Research Article
Year 2022,
Volume: 33 Issue: 3, 484 - 499, 31.12.2022
Abstract
Rekabetçi bir piyasada faaliyet göstermeye devam eden şirketler, rekabetçi kalabilmek için kaynaklarını en verimli şekilde kullanmaya çalışırlar. Artan müşteri geri bildirimleri ile birlikte, aynı pazarda rekabet eden çok sayıda firma nedeniyle, müşteri ihtiyaç ve isteklerini doğru analiz etmek ve beklentilere uygun hizmet üretmek giderek daha önemli hale geldi ve bu durum özellikle gıda hizmetleri endüstrisinde rekabette ön planda olmak için önemlidir. Yiyecek hizmeti işletmelerine yönelik sürekli değişen talep, faiz ve karşılaştırılabilir ücretlerin düzenlenmesindeki zorluk, rekabet ortamı ve kur artışları nedeniyle bu sektörde riskler ve belirsizlikler bulunmaktadır. Tüm bu koşullar ışığında restoranlar, performanslarını etkin bir şekilde ölçmek ve analiz etmek için çok yönlü bir araca ihtiyaç duyarlar. Bu nedenle, bu çalışma, İstanbul'da et lokantası, kebap ve köfte-döner olmak üzere üç kategoriye ayrılmış 15 bayinin performansını analiz etmek için Temel Bileşen Analizi (PCA) ve Kategorik Veri Zarflama Analizini (CAT-DEA) birleştirmektedir. Sonuçlar, her bir kategorinin yalnızca bir verimli restorana sahip olduğunu ve on beş bayiden toplamda üç bayinin verimli olduğunu göstermektedir. Önerilen CAT-DEA tabanlı yaklaşıma ek olarak, yemek hizmeti endüstrisinde restoran performansı ile çeşitli çevresel faktörler (veya ilgili göstergeler) arasındaki bağlantıyı araştırmak için üç araştırma hipotezi oluşturulmuş ve analiz edilmiştir.
Keywords
Kategorik VZA Boyut İndirgeme Temel Bileşenler Analizi Performans Ölçme Restaurantlar Categorical DEA Dimension Reduction Principal Component Analysis (PCA) Performance Measurement Restaurants.
References
- Adler, N., & Golany, B. (2001). Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe. European Journal of Operational Research, 132(2), 260-273.
- Adler, N., & Yazhemsky, E. (2010). Improving discrimination in data envelopment analysis: PCA–DEA or variable reduction. European Journal of Operational Research, 202(1), 273- 284.
- Albayrak, A. (2015). Müşterilerin restoran seçimlerini etkileyen faktörler: İstanbul Örneği. Anatolia: Turizm Araştırmaları Dergisi, 25(2), 190-201.
- Andrejić, M., Bojović, N., & Kilibarda, M. (2013). Benchmarking distribution centres using Principal Component Analysis and Data Envelopment Analysis: A case study of Serbia. Expert Systems with Applications, 40(10), 3926–3933.
- Andrejić, M., Bojović, N., & Kilibarda, M. (2016). A framework for measuring transport efficiency in distribution centers. Transport Policy, 45, 99–106.
- Aydın U., Karadayı M.A., Ülengin F., Ülengin K.B. (2021). Enhanced Performance Assessment of Airlines with Integrated Balanced Scorecard, Network-Based Superefficiency DEA and PCA Methods. In: Topcu Y.I., Özaydın Ö., Kabak Ö., Önsel Ekici Ş. (eds) Multiple Criteria Decision Making. MCDM 2019. Contributions to Management Science. Springer, Cham.
- Bal, H., & Özsoy, V. S. (2016). Temel Bileşenler Analizi ile Vza Modellerinin Seçilmesi ve Birimlerin Sıralanması: Şehirlerin Ekonomik Performansı Üzerine Bir Uygulama. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, ICEBSS Special Issue, 125-135.
- 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.
- Banker, R. D., & Morey, R. C. (1986a). Efficiency analysis for exogenously fixed inputs and outputs. Operations Research, 34(4), 513-521.
- Banker, R. D., & Morey, R. C. (1986b). The use of categorical variables in data envelopment analysis. Management Science, 32(12), 1613-1627.
- Barros, C.P., & Wanke, P. (2015). An analysis of african airlines efficiency with two-stage TOPSIS and neural networtks. Journal of Air Transport Management. 44–45, 90–102.
- Botti, L., Briec, W., & Cliquet, G. (2009). Plural forms versus franchise and company-owned systems: A DEA approach of hotel chain performance. Omega, 37(3), 566–578.
- Bravo-Ureta, B. E., Solís, D., López, V. H. M., Maripani, J. F., Thiam, A., & Rivas, T. (2007). Technical efficiency in farming: a meta-regression analysis. Journal of Productivity Analysis, 27(1), 57-72.
- Chang, Y.T., Park, H.S., Jeong, J.B., & Lee, J.W. (2014). Evaluating economic and environmental efficiency of global airlines: A SBM-DEA approach. Transportation Research Part D: Transport and Environment, 27, 46-50.
- Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
- 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.
- Chiang, C. I., & Sheu, R. S. (2020). How the sustainability of your recipes? International Journal of Gastronomy and Food Science, 22(48), 100244.
- Dinçer, H., Hacıoğlu, Ü., & Yüksel, S. (2017) Balanced scorecard based performance measurement of European airlines using a hybrid multicriteria decision making approach under the fuzzy environment. Journal of Air Transport Management, 63, 17-33.
- Duman, G. M., Tozanli, O., Kongar, E., & Gupta, S. M. (2017). A holistic approach for performance evaluation using quantitative and qualitative data: A food industry case study. Expert Systems with Applications, 81, 410–422.
- Gharakhani, D., Maghferati, A. P., & Jalalifar, S. (2012). Evaluation of the efficiency of restaurants using DEA method (The case of Iran). Life Science Journal, 9(4), 530-534.
- Giménez-García, V. M., Martínez-Parra, J. L., & Buffa, F. P. (2007). Improving resource utilization in multi-unit networked organizations: The case of a Spanish restaurant chain. Tourism Management, 28(1), 262–270.
- Gnewuch M., & Wohlrabe K. (2018). Super-efficiency of education institutions: an application to economics departments. Education Economics, 26(6), 610-623.
- Grmanová, E., & Strunz, H. (2017). Efficiency of insurance companies: Application of DEA and Tobit analyses. Journal of International Studies, 10(3), 250- 263.
- He, P., Sun, Y., Shen, H., Jian, J., & Yu, Z. (2019). Does environmental tax affect energy efficiency? An empirical study of energy efficiency in OECD countries based on DEA and Logit model. Sustainability, 11(14), 3792.
- Jothimani D., Shankar R., & Yadav, S.S. (2017). A PCA-DEA framework for stock selection in Indian stock market. Journal of Modelling in Management, 12(3), 386-403.
- Karsak, E. E., & Karadayi. (2017). Imprecise DEA framework for evaluating health-care performance of districts. Kybernetes, 46(4), 706–727.
- Koşan, L., & Karadeniz, E. (2014). Konaklama ve yiyecek hizmetleri alt sektörünün finansal performansının Dupont finansal analiz sistemi kullanılarak incelenmesi. Seyahat ve Otel İşletmeciliği Dergisi, 11(2), 75–89.
- Liu, W., Xia, Y. & Hou, J. (2019). Health expenditure efficiency in rural China using the super-SBM model and the Malmquist productivity index. International Journal for Equity in Health, 18(1):111.
- Liu, J.S., Yang, C., Lu, W.M. & Chuang, M.A. (2009). A Network-based approach for increasing discrimination in data envelopment analysis. Journal of the Operational Research Society, 60 (11), 1502-1510.
- 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.
- Brown, D.M., & Hoover, L.W. (1990). Productivity measurement in foodservice: Past accomplishments—a future alternative. Journal of the American Dietetic Association, 90(7), 973-978.
- Mallikarjun, S. (2015). Efficiency of US airlines: a strategic operating model. Journal of Air Transport Management, 43:46-56 McDonald, J. (2009). Using least squares and tobit in second stage DEA efficiency analyses. European Journal of Operational Research, 197(2), 792-798.
- Nasser, A. (2019). Measuring the performance of hospitals in Lebanese qadas Using PCA- DEA model. Computer and Information Science,12(1), 23-32.
- Özden, Ü. H. (2008). Veri zarflama analizi (VZA) ile Türkiye’ deki vakıf üniversitelerinin etkinliğinin ölçülmesi. Istanbul University Journal of the School of Business Administration, 2, 167–185.
- Parte, L., & Alberca, P. (2019). A multistage model to evaluate the efficiency the bar industry. International Journal of Hospitality Management, 77, 512–522.
- Peixoto, M. G. M., Musetti, M. A., & de Mendonça, M. C. A. (2020). Performance management in hospital organizations from the perspective of Principal Component Analysis and Data Envelopment Analysis: The case of Federal University Hospitals in Brazil. Computers & Industrial Engineering, 150, 106873.
- Pineda, P.J.G., Liou, J.J.H., Hsu, C., & Chuang, Y. (2018). An Integrated MCDM Model for improving airline operational and financial performance. Journal of Air Transport Management, 68, 103–117.
- Põldaru, R., & Roots, J. (2014). A PCA-DEA approach to measure the quality of life in estonian counties. Socio-Economic Planning Sciences, 48(1), 65–73.
- Reynolds, D., & Biel, D. (2007). Incorporating satisfaction measures into a restaurant productivity index. International Journal of Hospitality Management, 26(2), 352–361.
- Reynolds, D., & Thompson, G. M. (2007). Multiunit restaurant productivity assessment using three-phase data envelopment analysis. International Journal of Hospitality Management, 26(1), 20–32.
- Reynolds, D., & Taylor, J. (2011). Validating a DEA-based menu analysis model using structural equation modeling. International Journal of Hospitality Management, 30(3), 584–587.
- Roh, E. Y., & Choi, K. (2010). Efficiency comparison of multiple brands within the same franchise: Data envelopment analysis approach. International Journal of Hospitality Management, 29(1), 92–98.
- Rouse, P., Putterill, M., & Ryan, D. (2002). Integrated performance measurement design: insights from an application in aircraft maintenance. Management Accounting Research, 13 (2), 229–248.
- 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.
- Saranga H, & Nagpal, R. (2016). Drivers of operational efficiency and its impact on market performance in the Indian Airline industry. Journal of Air Transport Management, 53, 165-176.
- Sıngh, D., Torres, E. N., & Robertson-Ring, A. (2016). Playing for first place: An analysis of online reviews and their impact on local market rankings. Advances in Hospitality and Tourism Research, 4(1), 32-51.
- Stoica, O., Mehdian, S., & Sargu, A. (2015). The Impact of Internet Banking on the Performance of Romanian Banks: DEA and PCA Approach. Procedia Economics and Finance, 20(15), 610–622.
- Tepe, M. (2006). Kıyaslama çalışmasında veri zarflama analizi kullanımı. Doctoral dissertation, Istanbul Technical University, Istanbul.
- Tsionas, M.G., Chen, Z., & Wanke, P. (2017). A structural vector autoregressive model of technical efficiency and delays with an application to Chinese airlines. Transportation Research Part A: Policy and Practice, 101, 1-10.
- Uslu Cibere, G., Başaran, M. A., & Kantarcı, K. (2020). Evaluation of Hotel Performance Attributes Through Consumer Generated Reviews: The Case of Bratislava. Advances in Hospitality and Tourism Research, 8(1), 48-75.
- Wanke, P., Azad, M. A. K., Barros, C. P., & Hassan, M. K. (2016). Predicting efficiency in Islamic banks: An integrated multicriteria decision making (MCDM) approach. Journal of International Financial Markets, Institutions and Money, 45, 126-141.
- Wu, H., Li, Y. (2017). The Impacts of Female Executives on Firm Performances: Based on Principle Component Analysis (PCA) and Data Envelopment Analysis (DEA). In Proceedings of the Tenth International Conference on Management Science and Engineering Management, 223-235. Springer, Singapore.
- Yap, G. L. C., Ismail, W. R., & Isa, Z. (2013). An alternative approach to reduce dimensionality in data envelopment analysis. Journal of Modern Applied Statistical Methods, 12(1), 17.
- Yıldırım, E. (2010). Veri zarflama analizinde girdi ve çıktıların belirlenmesindeki kararsızlık problemi için temel bileşenler analizine dayalı bir çözüm önerisi. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 39(1), 141-153.
- Yürüşen, S. (2011). Veri zarflama analizi ile bayi performansının hesaplanması: Otomotiv sektöründe bir uygulama. Master Dissertation, Istanbul Technical University, Istanbul.
- Zou, B., Kwan, I., Hansen, M., Rutherford, D., & Kafle, N. (2016). Airline fuel efficiency: assessment methodologies and applications in the US domestic airline industry. Airline Efficiency, 5, 317-353.
Year 2022,
Volume: 33 Issue: 3, 484 - 499, 31.12.2022
Abstract
Companies that continue to operate in a competitive market strive the most efficient use of their resources in order to remain competitive. Nowadays, with increasing customer feedback, properly analyzing customer needs and requests and producing services in accordance with expectations have become increasingly important due to the large number of companies competing in the same market, and this is especially important to be at the forefront of competitors in the food services industry. There are risks and uncertainties owing to the continuously changing demand for food service enterprises, the difficulty to regulate interest and comparable charges, the competitive environment, and currency rate hikes. In light of all of these circumstances, restaurants require a versatile tool to effectively measure and analyze their performance. Therefore, this study combines Principal Component Analysis (PCA) and Categorical Data Envelopment Analysis (CAT-DEA) to analyze the performance of 15 dealers in Istanbul, divided into three categories: steakhouse, kebab, and meatball-doner. The results demonstrate that each category has just one efficient restaurant, for a total of three efficient restaurants out of fifteen. In addition to the suggested CAT-DEA-based framework, three research hypotheses are constructed and analyzed to investigate the link between restaurant performance and various environmental factors (or relevant indicators) in the food service industry.
Keywords
Categorical DEA Dimension Reduction Principal Component Analysis (PCA) Performance Measurement Restaurants.
References
- Adler, N., & Golany, B. (2001). Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe. European Journal of Operational Research, 132(2), 260-273.
- Adler, N., & Yazhemsky, E. (2010). Improving discrimination in data envelopment analysis: PCA–DEA or variable reduction. European Journal of Operational Research, 202(1), 273- 284.
- Albayrak, A. (2015). Müşterilerin restoran seçimlerini etkileyen faktörler: İstanbul Örneği. Anatolia: Turizm Araştırmaları Dergisi, 25(2), 190-201.
- Andrejić, M., Bojović, N., & Kilibarda, M. (2013). Benchmarking distribution centres using Principal Component Analysis and Data Envelopment Analysis: A case study of Serbia. Expert Systems with Applications, 40(10), 3926–3933.
- Andrejić, M., Bojović, N., & Kilibarda, M. (2016). A framework for measuring transport efficiency in distribution centers. Transport Policy, 45, 99–106.
- Aydın U., Karadayı M.A., Ülengin F., Ülengin K.B. (2021). Enhanced Performance Assessment of Airlines with Integrated Balanced Scorecard, Network-Based Superefficiency DEA and PCA Methods. In: Topcu Y.I., Özaydın Ö., Kabak Ö., Önsel Ekici Ş. (eds) Multiple Criteria Decision Making. MCDM 2019. Contributions to Management Science. Springer, Cham.
- Bal, H., & Özsoy, V. S. (2016). Temel Bileşenler Analizi ile Vza Modellerinin Seçilmesi ve Birimlerin Sıralanması: Şehirlerin Ekonomik Performansı Üzerine Bir Uygulama. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, ICEBSS Special Issue, 125-135.
- 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.
- Banker, R. D., & Morey, R. C. (1986a). Efficiency analysis for exogenously fixed inputs and outputs. Operations Research, 34(4), 513-521.
- Banker, R. D., & Morey, R. C. (1986b). The use of categorical variables in data envelopment analysis. Management Science, 32(12), 1613-1627.
- Barros, C.P., & Wanke, P. (2015). An analysis of african airlines efficiency with two-stage TOPSIS and neural networtks. Journal of Air Transport Management. 44–45, 90–102.
- Botti, L., Briec, W., & Cliquet, G. (2009). Plural forms versus franchise and company-owned systems: A DEA approach of hotel chain performance. Omega, 37(3), 566–578.
- Bravo-Ureta, B. E., Solís, D., López, V. H. M., Maripani, J. F., Thiam, A., & Rivas, T. (2007). Technical efficiency in farming: a meta-regression analysis. Journal of Productivity Analysis, 27(1), 57-72.
- Chang, Y.T., Park, H.S., Jeong, J.B., & Lee, J.W. (2014). Evaluating economic and environmental efficiency of global airlines: A SBM-DEA approach. Transportation Research Part D: Transport and Environment, 27, 46-50.
- Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
- 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.
- Chiang, C. I., & Sheu, R. S. (2020). How the sustainability of your recipes? International Journal of Gastronomy and Food Science, 22(48), 100244.
- Dinçer, H., Hacıoğlu, Ü., & Yüksel, S. (2017) Balanced scorecard based performance measurement of European airlines using a hybrid multicriteria decision making approach under the fuzzy environment. Journal of Air Transport Management, 63, 17-33.
- Duman, G. M., Tozanli, O., Kongar, E., & Gupta, S. M. (2017). A holistic approach for performance evaluation using quantitative and qualitative data: A food industry case study. Expert Systems with Applications, 81, 410–422.
- Gharakhani, D., Maghferati, A. P., & Jalalifar, S. (2012). Evaluation of the efficiency of restaurants using DEA method (The case of Iran). Life Science Journal, 9(4), 530-534.
- Giménez-García, V. M., Martínez-Parra, J. L., & Buffa, F. P. (2007). Improving resource utilization in multi-unit networked organizations: The case of a Spanish restaurant chain. Tourism Management, 28(1), 262–270.
- Gnewuch M., & Wohlrabe K. (2018). Super-efficiency of education institutions: an application to economics departments. Education Economics, 26(6), 610-623.
- Grmanová, E., & Strunz, H. (2017). Efficiency of insurance companies: Application of DEA and Tobit analyses. Journal of International Studies, 10(3), 250- 263.
- He, P., Sun, Y., Shen, H., Jian, J., & Yu, Z. (2019). Does environmental tax affect energy efficiency? An empirical study of energy efficiency in OECD countries based on DEA and Logit model. Sustainability, 11(14), 3792.
- Jothimani D., Shankar R., & Yadav, S.S. (2017). A PCA-DEA framework for stock selection in Indian stock market. Journal of Modelling in Management, 12(3), 386-403.
- Karsak, E. E., & Karadayi. (2017). Imprecise DEA framework for evaluating health-care performance of districts. Kybernetes, 46(4), 706–727.
- Koşan, L., & Karadeniz, E. (2014). Konaklama ve yiyecek hizmetleri alt sektörünün finansal performansının Dupont finansal analiz sistemi kullanılarak incelenmesi. Seyahat ve Otel İşletmeciliği Dergisi, 11(2), 75–89.
- Liu, W., Xia, Y. & Hou, J. (2019). Health expenditure efficiency in rural China using the super-SBM model and the Malmquist productivity index. International Journal for Equity in Health, 18(1):111.
- Liu, J.S., Yang, C., Lu, W.M. & Chuang, M.A. (2009). A Network-based approach for increasing discrimination in data envelopment analysis. Journal of the Operational Research Society, 60 (11), 1502-1510.
- 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.
- Brown, D.M., & Hoover, L.W. (1990). Productivity measurement in foodservice: Past accomplishments—a future alternative. Journal of the American Dietetic Association, 90(7), 973-978.
- Mallikarjun, S. (2015). Efficiency of US airlines: a strategic operating model. Journal of Air Transport Management, 43:46-56 McDonald, J. (2009). Using least squares and tobit in second stage DEA efficiency analyses. European Journal of Operational Research, 197(2), 792-798.
- Nasser, A. (2019). Measuring the performance of hospitals in Lebanese qadas Using PCA- DEA model. Computer and Information Science,12(1), 23-32.
- Özden, Ü. H. (2008). Veri zarflama analizi (VZA) ile Türkiye’ deki vakıf üniversitelerinin etkinliğinin ölçülmesi. Istanbul University Journal of the School of Business Administration, 2, 167–185.
- Parte, L., & Alberca, P. (2019). A multistage model to evaluate the efficiency the bar industry. International Journal of Hospitality Management, 77, 512–522.
- Peixoto, M. G. M., Musetti, M. A., & de Mendonça, M. C. A. (2020). Performance management in hospital organizations from the perspective of Principal Component Analysis and Data Envelopment Analysis: The case of Federal University Hospitals in Brazil. Computers & Industrial Engineering, 150, 106873.
- Pineda, P.J.G., Liou, J.J.H., Hsu, C., & Chuang, Y. (2018). An Integrated MCDM Model for improving airline operational and financial performance. Journal of Air Transport Management, 68, 103–117.
- Põldaru, R., & Roots, J. (2014). A PCA-DEA approach to measure the quality of life in estonian counties. Socio-Economic Planning Sciences, 48(1), 65–73.
- Reynolds, D., & Biel, D. (2007). Incorporating satisfaction measures into a restaurant productivity index. International Journal of Hospitality Management, 26(2), 352–361.
- Reynolds, D., & Thompson, G. M. (2007). Multiunit restaurant productivity assessment using three-phase data envelopment analysis. International Journal of Hospitality Management, 26(1), 20–32.
- Reynolds, D., & Taylor, J. (2011). Validating a DEA-based menu analysis model using structural equation modeling. International Journal of Hospitality Management, 30(3), 584–587.
- Roh, E. Y., & Choi, K. (2010). Efficiency comparison of multiple brands within the same franchise: Data envelopment analysis approach. International Journal of Hospitality Management, 29(1), 92–98.
- Rouse, P., Putterill, M., & Ryan, D. (2002). Integrated performance measurement design: insights from an application in aircraft maintenance. Management Accounting Research, 13 (2), 229–248.
- 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.
- Saranga H, & Nagpal, R. (2016). Drivers of operational efficiency and its impact on market performance in the Indian Airline industry. Journal of Air Transport Management, 53, 165-176.
- Sıngh, D., Torres, E. N., & Robertson-Ring, A. (2016). Playing for first place: An analysis of online reviews and their impact on local market rankings. Advances in Hospitality and Tourism Research, 4(1), 32-51.
- Stoica, O., Mehdian, S., & Sargu, A. (2015). The Impact of Internet Banking on the Performance of Romanian Banks: DEA and PCA Approach. Procedia Economics and Finance, 20(15), 610–622.
- Tepe, M. (2006). Kıyaslama çalışmasında veri zarflama analizi kullanımı. Doctoral dissertation, Istanbul Technical University, Istanbul.
- Tsionas, M.G., Chen, Z., & Wanke, P. (2017). A structural vector autoregressive model of technical efficiency and delays with an application to Chinese airlines. Transportation Research Part A: Policy and Practice, 101, 1-10.
- Uslu Cibere, G., Başaran, M. A., & Kantarcı, K. (2020). Evaluation of Hotel Performance Attributes Through Consumer Generated Reviews: The Case of Bratislava. Advances in Hospitality and Tourism Research, 8(1), 48-75.
- Wanke, P., Azad, M. A. K., Barros, C. P., & Hassan, M. K. (2016). Predicting efficiency in Islamic banks: An integrated multicriteria decision making (MCDM) approach. Journal of International Financial Markets, Institutions and Money, 45, 126-141.
- Wu, H., Li, Y. (2017). The Impacts of Female Executives on Firm Performances: Based on Principle Component Analysis (PCA) and Data Envelopment Analysis (DEA). In Proceedings of the Tenth International Conference on Management Science and Engineering Management, 223-235. Springer, Singapore.
- Yap, G. L. C., Ismail, W. R., & Isa, Z. (2013). An alternative approach to reduce dimensionality in data envelopment analysis. Journal of Modern Applied Statistical Methods, 12(1), 17.
- Yıldırım, E. (2010). Veri zarflama analizinde girdi ve çıktıların belirlenmesindeki kararsızlık problemi için temel bileşenler analizine dayalı bir çözüm önerisi. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 39(1), 141-153.
- Yürüşen, S. (2011). Veri zarflama analizi ile bayi performansının hesaplanması: Otomotiv sektöründe bir uygulama. Master Dissertation, Istanbul Technical University, Istanbul.
- Zou, B., Kwan, I., Hansen, M., Rutherford, D., & Kafle, N. (2016). Airline fuel efficiency: assessment methodologies and applications in the US domestic airline industry. Airline Efficiency, 5, 317-353.
There are 56 citations in total.
Details
| Primary Language | English |
|---|---|
| Subjects | Industrial Engineering |
| Journal Section | Research Articles |
| Authors | |
| Early Pub Date | December 18, 2022 |
| Publication Date | December 31, 2022 |
| Acceptance Date | November 21, 2022 |
| Published in Issue | Year 2022 Volume: 33 Issue: 3 |
