Employees’ reskilling and upskilling for industry 5.0: Selecting the best professional development programmes

Ramona Diana Leon

Technology in Society, 2023, vol. 75, issue C

Abstract: The current research aims at developing a multi-criteria decision-making methodology, based on analytic network process (ANP), for selecting the appropriate professional development programmes for enhancing employees' reskilling and upskilling, in the Industry 5.0 context. Thus, a four-stage methodology, which combines the qualitative approach of the Delphi study with the quantitative approach of the multi-criteria decision-making technique of ANP, is proposed and tested in the three largest companies from the Romanian manufacture of coke and refined petroleum products industry. The results show that teamwork, online communities of practice and enterprise social networks are among the best options. Furthermore, the most influential factors are employees' psychological profile (namely, interpersonal trust and self-efficacy) and human capital (especially, inclusiveness and job satisfaction). These findings have both theoretical and practical implications. At the theoretical level, they provide a nexus between human resource management and operations management by showing how a methodology based on ANP can be applied for solving a human resource issue. At the practical level, they help managers to decide which professional development programmes to implement for employees' reskilling and upskilling by providing them an easily customizable tool that takes into account employees' characteristics and company's human and structural capital.

Keywords: Industry 5.0; Human resources; Skills development; Professional development programmes; Analytic network process (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:75:y:2023:i:c:s0160791x23001987

DOI: 10.1016/j.techsoc.2023.102393

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