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The Spanish Airport System: a Critical Assessment of the Impact of AENA’S Managerial Decisions on Airports’ Technical Efficiencies

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The Spanish Airport System: a Critical Assessment of the Impact of AENA’S Managerial Decisions on Airports’ Technical Efficiencies ADVERTIMENT. Lʼaccés als continguts dʼaquesta tesi queda condicionat a lʼacceptació de les condicions dʼús establertes per la següent llicència Creative Commons: http://cat.creativecommons.org/?page_id=184 ADVERTENCIA. El acceso a los contenidos de esta tesis queda condicionado a la aceptación de las condiciones de uso establecidas por la siguiente licencia Creative Commons: http://es.creativecommons.org/blog/licencias/ WARNING. The access to the contents of this doctoral thesis it is limited to the acceptance of the use conditions set by the following Creative Commons license: https://creativecommons.org/licenses/?lang=en Universitat Autònoma de Barcelona (UAB) Business Department Faculty of Economics and Business iDEM International Doctorate in Entrepreneurship and Management Industrial Doctorate Programme 2015 DI84 International Doctorate Doctoral Thesis The Spanish airport system: A critical assessment of the impact of AENA’s managerial decisions on airports’ technical efficiencies Ph.D. candidate Ane Elixabete Ripoll Zarraga Supervisor Dr Fabiola Portillo Pérez de Viñaspre (Universidad de la Rioja) Tutor Professor Diego Prior Jiménez (Universitat Autònoma de Barcelona) July 2018 Doctoral Thesis The Spanish airport system: A critical assessment of the impact of AENA’s managerial decisions on airports’ technical efficiencies Universitat Autònoma de Barcelona (UAB) Business Department Faculty of Economics and Business iDEM International Doctorate in Entrepreneurship and Management (The 40th anniversary 1978-2018) Industrial Doctorate Programme 2015 DI84 International Doctorate Supervisor Ph.D. candidate Dr Fabiola Portillo Pérez de Viñaspre Ane Elixabete Ripoll Zarraga Abstract This Thesis addresses the application to the airport industry of alternative methodological approaches to the conventional models commonly classified as non-parametric and parametric methods. The aim is to estimate and to confirm the consistency of the Spanish airports’ efficiency across time. Therefore, several approaches are used in order to overcome specific limitations that the methodologies present compared to the other. Within the non-parametric techniques Data Envelopment Analysis (DEA) is used and as parametric models, Stochastic Frontier Analysis (SFA). DEA has been extensively used worldwide in the airport industry and some studies refer to the Spanish case. Nevertheless, the conventional DEA models present some limitations; for example, they tend not to incorporate time related effects. The literature shows a lack of usage of SFA in empirical studies. Therefore, relevant insights are to be learned from the application to the Spanish airport system. One important matter regarding few studies considering the Spanish airports is the lack of individual relevant financial information published by AENA. AENA is a government-owned company and manager of all the Spanish airports. The degree of centralisation of management is to the extent that airports managers cannot decide commercial policies (e.g. price and quality of the services provided). Additionally, the studies neither critically question nor assess the reliability of the data regarding representing a fair and true view of how the airports are performing from an operational perspective. This Thesis is a compilation of chapters (four research papers) and one paper in progress. All the papers are empirical base with specific objectives in order to analyse the airports from different perspectives including the geographical location and the tourism attractiveness. Firstly, one major problem addressed in this Thesis is the reliability of the data provided by AENA, particularly with respect to investment (cost of capital). Secondly, to estimate the individual efficiencies of the airports and to evaluate the consistency of the most efficient airports not only across time, but supported by the application of the two stated methodological approaches. Managerial and policymakers’ recommendations are drawn to improve the overall efficiency of the Spanish airport system. All the papers have been presented in international conferences relevant in the airport and aviation industry and also in methodological conferences. With the exception of the fifth paper (ongoing work), all the papers have been sent to refereed journals (peer review) cited at the Journal Citation Reports (JCR) and they are currently under review. Some extractions have been published as case studies and dissemination articles (The Public Sphere Journal of Public Policy, February 2017; Inside O.R., March 2018) The first paper uses Data Envelopment Analysis (DEA) combined with Multidimensional Scaling (MDS). The analysis is a cross-sectional study in 2013. One of the main issues of DEA is the inputs and outputs to be chosen. It is essential to critically assess the relevance of the variables to estimate the efficiency scores that could be potentially biased. The consideration of this combined methodology is that the efficiency scores are a consequence of the inputs and outputs chosen. This methodology helps disregard irrelevant combination of inputs and outputs. Additionally, it draws insights into the structural characteristic of the decision making units not captured by the conventional DEA potentially affecting the efficiency. The second paper is based on the same previous methodology, but for panel data within a five- year period of time (2009-2013). The aim is to confirm the previous findings (first research paper) and the robustness of the efficiency frontier and internal structural characteristics of the airports. This paper also analyses the relevance of the different years of the study according to the several dimensions identified. The third paper is based on centralised DEA in order to address the strong degree of centralised management applied by AENA. The conventional DEA models assume that changes in inputs and outputs to become more efficient are feasible. Nevertheless, the Spanish airports’ managers do not have decision power, but AENA. Considering that all the airports are managed as a whole, this model addresses a potential reallocation of resources from one airport to another one with the aim of increasing the overall traffic for the system. Centralised DEA has been applied in the finance and banking sectors, but not in the airport industry with one paper in human resources reallocation. In this study, a non-oriented and non-radial approach is used (Slack-Based Inefficiency) to identify the individual pathway for each airport and for each input and output, rather than an overall radial reduction of inputs or an overall increment of outputs. The fourth paper applies Stochastic Frontier Analysis (SFA) with the inclusion of fixed effects in the production function for a five-year period (panel data, 2009-2013). To control the special features of the decision-making units is essential to avoid model misspecifications. In a second step regression, the geographical location of the airports is intrinsically considered by analysing areas identified as touristic versus non-touristic and several touristic variables as potential drivers of airports’ efficiency. Finally, the fifth paper also applies SFA with the consideration of environmental variables in the inefficiency term (panel data, 2009-2013). A post-analysis of the number of airports within an amenity distance (catchment areas) is performed and closure recommendations are drawn regarding the most inefficient airports with a minimum impact on connectivity. Keywords: Data Envelopment Analysis (DEA); Stochastic Frontier Analysis (SFA); Centralised DEA; Multidimensional Scaling (MDS); Visualisation; Slack-Based Inefficiency (SBI); Technical Efficiency; Benchmarking; Dynamism; Centralised management; Environmental Variables; Fixed Effects; Catchment Areas; Spanish airport system; AENA JEL Codes: H54 Infrastructures; C33 Panel data models; C38 Classification methods; C61 Optimization Techniques Dynamic Analysis Table of Contents Acknowledgments ................................................................................................................................... i Acronyms ............................................................................................................................................... ii 1. Chapter one: Introduction ........................................................................................................... 17 1.1. Literature Review ............................................................................................................. 23 1.1.1. Methodology ........................................................................................................ 23 1.1.2. The Airport Industry ............................................................................................. 26 1.2. Regulatory Framework ..................................................................................................... 32 1.3. Data Description ............................................................................................................... 37 1.4. Results and Discussion ...................................................................................................... 42 2. Chapter two: Spanish airports: a Visual Study of Management Efficiency ................................. 55 List of Tables ..................................................................................................................................... 57 List of Figures ..................................................................................................................................
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