The use of a national macro-environmental framework in selecting the appropriate airport ownership and management model. - Chaouk, Mohammed H. (Cranfield University, 2019)
The continuous increase in air traffic has placed pressure on governments to develop their airports in order to accommodate increasing demand. As a result, governments are opting to implement different airport ownership and management models, especially privatization, to finance the development of projects, improve operational and financial efficiency, and to enhance the quality of service of their airports. However, it has been observed that this trend towards airport privatization, especially in developing countries, has to a large extent been guided by international consultants who seldom appreciate local political, cultural and economic contexts within which airports are managed. Consequently, there have been many examples of privatization transactions, not achieving the required and expected outcomes. Therefore, this study proposes a framework to identify the airport ownership and management model that best suits the local circumstances of a country. The framework is based on five national macro-environmental factors that are found to be significantly influencing the efficiency of airports. These national macro-environmental factors are identified by first measuring the efficiency of a sample of international airports using Data Envelopment Analysis (DEA), and secondly by conducting a truncated regression coupled with Simar and Wilson bootstrapping technique to test the significance of a set of national macro-environment factors on airport efficiency. The identification of these factors fills in the gap in the literature that is related to the relationship between the airport performance and non-discretionary variables. Finally, the proposed framework helps policymakers to identify which ownership and management model is most appropriate given prevailing national macro-environmental conditions.
Keywords: Airport efficiency; privatisation; framework development; DEA; second-stage regression; ownership and management models