Buradasınız

KURUMSAL FİRMALAR İÇİN BİR FİNANSAL PERFORMANS KARŞILAŞTIRMA MODELİNİN GELİŞTİRİLMESİ

DEVELOPMENT OF A FINANCIAL PERFORMANCE BENCHMARKING MODEL FOR CORPORATE FIRMS

Journal Name:

Publication Year:

Abstract (2. Language): 
In this study, we developed a financial performance evaluation model to rank the corporate firms of 24 sectors in the Turkish economy.The developed model is based on the financial ratiosand Technique for Order Preference by Similiarity to Ideal Solution (TOPSIS)approach. This model of ferscorporate firm’s rating scores with respect to its competitors belonging to the same industry. The developed model is coded in Visual Basic and tested with real case studies. Financial performance evaluation rankings obtained from TOPSIS, Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Grey Relational Grade (GRA), and Multi-Objective Optimization on thebasis of Ratio Analysis (MOORA) methods were compared by using Spearman's rank correlation test. Based on the test results, it was found that the TOPSIS method is the most appropriate method for the evaluation of financial performance. An application is also provided in the paper for illustrative purposes.
Abstract (Original Language): 
Bu çalışmada Türkiye ekonomisindeki 24 sektördeki kurumsal firmaların sıralanmasına yönelik bir finansal performans değerlendirme modeli geliştirilmiştir.Geliştirilen model finansal oranlar ve İdeal Çözümlere Yakınlık Yoluyla Tercihlerin Sıralanması Tekniği (Technique for Order Preference by Similiarity to Ideal Solution- TOPSIS) yöntemi üzerine kurulmuştur.Model, aynı sektöre aitkurumsal firmaların rakiplerine göre derecelendirme puanlarını sunmaktadır. Geliştirilen model Visual Basic programıyla kodlanmış ve gerçek hayat çalışmalarıyla test edilmiştir. TOPSIS, Çok Kriterli Eniyileme ve Uzlaşık Çözüm (Vise Kriterijumska Optimizacija I Kompromisno Resenje-VIKOR), Gri İlişkisel Analiz (Grey Relational Grade-GRA) ve Oran Analizi Temelli Çok Amaçlı Eniyileme (Multi-Objective Optimization on the basis of Ratio Analysis-MOORA) yöntemlerinden elde edilen finansal performans değerlendirme sıralamaları Spearman’ın Sıra İlişkisi Testi kullanılarak karşılaştırılmıştır. Test sonuçlarına göre finansal performans değerlendirme modeli için en uygun sıralama yönteminin TOPSIS yöntemi olduğu bulunmuştur. Makalede modelin çalışmasını gösteren bir uygulamaya da ayrıca yer verilmiştir.
71
85

REFERENCES

References: 

1. Akgüç, Ö., Kredi Taleplerinin
Değerlendirilmesi, Avcıol Basın-Yayın, 5.baskı,
İstanbul, 1991.
2. Altman, E.I., Haldeman, R.G., ve Narayanan, P.,
“Zetaanalysis: A new model toidentifybankruptcy
risk of corporations”, Journal of Bankingand
Finance, Cilt 1, 29–54, 1977.
3. Dagdeviren, M., Eraslan, E.,
“Prioritydetermination in strategicenergypolicies
in Turkeyusinganalytic network process (ANP)
withgroupdecisionmaking”, International
Journal Of Energy Research, Cilt 32, No 11,
1047-1057, 2008.
4. Aksakal, E., Dagdeviren, M., ”An
IntegratedApproachFor Personel Selection With
Demateland ANP Methods”, Journal of The
Faculty of Engineering and Architecture of
Gazi University, Cilt 25, No 4, 905-913, 2010.
5. Yalcin, N., Bayrakdaroglu, A., ve Kahraman, C.,
“Application of Fuzzy Multi-Criteria Decision
Making Methods for Financial Performance
Evaluation of Turkish Manufacturing Industries”,
Expert Systems with Applications, Cilt 39,
350–364, 2012.
6. Dagdeviren, M., Eraslan, E., “SupplierSelection
Using PROMETHEE Sequencing Method”,
Journal of The Faculty of Engineering and
Architecture of Gazi University, Cilt 23, No 1,
69-75, 2008.
7. Yilmaz, B., Dagdeviren, M., “Comparative
Analysis of PROMETHEE andFuzzy
PROMETHEE Methods in EquipmentSelection
Problem”, Journal of The Faculty of
Engineering and Architecture of Gazi
University, Cilt 25, No 4, 811-826, 2010.
8. Mostafa, M., “Benchmarking Top Arab Banks’
Efficiency Through Efficient Frontier Analysis”,
Industrial Management and Data System, Cilt
107, No 6, 802-823, 2007.
9. Voulgaris, F., Doumpos, M., ve Zopounidis, C.,
“On the Evaluation of Greek Industrial SMEs’
Performance via Multicriteria Analysis of
Financial Ratios”, Small Business Economics,
Cilt 15,127–136, 2000.
10. Wang, Y.-J., Combining Grey Relation Analysis
with FMCGDM to Evaluate Financial
Performance of Taiwan Container Lines”,Expert
Systems with Applications, Cilt 36, 2424–2432,
2009.
11. Brauers, W.K.M., “Multi-Objective Seaport
Planning by MOORA decision Making”, Annals
of Operation Research, Cilt 206, 39–58, 2013.
12. İç, Y.T., “A TOPSIS Based Design of
Experiment Approach to Assess Company
Ranking”, Applied Mathematics and
Computation, Cilt 227, 630–647, 2014.
Kurumsal Firmalar İçin Bir Finansal Performans Karşılaştırma … Y. T. İç ve ark.
Gazi Üniv. Müh. Mim. Fak. Der. Cilt 30, No 1, 2015 85
13. İç. Y.T., Yurdakul, M., “Analitik Hiyerarşi Süreci
(AHS) Yöntemini Kullanan Bir Kredi
Değerlendirme Sistemi”, Journal of The Faculty
of Engineering and Architecture of Gazi
University, Cilt 15, No 1, 1-14, 2000.
14. Yurdakul, M., İç, Y.T., “AHP Approach in the
Credit Evaluation of the Manufacturing Firms in
Turkey”, International Journal of Production
Economics, Cilt 88, 269-289, 2004.
15. Yurdakul, M., İç, Y.T., “Türk Otomotiv
Firmalarinin Performans Ölçümü ve Analizine
Yönelik TOPSIS Yöntemini Kullanan Bir Örnek
Çalışma”, Journal of The Faculty of
Engineering and Architecture of Gazi
University, Cilt 18, No 1, 1-18, 2003.
16. Ertugrul, I., Karakasoglu, N., “Performance
Evaluation of Turkish Cement Firms with Fuzzy
Analytic Hierarchy Process and TOPSIS
methods”, Expert Systems with Applications,
Cilt 36, 702–715, 2009.
17. İç. Y.T., Yurdakul, M., “Development of a
QuickCredibilityScoringDecisionSupportSystem
usingFuzzy TOPSIS”, Expert Systems with
Applications, Cilt 37, 567–574, 2010.
18. Secme N.Y., Bayrakdaroglu, A., Kahraman, C.
“Fuzzy Performance Evaluation in Turkish
Banking Sector using Analytic Hierarchy Process
and TOPSIS”, Expert Systems with
Applications, Cilt 36, 11699–11709, 2009.
19. Babic, Z., Plazibat, N., “Ranking of Enterprises
based on Multi Criterial Analysis”,
International Journal of Production
Economics, Cilt 56-57, 29-35, 1998.
20. Deng, H., Yeh, C-H., ve Willis, R.J., “Inter-
Company Comparison using Modified TOPSIS
with Objective Weights”, Computers and
Operation Research, Cilt 27, 963-973, 2000.
21. Moghimi, R., Anvari, A., “An Integrated Fuzzy
MCDM approach and analysis to Evaluate the
Financial Performance of Iranian Cement
Companies”, International Journal of
Advanced Manufacturing Technology, Cilt 71,
685–698, 2014.
22. Bulgurcu, B., K., “Application of TOPSIS
Technique for Financial Performance Evaluation
of Technology Firms in Istanbul Stock Exchange
Market”, Procedia - Social and Behavioral
Sciences, Cilt 62,1033 – 1040, 2012.
23. Feng, C-M., Wang, R-T., “Performance
Evaluation for Airlines Including the
Consideration of Financial Ratios”, Journal of
Air Transport Management, Cilt 6 133-142,
2000.
24. Wang, Y-J., “Applying FMCDM to Evaluate
Financial Performance of Domestic Airlines in
Taiwan”, Expert Systems with Applications,
Cilt 34, 1837–1845, 2008.
25. Tung, C-T., Lee, Y.-J., “The Innovative
Performance Evaluation Model of Grey Factor
Analysis: A Case Study of Listed Biotechnology
Corporations in Taiwan”, Expert Systems with
Applications, Cilt 37, 7844–7851, 2010.
26. Lee, P., T-W., Lin, C-W., Shin, S-H., “A
Comparative Study on Financial Positions of
Shipping Companies in Taiwan and Korea using
Entropy and Grey Relation Analysis”,Expert
Systems with Applications, Cilt 39, 5649–5657,
2012.
27. Kung, C-Y., Wen, K-L., “Applying Grey
Relational Analysis and Grey Decision-Making
to Evaluate the Relationship Between Company
Attributes and its Financial Performance—A
Case Study of Venture Capital Enterprises in
Taiwan”, Decision Support Systems, Cilt
43,842–852, 2007.
28. Huang,C-J., Kuo-Chung, M.A., “Associating
Grey Relation and Cluster Analysis to Perform
Financial Characteristic Study on Enterprises in
China”, Journal of Information &
Optimization Sciences, Cilt 32, No. 4, 945–957,
2011.
29. Brauers W.K.M., Zavadskas, E. K., Turskis, Z.,
Vilutiene, T., “Multi‐Objective Contractor's
Ranking by Applying the MOORA Method”,
Journal of Business Economics and
Management, Cilt 9, No. 4, 245-255, 2008.
30. Chakraborty, S., “Applications of the MOORA
MethodforDecisionMaking in Manufacturing
Environment”, International Journal of
Advanced ManufacturingTechnology, Cilt 54,
1155–1166, 2011.
31. Karande, P., Chakraborty, S., “Application of
Multi-Objective Optimization on the Basis of
Ratio Analysis (MOORA) Method for Materials
Selection”, Materials and Design, Cilt 37, 317–
324, 2012.
32. İç, Y.T., Yıldırım, S., “MOORA-Based Taguchi
Optimisation for Improving Product or Process
Quality”, International Journal of Production
Research, Cilt 51, No. 11, 3321-3341, 2013.
33. İnternet: Kamuyu Aydınlatma Platformu, KAP,
www.kap.gov.tr.
34. Parkan, C., Wu, M-L., “Decision Making and
Performance Measurement Models with
Applications to Robot Selection”, Computers
and Industrial Engineering, Cilt 36, 503-523,
1999.
35. Opricovic, S., Tzeng, G.H., “Compromise
Solution by MCDM Methods: A Comparative
Analysis of VIKOR and TOPSIS”, European
Journal of Operational Research, Cilt 156,
445-455, 2004.
36. Deng, J., “Control problems of grey system”,
Systems & Control Letters, Cilt 1, 288–294,
1982.
37. İç, Y.T., Yıldırım, S., Çok Kriterli Karar Verme
Yöntemleriyle Birlikte Taguchi Yöntemini
Kullanarak Bir Ürünün Tasariminin
Geliştirilmesi”, Journal of The Faculty of
Engineering and Architecture of Gazi
University, Cilt 27, No 2, 447-458, 2012.

Thank you for copying data from http://www.arastirmax.com