As the interest in airport efficiency has grown worldwide, studies on it have been widely carried out. However, previous studies on airiport efficiency have mostly been focused on efficiency at individual airport level irrespective of whether they belong to airport groups or not. Some studies have sought to compare the efficiency of group airports and standalone airports. And the result of those studies were that standalone airports are more efficient than group airports. However, airport efficiency can be higher where the airport belongs to an airport group rather than when it is a standalone airport. This is because, in the case of the airport group, knowledge- transfer between airports belonging to it becomes easy, economies of scope are possible, and bargaining power is also expanded. On the other hand, an airport group may differ in efficiency depending on the number of airports that belong to it. This is because, as the number of airports goes up, the cost that can be saved through joint purchasing, recruitment, and training can be larger. However, even with growth in the number of airports, efficiency does not grow indefinitely, because, when the airport exceeds a certain number, economies of scale disappear and diseconomies of scale emerge, such as increased management costs. It can, therefore, be said that the relationship between the number group airports and efficiency is inverted U-shaped. Airport efficiency is also influenced by the market share of the largest airlines at airports. This is because, as the market share of the largest airlines rises, it is possible to efficiently allocate airport resources such as slots, check-in counters, and parking stations, and to collaborate with them in attracting airline passengers. The market share of a dominant airline gets even larger if the airport it serves belongs to an airport group. This can be explained by the fact that there is a tendency for an airport group to recognize the largest airline as the most cooperative partner in coordinating flight routes and resources at airports belonging to the airport group. This study first compares the efficiency between a group airport and a standalone airport and compares it with the previous research results, and then investigates how the airport efficiency is affected by the number of airports operated by the airport group. This paper also analyzes whether the share of the largest airlines affects the efficiency of airports and studies whether the market share of airlines in group airports is higher. First of all, among the data contained in the Airport Benchmarking Report published by the Air Transport Research Society (ATRS) every year, panel data of 2015-2017 inputs and outputs from 124 airports in Asia Pacific and Europe is used for data envelope analysis (DEA). The efficiency between group airports and standalone airports was compared by performing CEM (Coarsened Exact Matching) analysis and regression analysis using the airport efficiency scores calculated through DEA analysis. Subsequently, the relationship between the number of airports and the efficiency of 45 airports belonging to the airport group was analyzed using Tobit Regression. Finally, the relationship between the largest airline''s market share and airport efficiency and the relationship between the group''s airport and the largest airline''s market share were also analyzed through CEM analysis and Tobit Regression. As a result, it was found that group airports showed higher efficiency than standalone airports. This finding is against the previous research results, and is believed to be due to the improvement of accuracy by CEM analysis, expansion of sample airports, and diversification of variables in efficiency measurement. And that is ultimately because group airports are equipped with conditions to increase efficiency compared to standalone airports for reasons such as disseminating knowledge, achieving economies of scope, and expanding negotiation power. Meanwhile, the relationship between the number of group airports and the efficiency of the airports are found to be inverted U-shaped. It means that, as the number of airports within an airport group rises, so does the scale economies, contributing to enhancing efficiency until certain point, from which diseconomies of scale set in to adversely affect the efficiency of airports. The scale economy arises with the bargaining power enlarged by the airport growth in number (J. H. Park & Kim, 2020), reduction in managerial cost driven by bulk purchase and massive personnel recruitment/training, and frequent knowledge transfer which becomes frequent and easy within an airport group. But diseconomies of scale come about when the benefit of scale economies is offset with the growing managerial cost arising from duplication of management and complexity of procedures. This study, under the circumstances where conflicting interests are observed from local authorities and communities with the emergence of global airport groups actively acquiring ownership and/or concession of airports globally, has practical implication in determining the ideal number of airports to be operated in terms of maximization of airport efficiency. As for the relationship between the market share of largest airline and airport efficiency, it turned out that the higher the airline market share, the higher the airport efficiency is. Airports build partnerships with airlines and strive to stably attract passengers and secure profits. In this case, the airport will first establish a cooperative system with the largest airlines. Of course, it can hinder the entry of new airlines into the market, but it has a positive effect, at least in terms of airport efficiency. Finally, it was found that the share of the largest airlines was higher at the group airports. Both Airlines and airports ultimately belong to the network industry to transport passengers and cargo and complement each other. Operating multiple airports, airport groups can reasonably adjust air traffic, slots, and infrastructure in their airport system, cooperating with airlines, especially the largest airlines. Therefore, it was found that the share of airlines at group airports could be higher than at standalone airports. In last decades, airports have faced growing pressure from their stakeholders to improve efficiency for reasons of infrastructure constraints and privatization. This study provides answers to the question of whether existing airports should be operated individually or grouped and provided practical implications for policy decisions of governments as well as the airport authorities of each country by revealing that the share of the largest airlines has a positive effect on airport efficiency and that the group airports contribute to increasing the share of the largest airlines.
CHAPTER 1 INTRODUCTION 11.1 Background of the Research 11.1.1 Growing interest in airport efficiency 11.1.2 Researches driven by the interest in efficiency 31.1.3 Contribution of researches to stakeholders 41.2 Purpose of the research 51.2.1 Types of airport groups 51.2.2 Airport groups vs standalone airports 71.2.3 Group airports and airline dominance 101.3 Structure of this dissertation 11CHAPTER 2 THEORETICAL BACKGROUND 132.1 Aviation industry and airport efficiency 132.1.1 Liberalization and aviation industry 132.1.2 The privatization and commercialization in airport industry 182.1.3 Parties keen on airport efficiency study 212.1.4 Literature review on airport efficiency 232.2 Methodologies for assessing efficiency 282.2.1 Total Factor Productivity (TFP) 292.2.2 Stochastic Frontier Analysis (SFA) 312.2.3 Data Envelopment Analysis (DEA) 342.3 CEM (Coarsened Exact Matching) 37CHAPTER 3 HYPOTHESIS 393.1 Efficiency of group airports vs standalone airports 393.1.1 Integrated management of multiple airports and knowledge transfer 393.1.2 Centralized management of multiple airports and Scale and Scope Economies 423.1.3 Bargaining power of multiple airports 453.2 Number of group airports and scope economies 483.3 Airline market structure and efficiency 543.4 Airport group and airline market dominance 59CHAPTER 4 RESEARCH DESIGN 614.1 Methodology 614.1.1 Data envelopment analysis(DEA) 624.1.2 CEM (Coarsened Exact Matching) 654.1.3 Tobit Regression Analysis 694.2 Data and variable construction 704.2.1 Data 704.2.2 Variables 71CHAPTER 5 RESULTS OF EMPIRICAL TEST 795.1 Airport efficiency scores 795.2 Correlation across variables. 825.3 Results of regression analysis 835.3.1 Efficiency of group airports and standalone airports 835.3.2 Number of airports and airport efficiency 905.3.3 Airline dominance and airport efficiency 955.3.4 Airport group and airline market dominance 99CHAPTER 6 CONCLUSION 1036.1 Overall outcome of the research 1036.2 Contributions of the research 1086.3 Limitation of the research and recommendations for future study 110REFERENCES 111APPENDIX A 122APPENDIX B 128국문초록 132