کمبود ظرفیت و عوامل بهره وری در فرودگاه برزیل: شواهدی از برآوردهای تحلیل پوششی داده های راه اندازی شده
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|4595||2012||14 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Socio-Economic Planning Sciences, Volume 46, Issue 3, September 2012, Pages 216–229
This paper reports on the use of different approaches for assessing efficiency related-issues in 63 major Brazilian airports. Starting out with the bootstrapping technique presented in Simar and Wilson (1998, 2004), several DEA estimates were generated, allowing the use of confidence intervals and bias correction in central estimates to test for significant differences in efficiency levels, returns-to-scale, and input-decreasing/output-increasing potentials. The findings corroborate anecdotal and empirical evidence regarding a capacity shortfall within Brazilian airports, where infrastructure slack is virtually inexistent, regardless of the airport type and location
In the past few years, accelerated economic growth has increased the demands for airport services in Brazil. Between 2003 and 2008, the number of air passengers grew at an average rate of 10% per year  and, although the cargo tonnage remained relatively stable over the course of these years, value-added has increased significantly . This increasing air demand for reliable services has placed enormous pressure upon the Brazilian airport infrastructure. The situation is expected to get worse as the country will host the next Word Cup (2014) and Olympic Games (2016). Air transportation in Brazil was, until recently, regulated and controlled by the Departamento de Aviação Civil (Department of Civil Aviation or DAC) and investment in airport infrastructure was performed and operated by Infraero, a state owned company linked to the Brazilian government founded in 1973. Although a regulatory agency, Agência Nacional de Aviação Civil (National Agency for Civil Aviation or ANAC), was created specifically for the oversight of the civil aviation sector, taking over the responsibilities of the DAC , thus far, Infraero is still responsible for managing, renovating, building, and equipping Brazilian airports. Under pressure from anecdotal evidence suggesting a capacity shortfall in Brazilian airports  and , the Brazilian government initiated a sector deregulation/privatization process by the end of the first quarter of 2011. The first airport to be privatized, Natal, is a small one located in the Northeast region. This airport will serve as a testing pilot prior to large scale airport concession. The idea is to speed up capacity expansion projects in major airports (runways, gates, terminals, parking lots etc.) — by contracting them out to a private management authority under a long term lease to mitigate the risks of operational bottlenecks in 2014 and 2016 during the World Cup and the Olympic Games. Since time is short to handle adequately the future investments in infrastructure, an empirical investigation on factors affecting Brazilian airport returns-to-scale and slacks has become important. More precisely, it is desirable to provide benchmarks for improving the operations of airports that perform poorly, investigating which of hub/international/metropolitan area airports present superior performance. This paper presents a benchmark and efficiency analysis of 63 major Brazilian airports, administered by Infraero, based on cross sectional data for 2009, putting output-increase potentials and input slack – not only regarding the physical infrastructure, but also the available area for future capacity expansion – into perspective. A complementary approach is used for measuring the efficiency levels of major Brazilian airports and for characterizing their returns to scale condition: Data Envelopment Analysis (DEA) in its envelopment and multiplicative forms, respectively. Despite the increased use of DEA to measure the efficiency of airports over the last decade, there are still few studies that also exploit bootstrapping methodology to account for measurement errors in estimates within this particular transportation area , ,  and . Initially introduced by Simar and Wilson ,  and , bootstrapping allows sensitivity analyses on efficiency scores and slack, as well as on other scaling indicators, to be performed by repeatedly sampling from the original data. A sample distribution of these estimates is then obtained, from which confidence intervals may be derived . This paper uses the bootstrapping methodology to test, among other things, for the presence of scale inefficiency – input and output slack – and to determine the nature of returns to scale at the different Brazilian airports. Its contribution lies in an empirical application, inspired by the current debate in the Brazilian airport sector, in which anecdotal evidence suggests a capacity shortfall. Empirical results corroborate the evidence: the vast majority of major Brazilian airports are facing capacity constraints, regardless of their type (hub, international, or metropolitan) and their infrastructure level (whether infrastructure-intensive or not). More precisely, all Brazilian airports, with the exception of Galeão – an international, hub airport located in the Rio de Janeiro metropolitan area – are experiencing increasing returns-to-scale (IRS), and this is a key argument for upgrades. Furthermore, the vast majority of Brazilian airports are also managerially inefficient, i.e. with the exception of São Paulo’s Guarulhos and Congonhas airports – two of the five largest Brazilian airports – technical efficiency is low. All told, and including available area slack for future capacity expansion, these two elements suggest potential for accommodating future demand growth in the short (productivity gains) and long (increment of physical infrastructure) terms, respectively.
نتیجه گیری انگلیسی
Although there is strong worldwide evidence that airports owned/managed by governments are significantly less efficiency than airports with a private majority ownership, only very recently did the Brazilian government initiate a movement towards privatization and sector deregulation. The historical lack of pressure on Brazilian airports to be more competitive and productive, together with insufficient investments in infrastructure, led to operational bottlenecks and a capacity shortfall that may jeopardize passenger flows during the next World Cup (2014) and the Olympic Games (2016). The findings presented here corroborate previous studies ,  and  and anecdotal evidence with respect to the Brazilian case , ,  and . Not only do the vast majority of Brazilian airports present increasing returns-to-scale, but the output increasing-potentials are also severely constrained in the short term by low technical efficiency levels. Different from smaller countries (cf .), where in similar situations there may exist room for a policy of reallocation of traffic from severely congested airports to smaller ones, with lower occupancy rates, Brazil’s continental dimensions makes additional transportation costs and travel-times prohibitive. Our findings can serve as a resource for Brazilian airport authorities to administer the efficient future growth of passenger and cargo traffic when making use of currently available areas for capacity expansion. More precisely, it can aid in decision-making with respect to funding airport improvement projects and setting priorities, by means of establishing different policies for each airport cluster. The central idea is to identify short term (increase in efficiency levels) and long term actions (infrastructure expansion) to accommodate future demand growths. Another contribution of the paper lies in its demonstration of bootstrapping to evaluate, unambiguously, returns to scale and slack for each airport via confidence intervals and bias-corrected central estimates. Benchmarks for improving operations of Brazilian airports that perform poorly have also been provided, discussing the role of contextual variables – such as hub, international, regular flights, and location – on increased efficiency levels.