Optimizing Personnel Selection in Transportation: An Application of the BWM-CoCoSo Decision-Support Model
Journal Title: Journal of Organizations, Technology and Entrepreneurship - Year 2023, Vol 1, Issue 1
Abstract
In the logistics domain, the selection of personnel, particularly transport managers and drivers, is pivotal to operational efficacy, demanding a selection process that transcends traditional subjectivity and expertise scarcity. Addressing this, the Best Worst Method (BWM) integrated with the Combined Compromise Solution (CoCoSo) presents a novel decision-support model, employed here for the first time to refine the recruitment process within the transportation sector. Through the application of BWM, criteria weights were ascertained, a method that has shown superior performance and reliability in deriving consistent results. Concurrently, the CoCoSo method facilitated the ranking of candidates, demonstrating greater reliability and stability compared to existing methodologies. The fusion of these methods offers a distinctive approach, enhancing reliability in diverse problems and across various hierarchical strata. A meticulous compilation of evaluation criteria has been delineated, for drivers and transport managers alike, incorporating a gamut of competencies including but not limited to communication and negotiation skills, leadership skills, swift and autonomous decision-making capabilities, resilience under pressure, educational qualifications, proficiency in computer skills, and past work experience. For transport managers, additional competencies such as spatial coordination and orientation, levels of responsibility and precision, adeptness in working under pressure, operational task efficiency, comprehensive understanding of regulations, rules, and documentation, and a history of relevant work experience have been emphasized. This research marks a theoretical and practical contribution to the literature by providing a model crafted for the nuanced requisites of logistics roles. Empirical validation confirms the model's applicability and efficiency in real-world contexts, heralding its potential to refine the Human Resource Management (HRM) landscape in logistics. Consequently, this work signifies a paradigm shift in the strategic and systematic management of human resources in the logistics sector, furnishing industry decision-makers with a robust tool for personnel selection.
Authors and Affiliations
Milan Andrejić,Vukašin Pajić
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