Purpose: The purpose of the study is to identify the soft skills and abilities that are crucial to success in the fields of operations management (OM) and supply chain management (SCM), using the ONET database and the classification of a set of professional figures integrating values for task skills and abilities needed to operate successfully in these professions. Design/methodology/approach: The study used the ONET database to identify the soft skills and abilities required for success in OM and SCM industries. Correlation analysis was conducted to determine the tasks required for the job roles and their characteristics in terms of abilities and soft skills. ANOVA analysis was used to validate the findings. The study aims to help companies define specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the job position. Findings: As a result of the work, a set of soft skills and abilities was defined that allow, through correlation analysis, to explain a large number of activities required to work in the operations and SCM (OSCM) environment. Research limitations/implications: The work is inherently affected by the database used for the professional figures mapped and the scores that are attributed within ONET to the analyzed elements. Practical implications: The information resulting from this study can help companies develop specific assessments and tests for the roles of OM and SCM to measure individual attitudes and correlate them with the requirements of the job position. The study aims to address the need to identify soft skills in the human sphere and determine which of them have the most significant impact on the OM and SCM professions. Originality/value: The originality of this study lies in its approach to identify the set of soft skills and abilities that determine success in the OM and SCM industries. The study used the ONET database to correlate the tasks required for specific job roles with their corresponding soft skills and abilities. Furthermore, the study used ANOVA analysis to validate the findings in other sectors mapped by the same database. The identified soft skills and abilities can help companies develop specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the requirements of the job position. In addressing the necessity for enhanced clarity in the domain of human factor, this study contributes to identifying key success factors. Subsequent research can further investigate their practical application within companies to formulate targeted growth strategies and make appropriate resource selections for vacant positions.

Fantozzi, I.c., Di Luozzo, S., Schiraldi, M.m. (2024). On tasks and soft skills in operations and supply chain management: analysis and evidence from the O*NET database. THE TQM JOURNAL, 36(9), 53-74 [10.1108/TQM-04-2023-0104].

On tasks and soft skills in operations and supply chain management: analysis and evidence from the O*NET database

Fantozzi I. C.
;
Di Luozzo S.;Schiraldi M. M.
2024-01-01

Abstract

Purpose: The purpose of the study is to identify the soft skills and abilities that are crucial to success in the fields of operations management (OM) and supply chain management (SCM), using the ONET database and the classification of a set of professional figures integrating values for task skills and abilities needed to operate successfully in these professions. Design/methodology/approach: The study used the ONET database to identify the soft skills and abilities required for success in OM and SCM industries. Correlation analysis was conducted to determine the tasks required for the job roles and their characteristics in terms of abilities and soft skills. ANOVA analysis was used to validate the findings. The study aims to help companies define specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the job position. Findings: As a result of the work, a set of soft skills and abilities was defined that allow, through correlation analysis, to explain a large number of activities required to work in the operations and SCM (OSCM) environment. Research limitations/implications: The work is inherently affected by the database used for the professional figures mapped and the scores that are attributed within ONET to the analyzed elements. Practical implications: The information resulting from this study can help companies develop specific assessments and tests for the roles of OM and SCM to measure individual attitudes and correlate them with the requirements of the job position. The study aims to address the need to identify soft skills in the human sphere and determine which of them have the most significant impact on the OM and SCM professions. Originality/value: The originality of this study lies in its approach to identify the set of soft skills and abilities that determine success in the OM and SCM industries. The study used the ONET database to correlate the tasks required for specific job roles with their corresponding soft skills and abilities. Furthermore, the study used ANOVA analysis to validate the findings in other sectors mapped by the same database. The identified soft skills and abilities can help companies develop specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the requirements of the job position. In addressing the necessity for enhanced clarity in the domain of human factor, this study contributes to identifying key success factors. Subsequent research can further investigate their practical application within companies to formulate targeted growth strategies and make appropriate resource selections for vacant positions.
2024
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-IND/17
Settore ING-IND/35
English
Human factor
Job profiles
ONET
Operations and supply chain management
Soft skills
Fantozzi, I.c., Di Luozzo, S., Schiraldi, M.m. (2024). On tasks and soft skills in operations and supply chain management: analysis and evidence from the O*NET database. THE TQM JOURNAL, 36(9), 53-74 [10.1108/TQM-04-2023-0104].
Fantozzi, Ic; Di Luozzo, S; Schiraldi, Mm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/351943
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