-

Abstract

Nonprofit organizations, such as trade unions and foundations, should employ voluntary workers with high performances in order to fulfill their duties and services successfully. It is true that there are many factors in the assessment of the performance of these workers. Therefore, it seems to be a Multi-Criteria Decision Making (MCDM) problem, which requires taking many factors into consideration

Keywords

• -

GÖNÜLLÜ KURULUŞLARDA ÇALIŞANLARIN AHS VE ELECTRE YÖNTEMLERİNE GÖRE DEĞERLENDİRİLMESİ

Abstract

Sosyal alanda faaliyette bulunan dernek, vakıf, sendika gibi kâr amacı gütmeyen kuruluşların hizmetlerini başarılı bir şekilde yerine getirebilmeleri için gönüllü olarak çalışanlarının performansının yüksek olması gerekmektedir. Çalışanların performansını belirlemede birbirini etkileyen birçok faktörün etkili olduğu bilinmektedir. Bu açıdan diğer alanlarda olduğu gibi sosyal anlarda da hizmet veren gönüllülerin değerlendirilmesi birçok faktörün dikkate alınması gereken çok kriterli karar verme (ÇKKV) problemi olarak görülmektedir.

Bu çalışmanın amacı, sosyal alanda faaliyet gösteren bir derneğin gönüllü olarak çalışanlarının değerlendirilmesine yönelik bir karar verme modeli geliştirmektir. Bu süreçte derneğin yedi gönüllü çalışanı, 41 dernek üyesi tarafından 10 farklı faktöre göre değerlendirilmiştir. Faktör ağırlıkları, yönetim kurulu üyeleri tarafından Analitik Hiyerarşi Süreci (AHS) yöntemi kullanılarak belirlenmiş, gönüllü olarak çalışanların performansları ise Basit Ağırlıklı Toplama (BAT), Ağırlıklı Çarpım Modeli (AÇM) ve ELECTRE yöntemleri ile değerlendirilmiş ve elde edilen sonuçlar karşılaştırılmıştır.

Anahtar Kelimeler: Analitik Hiyerarşi Süreci (AHS), Basit Ağırlıklı Toplama (BAT), Ağırlıklı Çarpım Modeli (AÇM), ELECTRE, Çok Kriterli Karar Verme (ÇKKV)

Keywords

• Analitik Hiyerarşi Süreci (AHS), Basit Ağırlıklı Toplama (BAT), Ağırlıklı Çarpım Modeli

References

1. Afshari, A. R., Mojahed, M., Yusuff, R. M., Hong, T. S., Ismail, M. Y., (2010). “Personnel Selection Using ELECTRE”, Journal of Applied Sciences, Vol.10, 3068-3075.
2. Aksakal, E., Dağdeviren, M., Eraslan, E., Yüksel, İ, (2013). “Personel Selection based on Talent Management”, Procedia-Social and Behavioral Sciences, Vol. 73, 68-72.
3. Baležentis, A., Baležentis, T., Brauers, W. K., (2012). “Personnel Selection Based on Computing with Words and Fuzzy MULTIMOORA”, Expert Systems with Applications, Vol. 39, No. 9, 7961-7967.
4. Chen, C.T., Hwang, Y.C., Hung, W.Z., (2009). “Applying Multiple Linguistic PROMETHEE Method for Personnel Evaluation and Selection”. IEEE International Conference, 1312-1316.
5. Chen, L. S., Cheng, C. H., (2005). “Selecting IS personnel use fuzzy GDSS based on Metric Distance Method”, European Journal of Operational Research, Vol. 160, No. 3, 803–820.
6. Chien, C. F., Chen, L. F., (2008). “Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry”, Expert Systems with Applications, Vol. 34, No. 1, 280–290.
7. Fathi, M. R., Matin, H. Z., Zarchi, M. K., Azizollahi, S., (2011). “The Application of Fuzzy TOPSIS Approach to Personnel Selection for Padir Company Iran”, Journal of Management Research, Vol. 3, No. 2, 1-14.
8. Fengru, X. I., Zhang, L., (2011). “A Personnel Selection Model Based on TOPSIS”, Management Science, Vol. 5, No. 3, 107-110.

9. Gibney, R., Shang, J., (2007). “Decision making in academia: A case of the dean selection process”, Mathematical and Computer Modelling, Vol. 46, No. 7, 1030–1040.
10. Güngör, Z., Serhadlıoğlu, G., Kesen, S. E., (2009). “A fuzzy AHS approach to personnel selection problem”, Applied Soft Computing, Vol. 9, No. 2, 641–646.
11. Hwang, C.L., Yoon, K., (1981). Multiple attribute decision making: a state of the art survey. Springer-Verlag, New York.
12. Kabak, M., Burmaoğlu, S., Kazancoğlu, Y., (2012). “A fuzzy hybrid ÇKKV approach for professional selection”, Expert Systems with Applications, Vol. 39, No. 3 , 3516–3525.
13. Kalugina, E. Shvydun, S., (2014). “An Effective Personnel Selection Model”, Procedia Computer Science, Vol. 31, No. , 1102-1106.
14. Kelemenis, A., Askounis, D., (2010). “A new TOPSIS-based multi-criteria approach to personnel selection”, Expert Systems with Applications, Vol. 37, No. 7, 4999-5008.
15. Keršulienė, V., Turskis, Z. (2014). “An integrated multi-criteria group decision making process: selection of the chief accountant”, Procedia-Social and Behavioral Sciences, No. 110, 897-904.
16. Keršulienė, V., Turskis, Z., (2011). “Integrated Fuzzy Multiple Criteria Decision Making Model for Architect Selection”, Technological and Economic Development of Economy, Vol. 17, No. 4, 645-666.
17. Korkmaz, İ., Gökçen, H., Çetinyokuş, T. (2008). “An analytic hierarchy process and two-sided matching based decision support system for military personnel assignment”, Information Sciences, Vol. 178, No. 14, 2915-2927.
18. Lazarevic-Petrovic, S., (2001). “Personnel Selection Fuzzy Model”, International Transactions in Operational Research, Vol. 8, No. 1 , 89-105.
19. Lin, H. T., (2010). “Personnel selection using analytic network process and fuzzy data envelopment analysis approaches”, Computers & Industrial Engineering, Vol. 59, No. 4, 937-944.
20. McIntyre, C., Kirschenman, M., Seltveit, S., (1999). “Applying Decision Support Software in Selection of Division Director”, Journal of Management in Engineering, Vol. 15, No. 2, 86- 92.
21. Pang, J., Zhang, G., Chen, G., (2011). “ELECTRE I decision model of reliability design scheme for computer numerical control machine”, Journal of Software, Vol. 6, No. 5, 894-900.
22. Pimerol, J.C., Romero, S.B., (2000). Multi criteria decision in management: principles and practic, Kluwer Academic Publishers.
23. Polychroniou, P.V., Giannikos, I., (2009). ‘‘A fuzzy multicriteria decision-making methodology for selection of human resources in a Greek private bank’’, Career Development International, Vol. 14, No. 4, 372–387.
24. Rao R. V., (2008). “Evaluation of environmentally conscious manufacturing programs using multiple attribute decision-making methods”, Proceedings of the Institution of Mechanical Engineers - Part B - Engineering Manufacture, Vol. 222, No. 3, 441-451.
25. 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, Vol. 23, No. 2, 107–115.
26. Saaty, T. L., 1980. The Analytic Hierarchy Process, New York: McGraw-Hill.
27. Saaty, T.L., 1994. Fundamentals of Decision Making and Priority Theory With The Analytical Hierarchy Proces, Pittsburg, RWS Publ.
28. Saaty, T. L., 1999. The Analytic Hierarchy Process for Decision Making, Kobe, Japan.
29. Savitha, K., Chandrasekar, C., (2011). “Vertical Handover decision schemes using BAT and AÇM for Network selection in Heterogeneous Wireless Networks”, Global Journal of Computer Science and Technology, Vol. 11, No. 9, 21-22.
30. Wan, S. P., Wang, Q. Y., Dong, J. Y., (2013). “The extended VIKOR method for multi-attribute group decision making with triangular intuitionist fuzzy numbers”, Knowledge-Based Systems, No. 52, 65-77.
31. Wang, D., (2009). “Extension of TOPSIS Methodfor R& D Personnel Selection Problem with Interval Grey Number”, International conference on IEEE IEEM, 1-4.
32. Yoon, K. P., Hwang, C.-L., (1995). “Multiple Attribute Decision Making: An Introduction”, Sage University Paper Series on Quantitative Applications in the Social Sciences, 07-104, Thousand Oaks, California, USA.
33. Zhang, S-F., Liu, S-Y., (2011), “A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection”, Expert Systems with Applications, Vo. 38, No. 9, 11401–11405.