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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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  • P-ISSN1738-3110
  • E-ISSN2093-7717
  • SCOPUS, ESCI

Application of MCDM methods to Qualified Personnel Selection in Distribution Science: Case of Logistics Companies

Application of MCDM methods to Qualified Personnel Selection in Distribution Science: Case of Logistics Companies

The Journal of Distribution Science(JDS) / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2021, v.19 no.8, pp.25-35
https://doi.org/https://doi.org/10.15722/jds.19.8.202108.25
NONG, Nhu-Mai Thi (Faculty of Commerce, University of Finance - Marketing)
HA, Duc-Son (Faculty of Commerce, University of Finance - Marketing)

Abstract

Purpose: This study aims to propose an integrated MCDM model to support the qualified personnel selection in the distribution science. Research design, data, and methodology: The integrated approach of AHP and TOPSIS was employed to address the personnel selection problem. The AHP method was used to define the weights of the selection criteria, whereas the TOPSIS was applied to rank alternatives. The proposed model was then applied into a leading logistics company to select the best alternatives to be the sales deputy manager. Results: The results showed that Candidate 3 is the most qualified personnel for the sales deputy manager position as he is ranked first in the order of preference for recruitment. Conclusions: The proposed model provides the decision makers with more effective and time-saving methods than conventional ones. Therefore, the model can be applied to personnel selection around the world. In terms of theoretical contribution, this study proposes a personnel selection model for choosing the most appropriate candidates. In addition, the study adds to the theory of human resources management and logistics management the full set of personnel selection criteria including education, experience, skills, health, personality traits and foreign language.

keywords
AHP, Distribution Science, Logistics, MCDM, Qualified Personnel Selection, TOPSIS

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The Journal of Distribution Science(JDS)