Dergiler / TOJSAT / 2016 / Cilt: 6 Sayı: 1

ANALYZING EFFICIENCIES AND TOTAL FACTOR PRODUCTIVITIES OF STAR ALLIANCE MEMBER AIRLINES

Dergi
TOJSAT
Sayfa
5–12
Yayın Tarihi
2016-07-23
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Results show that there are differences in efficiencies and productivities of airline companies by the means of using their inputs to produce outputs while some of them are wasting their resource and some others are not

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Comparing the efficiency levels and productivities of domestic and international airline companies is an active research area in services sector and has lots of interests in business administration field.
📊
Temel Bulgular & Veri:Eight variables, including both inputs and outputs named as Number of Annual Passengers, Daily Departures, Number of Countries Served, Number of Airports Served, Revenue Passenger (Km), Sales Revenue ($), Number of Employees and Fleet of 26 airline companies are taken place in analysis for the years 2013 and 2014.
💡
Sonuç & Katkı:Results show that there are differences in efficiencies and productivities of airline companies by the means of using their inputs to produce outputs while some of them are wasting their resource and some others are not
🔬Tür:Araştırma Makalesi
📍Kapsam:2013 Verileri
⚙️Değişkenler:Airlines · Total Factor

Abstract

Comparing the efficiency levels and productivities of domestic and international airline companies is an active research area in services sector and has lots of interests in business administration field. In this study, Data Envelopment Analysis and Total Factor Productivity Analysis are used to compare the efficiencies and productivities of Star Alliance member international airline companies. Eight variables, including both inputs and outputs named as Number of Annual Passengers, Daily Departures, Number of Countries Served, Number of Airports Served, Revenue Passenger (Km), Sales Revenue ($), Number of Employees and Fleet of 26 airline companies are taken place in analysis for the years 2013 and 2014. Because of price differences in access the resources of services and goods that the companies used, the Variable Returns to Scale Method of Data Envelopment Analysis is used instead of Constant Returns to Scale Method to figure out efficiencies in years. Results show that there are differences in efficiencies and productivities of airline companies by the means of using their inputs to produce outputs while some of them are wasting their resource and some others are not

Anahtar kelimeler
🔖

Bu Makaleye Atıf Yap

ÖZ, Y., KÖKSAL, C. D. (2016). ANALYZING EFFICIENCIES AND TOTAL FACTOR PRODUCTIVITIES OF STAR ALLIANCE MEMBER AIRLINES. TOJSAT, Cilt: 6 Sayı: 1, 5–12. https://ajindex.com/articles/1008386

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (3)

  1. Arjomandi, A. & Seufert, J.H. (2014). An evaluation of the world's major airlines' technical and environmental performance (pp. 133-144). Econ. Model 41. Assaf, A.G. & Josiassen, A. (2012). European vs. US airlines: performance comparison in a dynamic market (pp. 317-326). Tourism Management 33. Barros, C.P. & Peypoch, N. (2009). An evaluation of European airlines’ operational performance (pp.525-533). International Journal of Production Economics 122. Barros, C.P. & Couto, E. (2013). Productivity analysis of European airlines, 2000-2011 (pp.11-13). Journal of Air Transport Management 31. Barros, C.P., Liang, Q.B. & Peypoch, N. (2013). The technical efficiency of US airlines (pp.139-148). Transportation Research Part A: Policy and Practice 50. Bosetti, V., Cassinelli, M. & Lanza, A. (2003). Using Data Envelopment Analysis to Evaluate Environmentally Conscious Tourism Management, Conference for Tourism and Sustainable Development. 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 (pp.46-50). Transportation Research Part D: Transport and Environment 27. Charnes, A., Cooper, W.W. & Rhodes, E. (1978). Measuring the efficiency of decision making units (pp.429- 444). European Journal of Operational Research 2. Charnes, F., Cooper, W.W., Lewin, A.Y. & Seiford, L.M. (1994). Data Envelopment Analysis: Theory, Methodology, and Application. Kluwer Academic. Chiou, Y.-C. & Chen, Y.-H. (2006). Route-Based Performance Evaluation of Taiwanese Domestic Airlines Using Data Envelopment Analysis (pp.116-127). Transportation Research Part E: Logistics and Transportation Review 42(2). Choi, K., Lee, D. & Olson, D.L. (2013). Service quality and productivity in the US airline industry: a service quality-adjusted DEA model (pp.1-24).
  2. Service Business. Cook, W.D., Tone, K. & Zhu, J. (2014). Data envelopment analysis: prior to choosing a model (pp.1-4). Omega 44. Fitzsimons, J. A. & Fitzsimmons, M. J. (1998).
  3. Service Management Operations, Strategy and Information Technology, New York, Irwin McGraw-Hill. Forsyth, P.J., Hill, R. & Trengove, C. (1986). Measuring airline efficiency (pp.61-81). Fiscal Studies 7. Gelles, Gregory M. & Mitchell, Douglas W. (1996). Returns to scale and economies of scale: Further observations (pp. 259–261). Journal of Economic Education 27 (3). Hirst, M. (2008). The Air Transport System. Library of Flight, Virginia. Hong, S. & Zhang, A. (2010). An efficiency