HYBRID PERFORMANCE ANALYSIS WITH MULTI-CRITERIA DECISION-MAKING METHODS: EXAMPLE OF STORE MANAGERS

Yıl 2024, Cilt: 4 Sayı: 2, 47 - 70, 13.09.2024

Sercan Edinsel , Cem Duran , Mehmet Alper Akdemir

Öz

Yöneticilerin performansının etkili bir şekilde değerlendirilmesi ve arttırılması, organizasyonel başarıya ulaşmak ve dinamik iş ortamında rekabet avantajını sürdürmek için çok önemlidir. Bu çalışma, iki önemli karar verme tekniğini birleştiren kapsamlı bir çerçeve kullanarak mağaza yöneticisi performans değerlendirmesi için yeni bir yaklaşım sunmaktadır: Küresel Bulanık Adım Adım Ağırlık Değerlendirme Oran Analizi (SF-SWARA) ve Küresel Bulanık Birleşik Uzlaşma Çözümü (SF-CoCoSo). Sunulan SF-SWARA-CoCoSo yöntemi, değerlendirme sürecine birden fazla bakış açısı ve nesnel kriter dahil ederek yöneticilerin performansını değerlendirmede yer alan doğal karmaşıklıkları ve öznellikleri ele almayı amaçlamaktadır. Bu çalışmanın amacı çok kriterli karar verme yöntemlerini hibrit bir şekilde uygulayarak mağaza yöneticilerinin performansını basit ve anlaşılır bir şekilde değerlendirilmesini sağlamaktır. Çalışmada Küresel Bulanık Adım Adım Ağırlık Değerlendirme Oran Analizi (SF-SWARA) ve Küresel Bulanık Birleşik Uzlaşma Çözümü (SF-CoCoSo) hibrit Çok Kriterli Karar Verme Yöntemi kullanılmıştır. Çalışmanın bulguları "Bilgi ve Eğitim Düzeyi" kriterinin mağaza yöneticisi için en önemli kriter olduğu ve en düşük öneme sahip kriterin ise “Ücret” kriteri olduğunu ortaya koymaktadır. Çalışmanın sonucunda en önemli kriter olduğu tespit edilen "Bilgi ve Eğitim Düzeyi" kriterinin günümüzün bilgi çağı olması nedeni ile ortaya çıktığı sonucuna varılmıştır.

Anahtar Kelimeler

Mağaza Müdürü, Çok Kriterli Karar Verme, Performans Değerlendirme, SF-SWARA, SF-CoCoSo

HYBRID PERFORMANCE ANALYSIS WITH MULTI-CRITERIA DECISION MAKING METHODS: EXAMPLE OF STORE MANAGERS

Öz

Effectively evaluating and enhancing managers' performance is crucial for achieving organizational success and maintaining competitive advantage in a dynamic business environment. This paper presents a new approach for store manager performance evaluation using a comprehensive framework that combines two important decision-making techniques: Global Fuzzy Step-by-Step Step Weight Rating Ratio Analysis (SF-SWARA) and Global Fuzzy Combined Consensus Solution (SF-CoCoSo). The presented SF-SWARA-CoCoSo method aims to address the inherent complexities and subjectivities involved in evaluating managers' performance by incorporating multiple perspectives and objective criteria into the evaluation process. The aim of this study is to apply multi-criteria decision-making methods in a hybrid way to evaluate the performance of store managers in a simple and understandable way. Global Fuzzy Step-by-Step Step Weight Rating Ratio Analysis (SF-SWARA) and Global Fuzzy Combined Consensus Solution (SF-CoCoSo) hybrid Multi-Criteria Decision Making Method were used in the study. The findings of the study reveal that the “Knowledge and Training Level” criterion is the most important criterion for the store manager and the criterion with the lowest importance is the “Salary” criterion. As a result of the study, it is concluded that the criterion “Knowledge and Education Level”, which is determined to be the most important criterion, has emerged due to the fact that today is the information age.

Anahtar Kelimeler

Store Manager, Multi-Criteria Decision Making, Performance Evaluation, SF-SWARA, SF-CoCoSo

Kaynakça

• Afshari, A. & Letić, D. (2016). Linguistic evaluating the employee’s performance. VI International Symposium Engineering Management and Competitiveness 2016 (EMC 2016)17- 18th June 2016, Kotor, Montenegro. Doi:10.13140/RG.2.1.4003.2882.
• Ahmed, I., Sultana, I, Paul, S. K., & Azeem, A., (2013). Employee performance evaluation: A fuzzy approach. International Journal of Productivity and Performance Management, Vol. 62 Issue: 7, 718-734, https://doi.org/10.1108/IJPPM-01-2013-0013
• 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.
• Daft, R. L. (2008). Organization Theory and Design. United States of America: South-Western/ Cengage Learning.
• Edinsel, S. & Işıkçı, E. (2023). “Manager Performance Evaluation with Hybrid Multimoora Method: An Application in Logistics Industry”, International Social Mentality and Researcher Thinkers Journal, (ISSN:2630-631X) 9(75): 4381-4393. DOI: http://dx.doi.org/10.29228/smryj.72105
• Esen, H., Hatipoğlu, T., & Boyacı, A. İ. (2016). A fuzzy approach for performance appraisal: the evaluation of a purchasing specialist. In Computational Intelligence: International Joint Conference, IJCCI 2014 Rome, Italy, October 22-24, 2014 Revised Selected Papers (pp. 235- 250). Springer International Publishing.
• Falsafi, N., Zenouz, R.Y. & Mozaffari, M.M. (2011). Employees’ performance appraisal with TOPSIS under fuzzy environment. Int. J. Society Systems Science, Vol. 3, No. 3, pp.272–290. Genç, K. Y. (2020). The Management of Street Economy. Global Street Economy and Micro Entreproneurship (Edt.: S. Grima, Osman Sirkeci, Kamuran Elbeyoğlu). England: EmeraldPublication.
• Ghoushchi, S. J., Bonab, S. R., Ghiaci, A. M., Haseli, G., Tomaskova, H., & Hajiaghaei-Keshteli, M. (2021). Landfill site selection for medical waste using an integrated SWARA-WASPAS framework based on spherical fuzzy set. Sustainability, 13(24), 13950. https://doi.org/10.3390/su132413950
• Hermawan, A. & Damiyati, A. (2020). Decision support system for employee performance assessment with SAW and TOPSIS Methods. eCo-Buss. 2. 50-70. 10.32877/eb.v2i3.139. Higgs, M., Plewnia, U., & Ploch, J. (2005). Influence of team composition and task complexity on team performance. Team Performance Management: An International Journal, 11(7/8), 227- 250.
• Hooshang M. B. & James G. L., (2008),"Fuzzy logic and performance evaluation: discussion and application", International Journal of Productivity and Performance Management, Vol. 57 Iss 3 pp. 237 – 246 http://dx.doi.org/10.1108/17410400810857248.
• Hutahaean, J., Suriani, S., Supriyanto, H., Amin, M. & Azhar, Z. (2021). Implementation of simple additive weighting method in evaluating employee performance for job promotion recommendations. Webology. 19. 123-132. Doi: 10.14704/WEB/V19I1/WEB19009.
• Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of business economics and management, 11(2), 243-258.
• Kieu, P. T., Nguyen, V. T., Nguyen, V. T., & Ho, T. P. (2021). A spherical fuzzy analytic hierarchy process (SF-AHP) and combined compromise solution (CoCoSo) algorithm in distribution center location selection: A case study in agricultural supply chain. Axioms, 10(2), 53. https://doi.org/10.3390/axioms10020053
• Kilduff, M., Angelmar, R. & Mehra, A. (2000), “Top management team diversity and firm performance: examining the role of cognitions”, Organization Science, Vol. 11 No. 1, pp. 21-34.
• Kumar, V., Kalita, K., Chatterjee, P., Zavadskas, E. K., & Chakraborty, S. (2022). A SWARACoCoSo- based approach for spray painting robot selection. Informatica, 33(1), 35-54. https://doi.org/10.15388/21-INFOR466
• Kutlu Gündoğdu, F. K., & Kahraman, C. (2019a). A novel fuzzy TOPSIS method using emerging interval-valued spherical fuzzy sets. Engineering Applications of Artificial Intelligence, 85, 307- 323. https://doi.org/10.1016/j.engappai.2019.06.003
• Lidinska, L., & Jablonsky, J. (2018). AHP model for performance evaluation of employees in a Czech management consulting company. Central European Journal of Operations Research, 26, 239-258.
• Milani N., Rabieea M., & Shahmansouri A., (2018). Evaluate the efficiency of the company's employees by using VIKOR and AHP approach in Persian corporate insurance. International Journal of Business Economics and Management Studies Vol. 6, No. 2, 2018, pp. 71-79. ISSN 2348-3016
• Nobari S.M., Yousefi V., Mehrabanfar E., Jahanikia A.H. & Khadivi A.M. (2019) Development of a complementary fuzzy decision support system for employees’ performance evaluation, Economic Research, 32:1, 492-509, DOI: 10.1080/1331677X.2018.1556106
• Noor, S., Tajik, O., & Golzar, J. (2022). Simple random sampling. International Journal of Education & Language Studies, 1(2), 78-82.
• Nursari S.R.C. & Murtako A. (2020). Decision support system for employee performance evaluation with promethe method. case study: Faculty of Engineering, Pancasila University. Distance Learning Vol. 3 No. 1.
• Ozkan, C., Keskin, G. A., & Omurca, S. I. (2014). A Variant Perspective to Performance Appraisal System: Fuzzy C–Means Algorithm. International Journal of Industrial Engineering, 21(3).
• Saidin, M. S., Lee, L. S., Bakar, M. R. A., & Ahmad, M. Z. (2022). A New Divergence Measure based on Fuzzy TOPSIS for Solving Staff Performance Appraisal. Malaysian Journal of Mathematical Sciences, 16(3).
• 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.
• Sumarno, A., Setiawan, M. & Aisjah, S. (2021). Employees Performance ealuation in Defense Ministry of the Republic of Indonesia based on multicriteria decision making (MCDM) and system dynamic (SD). International Journal of Operations and Quantitative Management. 27. 245. 10.46970/2021.27.3.4.
• Taş, M. A., Çakır, E., & Ulukan, Z. (2021). Spherical fuzzy SWARA-MARCOS approach for green supplier selection. 3C Tecnologia, 115-133.
• Yazdani, M., Wen, Z., Liao, H., Banaitis, A., & Turskis, Z. (2019). A grey combined compromise solution (CoCoSo-G) method for supplier selection in construction management. Journal of Civil Engineering and Management, 25(8), 858-874. https://doi.org/10.3846/jcem.2019.11309