Abstract Performance management, as a systematic and continuous process of planning, measuring and improving performance, is an important endeavor for any organization, regardless of being private or public. To understand the current state of research on performance management, a comprehensive bibliometric study was conducted. This paper aims to provide a co-occurrence analysis to identify and explore clusters, prevailing and emerging themes, and future research directions. For this purpose data was collected from the WoS database and processed with VOSviewer and Microsoft Excel. The paper contains visual representations of clusters, keywords and their relationships, as well as an analysis of the novelty of the concepts. Based on the average published year (APY), the hottest keywords identified are Covid-19 (APY: 2021), followed by Industry 4.0 (APY: 2020.17), together with other 4IR tools (big data analytics, big data, machine learning, artificial intelligence, cloud, Iot, etc.). Resulting from the analysis of concepts with APY after 2017, in terms of their representativeness (occurrence), links, and total link strengths (TLS) with other items from the map, three concepts significantly emerged: framework (Cluster 1); public sector (Cluster 3); sustainability (Cluster 4). Based on the overall findings, new research directions were proposed.
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Stored only when both papers are in the corpus — 8 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.