Competence management plays a pivotal role in enhancing the competitiveness of organizations in today's fast-changing business environment. In particular, the use of ontologies for the structured management of competence data has proven to be strategic in various industries (such as, manufacturing, aviation and construction) and for different industrial processes (from supply chain management to product lifecycle management). However, despite their demonstrated utility, there remains a significant gap in the literature regarding the specific implications of employing ontologies for competence management in industrial contexts. Hence, the primary objective of this study is to investigate the implications of employing ontologies for competence management in industrial settings. By conducting a Systematic Literature Review (SLR) and bibliometric analysis about this topic, we aim to shed light on the intricacies of utilizing ontologies in managing competence and identify key areas for future research. The conducted keyword co-occurrence analysis identifies six thematic clusters: "Knowledge Representation of Manufacturing Processes"; "Education for Software Engineering"; "Semantic Technologies for Decision Making"; "AI for Knowledge Management", "Ontologies for Human Resource Management (HRM)" and "Competence Management for Industrial Innovation". From an academic perspective, this paper provides an overview of the implication of ontologies in industrial competence management underscoring the importance of ontologies in structuring competence- related information, facilitating decision-making processes and promoting innovation within organizations. Moreover, the study reveals a growing trend of research in this area, with emerging trends reflecting the integration of ontologies with advanced technologies, such as artificial intelligence and machine learning, which would enable organizations to rapidly adapt to changes in today's industrial environment. From a managerial perspective, instead, the study offers insights into best practices and challenges associated with the adoption of ontologies, guiding strategic decisions toward future trends and innovations in competence management.
Ontologies for Competence-Based Management: A Bibliometric Analysis in the Industrial Sector
Lazoi, M;Lezzi, M
2024-01-01
Abstract
Competence management plays a pivotal role in enhancing the competitiveness of organizations in today's fast-changing business environment. In particular, the use of ontologies for the structured management of competence data has proven to be strategic in various industries (such as, manufacturing, aviation and construction) and for different industrial processes (from supply chain management to product lifecycle management). However, despite their demonstrated utility, there remains a significant gap in the literature regarding the specific implications of employing ontologies for competence management in industrial contexts. Hence, the primary objective of this study is to investigate the implications of employing ontologies for competence management in industrial settings. By conducting a Systematic Literature Review (SLR) and bibliometric analysis about this topic, we aim to shed light on the intricacies of utilizing ontologies in managing competence and identify key areas for future research. The conducted keyword co-occurrence analysis identifies six thematic clusters: "Knowledge Representation of Manufacturing Processes"; "Education for Software Engineering"; "Semantic Technologies for Decision Making"; "AI for Knowledge Management", "Ontologies for Human Resource Management (HRM)" and "Competence Management for Industrial Innovation". From an academic perspective, this paper provides an overview of the implication of ontologies in industrial competence management underscoring the importance of ontologies in structuring competence- related information, facilitating decision-making processes and promoting innovation within organizations. Moreover, the study reveals a growing trend of research in this area, with emerging trends reflecting the integration of ontologies with advanced technologies, such as artificial intelligence and machine learning, which would enable organizations to rapidly adapt to changes in today's industrial environment. From a managerial perspective, instead, the study offers insights into best practices and challenges associated with the adoption of ontologies, guiding strategic decisions toward future trends and innovations in competence management.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


