An integrated decision analysis methodology based on IF-DEMATEL and IF-ELECTRE for personnel selection
作者:
Highlights:
• A hybrid decision-support methodology is developed for personnel selection problem.
• DEMATEL and ELECTRE methods under intuitionistic fuzzy environment are employed.
• Both cardinal and ordinal evaluations of candidates are considered
• An application case is performed in a manufacturing company for the selection of key personnel.
摘要
Due to its complex, time-demanding, and multifaceted structure, personnel selection is considered as a multicriteria decision-making problem, the framework of which includes both qualitative and quantitative criteria. Although various techniques have been proposed to address this problem in various industries, a robust methodology that is capable of explicitly considering the presence of uncertainty/vagueness is still a necessity. Therefore, with this study, we propose an integrated methodology that leverages Decision Making Trial and Evaluation Laboratory (DEMATEL) and Elimination and Choice Expressing the Reality (ELECTRE) methods under Intuitionistic Fuzzy (IF) environment. Within the proposed methodology, firstly, the IF-DEMATEL method is employed to obtain the importance-weights of the elicited criteria, and then the IF-ELECTRE method is formulated and applied to rank the candidates based on cardinal and ordinal evaluations. To illustrate the viability of the proposed methodology, an application case is performed at an air-filter manufacturing company. Hence, this study aims to contribute to the theoretical and practical extent of the related literature by proposing and illustrating an integrated analytics methodology capable of addressing personnel selection decisions in complex and imprecise real-world scenarios.
论文关键词:Business analytics,Group decision-making,IF-DEMATEL,IF-ELECTRE,Multicriteria decision-making (MCDM),Personnel selection
论文评审过程:Received 17 November 2019, Revised 6 July 2020, Accepted 6 July 2020, Available online 16 July 2020, Version of Record 19 August 2020.
论文官网地址:https://doi.org/10.1016/j.dss.2020.113360