FINANCIAL PERFORMANCE EVALUATION OF TURKISH AIRLINE COMPANIES USING INTEGRATED FUZZY AHP FUZZY TOPSIS MODEL*

Year 2018, 18. EYI Special Issue, 583 - 598, 20.01.2018

Selçuk Perçin , Eyad Aldalou

https://doi.org/10.18092/ulikidince.347925

Cited By: 20

Abstract

Emerging changes in global markets and
financial crisis led to increase in uncertainty and instability of the
financial and business environments, which lead to increase in the importance
of making efficient financial decisions, along with the complexity of the
financial decision making process. The aim of this
study is to propose a financial performance evaluation model, based on ratio
analysis of solvency, efficiency, and profitability, utilizing the integrated
Fuzzy AHP Fuzzy TOPSIS. Fuzzy AHP method is used to assign weights for the
evaluation criteria, and Fuzzy TOPSIS method is used to rank alternatives.
Profitability and Solvency are the most important criteria, the Return On
Assets and Return On Sales a company can achieve are the most important norms
to reflect how well a company financially operates. The application of this
model on airline companies listed in Istanbul Stock Exchange showed that
Pegasus has a better financial performance than Turkish Airlines.  

Keywords

Financial Performance Evaluation, Fuzzy AHP, Fuzzy TOPSIS, Aviation

FINANCIAL PERFORMANCE EVALUATION OF TURKISH AIRLINE COMPANIES USING INTEGRATED FUZZY AHP FUZZY TOPSIS MODEL*

Abstract

Finansal ve ticari çevrelerde belirsizliğe ve
istikrarsızlığa, küresel piyasalarda ortaya çıkan değişiklikler ve finansal
krizler neden olmuştur. Bu değişiklikler finansal karar verme sürecinin
karmaşıklığı ile birlikte, etkin finansal karar verme sürecinin önemini
artırmıştır. Bu çalışmanın amacı bütünleşik Bulanık AHP, Bulanık TOPSIS
yöntemleriyle bir finansal analiz modeli oluşturmaktır. Ödeme gücü, faaliyet ve
karlılık oran analizi, kriterlerin ve alt-kriterlerin ağırlıklarını saptamak
için Bulanık AHP, alternatifleri sıralamak için Bulanık TOPSIS yöntemleri
kullanılmıştır. Kârlılık ve Borç Ödeme Gücü en önemli kriterler ve bir şirketin
elde edebileceği Varlık Getirisi ve Satış Getirisi, bu şirketin mali açıdan ne
kadar iyi çalıştığını gösteren en önemli normlardır.  Bu modelin Borsa İstanbul’da işlem gören
havacılık sektöründe çalışan şirketlere uygulanması, Pegasus’un Türk
Havayolları'na göre daha iyi bir finansal performansa sahip olduğunu
göstermiştir.

Keywords

finansal performans değerlendirilmesi, Bulanık AHP, Bulanık TOPSİS, havacılık

References

• Abdul Hamid, M. & Azmi, S. M. (2011). The Performance of Banking during 2000-2009: Bank Islam Malaysia Berhad and Conventional Banking in Malaysia. International Journal of Economics and Management Sciences, 1:1, 09-19.
• Aliakbari Nouri, F., Khalili Esbouei, S. & Antucheviciene, J. (2015). A Hybrid MCDM Approach Based on Fuzzy ANP and Fuzzy TOPSIS for Technology Selection. INFORMATICA, 26:3, 369–388.
• Aydogan, E. K., Demirtas, O. & Dagdeviren, M. (2015). A New Integrated Fuzzy Multi-Criteria Decision Model for Performance Evaluation. Business and Management Studies, 1: 1.
• Bellman, R.E. & Zadeh, L. A. (1970). Decision making in a fuzzy environment, 17:4.
• Calomiris, C. W. & Mason, J. R. (1994). Contagion and Bank Failures During the Great Depression: The June 1932 Chicago Banking Panic. NBER Working Paper #4934.
• Chabotar, K. J. (1989). Financial Ratio Analysis Comes to Nonprofits. The Journal of Higher Education; 60:2, 188.
• Chang, D-Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95, 649-655.
• Chang, T-H. & Wang, T-C. (2009). Using the fuzzy multi-criteria decision making approach for measuring the possibility of successful knowledge management. Information Sciences, 179, 355–370.
• Çakır, S. & Perçin, S. (2013). R&D Performance Measurement in EU Countries Using Combined Entropy Weight-TOPSIS Method. Uludağ Journal of Economy and Society: 1, 77- 95
• DHMI Official site (2017): http://www.dhmi.gov.tr/
• Eyüboğlu, K. & Çelik, P. (2016). Financial Performance Evaluation of Turkish Energy Companies with Fuzzy AHP and Fuzzy TOPSIS Methods. Business and Economics Research Journal, 7, 21-37.
• Feng, C. M. & Wang, R. T. (2000). Performance evaluation for airlines including the consideration of financial ratios. Journal of Air Transport Management, 6, 133-142.
• Gibson, C. H. (2011). Financial reporting and analysis using financial accounting information, (12th ed.). South-western.
• International Air Transport Association (IATA), IATA annual review 2017. http://www.iata.org/publications/
• Jahanshahloo, G.R., Hosseinzadeh Lotfi, F. & Izadikhah, M. (2006). Extension of the TOPSIS method for decision-making. Applied Mathematics and Computation, 181:2, 1544-1551.
• Kahraman, C., Cebeci, U. & Ruan, D. (2004). Multi-attribute comparison of catering service companies using fuzzy AHP: The case of Turkey. Int. J. Production Economics, 87, 171–184. Kaya, T. (2010). Multi-attribute Evaluation of Website Quality in E-business Using an Integrated Fuzzy AHP TOPSIS Methodology, International Journal of Computational Intelligence Systems, 3:3, 301-314.
• Kaya, T. & Kahraman, C. (2010). Multicriteria decision making in energy planning using a modified fuzzy TOPSIS methodology. Expert Systems with Applications, 38, 6577–6585.
• Kumar, P. & Kumar Singh, R. (2016). Solving the vendor selection problem using fuzzy TOPSIS. International Conference in Recent Advances in Mechanical Engineering (RAME-2016).
• Kumbirai, M. & Webb, R. (2010). A financial Ratio Analysis of Commercial Bank Performance in South Africa. African Review of Economics and Finance, 2:1.
• Kuo, M-S., Tzeng, G-H. & Huang, W-C. (2007). Group decision-making based on concepts of ideal and anti-ideal points in a fuzzy environment. Mathematical and Computer Modelling, 45, 324–339.
• Mahendran, P. (2014). A Fuzzy AHP Approach for Selection of Measuring. Instrument for Engineering College Selection. Applied Mathematical Sciences, 8:44, 2149 – 2161.
• Mavi, R. K. (2014). Indicators of Entrepreneurial University: Fuzzy AHP and Fuzzy TOPSIS Approach. J Knowl Econ, 5, 370–387.
• Mohaghar, A., Fathi, M. R., Faghih, A. & Turkayesh, M. M. (2012). An Integrated Approach of Fuzzy ANP and Fuzzy TOPSIS for R&D Project Selection: A Case Study. Australian Journal of Basic and Applied Sciences, 6:2, 66-75.
• Nissim, D. & Penman, S. (2001). Ratio Analysis and Equity Valuation: From Research to Practice. Review of Accounting Studies, 6, 109–154.
• Onut, S., Efendigil, T. & Kara, S. S. (2010). A combined fuzzy MCDM approach for selecting shopping center site: An example from Istanbul, Turkey. Expert Systems with Applications, 37, 1973–1980.
• Ömurbek, V. & Kinay, B. (2013). A TOPSIS-Based Financial Performance Assessment Study on Airline Industry. The Journal of Faculty of Economics and Administrative Sciences, 18, 343-363.
• Özdağoğlu, A. & Güler, M. E. (2016). E-service quality of internet based banking using combined fuzzy AHP and fuzzy TOPSIS. Tehnički vjesnik, 23:4, 1109-1116.
• Pegasus airlines annual reports, 2012-16. http://www.pegasusinvestorrelations.com/
• Poplawska, J. (2014). Decision support framework for resources allocation to corporate social responsibility (CSR) programmes (not published PDH thesis). University of Portsmouth, England.
• Reilly, F.K. & Brown, K.C. (2003). Investment analysis and portfolio management (7th ed.). South-Western, MOc.
• Shukla, R. K., Garg, D. & Agarwal, A. (2014). An integrated approach of Fuzzy AHP and Fuzzy TOPSIS in modeling supply chain coordination. Production & Manufacturing Research: An Open Access Journal, 2:1, 415-437.
• Sun, C-C. (2010). A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert Systems with Applications, 37, 7745–7754.
• Teker, S., Teker, D. & Guner, G. (2016). Financial Performance of Top 20 Airlines. Procedia - Social and Behavioral Sciences, 235, 603-610.
• Turkish airlines annual reports, 2012-16. http://investor.turkishairlines.com/en
• Wood, D. A. (2016). Supplier Selection for Development of Petroleum Industry Facilities, Applying Multi-criteria Decision Making.... Journal of Natural Gas Science and Engineering, 28, 1-19.
• Yalcin, N., Bayrakdaroglu, A. & Kahraman, C. (2012). Application of fuzzy multi-criteria decision making methods for financial performance evaluation of Turkish manufacturing industries. Expert Systems with Applications, 39, 350–364.
• Yavuz, M. (2016). Equipment Selection by using Fuzzy TOPSIS Method. IOP Conf. Series: Earth and Environmental Science 44, 042040.
• Zietlow, J. (2010). Nonprofit financial objectives and financial responses to a tough economy. Journal of Corporate Treasury Management, 3:3, 238–248
• Zopounidis, C. & Doumpos, M. (2002). Multi-criteria Decision Aid in Financial Decision Making: Methodologies and Literature Review. J. Multi-Crit. Decis. Anal. 11, 167–186.
• Zyoud, S. H., Kaufmann, L. G., Shaheen, H., Samhan, S. & Fuchs-Hanusch, D. (2016). A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS. Expert Systems with Applications, 61, 86–105.