Supplementary material - dataset of papers relating to change management (176 studies)
Description
Dataset of papers used for a systematic literature review of change management practices across industrial fields. Papers were retrieved from Scopus and WOS, along with their bibliographic data, and classified in terms of the methodology applied, country of the study, industrial field.
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Two databases, i.e. Scopus and Web of Science (WOS), were utilized for document search. Employing a specific query, 'TITLE/ABS/KEY("change management" AND (optimiz* OR optimis*))' yielded an initial retrieval of 647 articles from Scopus and 324 from WOS, including various document types. The following inclusion/exclusion criteria were then applied: • Only documents type 'articles' and 'reviews' were retained, narrowing down the count to 320 articles from Scopus and 218 from WOS; • Further refinements were carried out by restricting the selection to articles written exclusively in English, resulting in 291 articles from Scopus and 197 from WOS. 2. Merging: A complete overview of the sample was obtained by merging the outcomes from Scopus and WOS, yielding 488 articles. After eliminating duplicates, the sample was resized to 318 distinct articles. Exclusion of articles lacking authorship details further reduced the count to 314 . 3. Manual screening: The authors conducted a meticulous manual screening, thoroughly examining articles by reviewing abstracts, titles, and keywords. Inclusion or exclusion decisions were based on the following predefined criteria: • Relevance to change management, change processes, leadership in change, organizations undergoing change, and change management models focusing on process optimization; • Exclusion of articles solely concentrating on mathematical models without substantive considerations for change management. • Inclusion of articles addressing related themes such as resilience, communication, leadership, and resistance within the context of change management, aligning with the findings from the paper “Change management in the public sector: A Preliminary Analysis” (Bottani et al., 2023). Studies were categorized into empirical studies, mathematical model, conceptual research and modelling and simulation.