Research Article
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Human Resources Manager Selection Based on Fuzzy and Intuitionistic Fuzzy Numbers for Logistics Companies

Year 2022, Volume: 4 Issue: 2, 254 - 286, 28.12.2022

Karahan Kara Sercan Edinsel Galip Cihan Yalçın

https://doi.org/10.54410/denlojad.1211835

Abstract

Qualified managers are needed for the systematic functioning of logistics management applications. In logistics companies, the human resources manager takes part in determining the amount of personnel needed, supplying personnel, and creating personnel task forms. For successful human resources management, a qualified human resources manager should be selected. In the literature, it is seen that the manager selection problem is handled with multi criteria decision making (MCDM) methods. The aim of this research is to determine the problem criteria of human resources manager selection for logistics companies and to apply them with hybrid MCDM methods. With the in-depth literature review, ten criteria were determined for the logistics company human resources manager selection problem. The intuitionistic fuzzy weighted averaging (IFWA) method was used to weight the criteria. The fuzzy multi attribute ideal-real comparative analysis (F-MAIRCA) method was applied for the ranking of the four candidate managers. The application was made on a logistics company operating in Turkey. Research methods are based on fuzzy and intuitionistic fuzzy numbers. As a result of the study, the most important criterion in the selection of logistics human resources manager was determined as the experience criterion. Among the four candidates, the first candidate was seen as the best manager candidate. Suggestions have been developed for logistics companies, human resources manager candidates and researchers based on the research outputs. In addition, with this research, the IFWA and F-MAIRCA hybrid method has been brought to the literature.

Keywords

Manager Selection Problem Fuzzy Logic Intuitionistic Fuzzy Numbers F-MAIRCA IFWA

References

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HUMAN RESOURCES MANAGER SELECTION BASED ON FUZZY AND INTUITIONISTIC FUZZY NUMBERS FOR LOGISTICS COMPANIES

Year 2022, Volume: 4 Issue: 2, 254 - 286, 28.12.2022

Karahan Kara Sercan Edinsel Galip Cihan Yalçın

https://doi.org/10.54410/denlojad.1211835

Abstract

Lojistik yönetim fonksiyonlarının sistematik işlemesi için nitelikli yöneticilere ihtiyaç duyulmaktadır. Lojistik firmalarda insan kaynakları yöneticisi personel ihtiyacının belirlenmesi, personel temini ve personel görev formlarının oluşturulmasını rol almaktadır. Başarılı insan kaynakları yönetimi için nitelikli insan kaynakları yöneticisi seçimi yapılmalıdır. Literatürde yönetici seçim problemini çok kriterli karar verme yöntemleriyle ele alındığına rastlanmaktadır. Bu araştırmanın amacı lojistik firmalar için insan kaynakları yöneticisi seçim problem kriterlerinin belirlenmesi ve hibrit ÇKKV yöntemleriyle uygulanmasıdır. Derinlemesine yapılan literatür incelemesi sonucunda lojistik firma insan kaynakları yöneticisi için on kriter belirlenmiştir. Kriterlerin ağırlıklandırılmasında IFWA yöntemi uygulanmıştır. Dört aday yöneticinin sıralamasında ise F-MAIRCA yöntemi uygulanmıştır. Araştırmaya ait uygulama Türkiye’de faaliyet gösteren bir lojistik firma üzerinde yapılmıştır. Araştırma yöntemleri bulanık ve sezgisel bulanık sayılara dayalı ele alınmıştır. Çalışma sonucunda lojistik insan kaynakları yönetici seçiminde en önemli kriter tecrübe kriteri olarak belirlenmiştir. Dört aday arasından birinci aday en iyi yönetici adayı olarak görülmüştür. Araştırma sonucunda lojistik firmalara, insan kaynakları yönetici adaylarına ve araştırmacılara yönelik öneriler geliştirilmiştir. Ayrıca bu araştırmayla IFWA ve F-MAIRCA hibrit yöntemi literatüre kazandırılmıştır.

Keywords

Yönetici Seçim Problemi Bulanık Mantık Sezgisel Bulanık Mantık IFWA F-MAIRCA Manager Selection Problem Fuzzy Logic Intuitionistic Fuzzy Numbers

References

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  • Afshari, A. R., & Kowal, J. (2017). Decision Making Methods for the Selection of ICT Project Manager. Gospodarka, Rynek, Edukacja, 18(4), 19-28. http://dx.doi.org/10.2139/ssrn.3118075
  • Afshari, A. R., & Yusuff, R. M. (2013). Fuzzy integral project manager selection. Australian Journal of Multi-Disciplinary Engineering, 9(2), 149-154. https://doi.org/10.7158/14488388.2013.11464855
  • Akça, N., Sönmez, S., Gür, Ş. Yilmaz, A., & Tamer, E. (2018). Kamu hastanelerinde analitik ağ süreci yöntemi ile finans yöneticisi seçimi. Optimum Ekonomi ve Yönetim Bilimleri Dergisi, 5(2), 133-146. https://doi.org/10.17541/optimum.390536
  • Atanassov K. (1986). Intuitionistic fuzzy sets. Fuzzy Set And Systems Journal, 20, 87–96.
  • Baležentis, T., & Zeng, S. (2013). Group multi-criteria decision making based upon interval-valued fuzzy numbers: an extension of the MULTIMOORA method. Expert Systems with Applications, 40(2), 543-550. https://doi.org/10.1016/j.eswa.2012.07.066
  • Bonissone, P. P., Subbu, R., & Lizzi, J. (2009). Multicriteria decision making (MCDM): a framework for research and applications. IEEE Computational Intelligence Magazine, 4(3), 48-61. https://doi.org/10.1109/MCI.2009.933093
  • Boral, S., Howard, I., Chaturvedi, S. K., McKee, K., & Naikan, V. N. A. (2020). An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA. Engineering Failure Analysis, 108, 104195. https://doi.org/10.1016/j.engfailanal.2019.104195
  • Boran, F. E., Genç, S., Kurt, M., & Akay, D. (2009). A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert systems with applications, 36(8), 11363-11368. https://doi.org/10.1016/j.eswa.2009.03.039
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  • Cetin, E. I., & Icigen, E. T. (2017). Personnel selection based on step-wise weight assessment ratio analysis and multi-objective optimization on the basis of ratio analysis methods. International Journal of Economics and Management Engineering, 11(11), 2718-2722. https://doi.org/10.5281/zenodo.1314471
  • Chaghooshi, A., Arab, A., & Dehshiri, S. (2016). A fuzzy hybrid approach for project manager selection. Decision Science Letters, 5(3), 447-460. https://doi.org/10.5267/j.dsl.2016.1.001
  • Chen, K. S., Wang, C. H., & Tan, K. H. (2019). Developing a fuzzy green supplier selection model using six sigma quality indices. International Journal of Production Economics, 212, 1-7.
  • Chen, L. S., & Cheng, C. H. (2005). Selecting IS personnel use fuzzy GDSS based on metric distance method. European journal of operational research, 160(3), 803-820. https://doi.org/10.1016/j.ejor.2003.07.003
  • Chen, C. T., Hwang, Y. C., & Hung, W. Z. (2009). Applying multiple linguistic PROMETHEE method for personnel evaluation and selection. In 2009 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1312-1316). IEEE. https://doi.org/10.1109/IEEM.2009.5373021
  • Celikbilek, Y. (2018). A grey analytic hierarchy process approach to project manager selection, Journal of Organizational Change Management, 31(3), 749-765. https://doi.org/10.1108/JOCM-04-2017-0102
  • Dodangeh, J., Sorooshian, S., & Afshari, A. R. (2014). Linguistic Extension for Group Multicriteria Project Manager Selection. Journal of Applied Mathematics, 2014, 1-8. https://doi.org/10.1155/2014/570398
  • Ecer, F. (2022). An extended MAIRCA method using intuitionistic fuzzy sets for coronavirus vaccine selection in the age of COVID-19. Neural Computing and Applications, 34(7), 5603-5623. https://doi.org/10.1007/s00521-021-06728-7
  • Ecer, F., Böyükaslan, A., & Hashemkhani Zolfani, S. (2022). Evaluation of cryptocurrencies for investment decisions in the era of Industry 4.0: a borda count-based intuitionistic fuzzy set extensions EDAS-MAIRCA-MARCOS multi-criteria methodology. Axioms, 11(8), 404. https://doi.org/10.3390/axioms11080404
  • Erdin, C. (2019). Bulanık Topsis Yöntemiyle Yönetici Seçimi. Yıldız Sosyal Bilimler Enstitüsü Dergisi, 3(1), 37-50.
  • Gao, J., Guo, F., Ma, Z., & Huang, X. (2021). Multi-criteria decision-making framework for large-scale rooftop photovoltaic project site selection based on intuitionistic fuzzy sets. Applied Soft Computing, 102, 107098. https://doi.org/10.1016/j.asoc.2021.107098
  • Gigović, L., Pamučar, D., Bajić, Z., & Milićević, M. (2016). The combination of expert judgment and GIS-MAIRCA analysis for the selection of sites for ammunition depots. Sustainability, 8(4), 372. https://doi.org/10.3390/su8040372
  • Gilan, S. S., Sebt, M. H., & Shahhosseini, V. (2012). Computing with words for hierarchical competency-based selection of personnel in construction companies. Applied Soft Computing, 12(2), 860-871. https://doi.org/10.1016/j.asoc.2011.10.004
  • Gul, M., & Ak, M. F. (2020). Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA. Stochastic Environmental Research and Risk Assessment, 34(8), 1231-1262. https://doi.org/10.1007/s00477-020-01816-x
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Details

Primary Language English
Subjects Business Administration
Journal Section Araştırma Makaleleri
Authors

Karahan Kara 0000-0002-1359-0244

Sercan Edinsel 0000-0003-2831-7504

Galip Cihan Yalçın 0000-0001-9348-0709

Publication Date December 28, 2022
Submission Date November 29, 2022
Acceptance Date December 7, 2022
Published in Issue Year 2022 Volume: 4 Issue: 2

Cite

APA Kara, K., Edinsel, S., & Yalçın, G. C. (2022). Human Resources Manager Selection Based on Fuzzy and Intuitionistic Fuzzy Numbers for Logistics Companies. Mersin Üniversitesi Denizcilik Ve Lojistik Araştırmaları Dergisi, 4(2), 254-286. https://doi.org/10.54410/denlojad.1211835
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