Пассажирские авиаперевозчики: влияние бизнес-модели на операционную эффективность
Цель данного исследования – оценка влияния бизнес-модели авиакомпании на ее операционную эффективность. Последняя понимается как техническая эффективность авиаперевозчика, определяемая в системе переменных «входа» и «выхода». Роль первых играют ресурсы авиакомпании по перевозке пассажиров и предоставляемые им сервисы (сервисные факторы). Вторые представлены множеством показателей, характеризующих результат деятельности авиакомпании. Как показал обзор литературы и баз данных, ключевые различия в бизнес-моделях авиаперевозчиков состоят в предоставляемых пассажирам услугах. Анализ публикаций по сервисам авиаперевозчиков выявил отсутствие исследований, посвященных изучению влияния спектра предоставляемых услуг и их качества на операционную эффективность авиакомпаний.
В ВКР влияние типа бизнес-модели на операционную эффективность авиаперевозчиков анализируется через сервисные факторы. Его количественная оценка производится с помощью метода DEA на основе отчетных данных 10 американских авиакомпаний за период с 2005 по 2018 год.
Полученные оценки указывают на то, что наибольшее влияние сервисные факторы оказывают на операционную эффективность компаний с гибридной бизнес-моделью. В компаниях с классической и бюджетной бизнес-моделями влияние сервисных факторов проявляется в значительно меньшей степени. На основании полученных результатов предложены методики определения относительной эффективности авиаперевозчиков на их конкурентных рынках, представлен инструмент, который может быть использован менеджерами авиакомпаний для оценки предлагаемых услуг, а также сформулированы дальнейшие возможности для исследования.
INTRODUCTION ………………………………………………………………………………………………………….. 6
Chapter 1. BUSINESS-MODELS AND SERVICE FACTORS IN
PASSENGERS AIR CONVEYANCE…………………………………………………………………………….. 10
1.1 The literature review on business-model concept for airline industry ……………………. 10
1.1.1 Full-service Carriers ……………………………………………………………………………………. 11
1.1.2 Low-cost Carriers ……………………………………………………………………………………….. 13
1.1.3 Hybrid Carriers …………………………………………………………………………………………… 18
1.2 Service factors ……………………………………………………………………………………………….. 20
1.3 Conclusion …………………………………………………………………………………………………….. 23
Chapter 2. STUDY OF AIR CARRIERS OPERATIONAL PERFORMANCE: METHODOLOGY AND DESIGN…………………………………………………………………………………. 24
2.1 Service Quality Measurement ………………………………………………………………………….. 24
2.2 Operational performance and Data Envelopment Analysis ………………………………….. 27
2.3 Research design ……………………………………………………………………………………………… 32
2.3.1 Stage 1. Assessment of operational performance…………………………………………….. 33
2.3.2 Stage 2. Assessment of service performance…………………………………………………… 35
2.4 Conclusion …………………………………………………………………………………………………….. 38 Chapter 3. EMPIRICAL STUDY OF US AIR CARRIERS IN 2005-2018 …………………….. 39 3.1 The object of the study and empirical data………………………………………………………………. 39 3.2 Results of the operational performance analysis ………………………………………………………. 43 3.3 Results of the operational performance analysis with service factors included …………….. 47 CONCLUSION ……………………………………………………………………………………………………………. 51 List of References…………………………………………………………………………………………………………. 55 Appendices ……………………………………………………………………………………………………………… 66 Appendix 1. Abbreviations used in the text and Appendix 1…………………………………………… 66
Appendix 2. The initial data set…………………………………………………………………………………… 69
Having started only a little over 100 years ago, air transportation has become a part of everyday life of the mankind, and nowadays it is impossible to imagine human life without air travelling. It is amazing that the distance between almost any two different points on the Globe can be covered within 24 hours. The flourishing of air transportation fell for the period after World War II, when engineering solutions, developed for the needs of military aviation, were successfully transferred to civil aircrafts manufacturing.
Prior to 1970s flights were perceived as an attribute of luxury. For an individual each flight was an exceptional event, and only very wealthy people could afford to fly. The flight as a commercial product contained a lot of services on board as well as on the ground both before the take off and after the landing. Passengers could relax in the comfortable halls of the airports. Thus, appeared the classic business-model or full-service business-model (FSC) of air carriers with its intrinsic attribute – a large number of additional services besides the flight.
In 1973, after the Yom Kippur War and the oil embargo, it became apparent that it would be extremely difficult for airlines to survive in the environment with high and unstable price for oil, as the aviation fuel is a major component of the airline’s costs. This drastic change in the environment gave impetus for developing of the budget business-model or low-cost business- model (LCC). Southwest Airlines became a pioneer LCC – it had begun the service just 2 years prior to the oil embargo, and the airline business-model, by sudden, became successful.
The emergence of new types of aircraft, which were more efficient in fuel consumption, able to fly longer distances and more comfortable for passengers, made air travelling more common in 1980s. Many new low-cost carriers appeared in the market, thus, increasing the rate of competition with existing full-service air carriers. The industry entered the mature stage in the late 1990s – early 2000s. This was manifested by a large number of mergers and acquisitions, growing promotion costs and increased attention to the scope of services and their quality and, most importantly, operational costs.
High attention to operational costs and bundle of services provided to the passengers were the main sources to generate a new business-model – hybrid business-model. Although there are still disputes over the existence of hybrid air carriers, in this work we will highlight special features discriminating such type of airlines, at least, on operational level.
6
Increased competition rate has forced the airlines to search for the new competitive advantages. Operational efficiency became one of the main advantages in the beginning of XXI century for airlines. From its inception, the air transport industry is capital-intensive, and at the same time the carriers must keep ticket prices at the level needed to maintain and increase consumer demand.
Modern world is highly dynamic. The airlines are now in the situation of creative saturation, when they have already run out of ideas on new sources to obtain the competitive advantages what makes carriers quite similar to each other. Low-cost business-model and full-service business-model are both shifting towards each other, inosculating with the hybrid business-model (Urban et al., 2018).
Research relevance of the study is determined by airlines management need in:
1. tracking the quality of the service the airline provides and comparing it with that of competitors;
2. evaluating the influence of newly introduced services on the market position of an airline;
3. identification of the way service factors affects operational performance of the company.
The following examples confirm relevance of the study. In 2017 International Airlines Group established an airline called LEVEL. It offers low-cost transatlantic flights from Western Europe, being the unique type of airline. Hybrid airline Scoot (previously named Tigerair) introduced long- haul flights with economy and business classes onboard, and the business class is quite special: it has the amenities that are common for economy class of a full-service airline with more spacious seats and wi-fi included in the price of the ticket. On the other side, full-service carriers have started to introduce economy classes with low-cost like service – for example, Finnair offers no- frill services on its North European flights. To compete, non-typical airlines started to emerge – for example, in 2015 a boutique airline called La Compagnie was established in France. It operates a fully business-class Airbus A321neo cabin on transatlantic flights from Paris and London to New York with Michelin two-course meals, 15.7-inch touchscreens and free in-flight Wi-Fi. The airline also offers some unique services like all-you-can-fly for $40 000 per year.
Combination of service factors and changes in airline business-models gives food for thought and raises a question: “How service factors influence the airline efficiency for different business- models?”. Under the term of “efficiency” the technical efficiency score, estimated by Data Envelopment Analysis, is considered. The research gap of the study is formed after the thorough
7
literature analysis, which shown that there is a significant amount of studies on the topics of “airline operational performance”, “airline business-models” and “airline scope of services and service quality”, however, there exist no works on the intersection of these topics. This study is pioneer in this field.
The aim of the research is to evaluate the influence of different business-models through service factors on airline efficiency.
The following research questions are going to be answered:
• How an airline can account and measure the effects of service factors?
• Is an influence of service factors on airline operational performance dependent on
business-model of the airline?
• What is the performance improvement potential?
The research objectives of this thesis are the following:
1. To analyze the historical perspective that has formed the current aviation market.
2. To conduct the literature review in order to analyze the historical development of airline
business-models.
3. To examine the existing airline business-models and highlight their main features
through the real business examples.
4. To understand what the operational performance of an airline is.
5. To analyze what are the service factors for an airline and what is underneath the term
“service quality” for an airline?
6. To understand how the service quality is identified and measured.
7. To examine the models that are used to evaluate the service quality and performance
and select the most suitable one.
8. To conduct an empirical research in order to understand the influence of service factors
on operational performance of an airline in different airline business-models with the
use of Data Envelopment Analysis methodology.
9. To analyze the results and provide managerial implication and further research areas
based on the results.
The structure of the work corresponds to the logic of the research objectives mentioned above and consists of Introduction, three main Chapters, Conclusion, List of References and Appendices.
8
The first chapter considers the historical development of air carriers, key events that have shaped the activities of an airline and business-models of air carriers in general. Then the existing airline business-models and their key features are described, and the features of airline business-models are compared between each other. After that, the service factors of air carriers are described.
The second chapter begins with the service quality measurement topic and the models that are used to measure service quality at whole and in airlines in particular. Then the most suitable methodology for this research is selected – it is Data Envelopment Analysis. It is described and the examples of the methodology usage are presented. The process of selection of the dataset and the dataset itself are described. In the end of the chapter the research design and the stages of the analysis all inputs in outputs for the methodology used are described.
In the third chapter the results of the analysis are revealed and the conclusions about the impact of scope of services on operational performance of an airline for different airline business-models are drawn with further recommendations provided.
The object of the study is 10 largest US-based airlines, that represent different business-models. US airlines are selected because the national market in the United States is fully deregulated and highly competitive. There are several major carriers representing each business-model, so the comparison of different models is possible. Also, the routes within the United States are of different distance, so there is a variety of aircrafts used, what affects the operational efficiency and the services.
The subject of the research is airline’s business-model influence on its operational performance. The difference between airline business-models can be easily observed by the scope of service provided and their quality, so these become the main interest of the research.
The theoretical basis of the study is classical foreign articles and monographs on the business activities of air carriers, as well as research papers on the efficiency of air carriers and their service factors.
In order to collect data for the empirical part, the official website of Bureau of Transportation Statistics of the United States, the official websites of airlines and the official IATA website.
The research consists of two models – operational and service. The first one gives an understanding of pure operational performance of an airline and consists of operational performance indicators only.
The aggregated result of this model has been estimated from monthly data on air passengers’ conveyance and produced monthly performance score for each company. An average performance of airline for 168 months was then calculated. It gives a broad understanding of relative positioning of each airline to its competitors. The best performance is shown by Hawaiian Airlines with 0.975 and the worst one is from Southwest Airlines of 0.848. Comparing business-models, it is worth mentioning that highest average scores are present by hybrid airlines as they are keeping their fragile balance. Following hybrid airlines, there are full-service airlines which surprisingly have higher operational performance score than low-cost airlines. This happens on the US market due to network structure of low-cost airlines and country specificity.
Yearly data gives us the understanding about the changes of operational performance of airlines from year to year and it reflects how airlines have sustained the crisis, bankruptcies or mergers. That is very easy to follow through the crisis of 2009, the recovery from it and then the new years of intensive rivalry in mid 2010-s. Tis opportunity to track the changes gives a room of thoughts to be taken into account as the airline is the one which knows what were the changes and how they changed the positioning to other airlines.
Based on the results of operational model, the data point for the service model were selected with score higher than 0.93. This selection is done in order to select the airlines and the periods, in which service factors are not affected by the low operational performance of an airline.
The results of the service model give an understanding of influence of service factors on operational performance and it varies for different business-models. For hybrid airlines the influence is the highest as they are the one which provide some extras, but still widely used ones. These extras give a significant boost, especially if we compare to other business-models, but there might be another side as if something goes wrong, a hybrid airline will have big problems like Air Berlin had. The company started to shift to full-service model on its long-haul services, and it
51
made the airline go bankrupt. Experts’ opinion on the airline business-models convergence is confirmed by the results of operational efficiency estimations for each airline business-model.
For full-service and low-cost airlines, the influence is lower, and, there are some examples of negative influence among these types of airlines. The thing is that for these business-models level of expectation has been formed many years ago, and deviations from them can be met unpleasantly by the customers. Well-established business-models are less affected by the service quality.
Another important thing to mention is the dataset collected – it includes vast amount of data that can be used for further research as well as for the teaching purposes on Operational Efficiency, Advanced Methods of Research and Analysis and other courses. This large data set gave an incentive to split it, as it is impossible to draw any conclusion when analyzing the data set as whole. The companies and the periods are different, what misleads to incorrect interpretation and false conclusions.
1. Abu‐El Samen, A. A., Akroush, M. N., & Abu‐Lail, B. N. (2013). Mobile SERVQUAL. International Journal of Quality & Reliability Management.
2. Alamdari, F., & Fagan, S. (2005). Impact of the adherence to the original low-cost model on the profitability of low-cost airlines. Transport Reviews, 25(3), 377–392. https://doi.org/10.1080/01441640500038748
3. Alaska Airlines. (2020, January). Network | Alaska Airlines. https://newsroom.alaskaair.com/network
4. Ali, F., Dey, B. L., & Filieri, R. (2015). An assessment of service quality and resulting customer satisfaction in Pakistan International Airlines. International Journal of Quality & Reliability Management.
5. American Airlines. (2007, June). American Eagle Airlines: At A Glance. https://web.archive.org/web/20070716220614/http://www.aa.com/content/amrcorp/corpo rateInformation/facts/americaneagle.jhtml
6. American Airlines. (2020). American Airlines Group. https://www.aa.com/i18n/customer- service/about-us/american-airlines-group.jsp
7. Arjomandi, A., & Seufert, J. H. (2014). An evaluation of the world’s major airlines’ technical and environmental performance. Economic Modelling, 41, 133–144.
8. Assaf, A. G., & Josiassen, A. (2011). The operational performance of UK airlines: 2002‐ 2007. Journal of Economic Studies.
9. Assaf, A., & Matawie, K. M. (2010). Improving the accuracy of DEA efficiency analysis: a bootstrap application to the health care foodservice industry. Applied Economics, 42(27), 3547–3558.
10. Atalay, B., Gokten, S., & Turkcan, M. (2018). An overview of measuring and reporting intellectual capital. In Contributions to Economics (pp. 369–388). Physica-Verlag. https://doi.org/10.1007/978-3-319-78494-6_18
11. Banker,R.D.,&Johnston,H.H.(1994).Evaluatingtheimpactsofoperatingstrategieson efficiency in the US airline industry. In Data Envelopment Analysis: Theory, Methodology, and Applications (pp. 97–128). Springer.
12. 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.
13. Barnum,J.W.(1998).WhatPromptedAirlineDeregulation20YearsAgo?WhatWerethe Objectives of That Deregulation and How Were They Achieved?
55
14. Barros, Carlos P, Liang, Q. Bin, & Peypoch, N. (2013). The technical efficiency of US Airlines. Transportation Research Part A: Policy and Practice, 50, 139–148.
15. Barros, Carlos Pestana, & Peypoch, N. (2009). An evaluation of European airlines’ operational performance. International Journal of Production Economics, 122(2), 525– 533. https://doi.org/10.1016/j.ijpe.2009.04.016
16. Belobaba,P.,Odoni,A.,&Barnhart,C.(2015).Theglobalairlineindustry.JohnWiley& Sons.
17. Bhadra, D. (2009). Race to the bottom or swimming upstream: Performance analysis of
US airlines. Journal of Air Transport Management, 15(5), 227–235. https://doi.org/10.1016/j.jairtraman.2008.09.014
18. Bloomberg. (2019). American Airlines Inc – Company Profile and News – Bloomberg Markets. https://www.bloomberg.com/profile/company/AMR1:US
19. Boland,D.,Morrison,D.,&O’Neill,S.(2002).ThefutureofCRMintheairlineindustry: A new paradigm for customer management. IBM Institute for Business Value, 3(1), 1–17.
20. Butt, M. M., & de Run, E. C. (2010). Private healthcare quality: applying a SERVQUAL
model. International Journal of Health Care Quality Assurance.
21. Buttle, F. (1996). SERVQUAL: review, critique, research agenda. European Journal of
Marketing.
22. CAPA. (2018). Longhaul low cost airlines: World Airways to be US’ first.
https://centreforaviation.com/analysis/reports/longhaul-low-cost-airlines-world-airways-
to-be-us-first-405559
23. Chang, Y.-H., & Yeh, C.-H. (2002). A survey analysis of service quality for domestic
airlines. European Journal of Operational Research, 139(1), 166–177.
24. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision
making units. European Journal of Operational Research, 2(6), 429–444.
25. Chen, Y.-H., Tseng, M.-L., & Lin, R.-J. (2011). Evaluating the customer perceptions on
in-flight service quality. African Journal of Business Management, 5(7), 2854.
26. Chiang Leong, C. (2008). An importance-performance analysis to evaluate airline service quality: the case study of a budget airline in Asia. Journal of Quality Assurance in
Hospitality & Tourism, 8(3), 39–59.
27. 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.
28. Choi,K.(2017).Multi-periodefficiencyandproductivitychangesinUSdomesticairlines.
Journal of Air Transport Management, 59, 18–25.
56
29. Chou, C.-C., Liu, L.-J., Huang, S.-F., Yih, J.-M., & Han, T.-C. (2011). An evaluation of airline service quality using the fuzzy weighted SERVQUAL method. Applied Soft Computing, 11(2), 2117–2128.
30. Chow, C. K. W. (2015). On-time performance, passenger expectations and satisfaction in the Chinese airline industry. Journal of Air Transport Management, 47, 39–47.
31. CNBC, & Leslie Josephs. (2020, February 13). Alaska Airlines, American partner for international flights from West Coast. https://www.cnbc.com/2020/02/13/alaska-airlines- american-partner-for-international-flights-from-west-coast.html
32. Cronin Jr, J. J., & Taylor, S. A. (1992). Measuring service quality: a reexamination and extension. Journal of Marketing, 56(3), 55–68.
33. Cronin Jr, J. J., & Taylor, S. A. (1994). SERVPERF versus SERVQUAL: reconciling performance-based and perceptions-minus-expectations measurement of service quality. Journal of Marketing, 58(1), 125–131.
34. Cui,Q.,&Li,Y.(2015).Evaluatingenergyefficiencyforairlines:AnapplicationofVFB- DEA. Journal of Air Transport Management, 44, 34–41.
35. Cui, Q., & Li, Y. (2017a). Airline efficiency measures under CNG2020 strategy: An application of a Dynamic By-production model. Transportation Research Part A: Policy and Practice, 106, 130–143.
36. Cui, Q., & Li, Y. (2017b). Airline efficiency measures using a Dynamic Epsilon-Based Measure model. Transportation Research Part A: Policy and Practice, 100, 121–134.
37. Cunningham,L.F.,Young,C.E.,&Lee,M.(2004).Perceptionsofairlineservicequality:
pre and post 9/11. Public Works Management & Policy, 9(1), 10–25.
38. Daft, J., & Albers, S. (2012). A profitability analysis of low-cost long-haul flight
operations. Journal of Air Transport Management, 19, 49–54.
39. Daft, J., & Albers, S. (2013). A conceptual framework for measuring airline business
model convergence. Journal of Air Transport Management, 28, 47–54.
40. DeNeufville,R.(2008).Low-costairportsforlow-costairlines:flexibledesigntomanage
the risks. Transportation Planning and Technology, 31(1), 35–68.
41. Delta Air Lines. (2016). Delta introduces RFID bag tracking.
https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=4&cad=rja&uact =8&ved=2ahUKEwiN_Nr2upfpAhVnoosKHb3_AiAQFjADegQIAxAB&url=https%3A %2F%2Fnews.delta.com%2Fdelta-introduces-innovative-baggage-tracking-process- 0&usg=AOvVaw1EBHtbwKnzOR3wP5kLWkdu
42. Delta Air Lines. (2017). Delta introduces facial recognition drop-off. https://news.delta.com/delta-plans-biometric-based-self-service-bag-drop
57
43. Delta Air Lines. (2019). Corporate Stats and Facts | Delta News Hub. https://news.delta.com/corporate-stats-and-facts
44. Departed Flights. (2007). ExpressJet Airlines Summer 2007 Route Map. http://www.departedflights.com/XJsummer2007.html
45. Dresner,M.,Lin,J.-S.C.,&Windle,R.(1996).Theimpactoflow-costcarriersonairport and route competition. Journal of Transport Economics and Policy, 309–328.
46. Elliott, K. M., & Roach, D. W. (1993). Service quality in the airline industry: are carriers getting an unbiased evaluation from consumers? Journal of Professional Services Marketing, 9(2), 71–82.
47. FAA. (n.d.). OST_R | BTS | Transtats. Retrieved April 8, 2020, from https://www.transtats.bts.gov/glossary.asp
48. Fageda, X., Suau-Sanchez, P., & Mason, K. J. (2015). The evolving low-cost business model: Network implications of fare bundling and connecting flights in Europe. Journal of Air Transport Management, 42, 289–296.
49. Farooq, M. S. (2016). Social support and entrepreneurial skills as antecedents of entrepreneurial behaviour. PhD Thesis, Universiti Malaysia Sarawak (UNIMAS), Malaysia.
50. Federal Aviation Administration. (n.d.-a). American Airlines AOC. Retrieved May 10,
2020, from https://av- info.faa.gov/detail.asp?DSGN_CODE=AALA&OPER_FAR=121+&OPER_NAME=A MERICAN+AIRLINES+INC
51. Federal Aviation Administration. (n.d.-b). Delta Air Line AOC. Retrieved May 10, 2020, from https://av- info.faa.gov/detail.asp?DSGN_CODE=DALA&OPER_FAR=121&OPER_NAME=DEL TA+AIR+LINES+INC&DSGN_CODE=DALA&OPER_FAR=121&OPER_NAME=DE LTA+AIR+LINES+INC
52. Fethi,M.D.,Jackson,P.M.,&Weyman-Jones,T.G.(2000).Measuringtheefficiencyof European airlines: an application of DEA and Tobit Analysis.
53. Flight International. (2007, March). Directory: World Airlines. 120.
54. FlightGlobal. (2017, October 6). Virgin America flights become Alaska next April | News | Flight Global. https://www.flightglobal.com/virgin-america-flights-become-alaska-next-
april/125646.article
55. Forbes. (2017). Best & Worst Of Aviation 2017: Airlines And Alliances.
https://www.forbes.com/sites/larryolmsted/2017/12/21/best-worst-of-aviation-2017- airlines-and-alliances/#96c877625561
58
56. Francis, G., Humphreys, I., Ison, S., & Aicken, M. (2006). Where next for low cost airlines? A spatial and temporal comparative study. Journal of Transport Geography, 14(2), 83–94.
57. Frontier Airlines. (2020). About Us | Frontier Airlines. Flyfrontier.Com. https://www.flyfrontier.com/about-us/
58. Fu, X., Dresner, M., & Oum, T. H. (2011). Effects of transport service differentiation in the US domestic airline market. Transportation Research Part E: Logistics and Transportation Review, 47(3), 297–305.
59. Fu, X., Lei, Z., Wang, K., & Yan, J. (2015). Low cost carrier competition and route entry in an emerging but regulated aviation market–The case of China. Transportation Research Part A: Policy and Practice, 79, 3–16.
60. Gay, C. (2016, April 23). Delta’s history: From dusting crops to connecting the world | Delta News Hub. https://news.delta.com/deltas-history-dusting-crops-connecting-world
61. Gilbert,D.,&Wong,R.K.C.(2003).Passengerexpectationsandairlineservices:aHong Kong based study. Tourism Management, 24(5), 519–532.
62. Gokten, S., & Gokten, P. O. (2017). Value Creation Reporting: Answering the Question „Value to Whom” according to the International Integrated Reporting Framework. Zeszyty Teoretyczne Rachunkowości, 91 (147), 145–169.
63. Good,D.H.,Röller,L.-H.,&Sickles,R.C.(1995).Airlineefficiencydifferencesbetween Europe and the US: implications for the pace of EC integration and domestic regulation. European Journal of Operational Research, 80(3), 508–518.
64. Gourdin, K. N. (1988). Bringing quality back to commercial air travel. Transportation Journal, 23–29.
65. Grajewski,M.,Köster,M.,&Turek,S.(2009).Mathematicalandnumericalanalysisofa robust and efficient grid deformation method in the finite element context. SIAM Journal on Scientific Computing, 31(2), 1539–1557.
66. Gramani, M. C. N. (2012). Efficiency decomposition approach: A cross-country airline analysis. Expert Systems with Applications, 39(5), 5815–5819.
67. Greer, M. R. (2006). Are the discount airlines actually more efficient than the legacy carriers?: A data envelopment analysis. International Journal of Transport Economics/Rivista Internazionale Di Economia Dei Trasporti, 37–55.
68. Gunston, B. (2008). Faster Than Sound: The Story of Supersonic Flight. Haynes Publishing.
69. Gustafsson, A., Ekdahl, F., & Edvardsson, B. (1999). Customer focused service
development in practice–a case study at Scandinavian Airlines System (SAS). 59
International Journal of Service Industry Management.
70. Hawaiaan Airlines. (2020). Corporate History | Hawaiian Airlines.
https://www.hawaiianairlines.com/about/corporate/history.asp
71. Hawaiian Airlines. (2012, January 11). Hawaiian Airlines Creating Maui Hub to Ease
Connections Statewide | Hawaiian Airlines | Newsroom. https://newsroom.hawaiianairlines.com/releases/hawaiian-airlines-creating-maui-hub-to- ease-connections-statewide
72. Heppenheimer, T. A., & Heppenheimer, T. (1995). Turbulent skies: the history of commercial aviation. Wiley New York.
73. Hermann,A.,&Rammal,H.G.(2010).Thegroundingofthe“flyingbank.”Management Decision.
74. Holloway,S.(2008).Straightandlevel:Practicalairlineeconomics.AshgatePublishing, Ltd.
75. Hong, S., & Zhang, A. (2010). An efficiency study of airlines and air cargo/passenger divisions: a DEA approach. World Review of Intermodal Transportation Research, 3(1– 2), 137–149.
76. Ikenberry,G.J.(1986).Theironyofstatestrength:comparativeresponsestotheoilshocks in the 1970s. International Organization, 40(1), 105–137.
77. JaneenChristoff.(2018,August3).VolarisNowSellingCodeshareFlightsWithFrontier. Travelpulse.Com. https://www.travelpulse.com/news/airlines/volaris-now-selling- codeshare-flights-with-frontier.html
78. JetBlue Airways. (n.d.). JetBlue | About JetBlue Airways. Retrieved May 24, 2020, from http://investor.jetblue.com/media-room/about-jetblue-airways
79. Jin, L. L. (1998). The Empirical Study on Domestic Passengers’ Choice Behavior of The Airlines. Unpublished Doctoral Dissertation. National Cheng Kung University, Tainan, Taiwan.
80. Joo, S.-J., & Fowler, K. L. (2014). Exploring comparative efficiency and determinants of efficiency for major world airlines. Benchmarking: An International Journal.
81. Kawasaki, A., & Lin, M. H. (2013). Airline Schedule Competition and the Entry Route Choices of Low‐Cost Carriers. Australian Economic Papers, 52(2), 97–114.
82. Kim,S.-B.,&Park,J.-W.(2017).Astudyontheimportanceofairlineselectionattributes by airline type: An emphasis on the difference of opinion in between Korean and overseas aviation experts. Journal of Air Transport Management, 60, 76–83.
83. Klophaus,R.,Conrady,R.,&Fichert,F.(2012).Lowcostcarriersgoinghybrid:Evidence from Europe. Journal of Air Transport Management, 23, 54–58.
60
84. Kurtulmuşoğlu, F. B., Can, G. F., & Tolon, M. (2016). A voice in the skies: Listening to airline passenger preferences. Journal of Air Transport Management, 57, 130–137.
85. Lawton, T. C. (2017). Strategic management in aviation: critical essays. Routledge.
86. Lee‐Ross, D. (2008). An exploratory study of the contextual stability of SERVQUAL amongst three retail clusters in far North Queensland. Journal of Place Management and
Development.
87. 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.
88. Lee,B.,&Worthington,A.(2010).Therelativeefficiencyofinternational,domestic,and
budget airlines: nonparametric evidence.
89. Li, W., Yu, S., Pei, H., Zhao, C., & Tian, B. (2017). A hybrid approach based on fuzzy
AHP and 2-tuple fuzzy linguistic method for evaluation in-flight service quality. Journal
of Air Transport Management, 60, 49–64.
90. Li,Y.,Wang,Y.,&Cui,Q.(2015).Evaluatingairlineefficiency:anapplicationofvirtual
frontier network SBM. Transportation Research Part E: Logistics and Transportation
Review, 81, 1–17.
91. Liou,J.J.H.,Hsu,C.-C.,Yeh,W.-C.,&Lin,R.-H.(2011).Usingamodifiedgreyrelation
method for improving airline service quality. Tourism Management, 32(6), 1381–1388.
92. Lohmann,G.,&Koo,T.T.R.(2013).Theairlinebusinessmodelspectrum.JournalofAir
Transport Management, 31, 7–9.
93. Lozano, S., & Gutiérrez, E. (2014). A slacks-based network DEA efficiency analysis of
European airlines. Transportation Planning and Technology, 37(7), 623–637.
94. 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.
95. Mallikarjun, S. (2015). Efficiency of US airlines: A strategic operating model. Journal of
Air Transport Management, 43, 46–56. https://doi.org/10.1016/j.jairtraman.2014.12.004
96. Maqsood Ali, M., Mohammad, A., & Maqsood Ali Assistant Professor, M. (2014). Customer Services in Saudi Arabian Airlines: A Case Study of Jazan Province INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS Customer Services in Saudi Arabian Airlines: A Case Study of Jazan Province.
https://www.researchgate.net/publication/316936867
97. Martín, J. C., Román, C., & Voltes-Dorta, A. (2009). A stochastic frontier analysis to
estimate the relative efficiency of Spanish airports. Journal of Productivity Analysis, 31(3), 61
163–176.
98. Mason, K. J., & Morrison, W. G. (2008). Towards a means of consistently comparing
airline business models with an application to the ‘low cost’airline sector. Research in
Transportation Economics, 24(1), 75–84.
99. Medina-Muñoz, D. R., Medina-Muñoz, R. D., & Suárez-Cabrera, M. Á. (2018).
Determining important attributes for assessing the attractiveness of airlines. Journal of Air
Transport Management, 70, 45–56.
100.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. https://doi.org/10.1016/j.tra.2011.04.015
101.Merkert, R., & Morrell, P. S. (2012). Mergers and acquisitions in aviation–Management and economic perspectives on the size of airlines. Transportation Research Part E: Logistics and Transportation Review, 48(4), 853–862.
102.Merkert, R., & Pearson, J. (2015). A non-parametric efficiency measure incorporating perceived airline service levels and profitability. Journal of Transport Economics and Policy (JTEP), 49(2), 261–275.
103.Merkert, R., & Williams, G. (2013). Determinants of European PSO airline efficiency– Evidence from a semi-parametric approach. Journal of Air Transport Management, 29, 11–16.
104.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.
105.Morandi, V., Malighetti, P., Paleari, S., & Redondi, R. (2015). Codesharing agreements by low-cost carriers: An explorative analysis. Journal of Air Transport Management, 42, 184– 191.
106.Muturi, D., Sagwe, J., & Namukasa, J. (2013). The influence of airline service quality on passenger satisfaction and loyalty. The TQM Journal.
107.Nadiri, H., Hussain, K., Ekiz, E. H., & Erdoğan, Ş. (2008). An investigation on the factors influencing passengers’ loyalty in the North Cyprus national airline. The TQM Journal.
108.NBC. (2009). What makes an airline ‘pet friendly’? http://www.nbcnews.com/id/30605983/ns/travel-pet_travel/t/what-makes-airline-pet- friendly/#.WvByUi9eOu0
109.Olivares, J. V. (2005). La SABENA. L’Aviation commerciale belge, 1923-2001. Des
origines au crash/Guy Vanthemsche. Bruselas, De Boeck, 2002, 341 pp. Investigaciones 62
de Historia Económica, 1(2), 228–230.
110.Omrani, H., & Soltanzadeh, E. (2016). Dynamic DEA models with network structure: An
application for Iranian airlines. Journal of Air Transport Management, 57, 52–61. 111.Ostrowski, P. L., O’Brien, T. V, & Gordon, G. L. (1993). Service quality and customer
loyalty in the commercial airline industry. Journal of Travel Research, 32(2), 16–24. 112.Parasuraman, Ananthanarayanan, Zeithaml, V. A., & Berry, L. L. (1988). Servqual: A
multiple-item scale for measuring consumer perc. Journal of Retailing, 64(1), 12. 113.Parasuraman, Anantharanthan, Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41–
50.
114.Parasuraman, Arun, Zeithaml, V. A., & Berry, L. L. (1994). Alternative scales for
measuring service quality: a comparative assessment based on psychometric and
diagnostic criteria. Journal of Retailing, 70(3), 201–230.
115.Park, J. W., Robertson, R., & Wu, C. L. (2005). Investigating the effects of service quality
on airline image and behavioral intentions: findings from Australian international air
passengers. Journal of Tourism Studies, 16(1), 2–11.
116.Parkin, D., & Hollingsworth, B. (1997). Measuring production efficiency of acute hospitals
in Scotland, 1991-94: validity issues in data envelopment analysis. Applied Economics,
29(11), 1425–1433.
117.Pereira, B. A., & Caetano, M. (2015). A conceptual business model framework applied to
air transport. Journal of Air Transport Management, 44, 70–76.
118.Pires, H. M., & Fernandes, E. (2012). Malmquist financial efficiency analysis for airlines.
Transportation Research Part E: Logistics and Transportation Review, 48(5), 1049–1055. 119.Porter, M. E. (2008). Competitive strategy: Techniques for analyzing industries and
competitors. Simon and Schuster.
120.Prayag, G. (2007). Assessing international tourists’ perceptions of service quality at Air
Mauritius. International Journal of Quality & Reliability Management. 121.Radović-Marković, M., Shoaib Farooq, M., & Marković, D. (2017). Strengthening the resilience of small and medium-sized enterprises. Review of Applied Socio-Economic
Research, 345–356.
122.Robledo, M. A. (2001). Measuring and managing service quality: integrating customer
expectations. Managing Service Quality: An International Journal.
123.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.
63
124.Schefczyk, M. (1993). Operational performance of airlines: an extension of traditional measurement paradigms. Strategic Management Journal, 14(4), 301–317.
125.Scheraga, C. A. (2004). Operational efficiency versus financial mobility in the global airline industry: A data envelopment and Tobit analysis. Transportation Research Part A: Policy and Practice, 38(5), 383–404. https://doi.org/10.1016/j.tra.2003.12.003
126.Sengupta, J. K. (1999). A dynamic efficiency model using data envelopment analysis. International Journal of Production Economics, 62(3), 209–218.
127.Seufert, J. H., Arjomandi, A., & Dakpo, K. H. (2017). Evaluating airline operational performance: A Luenberger-Hicks-Moorsteen productivity indicator. Transportation Research Part E: Logistics and Transportation Review, 104, 52–68.
128.Sjögren, S. (2016). Modeling airline efficiency–a comparison of international airlines using data envelopment analysis. Advances in Airline Economics, 5, 103–129.
129.SkyWest Airlines. (2017). Investor Update 2017.
130.SkyWest Airlines. (2020). SkyWest Airlines Fact Sheet. https://www.skywest.com/about-
skywest-airlines/facts/
131.Southwest Airlines. (2020). Southwest Airlines – Route Map.
https://www.southwest.com/flight/routemap_dyn.html
132.Sueyoshi, T., & Goto, M. (2012). DEA radial and non-radial models for unified efficiency
under natural and managerial disposability: theoretical extension by strong complementary
slackness conditions. Energy Economics, 34(3), 700–713.
133.Surovitskikh, S., & Lubbe, B. (2008). Positioning of selected Middle Eastern airlines in
the South African business and leisure travel environment. Journal of Air Transport
Management, 14(2), 75–81.
134.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.
135.The Associated Press. (2012). American Air signs deal to contract out some flying to
SkyWest. https://news.yahoo.com/american-air-signs-deal-contract-flying-skywest-
165209289.html?_esi=1
136.The Economist. (1997). Airlines – Freedom in the air.
https://www.economist.com/business/1997/04/03/freedom-in-the-air
137.The Economist. (2009). The high cost of a legacy airline.
https://www.economist.com/gulliver/2009/04/07/the-high-cost-of-a-legacy-airline 138.The Economist. (2013). Legacy vs low-cost carriers – Spot the difference | Gulliver | The
Economist. https://www.economist.com/gulliver/2013/03/26/spot-the-difference
64
139.Truitt, L. J., & Haynes, R. (1994). Evaluating service quality and productivity in the regional airline industry. Transportation Journal, 21–32.
140.Tsafarakis, S., Kokotas, T., & Pantouvakis, A. (2018). A multiple criteria approach for airline passenger satisfaction measurement and service quality improvement. Journal of Air Transport Management, 68, 61–75.
141.Tsantoulis, M., & Palmer, A. (2008). Quality convergence in airline co‐brand alliances. Managing Service Quality: An International Journal.
142.Urban, M., Klemm, M., Ploetner, K. O., & Hornung, M. (2018). Airline categorisation by applying the business model canvas and clustering algorithms. Journal of Air Transport Management, 71, 175–192.
143.USA Today. (2017). The fleet and hubs of United Airlines, by the numbers. https://www.usatoday.com/story/travel/flights/todayinthesky/2017/01/26/fleet-and-hubs- united-airlines-numbers/96983530/
144.Victoria Klesty, & Terje Solsvik. (2019, October 17). Norwegian Air, JetBlue tie up to expand transatlantic network – Reuters. https://www.reuters.com/article/us-norwegianair- jetblue-airways/norwegian-air-jetblue-tie-up-to-expand-transatlantic-network- idUSKBN1WW1BX
145.Vink, P. (2004). Comfort and design: principles and good practice. CRC press. 146.Wilson, S. (2002). Ansett: The Story of the Rise and Fall of Ansett 1936 – 2002. Aerospace
Publications.
147.Wu, H.-C., & Cheng, C.-C. (2013). A hierarchical model of service quality in the airline
industry. Journal of Hospitality and Tourism Management, 20, 13–22.
148.Wu, H.-C., & Ko, Y. J. (2013). Assessment of service quality in the hotel industry. Journal
of Quality Assurance in Hospitality & Tourism, 14(3), 218–244.
149.Wu, W.-Y., & Liao, Y.-K. (2014). A balanced scorecard envelopment approach to assess
airlines’ performance. Industrial Management & Data Systems.
150.Yu, M.-M. (2012). Performance assessment of transport services with the ERM-NDEA
model: evidence from a domestic airline in Taiwan. Transportation Planning and
Technology, 35(7), 697–714.
151.Zhu, Jing. (2017). Airline service quality performance: a comparison of air China and
Hainan airlines.
152.Zhu, Joe. (2011). Airlines performance via two-stage network DEA approach. Journal of
CENTRUM Cathedra: The Business and Economics Research Journal, 4(2), 260–269.
Последние выполненные заказы
Хочешь уникальную работу?
Больше 3 000 экспертов уже готовы начать работу над твоим проектом!
4.1 (20 отзывов)
5 (154 отзыва)
4.3 (248 отзывов)
4.9 (343 отзыва)
4.9 (5 отзывов)
5 (18 отзывов)
5 (44 отзыва)
4.5 (80 отзывов)
4.8 (40 отзывов)
