Comparative Network Efficiency Analysis of the Airlines in Turkey After Deregulation

Year 2024, Volume: 9 Issue: 1, 185 - 218, 29.02.2024

Murat Ahmet Doğan Ebül Muhsin Doğan Miraç Eren

https://doi.org/10.25229/beta.1361311

Abstract

Deregulation has significantly developed the civil air transport industry in an ever-globalizing world. Even though deregulation has caused significant structural transformations in airline companies, the effect of deregulation effect on the production, marketing efficiency, and competitiveness of airline carriers worldwide, especially in Turkey, has not been fully revealed yet. Therefore, this study aims to analyze the efficiency of Turkish air carriers after the deregulation process in Turkish civil aviation by dividing the efficiency into production and market efficiency. Production and marketing efficiencies of airlines were estimated using the window network data envelopment analysis methodology. Efficiency analysis results showed production efficiency at 0.887, marketing efficiency at 0.764, and system efficiency at 0.796. Results also indicate that low-cost airlines have a higher production efficiency score (0.918) than full-service airlines (0.825). In comparison, the marketing efficiency of full-service airlines (0.879) is higher than that of low-cost carriers (0.708). The study determined that the system efficiency does not change according to the business model. The system efficiency score of the full-service provider airlines with a larger market share is higher and more balanced. The close and dynamic monitoring of the air transport market and the continuation of operations under a business model incorporating an appropriate marketing mix will increase the marketing efficiency of the airlines.

Keywords

Airline efficiency, Network DEA, Window analysis, Production-marketing efficiencies

Serbestleşme Sonrası Türkiye'deki Havayollarının Karşılaştırmalı Ağ Etkinliği Analizi

Abstract

Serbestleşme/Deregülasyon, giderek küreselleşen dünyada sivil hava taşımacılığı sektörünü önemli ölçüde geliştirmiştir. Her ne kadar serbestleşme havayolu işletmelerinde önemli yapısal dönüşümlere neden olsa da deregülasyonun dünya genelinde ve özellikle Türkiye'de havayolu şirketlerinin üretim, pazarlama verimliliği ve rekabet gücü üzerindeki etkisi henüz tam olarak ortaya konmamıştır. Bu nedenle bu çalışma, Türk sivil havacılığındaki serbestleşme süreci sonrasında Türk havayolu işletmelerinin etkinliğini, üretim ve pazar etkinliği olarak ikiye ayırarak analiz etmeyi amaçlamaktadır. Havayolu şirketlerinin üretim ve pazarlama etkinlikleri pencere ağı veri zarflama analizi metodolojisi kullanılarak tahmin edilmiştir. Etkinlik analizi sonuçları üretim etkinliğinin 0.887, pazarlama etkinliğinin 0.764 ve sistem etkinliğinin 0.796 olduğunu göstermiştir. Sonuçlar ayrıca düşük maliyetli havayolu şirketlerinin tam hizmet veren havayolu şirketlerinden (0.825) daha yüksek bir üretim etkinliği skoruna (0.918) sahip olduğunu göstermektedir. Buna karşılık, tam hizmet sunan havayolu işletmelerinin pazarlama etkinliği (0,879) düşük maliyetli taşıyıcılarınkinden (0,708) daha yüksektir. Çalışmada, sistem etkinliğinin iş modeline göre değişmediği de tespit edilmiştir. Pazar payı yüksek olan tam hizmet sağlayıcı havayollarının sistem etkinliği skoru daha yüksek ve daha dengelidir. Hava taşımacılığı pazarının yakından ve dinamik bir şekilde izlenmesi ve uygun bir pazarlama karması içeren bir iş modeli altında faaliyetlerin sürdürülmesi, havayollarının pazarlama etkinliğini artırmasına imkân sunabilir.

Keywords

Havayolu Etkinliği, Ağ VZA, Üretim-Pazarlama Etkinliği

References

• Acemoglu, D., Laibson, D., & List, J. (2019). Microeconomics (2 ed.). Pearson. Alam, I. M. S., Ross, L. B., & Sickles, R. C. (2001). Time series analysis of strategic pricing behavior in the US airline industry. Journal of Productivity Analysis, 16(1), 49-62.
• Alam, I. M. S., & Sickles, R. C. (1998). The relationship between stock market returns and technical efficiency innovations: evidence from the US airline industry. Journal of Productivity Analysis, 9(1), 35-51.
• Arjomandi, A., & Seufert, J. H. (2014). An evaluation of the world's major airlines' technical and environmental performance. Economic Modelling, 41, 133-144.
• Asker, V. (2021a). Havayolu işletmelerinde iki aşamalı veri zarflama analizi ile etkinlik ölçümü. MANAS Sosyal Araştırmalar Dergisi, 10(4), 2373-2385.
• Asker, V. (2021b). Havayolu Stratejik İşbirliklerinde Veri Zarflama Analizi İle Finansal Performansın İncelenmesi. Journal of Aviation, 5(2), 181-191.
• Asker, V. (2022). DÜŞÜK MALİYETLİ HAVAYOLU İŞLETMELERİNDE BULANIK VERİ ZARFLAMA ANALİZİ İLE FİNANSAL VE OPERASYONEL ETKİNLİK ÖLÇÜMÜ. Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(23), 1-25.
• Asmild, M., Paradi, J. C., Aggarwall, V., & Schaffnit, C. (2004). Combining DEA window analysis with the Malmquist index approach in a study of the Canadian banking industry. Journal of productivity analysis, 21(1), 67-89.
• Assaf, A. (2011). A fresh look at the productivity and efficiency changes of UK airlines. Applied Economics, 43(17), 2165-2175.
• Balliauw, M., Meersman, H., Onghena, E., & Van de Voorde, E. (2018). US all-cargo carriers’ cost structure and efficiency: A stochastic frontier analysis. Transportation Research Part A: Policy and Practice, 112, 29-45.
• Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
• Barbot, C., Costa, Á., & Sochirca, E. (2008). Airlines performance in the new market context: A comparative productivity and efficiency analysis. Journal of Air Transport Management, 14(5), 270-274.
• Barrett, S. D. (1989). Deregulating European aviation—A case study. Transportation, 16(4), 311-327.
• Barros, C. P., & Couto, E. (2013). Productivity analysis of European airlines, 2000–2011. Journal of Air Transport Management, 31, 11-13.
• Barros, C. P., Liang, Q. B., & Peypoch, N. (2013). The technical efficiency of US Airlines. Transportation Research Part A: Policy and Practice, 50, 139-148.
• Barros, C. P., & Peypoch, N. (2009). An evaluation of European airlines’ operational performance. International Journal of Production Economics, 122(2), 525-533.
• Barros, C. P., & Wanke, P. (2015). An analysis of African airlines efficiency with two-stage TOPSIS and neural networks. Journal of Air Transport Management, 44, 90-102.
• Button, K. (2001). Deregulation and liberalization of European air transport markets. Innovation: The European Journal of Social Science Research, 14(3), 255-275.
• Byrnes, P., Färe, R., & Grosskopf, S. (1984). Measuring productive efficiency: an application to Illinois strip mines. Management science, 30(6), 671-681.
• Cao, Q., Lv, J., & Zhang, J. (2015). Productivity efficiency analysis of the airlines in China after deregulation. Journal of Air Transport Management, 42, 135-140.
• Cetin, T., & Eryigit, K. Y. (2018). Estimating the Economic Effects of Airline Deregulation. Journal of Transport Economics and Policy (JTEP), 52(4), 404-426.
• Chang, Y. C., & Yu, M. M. (2014). Measuring production and consumption efficiencies using the slack‐based measure network data envelopment analysis approach: the case of low‐cost carriers. Journal of Advanced Transportation, 48(1), 15-31.
• Charnes, A., Clark, C. T., Cooper, W. W., & Golany, B. (1985). A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the US air forces. Annals of Operations Research, 2, 95-112.
• Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
• Charnes, A., Cooper, W. W., & Rhodes, E. (1979). Measuring the efficiency of decision-making units. European journal of operational research, 3(4), 339-338.
• Chen, Z., Tzeremes, P., & Tzeremes, N. G. (2018). Convergence in the Chinese airline industry: A Malmquist productivity analysis. Journal of Air Transport Management, 73, 77-86.
• Chen, Z., Wanke, P., Antunes, J. J. M., & Zhang, N. (2017). Chinese airline efficiency under CO2 emissions and flight delays: A stochastic network DEA model. Energy Economics, 68, 89-108.
• Chiou, Y.-C., & Chen, Y.-H. (2006). Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis. Transportation Research Part E: Logistics and Transportation Review, 42(2), 116-127.
• Choi, K. (2017). Multi-period efficiency and productivity changes in US domestic airlines. Journal of Air Transport Management, 59, 18-25. Cook, W. D., & Zhu, J. (2014). Data envelopment analysis: A handbook of modeling internal structure and network.
• Cook, W. D., Zhu, J., Bi, G., & Yang, F. (2010). Network DEA: Additive efficiency decomposition. European journal of operational research, 207(2), 1122-1129.
• Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Handbook on data envelopment analysis.
• Cui, Q., & Yu, L.-T. (2021). A Review of Data Envelopment Analysis in Airline Efficiency: State of the Art and Prospects. Journal of Advanced Transportation, 2021.
• Çetin, T., & Benk, S. (2011). Regulation, deregulation, and competition in the Turkish airline industry. In The political economy of regulation in Turkey (pp. 193-214). Springer.
• da Silveira Pereira, D., & de Mello, J. C. C. S. (2021). Efficiency evaluation of Brazilian airlines operations considering the Covid-19 outbreak. Journal of Air Transport Management, 91, 101976.
• DHMİ. https://www.dhmi.gov.tr/Sayfalar/FaaliyetRaporlari.aspx
• Dickinson, J., & Lumsdon, L. (2010). Slow travel and tourism. Routledge.
• Distexhe, V., & Perelman, S. (1994). Technical efficiency and productivity growth in an era of deregulation: the case of airlines. Swiss Journal of Economics and Statistics, 130(4), 669-689.
• Dobson, A. (2007). Globalization and Regional Integration: The origins, development and impact of the single European aviation market. Routledge.
• Dobson, A. (2017). A history of international civil aviation: from its origins through transformative evolution. Routledge. DTÖ. Uluslararası Ticaret Verileri. Retrieved 27.02.2022 from https://stats.wto.org
• Duygun, M., Kutlu, L., & Sickles, R. C. (2016). Measuring productivity and efficiency: a Kalman filter approach. Journal of productivity analysis, 46(2), 155-167.
• Duygun, M., Prior, D., Shaban, M., & Tortosa-Ausina, E. (2016). Disentangling the European airlines efficiency puzzle: A network data envelopment analysis approach. Omega, 60, 2-14.
• Duygun, M., Shaban, M., Sickles, R. C., & Weyman-Jones, T. (2013a). Efficiency and productivity change in the European airlines industry in the post liberalization era. Online: http://rsickles.
• Duygun, M., Shaban, M., Sickles, R. C., & Weyman-Jones, T. (2013b). Efficiency and productivity change in the European airlines industry in the post liberalization era. Online: http://rsickles. .
• Färe, R., & Grosskopf, S. (1996). Productivity and intermediate products: A frontier approach. Economics letters, 50(1), 65-70.
• Färe, R., Grosskopf, S., & Whittaker, G. (2007). Network dea. In Modeling data irregularities and structural complexities in data envelopment analysis (pp. 209-240). Springer.
• Färe, R., Grosskopf, S., & Whittaker, G. (2014). Network Dea II. In Data Envelopment Analysis (pp. 307-327). Springer.
• Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281.
• Fethi, M. D. (2000). Efficiency and productivity growth in the European airlines industry: applications of Data Envelopment Analysis, Malmquist Productivity Index and Tobit Analysis. University of Leicester (United Kingdom).
• Gerede, E. (2010). The Evolution of Turkish Air Transport Industry: Significant Developments and the Impacts of 1983 Liberalization. Journal of Management & Economics, 17(2).
• Goetz, A. R., & Vowles, T. M. (2009). The good, the bad, and the ugly: 30 years of US airline deregulation. Journal of Transport Geography, 17(4), 251-263.
• Good, D. H., Röller, L.-H., & Sickles, R. C. (1995). Airline efficiency differences between Europe and the US: implications for the pace of EC integration and domestic regulation. European journal of operational research, 80(3), 508-518.
• Graham, D. R., Kaplan, D. P., & Sibley, D. S. (1983). Efficiency and competition in the airline industry. The Bell Journal of Economics, 118-138.
• Gramani, M. C. N. (2012). Efficiency decomposition approach: A cross-country airline analysis. Expert Systems with Applications, 39(5), 5815-5819.
• Halkos, G. E., & Tzeremes, N. G. (2009). Exploring the existence of Kuznets curve in countries' environmental efficiency using DEA window analysis. Ecological Economics, 68(7), 2168-2176.
• IATA. (2020). IATA Economics’ Chart of the Week. https://www.iata.org/en/iata-repository/publications/economic-reports/what-can-we-learn-from-past-pandemic-episodes/
• Jain, R. K., & Natarajan, R. (2015). A DEA study of airlines in India. Asia Pacific Management Review, 20(4), 285-292.
• Kao, C. (1995). Some properties of Pareto efficiency under the framework of data envelopment analysis. International journal of systems science, 26(9), 1549-1558.
• Kao, C., & Hwang, S.-N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European journal of operational research, 185(1), 418-429.
• Kao, C., & Hwang, S.-N. (2010). Efficiency measurement for network systems: IT impact on firm performance. Decision Support Systems, 48(3), 437-446.
• Kiracı, K., & Asker, V. (2019). Etkinlik ve etkinliği belirleyen faktörler: havayolu şirketleri üzerine ampirik bir inceleme. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 14(1), 25-50.
• Kottas, A. T., & Madas, M. A. (2018). Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants. Journal of Air Transport Management, 70, 1-17.
• Krugman, P., & Wells, R. (2018). Microeconomics (5 ed.). Worth Publishers. Lee, B. L., & Worthington, A. C. (2014). Technical efficiency of mainstream airlines and low-cost carriers: New evidence using bootstrap data envelopment analysis truncated regression. Journal of Air Transport Management, 38, 15-20.
• Li, Y., Wang, Y.-z., & Cui, Q. (2016). Has airline efficiency affected by the inclusion of aviation into European Union Emission Trading Scheme? Evidences from 22 airlines during 2008–2012. Energy, 96, 8-22.
• Lozano, S., & Gutiérrez, E. (2014). A slacks-based network DEA efficiency analysis of European airlines. Transportation Planning and Technology, 37(7), 623-637.
• Lu, W.-M., Hung, S.-W., Kweh, Q. L., Wang, W.-K., & Lu, E.-T. (2014). Production and marketing efficiencies of the US airline industry: a two-stage network DEA approach. In Data Envelopment Analysis (pp. 537-568). Springer.
• Lu, W.-M., Wang, W.-K., Hung, S.-W., & Lu, E.-T. (2012). The effects of corporate governance on airline performance: Production and marketing efficiency perspectives. Transportation Research Part E: Logistics and Transportation Review, 48(2), 529-544.
• Lufthansa. Annual Reports. Retrieved 01.03.2022 from https://investor-relations.lufthansagroup.com/en/publications.html
• Mallikarjun, S. (2015). Efficiency of US airlines: A strategic operating model. Journal of Air Transport Management, 43, 46-56.
• Martini, G., Scotti, D., & Volta, N. (2019). Global Airline Productivity, 1980– 2013. In Airline Economics in Europe. Emerald Publishing Limited.
• Merkert, R., & Hensher, D. A. (2011). The impact of strategic management and fleet planning on airline efficiency–A random effects Tobit model based on DEA efficiency scores. Transportation Research Part A: Policy and Practice, 45(7), 686-695.
• Mhlanga, O., Steyn, J., & Spencer, J. (2018). The airline industry in South Africa: drivers of operational efficiency and impacts. Tourism Review.
• Min, H., & Joo, S.-J. (2016). A comparative performance analysis of airline strategic alliances using data envelopment analysis. Journal of Air Transport Management, 52, 99-110.
• Pegasus. Annual Reports. Retrieved 01.03.2022 from https://www.pegasusyatirimciiliskileri.com/tr/operasyonel-ve-finansal-veriler/faaliyet-raporlari
• Pryke, R. (1991). American deregulation and European liberalisation. In Transport in a free market economy (pp. 220-241). Springer.
• Radačić, Ž., Tatalović, M., Mišetić, I., & Furlan, I. (2005). Application of Total Productivity Model within Croatia Airlines. Promet-Traffic&Transportation, 17(5), 253-260.
• Ramamurti, R., & Sarathy, R. (1997). Deregulation and globalization of airlines. The International trade journal, 11(3), 389-432.
• Sakthidharan, V., & Sivaraman, S. (2018). Impact of operating cost components on airline efficiency in India: A DEA approach. Asia Pacific Management Review, 23(4), 258-267.
• Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 US commercial banks. Management science, 45(9), 1270-1288.
• Sengupta, J. K. (1999). A dynamic efficiency model using data envelopment analysis. International Journal of Production Economics, 62(3), 209-218.
• Soltanzadeh, E., & Omrani, H. (2018). Dynamic network data envelopment analysis model with fuzzy inputs and outputs: An application for Iranian Airlines. Applied Soft Computing, 63, 268-288.
• Tavassoli, M., Faramarzi, G. R., & Saen, R. F. (2014). Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input. Journal of Air Transport Management, 34, 146-153.
• THY. Annual Reports. https://investor.turkishairlines.com/tr/mali-ve-operasyonel-veriler/faaliyet-raporlari
• Tsoukalas, G. (2007). Convergence in the US airline industry: a unit cost and productivity analysis Massachusetts Institute of Technology].
• Wang, C.-N., Tsai, T.-T., Hsu, H.-P., & Nguyen, L.-H. (2019). Performance evaluation of major Asian airline companies using DEA window model and grey theory. Sustainability, 11(9), 2701.
• Wanke, P., Barros, C. P., & Chen, Z. (2015). An analysis of Asian airlines efficiency with two-stage TOPSIS and MCMC generalized linear mixed models. International Journal of Production Economics, 169, 110-126.
• Williams, G. (2017). The airline industry and the impact of deregulation. Routledge.
• Yalçınkaya, A. (2019). Türk havayolu taşımacılığı sektörünün tarihsel gelişimi ve devlet müdahaleleri (1933-2006).
• Yalçınkaya, A., & Taşcı, D. (2020). Devletin Kurumsal Girişimciliği: Türk Havayolu Taşımacılığı Alanında Slot Tahsisine İlişkin Ardışık ve Çelişik Kurumsal İşler (1992-2010). Anadolu Üniversitesi Sosyal Bilimler Dergisi, 20(2), 173-196.
• Yu, H., Zhang, Y., Zhang, A., Wang, K., & Cui, Q. (2019). A comparative study of airline efficiency in China and India: A dynamic network DEA approach. Research in Transportation Economics, 76, 100746.
• Yu, M.-M., & Chen, L.-H. (2016). Assessment of transportation performance: a network structure. In Data Envelopment Analysis (pp. 17-43). Springer.
• Yu, M.-M., & See, K. F. (2023). Evaluating the efficiency of global airlines: A new weighted SBM-NDEA approach with non-uniform abatement factor. Research in Transportation Business & Management, 46, 100860.