Competition and efficiency in the Italian airport system: new insights from a conditional nonparametric frontier analysis

D’Alfonso, Tiziana; Daraio, Cinzia; Nastasi, Alberto

doi:10.1016/j.tre.2015.05.003

Cited by 36 publications

(8 citation statements)

References 65 publications

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“…Hence contributions can be divided not only between nonparametric and parametric but also between those studying technical https://doi.org/10.1016/j.jairtraman.2018.04.009 efficiency and those focusing on cost efficiency. Some studies investigate the impact on airport performance of variables such as airport competition, effects of LCC on airport operations and government corruption (whether corruption influences airports' decision-making) (Choo and Oum, 2013;D'Alfonso et al, 2015;Martini et al, 2013b;Yan and Oum, 2014).…”

Section: Introductionmentioning

confidence: 99%

Global decision support for airport performance and efficiency assessment

Baltazar

Rosa

Silva

2018

Journal of Air Transport Management

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Airport benchmarking depends on airport performance and efficiency indicators, and it is an important issue for business, operational management, regulatory agencies, airlines and passengers. Using the MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) approach, a hierarchical additive value model is constructed with criteria weights and value scales derived from expert's judgments (obtained by an online survey) and by comparison of different reference levels and profiles of performance. This model measures airport performance and efficiency and also peer benchmarks it within a set of direct competitors or selfbenchmarks itself during a specified period. GDS (Global Decision Support) model outputs, integrated into a management system, allows the identification of deficiencies requiring urgent intervention and corrective measures for its continuous improvement.

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Section: Introductionmentioning

confidence: 99%

Global decision support for airport performance and efficiency assessment

Baltazar

Rosa

Silva

2018

Journal of Air Transport Management

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“…Input-oriented models are based on the minimization of inputs, assuming the same level of outputs, whereas output-oriented models are based on the maximization of outputs by assuming the same level of inputs. e use of DEA models to calculate efficiency in airports is very common in the literature, as can be observed in Gillen and Lall [34], Fernandes and Pacheco [35], and D'alfonso et al [36]. However, according to Lo Storto [37], the airport operational efficiency is critically affected by the interaction of several activities and processes.…”

Section: Data Envelopment Analysis (Dea)mentioning

confidence: 99%

Infrastructure and Flight Consolidation Efficiency of Public and Private Brazilian International Airports: A Two-Stage DEA and Malmquist Index Approach

Pacagnella

Hollaender

Mazzanati

et al. 2020

Journal of Advanced Transportation

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Air transportation is a paramount element within the transport infrastructure of any country. In recent years, several factors have led to an increased demand in the civil aviation industry in Brazil, putting pressure on the country’s airport infrastructure, which by itself justifies industry-related efficiency studies. Although the airport efficiency analysis is widely discussed in the literature, studies aiming to compare public and private Brazilian international airports are still scarce. The main objective of this study is to comparatively analyze the efficiency of public and private Brazilian international airports. To do so, efficiency was studied under two mathematical approaches: the two-stage DEA model and the Malmquist Index. Subsequent statistical analyses show a significant difference in efficiency between government-managed airports and those under concession to the private sector.

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“…As for inputs, the most frequently used variables found in the literature are terminal area, apron area, number of runways, total runway length, number of employees, number of gates, and number of aircraft parking spaces (Gillen, Lall 1997;Wanke 2012;Lozano et al 2013;Merkert, Mangia 2014;D' Alfonso et al 2015;Chen et al 2017). Barros and Weber (2009) also use capital cost, labour cost and airport operating cost as inputs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Barros and Weber (2009) also use capital cost, labour cost and airport operating cost as inputs. Other input indicators have been considered such as number of baggage collection belts (Lozano et al 2013), number of check-in counters (D' Alfonso et al 2015). Specially, Yoshida and Fujimoto (2004) adopt time access cost as the input to study Japanese airport efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In respect to outputs, the most used indicators for airport outputs are the number of aircraft movements, the number of passengers, and the amount of cargo (Curi et al 2011;Gitto, Mancuso 2012;Lozano et al 2013;Merkert, Mangia 2014;D' Alfonso et al 2015;Örkcü et al 2016;Wanke, Barros 2017). Others have suggested aeronautical revenues, and non-aeronautical revenues as outputs (Adler, Liebert 2014;Lai et al 2015;Liu 2017;Fernandes, Pacheco 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

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Analysing Airport Efficiency in East China Using a Three-Stage Data Envelopment Analysis

et al. 2020

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This paper evaluates the Technical Efficiencies (TEs) of a group of airports in East China by applying a three-stage Data Envelopment Analysis (DEA) method. The merit of this method allows us to consider the impact of the environmental factors on measuring airport efficiencies. Three variables, i.e. per capita Gross Domestic Product (GDP), the proportion of the tertiary industry, and the number of tourists, are used to represent the environmental factors. The results show that the environmental factors have airport-specific impacts on the value of the efficiencies. Additionally, airport TE are dominated by both Pure Technical Efficiency (PTE) and Scale Efficiency (SE). Based on empirical results, airport specific strategies can be provided to enhance airport efficiency, such as taking the effects of environmental variables and the statistical noise into consideration when analysing the airport efficiency, improving airport efficiencies according to their own conditions and improving the PTE or SE according to their categorizations.

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Competition and efficiency in the Italian airport system: new insights from a conditional nonparametric frontier analysis

Cited by 36 publications

References 65 publications

Global decision support for airport performance and efficiency assessment

Global decision support for airport performance and efficiency assessment

Infrastructure and Flight Consolidation Efficiency of Public and Private Brazilian International Airports: A Two-Stage DEA and Malmquist Index Approach

Analysing Airport Efficiency in East China Using a Three-Stage Data Envelopment Analysis

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