BULANIK ANALİTİK HİYERARŞİ PROSESİ İLE PERSONEL SEÇİMİ VE BİR UYGULAMA

Personel seçimi organizasyonlar için önemli bir konu olup, karar verme sürecinde kesin olmayan ve belirsizverilerin kullanılmasını gerektirir. Bu çalışmada Bulanık Analitik Hiyerarşi Prosesi (BAHP) yöntemi ile personelseçimi probleminin çözümüne yönelik bir algoritma önerilmiştir. Önerilen algoritma bir işletmede terfi edecekpersonelin belirlenmesi amacıyla kullanılmış ve aday personeller için öncelik değerleri belirlenmiştir. Adaypersonellerin faktörler temelinde değerlendirilmesinde dilsel değişkenler kullanılmış ve bulanık ağırlıklarındurulaştırılması α-kesme ve iyimserlik indeksi temelinde geliştirilen bir durulaştırma işlemi ile yapılmıştır.

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  • Kaynak, T., İnsan Kaynakları Yönetimi,
  • İ.Ü.İşletme Fakültesi Yayınları, İstanbul, 1998.
  • Sabuncuoğlu, Z., İnsan Kaynakları Yönetimi,
  • Ezgi Yayınevi, Bursa, 2000.
  • Erdoğan, İ., İşletmelerde Personel Seçimi ve
  • Başarı Değerleme Teknikleri, İşletme İktisadı
  • Enstitüsü Yayınları, İstanbul, 1991.
  • Özgen, H., Öztürk, A., Yalçın, A., İnsan
  • Kaynakları Yönetimi, Nobel Kitabevi, Adana,
  • -
  • Bingöl, D., İnsan Kaynakları Yönetimi, Beta
  • Yayınları, İstanbul, 1998.
  • Arvey, R.D., Campion, J.E., “The employment
  • interview: A summary and review of recent
  • research”, Personel Psychology, 35(1), 281-322,
  • -
  • Gargano, M.L., Marose, R.A., Kleeck, L., “An
  • application of artificial neural Networks and
  • genetic algorithms to personnel selection in the
  • financial industry”, Proceedings of the First
  • International Conference on Artificial
  • Intelligence Applications, 257-262, 1991.
  • Miller, G.M., Feinzig, S.L., “Fuzzy sets and
  • personnel selection: Discussion and an
  • application”, Journal of Occupational and
  • Organizational Psychology, 66(1), 163-169,
  • -
  • Liang, S.L., Wang M.J., “Personnel selection
  • using fuzzy MCDM algorithm”, European
  • Journal of Operational Research, 78(2), 22-33,
  • -
  • Karsak, E.E, “Personnel selection using a fuzzy
  • MCDM approach based on ideal and anti-ideal
  • solutions”, Multiple Criteria Decision Making
  • in the New Millenium, Berlin, 425-432, 2001.
  • Hooper, R.S., Galvin, T.P., Kimler, R.A.,
  • Liebowitz, J., “Use of an expert system in a
  • personnel selection process”, Expert Systems
  • with Applications, 14(1), 425-432, 1998.
  • Bohanec, M., Urh, B., Rajkovic, V., “Evaluating
  • options by combined qualitative and quantitative
  • methods”, Acta Psychologica, 80(2), 67-89,
  • -
  • Timmermans, D., Vlek, C., “Multi-attribute
  • decision support and copmlexity: An evaluation
  • and process analysis of aided versus unaided
  • decision making”, Acta Psychologica, 80(1), 49-
  • , 1992.
  • Timmermans, D., Vlek, C., “Effects on decision
  • quality of supporting multi-attribute evaluation in groups”, Organizational Behavior and Human
  • Decision Processes, 68(2), 158-170, 1996.
  • Gardiner, A.R., Armstrong-Wright, D.,
  • “Employee selection and anti-discrimination law:
  • Implications for multi-criteria group decision
  • support”, Journal of Multi-Criteria Decision
  • Analysis, 9(1), 99-109, 2000.
  • Spyridakos, A., Siskos, Y., Yannacopoulos, D.,
  • Skouris, A., “Multicriteria job evaluation for
  • large organisations”, European Journal of
  • Operational Research, 130(2), 375-387, 2001.
  • Jessop, A., “Minimally biased weight
  • determination in personnel selection”, European
  • Journal of Operational Research, 153(2), 433-
  • , 2004.
  • Saaty, T.L., The Analytic Hierarchy Process,
  • McGraw-Hill, New York, 37-85, 1980.
  • Dağdeviren, M., “Analitik hiyerarşi prosesi ile
  • yeni bir analitik iş değerlendirme tekniğinin
  • geliştirilmesi”, Yüksek Lisans Tezi, Gazi
  • Üniversitesi Fen Bilimleri Enstitüsü, Ankara,
  • -63, 2002.
  • Zadeh, L.A., “Fuzzy sets”, Information and
  • Control, 8, 338-353, 1965.
  • Zimmermann, H.J., “Fuzzy Set Theory and its
  • Application”, Kluwer Academic Publishers,
  • Boston, 35-85, 1990.
  • Karsak, E.E., Tolga, E., “Fuzzy multi-criteria
  • decision-making procedure for evaluating
  • advanced manufacturing system investments”,
  • International Journal of Production
  • Economics, 69,49-64,2001.
  • Kahraman, C., Beşkese, A., Ruan, D.,
  • “Measuring flexibility of computer integrated
  • manufacturing systems using fuzzy cash flow
  • analysis”, Information Sciences, 168,77-
  • ,2004.
  • Ding, J.F., Liang, G.S., “Using fuzzy MCDM to
  • select partners of strategic alliances for liner
  • shipping”, Information Sciences, 173,197-
  • ,2005.
  • Van Laarhoven, P.J.M., Pedrycz, W., “A fuzzy
  • extension of Saaty’s priority theory”, Fuzzy Sets
  • and Systems, 11,229-241,1983.
  • Buckley, J.J., “Fuzzy hierarchical analysis”,
  • Fuzzy Sets and Systems,17,233-247,1985.
  • Chang, D.Y., “Applications of te extent analysis
  • method on fuzzy AHP”, European Journal of
  • Operational Research, 95(2), 649-655, 1996.
  • Cheng, C.H., “Evaluating naval tactical misilse
  • systems by fuzzy AHP based on the grade value
  • of membership function”, European Journal of
  • Operational Research, 96(2), 343-350, 1997.
  • Weck, M., Klocke, F., Schell, H., Rüenauver, E.,
  • “Evaluating alternative production cycles using
  • the extended fuzzy AHP method”, European
  • Journal of Operational Research, 100(2), 351-
  • , 1997.
  • Kahraman, C., Ulukan, Z., Tolga, E., “A fuzzy
  • weighted evaluation method using objective and
  • subjective measures”, Proceedings of the
  • International ICSC Symposium on
  • Engineering of Intelligent Systems, 1, 57-63,
  • -
  • Deng, H., “Multicriteria analysis with fuzzy
  • pairwise comparison”, International Journal of
  • Approximate Reasoning, 21(3), 215-231, 1999.
  • Lee, M., Pham, H., Zhang, X., “A methodology
  • for priority setting with application to software
  • development process”, European Journal of
  • Operational Research, 118(2), 375-389, 1999.
  • Chan, F.T.S., Chan, M.H., Tang, N.K.H.,
  • “Evaluation methodologies for technology
  • selection”, Journal of Materials Processing
  • Technology, 107(1-3), 330-337, 2000a.
  • Chan, F.T.S., Jiang, B., Tang, N.K.H., “The
  • development of intelligent decision support tools
  • to aid the design of flexible manufacturing
  • systems”, International Journal of Production
  • Economics, 65(1), 73-84, 2000b.
  • Kuo, R.J., Chi, S.C., Kao, S.S., “A decision
  • support system for selecting convenience store
  • location through integration of fuzzy AHP and
  • artificial neural network”, Computers in
  • Industry, 47(2), 199-214, 2002.
  • Mikhailov, L., Singh, M.G., “Fuzzy analytic
  • network process and its application to the
  • development of decision support systems”, IEEE
  • Transactions on Systems, Man and
  • Cybernetics-Part C: Applications and
  • Revıews, 33(1), 33-41, 2003.
  • Mikhailov, L., “A fuzzy approach to deriving
  • priorities from interval pairwise comparison
  • judgement”, European Journal of Operational
  • Research, 159(3), 687-704, 2004.
  • Mikhailov, L., Tsvetinov, P., “Evaluation of
  • services using a fuzzy analytic hierarchy
  • process”, Applied Soft Computing, Article in
  • pres, 2004.
  • Prakash, T.N., “Land Suitability Analysis for
  • Agricultural Crops: A Fuzzy Multicriteria
  • Decision Making Approach”, MSc Thesis, ITC
  • Institue, 2003.
  • Dağdeviren, M., “Performans Değerlendirme
  • Sürecinin Çok Ölçütlü Karar Verme Yöntemleri
  • İle Bütünleşik Modellenmesi”, Doktora Tezi,
  • Gazi Üniversitesi Fen Bilimleri Enstitüsü,
  • Ankara, 2005.