Project Manager Selection in a Fuzzy Environment: A Case in a Defense Industry

Yıl 2024, , 153 - 168, 28.06.2024

Burcu Tezcan , Tamer Eren

https://doi.org/10.54078/savsad.1193540

Öz

Defense industry projects are increasing in Turkey. Defense industry projects are in the project group with high cost and high added value. One of the most important reasons for the success of defense industry projects is the good formation of the project team. Choosing a good project manager is necessary to create a good project team. This study discusses the project manager selection problem in a company in the defense industry. The solution to this problem was carried out by considering the business procedures applied in real life. Twelve criteria were taken into account for the pre-selection of the project manager. The weighted Scoring (AP) method was used for pre-selection. Seven different criteria were determined for the candidates who passed the pre-selection. It is aimed to evaluate five candidates under these criteria. Pythagorean Fuzzy (PB) clusters were used to offer a wide evaluation scale to the decision maker. The weights of the seven criteria determined for the defense industry were calculated with the Pythagorean Fuzzy Analytical Hierarchy Method (PBAHP). The Pythagorean Bulanık Technique for Order Preference by Similarity to the Ideal Solution (PBTOPSIS) method determined the five candidates who passed the pre-selection. This study will guide you on how to select the project manager. In addition, the method combination used in the research and the methodology followed differ from other studies in the literature.

Anahtar Kelimeler

Defense industry, project manager selection, weighted scoring, PFAHP, PFTOPSIS

Bulanık Ortamda Proje Yöneticisi Seçimi: Savunma Sanayi Firmasında Bir Uygulama

Öz

Türkiye’de savunma sanayi projeleri artmaktadır. Savunma sanayi projeleri yüksek maliyetli ve katma değeri yüksek proje grubundandır. Savunma sanayi projelerinin başarılı olmasının en önemli sebeplerinde biri proje ekibinin iyi bir şekilde oluşturulmasıdır. İyi bir proje ekibinin oluşturulması için iyi bir proje yöneticisinin seçilmesi gerekmektedir. Bu çalışmada savunma sanayisindeki bir firmada proje yöneticisi seçim problemi ele alınmıştır. Bu problemin çözümünde, gerçek hayatta uygulanan iş prosedürleri dikkate alınarak gerçekleştirilmiştir. Proje yöneticisi seçiminde ön eleme için on iki kriter dikkate alınmıştır. Ön eleme yapmak için Ağırlıklı Puanlama (AP) yöntemi kullanılmıştır. Ön elemeyi geçen adaylar için farklı yedi adet kriter belirlenmiştir. Bu kriterler altında beş adayın değerlendirilmesi amaçlanmıştır. Karar vericiye geniş değerlendirme ölçeği sunan Pisagor Bulanık (PB) kümeler kullanılmıştır. Savunma sanayi için belirlenen yedi kriterin ağırlıkları Pisagor Bulanık Analitik Hiyerarşi Yöntemi (PBAHP) ile hesaplanmıştır. Ön elemeden geçen beş aday Pisagor Bulanık Technique for Order Preference by Similarity to Ideal Solution (PBTOPSIS) yöntemi ile sıralaması belirlenmiştir. Yapılan bu çalışma proje yöneticisinin nasıl seçileceğine yol gösterecektir. Ayrıca çalışmada kullanılan yöntem kombinasyonu ve izlenen metodoloji literatürdeki diğer çalışmalardan farklılık göstermektedir.

Anahtar Kelimeler

Savunma sanayi, proje yöneticisi seçimi, ağırlıklı puanlama yöntemi, PBAHP, PBTOPSIS

Kaynakça

• Akram, M., Dudek, W. A., & Ilyas, F. (2019). Group decision‐making based on pythagorean fuzzy TOPSIS method. International Journal of Intelligent Systems, 34(7), 1455-1475.
• Alguliyev, R. M., Aliguliyev, R. M., & Mahmudova, R. S. (2015). Multicriteria personnel selection by the modified fuzzy VIKOR method. The Scientific World Journal.
• Atanassov, K. (1988). Review and new results on intuitionistic fuzzy sets. Preprint Im-MFAIS-1-88, 5(1).
• Baran, T. (2018). Investigation of defence industry in Turkey and evaluation of the effects of defense industry spending on the economy. International Journal of Economics and Administrative Sciences, 2(4), 58-81.
• Carretta, T. R., & King, R. E. (2015). Personnel selection influences on remotely piloted aircraft human-system integration. Aerospace Medicine and Human Performance, 86(8), 736-741.
• Chaghooshi, A., & Arab, A., & Dehshiri, S. (2016). A fuzzy hybrid approach for project manager selection. Decision Science Letters, 5(3), 447-460.
• Chen, C. T., & Hung, W. Z. (2020). A two-phase model for personnel selection based on multi-type fuzzy information. Mathematics, 8(10), 1703.
• Costa, I. P. D. A., Terra, A. V., Moreira, M. Â. L., Pereira, M. T., Fávero, L. P. L., Santos, M. D., & Gomes, C. F. S. (2022). A systematic approach to the management of military human resources through the ELECTRE-MOr multicriteria method. Algorithms, 15(11), 422.
• Dağdeviren, M., Yavuz, S., Kılınç, N. (2009). Weapon selection using the AHP and TOPSIS methods under fuzzy environment, Expert Systems with Applications, 36(4), 8143-8151.
• Danışan, T., Özcan, E., & Eren, T. (2022). Personnel selection with multi-criteria decision making methods in the ready-to-wear sector. Tehnički vjesnik, 29(4), 1339-1347.
• Danışman, O. (2021). Ekip atama probleminin çok kriterli karar verme yöntemleri ile incelenmesi (Tez No. 315966) [Yüksek lisans tezi, Başkent Üniversitesi]. YÖK Ulusal Tez Merkezi.
• Demirci, A. E., & Kılıç, H. S. (2019). Personnel selection based on integrated multi-criteria decision making techniques. International Journal of Advances in Engineering and Pure Sciences, 31(2), 163-178.
• Ebrahimi, E., Fathi, M. R., & Sobhani, S. M. (2022). A modification of technique for order preference by similarity to ideal solution (TOPSIS) through fuzzy similarity method (A numerical example of the personnel selection). Journal of Applied Research on Industrial Engineering.
• Elidolu, G., Uyanık, T., & Arslanoğlu, Y. (2020, 21-23 Kasım). Seafarer personnel selection with fuzzy AHP. (M. Özcanlı & A. Çalık, Ed.) 5th International Mediterranean Science and Engineering Congress (pp. 632-636). https://drive.google.com/file/d/1Sij_1W-NDpWv3D_t6BvR4Aq_hxCupJuz/view
• Ersöz, F., & Kabak, M. (2010). Savunma sanayi uygulamalarında çok kriterli karar verme yöntemlerinin literatür araştırması. Savunma Bilimleri Dergisi, 9(1), 97-125.
• Gatewood, R. D., & Feild, H. S. (1987). A personnel selection program for small business. Journal of Small Business Management, 25(4), 16.
• Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In multiple attribute decision making (pp. 58-191). Springer.
• İlbahar, E., Karaşan, A., Cebi, S., & Kahraman, C. (2018). A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Safety science, 103, 124-136.
• Jasemi, M., & Ahmadi, E. (2018). A new fuzzy ELECTRE based multiple criteria method for personnel selection. Scientia Iranica, 25(2), 943-953.
• Kilic, H. S., Demirci, A. E., & Delen, D. (2020). An integrated decision analysis methodology based on IF-DEMATEL & IF-ELECTRE for personnel selection. Decision Support Systems, 137, 113360.
• Kumar, D. S., Radhika, S., & Suman, K. N. S. (2013). MADM methods for finding the right personnel in academic institutions. International Journal of u-and e-Service, Science and Technology, 6(5), 133-144.
• Kurtay, K. G., Gökmen, Y., Altundaş, A., & Dağıstanlı, H. A. (2021). Savunma sanayii projelerinin çok kriterli karar verme yöntemleriyle önceliklendirilmesi ve karşılaştırılması: Karma bir model önerisi. SAVSAD Savunma ve Savaş Araştırmaları Dergisi, 31(1), 1-24.
• 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.
• Liu, H. C., Qin, J. T., Mao, L. X., & Zhang, Z. Y. (2015). Personnel selection using interval 2‐tuple linguistic VIKOR method. Human Factors and Ergonomics in Manufacturing & Service Industries, 25(3), 370-384.
• Mcdaniel, M. A., Kepes, S., & Banks, G. C. (2011). The uniform guidelines are a detriment to the field of personnel selection. Industrial and Organizational Psychology, 4(4), 494-514.
• Nacar, E. N., & Erdebilli, B. (2021). Tesis yeri seçimine yeni bir bakış: Katmanlı çok kriterli karar verme yöntemi, Verimlilik Dergisi, 4, 103-117.
• Nong, N. M. T., & Ha, D. S. (2021). Application of MCDM methods to qualified personnel selection in distribution science: Case of logistics companies. Journal of Distrubution Science, 19(8), 25-35.
• Öztürk, F., & Kaya, G. K. (2020). Personnel selection with fuzzy VIKOR: An application in automotive supply industry. Gazi University Science Journal: Part C Design and Technology, 8(1), 94-108.
• Palczewski, K., & Sałabun, W. (2019). The fuzzy TOPSIS applications in the last decade. Procedia Computer Science, 159, 2294-2303.
• Petridis, K., Drogalas, G., & Zografidou, E. (2021). Internal auditor selection using a TOPSIS/non-linear programming model. Annals of Operations Research, 296(1), 513-539.
• Raj 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.
• Rani, P., Mishra, A. R., Pardasani, K. R., Mardani, A., Liao, H., & Streimikiene, D. (2019). A novel VIKOR approach based on entropy and divergence measures of Pythagorean fuzzy sets to evaluate renewable energy technologies in India. Journal of Cleaner Production, 238, 117936.
• Rouyendegh, B. D., & Erkan, T. E. (2013). An application of the fuzzy electre method for academic staff selection. Human Factors and Ergonomics in Manufacturing & Service Industries, 23(2), 107-115.
• Sang, X., Liu, X., & Qin, J. (2015). An analytical solution to fuzzy TOPSIS and its application in personnel selection for knowledge-intensive enterprise. Applied Soft Computing, 30, 190-204.
• Sasad sektör performans raporu. (2021). Sasad Yayınları. https://sasad.org.tr/sasad-sektor-performans-raporu-2021
• Stockholm International Peace Research Institute. (2021). Global military expenditure sees largest annual increase in a decade—says SIPRI—reaching $1917 billion in 2019. SIPRI.
• Şehitoğlu, A., & Chouseinoglou, O. (2022). Divite-and-conquer: A systematic approach for subcontractor selection in defense industry projects. International Journal of Industrial Engineering, 29(1). https://doi.org/10.23055/ijietap.2022.29.1.7001
• Tezcan, B., Özcan, N. A., Özcan, E., & Eren, T. (2020). Deprem sonrası mobil hizmet tesisi seçim problemi için çok kriterli bir karar modeli önerisi. International Journal Of Engineering Research and Development, 12(2), 753-763.
• Tezcan, B., & Eren, T. (2022). Orman yangınına sebep olan kriterlerin bulanık ortamda değerlendirilmesi, Politeknik Dergisi, 27(2), 545-558.
• Tezcan, B., Eren, T., Özcan, E., & Gür, Ş. (2019). Bir tekstil işletmesinde çok ölçütlü karar verme yöntemleri ile personellerin değerlendirilmesi. Trakya Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 8(2), 1-20.
• Tezcan, B., Alakaş, H. M., Özcan, E., & Eren, T. (2021). Afet sonrası geçici depo yeri seçimi ve çok araçlı araç rotalama uygulaması: Kırıkkale ilinde bir uygulama. Politeknik Dergisi, 26(1), 13-27.
• 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.
• Vatansever, K., & Oncel, M. (2014). Implementation of integrated multi-criteria decision making techniques for academic staff recruitment. Journal of Management Marketing and Logistics, 1(2), 111-126.
• Vural, D., Erkan, K. Ö. S. E., & Bayam, B. (2020). AHP ve VIKOR yöntemleri ile personel seçimi. Yalova Sosyal Bilimler Dergisi, 10(21), 70-89.
• Wiernik, B. M., Raghavan, M., Caretta, T. R., & Coovert, M. D. (2022). Developing and validating a serious game‐based assessment for cyber occupations in the US Air Force. International Journal of Selection and Assessment, 30(1), 27-47.
• Yager, R. R., & Abbasov, A. M. (2013). Pythagorean membership grades, complex numbers, and decision making. International Journal of Intelligent Systems, 28(5), 436-452.
• Yager, R. R. (2013). Pythagorean membership grades in multicriteria decision making. IEEE Transactions on Fuzzy Systems, 22(4), 958-965.
• Zadeh, L. A. (1999). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 100, 9-34.
• Zhang, X., & Xu, Z. (2014). Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. International Journal of Intelligent Systems, 29(12), 1061-1078.