Hybrid Approach to Supply Chain Project Manager Selection Problem

Abstract

Supply chain management covers the management of all processes, from determining the material needs of manufacturing companies to delivering value-added products to customers. Theoretical approaches and practical applications for supply chain management processes are presented in the literature. However, there is no project-based supply chain manager selection for the improvement of supply chain processes yet. In this research, the supply chain project manager selection problem is discussed. In this context, multi criteria decision making techniques used for project manager selection problem applications were used. According to the literature review and interviews with the manufacturing executive jury, seven criteria were determined. The criterion weights were determined by the fuzzy the stepwise weight assessment ratio analysis (F-SWARA) method. The grey operational competitiveness rating method (OCRA-G) method was applied to select the most suitable candidate among the four candidates. According to the research findings, the experience criterion was determined as the most important criterion in the selection of the supply chain project manager. The second candidate was found to be the most suitable candidate. In this research, an alternative hybrid model method for the project selection problem has been presented to the literature by using fuzzy and gray based approaches in a hybrid way. In addition, suggestions have been developed for manufacturing companies, supply chain project manager candidates and researchers.

A methodology for personnel selection in business development: An interval type 2-based fuzzy DEMATEL-ANP approach

“…Jin [ 43 ] combined the FMEA and DEMATEL methodologies with the TOPSIS method to analyze the unpredictability of the virtual team member selection problem and determine the risk priority number (RPN) for the MCDM criteria. Kara et al [ 44 ] employed multicriteria decision-making strategies for project manager selection problem applications. Seven criteria were determined based on a review of relevant literature and interviews with manufacturing executives.…”