Journals / Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik / 2018 / Cilt: 19 - Sayı: 2

PERSONNEL SELECTION FOR PROMOTION USING AN INTEGRATED FUZZY ANALYTIC HIERARCHY PROCESS-GREY RELATIONAL ANALYSIS METHODOLOGY: A REAL CASE STUDY

Pages
278–292
Publication Date
2022-10-11
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

To the authors’ knowledge, this will be the first study which integrates FuzzyAnalytic Hierarchy Process (FAHP) and Grey Relational Analysis (GRA) methodologies for human resources in the area ofindustrial engineering.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The basic idea of personnel selection is to choose the best candidate for a job.
📊
Key Findings & Data:FAHP is used to determine the importance weights of personnel (17 alternatives)according to personnel selection criteria (22 subcriteria are categorized under 5 main criteria).
💡
Conclusion & Impact:To the authors’ knowledge, this will be the first study which integrates FuzzyAnalytic Hierarchy Process (FAHP) and Grey Relational Analysis (GRA) methodologies for human resources in the area ofindustrial engineering.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The basic idea of personnel selection is to choose the best candidate for a job. Personnel selection is crucial in humanresources management and also it is very important for both academicians and industrialists. Personnel selection can be asolution to a Multi Criteria Decision Making (MCDM) problem.The aim of this paper is to determine the best personnel by integrating Fuzzy Analytic Hierarchy Process (FAHP) and GreyRelational Analysis (GRA) methodology. FAHP is used to determine the importance weights of personnel (17 alternatives)according to personnel selection criteria (22 subcriteria are categorized under 5 main criteria). Then, obtained fuzzyimportance weights are defuzzified by centroid method. After that, defuzzified importance weights of personnel according topersonnel selection criteria are integrated with a GRA model to prioritize the personnel alternatives. For a case study inTurkey, the ranking of the alternatives is calculated using the integrated FAHP-GRA model, and the best-performingpersonnel is selected for promotion. According to this methodology, managers/human resources department can easilypredict how they can evaluate and promote employees.The proposed methodology requires less data and analyzes many factors by removing complexity of statistics methods in theliterature. The main contribution of this study is to reduce data for a preference matrix using the integrated methodology. Asa result, the number of transactions decrease. To the authors’ knowledge, this will be the first study which integrates FuzzyAnalytic Hierarchy Process (FAHP) and Grey Relational Analysis (GRA) methodologies for human resources in the area ofindustrial engineering.

🔖

Cite This Article

NALBANT, K. G., BAŞLIGİL, H., ÖZDEMİR, Y. (2022). PERSONNEL SELECTION FOR PROMOTION USING AN INTEGRATED FUZZY ANALYTIC HIERARCHY PROCESS-GREY RELATIONAL ANALYSIS METHODOLOGY: A REAL CASE STUDY. Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik, Cilt: 19 - Sayı: 2, 278–292. https://ajindex.com/articles/438223

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (14)

  1. Ozdemir Y, Basligil H. Aircraft selection using Fuzzy ANP and the generalized Choquet Integral method: The Turkish Airlines case. Journal of Intelligent and Fuzzy Systems 2016; 31: 589-600
  2. Ozdemir Y, Nalbant KG, Basligil H. Evaluation of personnel selection criteria using Consistent Fuzzy Preference Relations. Operations Research and Information Engineering 2017; accepted
  3. Chen CT. Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems 2000; 114: 1-9
  4. Afshari AR, Mojahed M, Yusuff RM, Hong TS, Ismail MY. Personnel selection using ELECTRE. Journal of Applied Sciences 2010; 10: 3068-3075
  5. Kelemenis A, Askounis D. A new TOPSIS based multi-criteria approach to personnel selection. Expert Systems with Applications 2010; 37: 4999-5008
  6. Rashidi A, Jazebi F, Brilakis I. Neurofuzzy genetic system for selection of construction project managers. Journal of Construction Engineering and Management 2011; 137: 17-29
  7. Boran FE, Genç S, Akay D. Personnel selection based on intuitionistic fuzzy sets. Human Factors and Ergonomics in Manufacturing & Service Industries 2011; 21: 493-503
  8. Kabak M, Burmaoğlu S, Kazançoğlu Y. A fuzzy hybrid MCDM approach for professional selection. Expert Systems with Applications 2012; 39: 3516-3525
  9. Baležentis A, Baležentis T, Brauers WK. Personnel selection based on computing with words and fuzzy MULTIMOORA. Expert Systems with Applications 2012; 39: 7961-7967
  10. Roy B, Misra SK. An integrated DEMATEL and AHP approach for personnel estimation. International Journal of Computer Science and Information Technology & Security 2012; 2: 1206-1212
  11. Yu D, Zhang W, Xu Y. Group decision making under hesitant fuzzy environment with application to personnel evaluation. Knowledge Based Systems 2013; 52: 1-10
  12. Md Saad R, Ahmad MZ, Abu MS, Jusoh MS. Hamming Distance Method with subjective and objective weights for personnel selection. The Scientific World Journal 2014; ID 865495, 1-9, doi:10.1155/2014/865495
  13. Aggarwal R. Identifying and prioritizing human capital measurement indicators for personnel selection using fuzzy MADM. In: Pant M., Deep K, Nagar A, Bansal J, editors. Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing. Springer, New Delhi, 2014; 258: 427-439
  14. Violeta K, Turskis Z. A hybrid linguistic fuzzy multiple criteria group selection of a chief accounting offic