Network DEA approach to airports performance assessment considering undesirable outputs

Lozano, Sebastián; Gutiérrez, Ester; Moreno, Plácido

doi:10.1016/j.apm.2012.04.041

Cited by 189 publications

(112 citation statements)

References 32 publications

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“…Hence, Liu et al extended the radial measurement to a network radial analysis model [26]. Lozano et al [27] extended the DDF method to a network direction distance function (NDDF). Tone and Tsutsui put forward a network SBM model [28], and Fukuyama and Weber extended the SBI method to a network SBI [24].…”

Section: Undesirable Output In Deamentioning

confidence: 99%

Sustainability Evaluation of Railways in China Using a Two-Stage Network DEA Model with Undesirable Outputs and Shared Resources

Zhou

Han-hui

2017

Sustainability

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This paper constructs an additive two-stage network DEA (data envelopment analysis) model with consideration of undesirable outputs and shared inputs. Following the triple bottom line standard of sustainability, we calculate both the overall and sub-stage sustainability performance of railway transportation in China from 2002 to 2013, from the aspects of economy, environment and society. The results show that the overall sustainability of China's railway presents a character of first declining, then rising and declining again. Moreover, the railway sustainability of China's eastern areas are much better than that of the western and central areas, and the gap has become much larger since 2009. As for the sub-stage efficiency, neither the production stage nor the service stage of the railway is efficient in sustainability, and the efficiency of the production stage is lower than that of service stage and plays a greater impact on the overall sustainability. Therefore, in order to improve the overall sustainability of China's railways, it is essential to improve the level of railway engineering construction and develop technological innovations in railway production.

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Section: Undesirable Output In Deamentioning

confidence: 99%

Sustainability Evaluation of Railways in China Using a Two-Stage Network DEA Model with Undesirable Outputs and Shared Resources

Zhou

Han-hui

2017

Sustainability

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“…In this section, we exemplify our proposed method by analyzing and benchmarking the airport operations which can be observed as a two-process structure including "Aircraft Movement" and "Aircraft Loading" as the first and second processes, respectively Lall, 1997, 2001;Lozano et al, 2013). The first process uses three inputs; total runway area (I1S1), apron capacity In comparison with the structure proposed by Lozano et al (2013), we discard the number of delayed flights as an undesirable output of the first process since it is highly correlated with the accumulated flight delays.…”

Section: Applicationmentioning

confidence: 99%

“…In this research, we model the undesirable output of the first process (i.e., accumulated flight delays) as an input of this process. The dataset for 39 Spanish airports taken from Lozano et al (2013) is presented in Table 1. To highlight the importance of inescapable uncertainty in the performance analysis, particularly in airport operations, in this section, we extend the dataset reported in Table 1 into an uncertain data setting.…”

Section: -------Insert Figure 1 Here-------mentioning

confidence: 99%

“…The first process uses three inputs; total runway area (I1S1), apron capacity In comparison with the structure proposed by Lozano et al (2013), we discard the number of delayed flights as an undesirable output of the first process since it is highly correlated with the accumulated flight delays. The structural pattern is depicted in Figure 1.…”

Section: Applicationmentioning

confidence: 99%

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Benchmarking with network dea in a fuzzy environment

Hatami-Marbini

2019

RAIRO-Oper. Res.

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Abstract:Benchmarking is a powerful and thriving tool to enhance the performance and profitabilities of organizations in business engineering. Though performance benchmarking has practically and theoretically developed in distinct fields such as banking, education, health and so on, supply chain benchmarking across multiple echelons that includes certain characteristics such as intermediate measure differs from other fields. In spite of incremental benchmarking activities in practice, there is the dearth of a unified and effective guideline for benchmarking in organizations. Amongst the benchmarking tools, data envelopment analysis (DEA) as a non-parametric technique has been widely used to measure the relative efficiency of firms. However, the conventional DEA models that are bearing out precise input and output data turn out to be incapable of dealing with uncertainty, particularly when the gathered data encompasses natural language expressions and human judgements. In this paper, we present an imprecise network benchmarking for the purpose of reflecting the human judgments with the fuzzy values rather than precise numbers. In doing so, we propose the fuzzy network DEA models to compute the overall system scale and technical efficiency of those organizations whose internal structure is known. A classification scheme is presented based upon their fuzzy efficiencies with the aim of classifying the organizations. We finally provide a case study of the airport and travel sector to elucidate the details of the proposed method in this study. All additions and changes to the original manuscript are highlighted in this revision. AbstractBenchmarking is a powerful and thriving tool to enhance the performance and profitabilities of organizations in business engineering. Though performance benchmarking has practically and theoretically developed in distinct fields such as banking, education, health and so on, supply chain benchmarking across multiple echelons that includes certain characteristics such as intermediate measure differs from other fields. In spite of incremental benchmarking activities in practice, there is the dearth of a unified and effective guideline for benchmarking in organizations. Amongst the benchmarking tools, data envelopment analysis (DEA) as a non-parametric technique has been widely used to measure the relative efficiency of firms. However, the conventional DEA models that are bearing out precise input and output data turn out to be incapable of dealing with uncertainty, particularly when the gathered data encompasses natural language expressions and human judgements. In this paper, we present an imprecise network benchmarking for the purpose of reflecting the human judgments with the fuzzy values rather than precise numbers. In doing so, we propose the fuzzy network DEA models to compute the overall system scale and technical efficiency of those organizations whose internal structure is known. A classification scheme is presented based upon their fuzzy efficiencies with the aim of classifying ...

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“…It can be also extended to hybrid models by combining it with other Sustainability 2018, 10, 2852 3 of 16 decision-making methods, such as analytic hierarchy process (AHP), stochastic programming, goal programming, and neural networks. Thus, the network DEA model is used in the banking, aviation, transport, manufacturing, and sports industries; furthermore, the scope of its application continues to gradually expand [20].…”

Section: Literature Reviewmentioning

confidence: 99%

Supply Chain Efficiency Measurement to Maintain Sustainable Performance in the Automobile Industry

Kim

2018

Sustainability

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Abstract:The automobile industry is set to undergo a structural transformation in the progress toward next-generation industries that involve autonomous vehicles and connected cars. Thus, supply chain management has become increasingly important for corporate competitiveness. This study aims to identify opportunities for improving supply chain performance by quantifying the impact of suppliers on the supply chain. An analysis was conducted in two phases. First, the efficiency of 139 partners that supply automobile components to the Hyundai Motor Company was measured using the Charnes-Cooper-Rhodes model, while the efficiency of Hyundai Motor Company's 540 supply chains comprising partners, subsidiaries, and parent companies was measured using the network epsilon-based measure model. Second, the relationship between the partner efficiency and the supply chain efficiency was analyzed using the Mann-Whitney U test and the Tobit regression model. The results showed that efficient operation of partners hampers the efficiency of the total supply chain. Thus, there may be several partners that are not committed to quality improvement, while the Hyundai Motor Company seeks to promote quality management through win-win cooperation with partners. Consequently, automakers must review their partner management system, including their performance measurement and incentive systems.

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Network DEA approach to airports performance assessment considering undesirable outputs

Cited by 189 publications

References 32 publications

Sustainability Evaluation of Railways in China Using a Two-Stage Network DEA Model with Undesirable Outputs and Shared Resources

Sustainability Evaluation of Railways in China Using a Two-Stage Network DEA Model with Undesirable Outputs and Shared Resources

Benchmarking with network dea in a fuzzy environment

Supply Chain Efficiency Measurement to Maintain Sustainable Performance in the Automobile Industry

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