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.
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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
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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.
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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
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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.
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