Fuzzy assisted human resource management for supply chain management issues

Alshurideh, Muhammad Turki
Al Kurdi, Barween
Alzoubi, Haitham M.
Ghazal, Taher M.
Said, Raed A.
AlHamad, Ahmad Qasim
Hamadneh, Samer
Sahawneh, Nizar
Al-kassem, Amer Hani
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In addition, weights for criterion and links between dimensions and criteria were obtained using the Decision-making trial and evaluation laboratory and fuzzy analytical hierarchy process. Both methods can be combined since they serve various goals; earlier studies proposed using three-way type-1 fuzzy sets to achieve criteria weights and linkages across dimensions and criteria. The topics of HRM and Operation Management , respectively, include human resource management (HRM) and supply chain management (SCM). Although academics in each sector continue to advance SCM and HRM's role in developing more sustainable companies, integrating these two modern topics has been significantly delayed based on a more significant integration gap between HRM and SCM and fuzzy. The findings suggest that the educational criterion is more important than the other criteria since it is a cause and affects HRM directly. The research findings show that the suggested F-HRM-SCM technique is feasible, suggesting the educational criterion as the most persuasive factor in human resources management. Therefore, the study aims to provide the HRM-SCM connection with a synergistic and inclusive framework and suggest the research agenda for this integration. After achieving these aims, this paper highlights the consequences of fuzzy HRM-SCM integration in organizational sustainability and genuinely sustainable supply chains for academics, managers, and practitioners. The experimental results demonstrate that the proposed F-HRM-SCM model enhances the supply chain performance ratio of 98.9%, an efficiency ratio of 97.8%, employee satisfaction ratio of 96.7%, decision-making level by 98.2%, prediction ratio of 95.5%, and F1-score ratio of 97.4% compared to other existing approaches. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
This article is not available at CUD collection. The version of scholarly record of this article is published in Annals of Operations Research (2022), available online at: https://doi.org/10.1007/s10479-021-04472-8
Analytic hierarchy process, Fuzzy, Human resource management, Supply chain
Alshurideh, M. T., Al Kurdi, B., Alzoubi, H. M., Ghazal, T. M., Said, R. A., AlHamad, A. Q., . . . Al-kassem, A. H. (2022). Fuzzy assisted human resource management for supply chain management issues. Annals of Operations Research, https://doi.org/10.1007/s10479-021-04472-8