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Littérature scientifique sur le sujet « Airlines – Competitions – Econometric models »

Auteur : Grafiati

Publié le 10 mars 2023

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Articles de revues sur le sujet "Airlines – Competitions – Econometric models"

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Kiracı, Kasım. "Determinants of Financial Risk: An Empirical Application on Low-Cost Carriers." Scientific Annals of Economics and Business 66, no. 3 (2019): 335–49. http://dx.doi.org/10.47743/saeb-2019-0025.

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The airline industry has entered a rapid development and transformation process, especially after the Second World War. In this process, it is seen that the market structure changed and many private airlines were established. Due to increased competition, airlines have begun to follow various strategies and business models in order to gain a competitive advantage over each other. One of the business models successfully applied recently is the low-cost business model. Therefore, this study focuses on airline companies that applied the low-cost business model. The study aims to reveal the factors that determine the financial risk in airlines, which implements the low-cost business model. For this purpose, firstly, airline companies that implement the low-cost business model have been identified according to the classification in the literature. The study included an analysis of 13 airlines with the low-cost business model that was fully accessible to financial data for the 2004-2017 period. Panel data analysis was used in the study and Altman (1968) Z-Score and Springate (1978) S-Score were used in measuring financial risk. Empirical findings of the study reveal that firm leverage, asset structure, firm size, firm profitability, and liquidity ratio have an effect on financial risk.

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BARANOVA, Nina M., Sergei N. LARIN, and Dar'ya S. LOGINOVA. "Modeling the influence of intellectual potential on innovative development of PAO Aeroflot – Russian Airlines." Economic Analysis: Theory and Practice 20, no. 10 (2021): 1897–913. http://dx.doi.org/10.24891/ea.20.10.1897.

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Subject. The article investigates the innovative development of Aeroflot Group and analyzes the impact of factors of intellectual potential. Objectives. The purpose is to investigate the development of intellectual potential of Aeroflot Group by selected indicators, determine their impact on the innovative development of the company, and increase its competitiveness. Methods. We studied the works of Russian and foreign scientists, performed a regression analysis and econometric modeling on the basis of statistical data from the annual reports of Aeroflot Group for 2005–2020. To create econometric models, we applied the tools of the EViews 12 software package. Results. We built econometric models to study and forecast the innovative development of Aeroflot Group, given the influence of intellectual potential factors. The analysis of these models showed that the linear model is adequate and can be used in the practical activities of Aeroflot Group. The exponential model parameters and estimates proved to be insignificant, so it cannot be used for the research. Conclusions. The long-term economic growth of the country and its innovative development depend directly on such factors of intellectual potential as human capital, personnel skills (number and quality of labor force), increase in expertise and labor productivity, availability of social incentives. Therefore, the focus of national projects implementation in Russia is on accelerated innovative development of the country, using the factors of intellectual potential of enterprises and creating conditions for the growth of its quality and social incentives.

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Gasparetto, Thadeu, and Angel Barajas. "Economic effects of promotion and relegation in parallel competitions." Economics and Business Letters 11, no. 1 (2022): 7–15. http://dx.doi.org/10.17811/ebl.11.1.2022.7-15.

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Previous research evidence some negative effects after league relegations. However, these works focused only on domestic league figures, overlooking that football clubs play in simultaneous tournaments. Therefore, the effects of relegation in a domestic league on those simultaneous championships remain unclear. Our dataset comprises twenty men’s Brazilian State Championships from 2013 to 2017. Panel Data Ordinary Least Squares models are employed as econometric techniques. The results suggest that the promotions to the second tier of the Brazilian League increase both attendance and revenues of clubs while relegations impact them negatively. Nonetheless, the promotion to the top tier produces no significant increase, which may indicate a potential adverse demand effect. Further research may inspect whether it happens in European football.

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Abdelghany, Ahmed, Khaled Abdelghany, and Ching-Wen Huang. "An integrated reinforced learning and network competition analysis for calibrating airline itinerary choice models with constrained demand." Journal of Revenue and Pricing Management 20, no. 3 (2021): 227–47. http://dx.doi.org/10.1057/s41272-021-00309-y.

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Srinidhi, S., and Ajay K. Manrai. "International air transport demand: drivers and forecasts in the Indian context." Journal of Modelling in Management 9, no. 3 (2014): 245–60. http://dx.doi.org/10.1108/jm2-08-2013-0036.

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Purpose – This paper aims to provide a framework for the airlines to forecast demand, specifically on international routes operated from major metros of the USA and position their services by designing the service positioning matrix. Major benefits include route contemplation, effective fleet scheduling, decisions on aircraft and fuel purchases and developing optimal fare policies. Much effort has been directed to developing forecasts of air transport demand, particularly by airline companies and professional bodies in the air transport industry. However, detailed analysis of the characteristics of demand for air transport over long-haul or international routes is less researched. Design/methodology/approach – Major methodologies used were regression, time series analysis – Holts’ exponential smoothing method. Two econometric models are formulated that capture the direct and indirect drivers of airline demand in the Indian context. Forecasts of demand are made over the next seven years until 2020. Findings – It is interesting to find that demand not only is influenced by direct parameters such as population- and behavior-oriented parameters such as income, but the macroeconomic environment of the country concerned also plays a major role in demand origination. Variables like investment, gross domestic product, etc. contribute a lot in terms of international airline demand. It is also expected that in the Indian context, demand is on a spike path over the next seven years considering the macroeconomic environment and other general economic conditions. Research limitations/implications – This paper is developed and applied in the Indian context. Results may change when applied to different countries depending on their macroeconomic conditions. Practical implications – This study will be useful for any airline in route planning, and in formulating major policy decisions. Other benefits include effective fleet scheduling, decisions on aircraft and fuel purchases and developing optimal fare policies. Originality/value – This paper adds to the existing literature by developing two demand drivers’ models in the Indian context. It is first such attempt to analyse the Indian aviation industry ever since the Indian economic liberalization in 1991. Forecasts provided yield major benefits for airlines operating to and from India.

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La, Jiezhuoma, and Iryna Heiets. "THE IMPACT OF DIGITALIZATION AND INTELLIGENTIZATION ON AIR TRANSPORTATION SYSTEM." Aviation 25, no. 3 (2021): 159–70. http://dx.doi.org/10.3846/aviation.2021.15336.

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This study aims to provide insights into the impact levels of digitalization and intelligentization on air transport system (ATS) in Australia, China, the US, and India. Air transport system is one of the most efficient transport systems which contains three elements: air traffic control, airport, and airlines. In modern society, the importance of digitalization and intelligentization in ATS is attached to by publics. In this study, firstly, comparative analysis is used to analyze the different states of digitalization and intelligentization level and air transport system in sample countries. Then, correlation analysis is used to study the correlation of the different impact factors with the ATS in different countries. The third one is regression analysis, it is used to analyze the relationship between ATS and the development of digitalization and intelligentization in four sample countries. At last, forecasting analysis is used to predict the future trend of digitalization and intelligentization’s impact on ATS in the sample countries in the next few years. Then, the most significant impact factors for ATS will be obtained. Also, the future development trends of ATS under digitalization and intelligentization’s impact could be forecasted by using econometric models.

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Shirur, Srinivas. "Are Managers Measuring the Financial Risk in the Right Manner? An Exploratory Study." Vikalpa: The Journal for Decision Makers 38, no. 2 (2013): 81–94. http://dx.doi.org/10.1177/0256090920130205.

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The basic problem with corporate finance is that it deals with the fundamental analysis issues while the tools used are those applicable for technical analysis. That is the reason why finance managers often arrive at wrong decisions which snowball into issues like the subprime crisis. Initially, Markowitz model was used to calculate risk for portfolio management. It gave importance only to systematic risk as unsystematic risk could be avoided through diversification. Later on, CAPM model was developed for corporate finance and project finance for calculation of risk. Finance models dealing with risk management are applicable only for a short period and that too for an average of a large number of companies. The approach to apply risk measurement technique suitable for portfolio management to corporate finance is not correct. Even the econometric techniques applied to validate calculation of risk for portfolio management should be different from those applied for corporate finance. The present article analyses the problems of applying such risk measurement techniques for corporate finance purpose. A company faces mainly two types of risks: liquidity risk and bankruptcy risk. In case a company suffers from bankruptcy threat (which may or may not lead to actual bankruptcy), i.e., possibilities of closure due to losses, there will be two possibilities: The company may move with market index in normal times while it may come down suddenly with index and may not bounce back (Kink in the beta curve), as in the case of MTNL and Jet Airlines. There may be a sudden bankruptcy threat as in the case of Satyam. The latter case does not allow investors to react. However, corporate managers will have to take account of the first possibility of bankruptcy risk which cannot be ignored by assuming beta to be constant. This paper examines three companies, Mastek, Jet Airlines, and MTNL, in this category. The author suggests that instead of segregating risk into systematic and unsystematic risk, it should be segregated into bankruptcy and liquidity risk. In this way, unsystematic risk is also priced while determining the value of a company.

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Cheremnykh, A. A. "ANALYSIS OF FACTORS INFLUENCING THE PRICING OF AIR TICKETS." Applied Mathematics and Control Sciences, no. 1 (December 15, 2022): 196–213. http://dx.doi.org/10.15593/2499-9873/2022.1.10.

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The article is devoted to discussing topical issues about the formation of the price of plane tickets. The paper analyzes and evaluates the degree of influence of factors on the pricing process using regression analysis methods. At the first stage, a review of the available research sources of foreign and Russian authors was carried out, according to the results of which the main characteristics determining the price level of air tickets were identified and considered. In the course of studying the issue, the experience and conclusions, based on previously performed studies of foreign segments of air transportation, are extended to the selection and analysis of current data on the Russian market. The assessment of the degree of a possible influence of the considered price-forming indicators on air ticket fares was carried out using four econometric models of the dependence of ticket prices on exchange rates, fare/air route characteristics, socio-economic and secondary factors. They are checked for lowcost and economy segments based on information on 15 thousand of air tickets of Russian air carriers for the period from 19.01.2021 to 12.02.2021, presented in the form of a single data set. The data was collected independently by daily monitoring of information from the official websites of airlines, federal websites of Rosstat, and Rosaviation. As a result of the research conducted within the framework of this article, it was revealed that with an increase in the distance of the flight, the cost of the ticket increases proportionally. The average income of the population negatively affects prices in the economy and budget classes. A similar trend can be traced concerning the cost of jet fuel at the airport of departure and nonstop flights. Reducing the number of days between the dates of ticket purchase and flight departure will also affect the increase in ticket prices. With a decrease in the exchange rate of foreign currency, the cost of economy class air tickets changes significantly compared to the budget. The reverse trend is observed in the case of the IATA exchange rate, where the effect falls on the last group of shipments. The listed characteristics are identified as the most significant relative to the considered classes of tariff groups in the Russian aviation industry. The results of the work can be recommended to air carriers for use in the process of forming the cost of tickets to achieve maximum efficiency and profitability of the business, used by consumers of the airline services as a tool for finding and buying air tickets with the best conditions and offers.

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Thèses sur le sujet "Airlines – Competitions – Econometric models"

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NERO, Giovanni. "Intra-European airline competition : a theoretical and an empirical analysis." Doctoral thesis, 1996. http://hdl.handle.net/1814/5018.

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Defence date: 26 February 1996<br>Examining Board: Prof. David Encaoua, University of Paris I ; Prof. Ulrich Kohli, University of Geneva ; Prof. Stephen Martin, University of Copenhagen and EUI ; Prof. Jacques Pavaux, University of Toulouse ; Prof. Louis Phlips, EUI, Supervisor<br>First made available online: 7 September 2016

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"Growth, competitions and strategies in the air transport industry in Pearl River Delta of China." 2008. http://library.cuhk.edu.hk/record=b5893637.

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Xu, Fang.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.<br>Includes bibliographical references (leaves 75-79).<br>Abstracts in English and Chinese.<br>Abstract --- p.i<br>Acknowledgement --- p.ii<br>Chapter 1 --- Introduction --- p.1<br>Chapter 2 --- Background Information --- p.3<br>Chapter 2.1 --- Growth of Air-Transportation Industry --- p.3<br>Chapter 2.1.1 --- General Figures --- p.3<br>Chapter 2.1.2 --- Growth of Air Cargo Market --- p.3<br>Chapter 2.1.3 --- Regulatory Support --- p.5<br>Chapter 2.2 --- The Focus: Pearl River Delta --- p.6<br>Chapter 2.2.1 --- Strategic Moves of Airports --- p.8<br>Chapter 2.2.2 --- Investment and Development of Airlines --- p.12<br>Chapter 2.2.3 --- Hong Kong VS Shen Zhen --- p.13<br>Chapter 3 --- Airport Competition --- p.14<br>Chapter 3.1 --- Introduction --- p.14<br>Chapter 3.2 --- One-period two port competition model --- p.15<br>Chapter 3.2.1 --- The basic model --- p.15<br>Chapter 3.2.2 --- Stackelberg Game --- p.23<br>Chapter 3.2.3 --- Location factor --- p.26<br>Chapter 3.3 --- Two-period two port competition model --- p.27<br>Chapter 3.3.1 --- The basic model --- p.27<br>Chapter 3.3.2 --- Switching cost --- p.30<br>Chapter 3.4 --- Conclusion --- p.33<br>Chapter 4 --- Combined airline VS full-cargo airline --- p.34<br>Chapter 4.1 --- Introduction --- p.34<br>Chapter 4.2 --- Model Setup --- p.35<br>Chapter 4.2.1 --- Modelling Capacity and Cost --- p.35<br>Chapter 4.2.2 --- Modelling Demand --- p.37<br>Chapter 4.2.3 --- The Optimization Framework --- p.37<br>Chapter 4.2.4 --- Decomposition of the Decision Process --- p.39<br>Chapter 4.3 --- Step 1: Strategies in the Passenger Market --- p.40<br>Chapter 4.3.1 --- Carriers enter the game with zero-inventory --- p.40<br>Chapter 4.3.2 --- Incumbent carrier has established initial capacity --- p.42<br>Chapter 4.4 --- Step 2: Strategies in the Cargo Market --- p.45<br>Chapter 4.5 --- Centralized decision --- p.49<br>Chapter 4.5.1 --- Both airlines have zero initial capacity in the passenger market --- p.50<br>Chapter 4.5.2 --- One airline has non-zero initial capacity in the passenger market --- p.51<br>Chapter 4.5.3 --- Both airlines have initial capacity in the cargo market --- p.53<br>Chapter 4.6 --- Conclusion --- p.53<br>Chapter 5 --- Demand growth and shifting --- p.55<br>Chapter 5.1 --- Introduction --- p.55<br>Chapter 5.2 --- Competition Scenario --- p.56<br>Chapter 5.2.1 --- Growth and shifting of passenger demand --- p.56<br>Chapter 5.2.2 --- Growth and shifting of cargo demand --- p.60<br>Chapter 5.3 --- Centralized decision making --- p.64<br>Chapter 5.4 --- conclusion --- p.72<br>Chapter 6 --- Conclusion --- p.73<br>Bibliography --- p.75

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Livres sur le sujet "Airlines – Competitions – Econometric models"

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Borenstein, Severin. How airlines market work...or do they?: Regulatory reform in the airline industry. National Bureau of Economic Research, 2007.

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Borenstein, Severin. How airlines market work...or do they?: Regulatory reform in the airline industry. National Bureau of Economic Research, 2007.

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Borenstein, Severin. Competition and price dispersion in the U.S. airline industry. National Bureau of Economic Research, 1991.

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Borenstein, Severin. Competition and price dispersion in the U.S. airline industry. Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1991.

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Whinston, Michael Dennis. Entry, contestability, and deregulated airline markets: An event study analysis of People Express. National Bureau of Economic Research, 1990.

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Berry, Steven. Airline hubs: Costs, markups and the implications of customer heterogeneity. National Bureau of Economic Research, 1996.

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Escobari, Diego. Price dispersion under costly capacity and demand uncertainty. National Bureau of Economic Research, 2007.

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Escobari, Diego. Price dispersion under costly capacity and demand uncertainty. National Bureau of Economic Research, 2007.

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Hamermesh, Daniel S. A general model of dynamic labor demand. National Bureau of Economic Research, 1990.

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Good, David H. The structure of production, technical change, and efficiency in a multinational industry: An application to U.S. airlines. National Bureau of Economic Research, 1991.

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