Analyzing the Performances of Automotive Companies Using Entropy Based MAUT and SAW Methods

Yıl 2016, Cilt: 31 Sayı: 1, 227 - 255, 13.06.2016

Nuri Ömürbek , Meltem Karaatlı , Halil Furkan Balcı

https://doi.org/10.24988/deuiibf.2016311446

Öz

In this study, performances of automotive companies traded on BİST (Istanbul Stock Exchange) and also operated in our country have been compared with the multi-criteria decision making techniques. Data of the most important automotive companies operating in Turkey have been analyzed based on capital, stock certificate, marketing value, sales revenue, number of employees, net profit margin, current ratio, net profit/capital, net profit/sales and net sales/number of employees. Criteria applied on Performance measurement was gained operating reports of companies in 2014. Entropy method has been used to determine the weights of the criteria. Those weights have been used  MAUT (Multi-Attribute Utility Theory) and SAW (Simple Additive Weighting) methods to rank automative companies’ performances The findings highlight that the same companies were in the first three places in both methods.

Anahtar Kelimeler

Multiple Criteria Decision Making, Entropy, MAUT, SAW, Automotive

Entropi Temelli MAUT ve SAW Yöntemleri İle Otomotiv Firmalarının Performans Değerlemesi

Öz

Bu çalışmada ülkemizde faaliyet gösteren ve aynı zamanda BİST’de (Borsa İstanbul) işlem gören otomotiv sektöründe faaliyette bulunan firmaların performanslarının çok kriterli karar verme yöntemleri ile değerlendirilmesine çalışılmıştır. Türkiye’de faaliyet gösteren en önemli otomotiv şirketlerinin verileri; Sermaye, Hisse Senedi, Piyasa Değeri, Satış Geliri, Personel Sayısı, Net Kar Marjı, Cari Oran, net kar/sermaye, net kar/satışlar ve net satışlar/personel kriterleri çerçevesinde değerlendirilmiştir. Performans ölçümünde kullanılan kriterler ise firmaların 2014 faaliyet raporlarından elde edilmiştir. Öncelikle Entropi yöntemi ile kriterlerin ağırlıkları belirlenmiştir. Elde edilen kriter ağırlıkları önce MAUT (Multi-Attribute Utility Theory) yönteminde daha sonra SAW (Simple Additive Weighting) yönteminde kullanılarak firmaların performansları değerlendirilerek sıralama yapılmıştır. Değerlendirme sonucunda her iki yöntemde de ilk üç sırada aynı firmalar yer
almaktadır.

Anahtar Kelimeler

Çok Kriterli Karar Verme, Entropi, MAUT, SAW, Otomotiv

Kaynakça

• ABDULLAH, L., ADAWIYAH RABIATUL, C.W. (2014), “Simple Additive Weighting Methods of Multi Criteria Decision Making and Applications: A Decade Review”, International Journal of Information Processing and Management(IJIPM), 5(1), 34-49.
• AKTAŞ, R., DOĞANAY, M.M., GÖKMEN, Y., GAZİBEY, Y., TÜREN, U., (2015), Sayısal Karar Verme Yöntemleri, Beta Basım A.Ş., İstanbul.
• ASHOUR, O., OKUDAN KREMER, G.E., (2013), “A Simulation Analysis of The Impact of FAHP–MAUT Triage Algorithm On the Emergency Department Performance Measures”, Expert Systems with Applications, 40, 177–187.
• AFSHARI, A., MOJAHED, M., YUSUFF, R.M., (2010), “Simple Additive Weighting Approach to Personnel Selection Problem”, International Journal of Innovation, Management and Technology, 1(5), 511-511.
• ANANDA, J., HERATH, G., (2005), “Evaluating Public Risk Preferences in Forest Land-Use Choices Using Multi-Attribute Utility Theory”, Ecological Economics, 55, 408-419.
• ANTIL, P., SINGH, M., (2013), “Performance Measurement of An Industry Using Simple Additive Weight”, Internatıonal Journal for Research in Applıed Scıence and Engineering Technology, 1(3), 1-3.
• AYTAÇ, M., GÜRSAKAL, N., (2015), Karar Verme, Dora Basım Yayın Dağıtım A.Ş., Bursa.
• BOSTANCI, S.H., OCAKÇI, M., ŞEKERCİ, S., (2006), “Kentsel Silüetin Çeşitlilik Açısından Değerlendirilmesinde Entropi Yaklaşımı”, Journal of İstanbul Kültür University, 2, 83-95.
• CANBOLAT, Y.B., CHELST, K., GARG, N., (2007), “Combining Decision Tree and MAUT for Selecting A Country for A Global Manufacturing Facility”, Omega, 35, 312-325.
• CHEN, T., JIN, Y., QIU, X., CHEN, X., (2014), “A Hybrid Fuzzy Evaluation Method for Safety Assessment of Food-Waste Feed Based on Entropy and The Analytic Hierarchy Process Methods”, Expert Systems with Applications, 41, 7328–7337.
• CHON-HUAT, G., YUNG-CHIN, A.T., CHUN-HUNG, C., (1995), “A Revised Weighted Sum Decision Model For Robot Selection”, Computers Industry Engineering, 30(2), 193-199.
• ÇAKIR, S., PERÇİN, S., (2013), “Çok Kriterli Karar Verme Teknikleriyle Lojistik Firmalarında Performans Ölçüm”, Ege Akademik Bakış Dergisi, 13(4), 449-459.
• ÇINAR, Y., (2004), Çok Nitelikli Karar Verme ve Bankaların Mali Performanslarının Değerlendirilmesi Örneği, Ankara Üniversitesi Sosyal Bilimler Enstitüsü İşletme Anabilim Dalı Yüksek Lisans Tezi, Ankara.
• GOH, C.H., TUNG, Y.C.A., CHENG, C.H., (1995), “A Revised Weighted Sum Decision Model For Robot Selection”, Computers Industry Engineering, 30(2), 193-199.
• GOMEZ LIMON, J.A., ARRIAZA, M., RIESGO, L., (2003), “An MCDM Analysis of Agricultural Risk Aversion”, European Journal of Operational Research, 151, 569-585.
• GÖRENER, A., GÖRENER, Ö., (2008), “Türk Otomotiv Sektörünün Ülke Ekonomisine Katkıları Ve Geleceğe Yönelik Sektörel Beklentiler”, Journal of Yasar University, 3(10), 1213-1232.
• ISHIZAKA, A., NEMERY, P., (2013), Multi-Criteria Decision Analysis : Methods and Software, John Wiley & Sons Ltd. Published.
• KAILIPONI, P., (2010), “Analyzing Evacuation Decisions Using Multi-Attribute Utility Theory (MAUT)”, 1.International Conference on Evacuation Modeling and Management, Procedia Engineering, 3, 163-174.
• KIM, K.S., SONG, O., (2009), “A MAUT Approach For Selecting a Dismantling Scenario For The Thermal Column ın KRR-1”, Annals of Nuclear Energy, 36, 145–150.
• KIM, S.K., PARK, H.S., LEE, K.W., JUNG, C.H., (2007), “MAUT Approach for Selecting a Proper Decommissioning Scenario” , WM’07 Conference, February 25-March 1, Tucson.
• KONUŞKAN, Ö., UYGUN, Ö., (2014), “Çok Nitelikli Karar Verme (MAUT) Yöntemi ve Bir Uygulaması”, ISITES 2014, Karabük, 1403-1412.
• KÜÇÜKÖNDER, M., KARABULUT, M., (2007), “Çok Kriterli Analiz Yöntemi Kullanılarak Kahramanmaraş’ta Çöp Depolama Alanı Tespiti”, Coğrafi Bilimler Dergisi, 5, 55-76.
• LEE, P.T.W., LIN, C.W., SHIN, S.H., (2012), “A Comparative Study on Financial Positions of Shipping Companies in Taiwan and Korea Using Entropy and Grey Relation Analysis”, Expert Systems with Applications 39, 5649-5657.
• LOETSCHER, T., KELLER, J., (2002), “A Decision Support System for Selecting Sanitation Systems in Developing Countries”, Socio-Economic Planning Sciences, 36, 267-290.
• SHAKOURI, G.H., NABAEE, M., ALIAKBARISANI, S., (2014), “A “Quantitative Discussion On the Assessment of Power Supply Technologies: DEA (Data Envelopment Analysis) and SAW (Simple Additive Weighting) as Complementary Methods for the “Grammar”, Energy, 64, 640-647.
• ÖZKUL, S., (2001), “Su Kalitesi Gözlem Ağlarının Entropi Yöntemi ile Değerlendirilmesi”, Turk Journal Engineering Environment Science, 25, 435-452.
• SAVITHA, K., HANDRASEKAR, C., (2011), “Vertical Handover Decision Schemes Using Saw And Wpm for Network Selection in Heterogeneous Wireless Networks”, Global Journal of Computer Science and Technology, 11(9), 18-24.
• SHEMSHADI, A., SHIRAZI, H., TOREIHI, M., TAROKH M.J., (2011), “A Fuzzy VIKOR Method for Supplier Selection Based on Entropy Measure for Objective Weighting”, Expert Systems with Applications, 38, 12160-12167.
• TÜRKOĞLU, M., UYGUN, Ö., (2014), “VIKOR-MAUT Yöntemleri Kullanılarak Çukurova Bölgesel Havaalanı Yeri Seçimi”, ISITES, 1425-1433.
• WANG, S.O., WEE, Y.P., OFORI, G., (2002), “DSSDSS: A Decision Support System for Dewatering Systems Selection”, Building and Environment, 37, 625-645.
• WANG, T.C., LEE, H.D., (2009), “Developing A Fuzzy TOPSIS Approach Based On Subjective Weights And Objective Weights”, Expert Systems with Applications, 36, 8980–8985.
• WU, H.Yi., TZENG, G.H., CHEN, Y.H., (2009), “A Fuzzy MCDM Approach For Evaluating Banking Performance Based On Balanced Scorecard”, Expert Systems with Applications, 36, 10135-10147.
• YEH, C.H., (2003), “The Selection of Multiattribute Decision Making Methods for Scholarship Student Selection”, Internatıonal Journal of Selection And Assessment, 11(4), 289-296.
• YILDIZ, A., (2006), “Otomotiv Sektörü Performansının Değerlendirmesi”, Muğla Üniversitesi, Sosyal Bilimler Enstitüsü Dergisi, 16, 1-12.
• YOON, K.P., HWANG, C.L. (1995), Multiple Attribute Decision Making An Introuction, Sage University Papers, London.
• YURDAKUL, M., İÇ, Y.T., (2003). “Türk Otomotiv Firmalarının Performans Ölçümü Ve Analizine Yönelik Topsis Yöntemini Kullanan Bir Örnek Çalışma”, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 18(1), 1-18.
• ZIONTS, S., (1979), “MCDM : If not a Roman Numeral then What?”, Interfaces, 9(4), 94-101.