Araştırma Makalesi
BibTex RIS Kaynak Göster

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

Yıl 2022, Cilt: 4 Sayı: 2, 254 - 286, 28.12.2022
https://doi.org/10.54410/denlojad.1211835

Öz

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.

Kaynakça

  • Afshari, A. (2015). Selection of construction project manager by using Delphi and fuzzy linguistic decision making. Journal of Intelligent & Fuzzy Systems, 28(6), 2827-2838. https://doi.org/10.3233/IFS-151562
  • 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
  • Boran, F. E., Genç, S., & Akay, D. (2011). Personnel selection based on intuitionistic fuzzy sets. Human Factors and Ergonomics in Manufacturing & Service Industries, 21(5), 493-503. https://doi.org/10.1002/hfm.20252
  • 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
  • İbicioğlu, H., & Ünal, Ö. F. (2014). Analitik hiyerarşi prosesi ile yetkinlik bazlı insan kaynakları yöneticisi seçimi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 28(4), 55-78.
  • Javadein, S. R. S Fathi, M. R., Behrooz, A., & Sadeghi, M. R. (2013). Human Resource Manager Selection Based on Logarithmic Fuzzy Preference Programming and TOPSIS Methods. International Journal of Human Resource Studies, 3(2), 14. https://doi.org/10.5296/ijhrs.v3i2.3591
  • Jazebi, F., & Rashidi, A. (2013). An automated procedure for selecting project managers in construction firms. Journal of Civil Engineering and Management, 19(1), 97-106. https://doi.org/10.3846/13923730.2012.738707
  • Jereb, E., Rajkovic, U., & Rajkovic, V. (2005). A hierarchical multi‐attribute system approach to personnel selection. International Journal of Selection and Assessment, 13(3), 198-205. https://doi.org/10.1111/j.1468-2389.2005.00315.x
  • Kaygin, C. Y., Tazegül, A., & Yazarkan, H. (2016). Estimation Capability of Financial Failures and Successes of Enterprises Using Data Mining and Logistic Regression Analysis. Ege Akademik Bakis, 16(1), 147.
  • Kelemenis, A., & Askounis, D. (2010). A new TOPSIS-based multi-criteria approach to personnel selection. Expert systems with applications, 37(7), 4999-5008. https://doi.org/10.1016/j.eswa.2009.12.013
  • Kelemenis, A., Ergazakis, K., & Askounis, D. (2011). Support managers’ selection using an extension of fuzzy TOPSIS. Expert Systems with Applications, 38(3), 2774-2782. https://doi.org/10.1016/j.eswa.2010.08.068
  • Kumari, R., & Mishra, A. R. (2020). Multi-criteria COPRAS method based on parametric measures for intuitionistic fuzzy sets: application of green supplier selection. Iranian journal of science and technology, Transactions of Electrical Engineering, 44(4), 1645-1662. https://doi.org/10.1007/s40998-020-00312-w
  • Kusumawardani, R. P., & Agintiara, M. (2015). Application of fuzzy AHP-TOPSIS method for decision making in human resource manager selection process. Procedia computer science, 72, 638-646. https://doi.org/10.1016/j.procs.2015.12.173
  • Lipiec, J. (2001). Human resources management perspective at the turn of the century. Public Personnel Management, 30(2), 137-146. https://doi.org/10.1177/009102600103000201
  • Manaan, O. A., Ahadzie, D. K., Panford, J. K., & Proverbs, D. G. (2014). Competency-based evaluation of project managers’ performance in mass house building projects in Ghana–the fuzzy set theory approach. Journal of Science and Technology (Ghana), 34(1), 46-62. https://doi.org/10.4314/just.v34i1.5
  • Marlowe, C. M., Schneider, S. L., & Nelson, C. E. (1996). Gender and Attractiveness Biases in Hiring Decisions: Are More Experienced Managers Less Biased. Journal of Applied Psychology, 81(1), 11.
  • Mishra, A., Sisodia, G., Raj Pardasani, K., & Sharma, K. (2020). Multi-criteria IT personnel selection on intuitionistic fuzzy information measures and ARAS methodology. Iranian Journal of Fuzzy Systems, 17(4), 55-68. https://doi.org/10.22111/IJFS.2020.5406
  • Nakiboglu, G., & Bulgurcu, B. (2021). Supplier selection in a Turkish textile company by using intuitionistic fuzzy decision-making. The Journal of the Textile Institute, 112(2), 322-332. https://doi.org/10.1080/00405000.2020.1747675
  • Oztaysi, B., Onar, S. C., Kahraman, C., & Gok, M. (2020). Call center performance measurement using intuitionistic fuzzy sets. Journal of Enterprise Information Management, 33(6), 1647-1668. https://doi.org/10.1108/JEIM-04-2017-0050
  • Özbek, A. (2014). Yöneticilerin çok kriterli karar verme yöntemi ile belirlenmesi. Journal of Management and Economics Research, 12(24), 209-225. http://dx.doi.org/10.11611/JMER314
  • Özbek, A. (2015). Akademik birim yöneticilerinin MOORA yöntemiyle seçilmesi: Kırıkkale üzerine bir uygulama. Erciyes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 1(38), 1-18.
  • Pamučar, D., Vasin, L., & Lukovac, L. (2014). Selection of railway level crossings for investing in security equipment using hybrid DEMATEL-MARICA model. In XVI international scientific-expert conference on railway, railcon (pp. 89-92).
  • Rahimi, M., Kumar, P., Moomivand, B., & Yari, G. (2021). An intuitionistic fuzzy entropy approach for supplier selection. Complex & Intelligent Systems, 7(4), 1869-1876. https://doi.org/10.1007/s40747-020-00224-6
  • Rashidi, A., Jazebi, F., & Brilakis, I. (2011). Neurofuzzy genetic system for selection of construction project managers. Journal of Construction Engineering and Management, 137(1), 17-29.
  • Sabina, M. N., & Davood, H. Z. (2013). Designing a fuzzy model for decision support systems in the selection and recruitment process. African Journal of Business Management, 7(16), 1486-1491. https://doi.org/10.5897/AJBM11.2803
  • Sadatrasool, M., Bozorgi-Amiri, A., & Yousefi-Babadi, A. (2016). Project manager selection based on project manager competency model: PCA–MCDM Approach. Journal of Project Management, 1(1), 7-20. https://doi.org/10.5267/j.jpm.2017.1.004
  • Sadeghi, H., Mousakhani, M., Yazdani, M., & Delavari, M. (2014). Evaluating project managers by an interval decision-making method based on a new project manager competency model. Arabian Journal for Science and Engineering, 39(2), 1417-1430. https://doi.org/10.1007/s13369-013-0631-0
  • Salimian, S., & Mousavi, S. M. (2022). The selection of healthcare waste treatment technologies by a multi-criteria group decision-making method with intuitionistic fuzzy sets. Journal of Industrial and Systems Engineering, 14(1), 205-220.
  • Schitea, D., Deveci, M., Iordache, M., Bilgili, K., Akyurt, I. Z., & Iordache, I. (2019). Hydrogen mobility roll-up site selection using intuitionistic fuzzy sets based WASPAS, COPRAS and EDAS. International Journal of Hydrogen Energy, 44(16), 8585-8600. https://doi.org/10.1016/j.ijhydene.2019.02.011
  • Singh, M, Rathi, R, Antony, J & Garza-Reyes, JA (2021). Lean Six Sigma Project Selection in a Manufacturing Environment Using Hybrid Methodology Based on Intuitionistic Fuzzy MADM Approach. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2021.3049877
  • Thakre, T.A., Chaudhari, O.K. and Dhawade, N.R. (2017). Recruitment of personnel in a bank using AHP-FLP model. Advances in Modelling and Analysis A, 54(3), 407–423.
  • Turk, S. (2022). Taguchi Loss Function in Intuitionistic Fuzzy Sets along with Personal Perceptions for the Sustainable Supplier Selection Problem. Sustainability, 14(10), 6178. https://doi.org/10.3390/su14106178
  • Uğur, L. O. (2017). MOORA optimizasyon yaklaşımı ile inşaat proje müdürü seçimi: Çok kriterli bir karar verme uygulaması. Politeknik dergisi, 20(3), 717-723. https://doi.org/10.2339/politeknik.339408
  • Urosevic, S., Karabasevic, D., Stanujkic, D., & Maksimovic, M. (2017). An Approach to Personnel Selection in the Tourism Industry Based on the SWARA and the WASPAS Methods. Economic Computation and Economic Cybernetics Studies And Research, 51(1), 75-88.
  • Wan, S. P., Wang, Q. Y., & Dong, J. Y. (2013). The extended VIKOR method for multi-attribute group decision making with triangular intuitionistic fuzzy numbers. Knowledge-Based Systems, 52, 65-77. https://doi.org/10.1016/j.knosys.2013.06.019
  • Wu, W. W., & Lee, Y. T. (2007). Developing global managers’ competencies using the fuzzy DEMATEL method. Expert systems with applications, 32(2), 499-507. https://doi.org/10.1016/j.eswa.2005.12.005
  • Xing, B., & Zhang, A. D. (2006, October). Application of fuzzy analytical hierarchy process in selecting a project manager. In 2006 International Conference on Management Science and Engineering (pp. 1417-1421). IEEE. https://doi.org/10.1109/ICMSE.2006.314252
  • Xiong, L., Zhong, S., Liu, S., Zhang, X., & Li, Y. (2020). An Approach for Resilient-Green Supplier Selection Based on WASPAS, BWM, and TOPSIS under Intuitionistic Fuzzy Sets. Mathematical Problems in Engineering, 2020, 1-18. https://doi.org/10.1155/2020/1761893
  • Xu, Z. (2007). Intuitionistic fuzzy aggregation operators. IEEE Transactions on fuzzy systems, 15(6), 1179-1187. https://doi.org/10.1109/TFUZZ.2006.890678
  • Varajão, J., & Cruz-Cunha, M. M. (2013). Using AHP and the IPMA Competence Baseline in the project managers selection process. International Journal of Production Research, 51(11), 3342-3354. https://doi.org/10.1080/00207543.2013.774473
  • Zavadskas, E. K., Turskis, Z., Tamosaitiene, J., & Marina, V. (2008). Selection of construction project managers by applying COPRAS-G method. Computer Modelling and New Technologies, 12(3), 22-28.
  • Zavadskas, E. K., Vainiūnas, P., Turskis, Z., & Tamošaitienė, J. (2012). Multiple criteria decision support system for assessment of projects managers in construction. International journal of information technology & decision making, 11(02), 501-520. https://doi.org/10.1142/S0219622012400135
  • Zhao, L., Guo, Y., & Cui, W. (2009). The application of fuzzy comprehensive evaluation methods in the selection of a project manager. In 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology (pp. 1387-1391). IEEE. https://doi.org/10.1109/ICCIT.2009.233
  • Zhou, Z., Dou, Y., Zhang, X., Zhao, D., & Tan, Y. (2018). A group decision-making model for wastewater treatment plans selection based on intuitionistic fuzzy sets. Journal of Environmental Engineering and Landscape Management, 26(4), 251-260. https://doi.org/10.3846/jeelm.2018.6122
  • Zolfani, S. H., Rezaeiniya, N., Aghdaie, M. H., & Zavadskas, E. K. (2012). Quality control manager selection based on AHP-COPRAS-G methods: a case in Iran. Economic research-Ekonomska istraživanja, 25(1), 72-86. https://doi.org/10.1080/1331677X.2012.11517495

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

Yıl 2022, Cilt: 4 Sayı: 2, 254 - 286, 28.12.2022
https://doi.org/10.54410/denlojad.1211835

Öz

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.

Kaynakça

  • Afshari, A. (2015). Selection of construction project manager by using Delphi and fuzzy linguistic decision making. Journal of Intelligent & Fuzzy Systems, 28(6), 2827-2838. https://doi.org/10.3233/IFS-151562
  • 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
  • Boran, F. E., Genç, S., & Akay, D. (2011). Personnel selection based on intuitionistic fuzzy sets. Human Factors and Ergonomics in Manufacturing & Service Industries, 21(5), 493-503. https://doi.org/10.1002/hfm.20252
  • 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
  • İbicioğlu, H., & Ünal, Ö. F. (2014). Analitik hiyerarşi prosesi ile yetkinlik bazlı insan kaynakları yöneticisi seçimi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 28(4), 55-78.
  • Javadein, S. R. S Fathi, M. R., Behrooz, A., & Sadeghi, M. R. (2013). Human Resource Manager Selection Based on Logarithmic Fuzzy Preference Programming and TOPSIS Methods. International Journal of Human Resource Studies, 3(2), 14. https://doi.org/10.5296/ijhrs.v3i2.3591
  • Jazebi, F., & Rashidi, A. (2013). An automated procedure for selecting project managers in construction firms. Journal of Civil Engineering and Management, 19(1), 97-106. https://doi.org/10.3846/13923730.2012.738707
  • Jereb, E., Rajkovic, U., & Rajkovic, V. (2005). A hierarchical multi‐attribute system approach to personnel selection. International Journal of Selection and Assessment, 13(3), 198-205. https://doi.org/10.1111/j.1468-2389.2005.00315.x
  • Kaygin, C. Y., Tazegül, A., & Yazarkan, H. (2016). Estimation Capability of Financial Failures and Successes of Enterprises Using Data Mining and Logistic Regression Analysis. Ege Akademik Bakis, 16(1), 147.
  • Kelemenis, A., & Askounis, D. (2010). A new TOPSIS-based multi-criteria approach to personnel selection. Expert systems with applications, 37(7), 4999-5008. https://doi.org/10.1016/j.eswa.2009.12.013
  • Kelemenis, A., Ergazakis, K., & Askounis, D. (2011). Support managers’ selection using an extension of fuzzy TOPSIS. Expert Systems with Applications, 38(3), 2774-2782. https://doi.org/10.1016/j.eswa.2010.08.068
  • Kumari, R., & Mishra, A. R. (2020). Multi-criteria COPRAS method based on parametric measures for intuitionistic fuzzy sets: application of green supplier selection. Iranian journal of science and technology, Transactions of Electrical Engineering, 44(4), 1645-1662. https://doi.org/10.1007/s40998-020-00312-w
  • Kusumawardani, R. P., & Agintiara, M. (2015). Application of fuzzy AHP-TOPSIS method for decision making in human resource manager selection process. Procedia computer science, 72, 638-646. https://doi.org/10.1016/j.procs.2015.12.173
  • Lipiec, J. (2001). Human resources management perspective at the turn of the century. Public Personnel Management, 30(2), 137-146. https://doi.org/10.1177/009102600103000201
  • Manaan, O. A., Ahadzie, D. K., Panford, J. K., & Proverbs, D. G. (2014). Competency-based evaluation of project managers’ performance in mass house building projects in Ghana–the fuzzy set theory approach. Journal of Science and Technology (Ghana), 34(1), 46-62. https://doi.org/10.4314/just.v34i1.5
  • Marlowe, C. M., Schneider, S. L., & Nelson, C. E. (1996). Gender and Attractiveness Biases in Hiring Decisions: Are More Experienced Managers Less Biased. Journal of Applied Psychology, 81(1), 11.
  • Mishra, A., Sisodia, G., Raj Pardasani, K., & Sharma, K. (2020). Multi-criteria IT personnel selection on intuitionistic fuzzy information measures and ARAS methodology. Iranian Journal of Fuzzy Systems, 17(4), 55-68. https://doi.org/10.22111/IJFS.2020.5406
  • Nakiboglu, G., & Bulgurcu, B. (2021). Supplier selection in a Turkish textile company by using intuitionistic fuzzy decision-making. The Journal of the Textile Institute, 112(2), 322-332. https://doi.org/10.1080/00405000.2020.1747675
  • Oztaysi, B., Onar, S. C., Kahraman, C., & Gok, M. (2020). Call center performance measurement using intuitionistic fuzzy sets. Journal of Enterprise Information Management, 33(6), 1647-1668. https://doi.org/10.1108/JEIM-04-2017-0050
  • Özbek, A. (2014). Yöneticilerin çok kriterli karar verme yöntemi ile belirlenmesi. Journal of Management and Economics Research, 12(24), 209-225. http://dx.doi.org/10.11611/JMER314
  • Özbek, A. (2015). Akademik birim yöneticilerinin MOORA yöntemiyle seçilmesi: Kırıkkale üzerine bir uygulama. Erciyes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 1(38), 1-18.
  • Pamučar, D., Vasin, L., & Lukovac, L. (2014). Selection of railway level crossings for investing in security equipment using hybrid DEMATEL-MARICA model. In XVI international scientific-expert conference on railway, railcon (pp. 89-92).
  • Rahimi, M., Kumar, P., Moomivand, B., & Yari, G. (2021). An intuitionistic fuzzy entropy approach for supplier selection. Complex & Intelligent Systems, 7(4), 1869-1876. https://doi.org/10.1007/s40747-020-00224-6
  • Rashidi, A., Jazebi, F., & Brilakis, I. (2011). Neurofuzzy genetic system for selection of construction project managers. Journal of Construction Engineering and Management, 137(1), 17-29.
  • Sabina, M. N., & Davood, H. Z. (2013). Designing a fuzzy model for decision support systems in the selection and recruitment process. African Journal of Business Management, 7(16), 1486-1491. https://doi.org/10.5897/AJBM11.2803
  • Sadatrasool, M., Bozorgi-Amiri, A., & Yousefi-Babadi, A. (2016). Project manager selection based on project manager competency model: PCA–MCDM Approach. Journal of Project Management, 1(1), 7-20. https://doi.org/10.5267/j.jpm.2017.1.004
  • Sadeghi, H., Mousakhani, M., Yazdani, M., & Delavari, M. (2014). Evaluating project managers by an interval decision-making method based on a new project manager competency model. Arabian Journal for Science and Engineering, 39(2), 1417-1430. https://doi.org/10.1007/s13369-013-0631-0
  • Salimian, S., & Mousavi, S. M. (2022). The selection of healthcare waste treatment technologies by a multi-criteria group decision-making method with intuitionistic fuzzy sets. Journal of Industrial and Systems Engineering, 14(1), 205-220.
  • Schitea, D., Deveci, M., Iordache, M., Bilgili, K., Akyurt, I. Z., & Iordache, I. (2019). Hydrogen mobility roll-up site selection using intuitionistic fuzzy sets based WASPAS, COPRAS and EDAS. International Journal of Hydrogen Energy, 44(16), 8585-8600. https://doi.org/10.1016/j.ijhydene.2019.02.011
  • Singh, M, Rathi, R, Antony, J & Garza-Reyes, JA (2021). Lean Six Sigma Project Selection in a Manufacturing Environment Using Hybrid Methodology Based on Intuitionistic Fuzzy MADM Approach. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2021.3049877
  • Thakre, T.A., Chaudhari, O.K. and Dhawade, N.R. (2017). Recruitment of personnel in a bank using AHP-FLP model. Advances in Modelling and Analysis A, 54(3), 407–423.
  • Turk, S. (2022). Taguchi Loss Function in Intuitionistic Fuzzy Sets along with Personal Perceptions for the Sustainable Supplier Selection Problem. Sustainability, 14(10), 6178. https://doi.org/10.3390/su14106178
  • Uğur, L. O. (2017). MOORA optimizasyon yaklaşımı ile inşaat proje müdürü seçimi: Çok kriterli bir karar verme uygulaması. Politeknik dergisi, 20(3), 717-723. https://doi.org/10.2339/politeknik.339408
  • Urosevic, S., Karabasevic, D., Stanujkic, D., & Maksimovic, M. (2017). An Approach to Personnel Selection in the Tourism Industry Based on the SWARA and the WASPAS Methods. Economic Computation and Economic Cybernetics Studies And Research, 51(1), 75-88.
  • Wan, S. P., Wang, Q. Y., & Dong, J. Y. (2013). The extended VIKOR method for multi-attribute group decision making with triangular intuitionistic fuzzy numbers. Knowledge-Based Systems, 52, 65-77. https://doi.org/10.1016/j.knosys.2013.06.019
  • Wu, W. W., & Lee, Y. T. (2007). Developing global managers’ competencies using the fuzzy DEMATEL method. Expert systems with applications, 32(2), 499-507. https://doi.org/10.1016/j.eswa.2005.12.005
  • Xing, B., & Zhang, A. D. (2006, October). Application of fuzzy analytical hierarchy process in selecting a project manager. In 2006 International Conference on Management Science and Engineering (pp. 1417-1421). IEEE. https://doi.org/10.1109/ICMSE.2006.314252
  • Xiong, L., Zhong, S., Liu, S., Zhang, X., & Li, Y. (2020). An Approach for Resilient-Green Supplier Selection Based on WASPAS, BWM, and TOPSIS under Intuitionistic Fuzzy Sets. Mathematical Problems in Engineering, 2020, 1-18. https://doi.org/10.1155/2020/1761893
  • Xu, Z. (2007). Intuitionistic fuzzy aggregation operators. IEEE Transactions on fuzzy systems, 15(6), 1179-1187. https://doi.org/10.1109/TFUZZ.2006.890678
  • Varajão, J., & Cruz-Cunha, M. M. (2013). Using AHP and the IPMA Competence Baseline in the project managers selection process. International Journal of Production Research, 51(11), 3342-3354. https://doi.org/10.1080/00207543.2013.774473
  • Zavadskas, E. K., Turskis, Z., Tamosaitiene, J., & Marina, V. (2008). Selection of construction project managers by applying COPRAS-G method. Computer Modelling and New Technologies, 12(3), 22-28.
  • Zavadskas, E. K., Vainiūnas, P., Turskis, Z., & Tamošaitienė, J. (2012). Multiple criteria decision support system for assessment of projects managers in construction. International journal of information technology & decision making, 11(02), 501-520. https://doi.org/10.1142/S0219622012400135
  • Zhao, L., Guo, Y., & Cui, W. (2009). The application of fuzzy comprehensive evaluation methods in the selection of a project manager. In 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology (pp. 1387-1391). IEEE. https://doi.org/10.1109/ICCIT.2009.233
  • Zhou, Z., Dou, Y., Zhang, X., Zhao, D., & Tan, Y. (2018). A group decision-making model for wastewater treatment plans selection based on intuitionistic fuzzy sets. Journal of Environmental Engineering and Landscape Management, 26(4), 251-260. https://doi.org/10.3846/jeelm.2018.6122
  • Zolfani, S. H., Rezaeiniya, N., Aghdaie, M. H., & Zavadskas, E. K. (2012). Quality control manager selection based on AHP-COPRAS-G methods: a case in Iran. Economic research-Ekonomska istraživanja, 25(1), 72-86. https://doi.org/10.1080/1331677X.2012.11517495
Toplam 65 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Araştırma Makaleleri
Yazarlar

Karahan Kara 0000-0002-1359-0244

Sercan Edinsel 0000-0003-2831-7504

Galip Cihan Yalçın 0000-0001-9348-0709

Yayımlanma Tarihi 28 Aralık 2022
Gönderilme Tarihi 29 Kasım 2022
Kabul Tarihi 7 Aralık 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 4 Sayı: 2

Kaynak Göster

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

                                                          Mersin University Journal of Maritime and Logistics Research