Michali, Maria, Emrouznejad, Ali, Dehnokhalaji, Akram and Clegg, Ben (2021). Noise-pollution efficiency analysis of European railways:A network DEA model. Transportation Research Part D: Transport and Environment, 98 ,
Abstract
One of the most important effects that railways have on the environment is noise pollution, notably in Europe. The purpose of this study is to evaluate the environmental efficiency of railways in 22 European countries, considering two factors; a country’s response in retrofitting their wagon fleet with more silent braking technology and the number of people affected by railway noise. The railway transport process efficiency is decomposed into assets and service efficiency. The additive decomposition network Data Envelopment Analysis (NDEA) approach is customised to account for intermediate and undesirable outputs. Results suggest that Estonia, Germany and Poland are overall environmentally efficient and that except for Finland, asset efficient countries are also service efficient; the inverse does not hold. Sensitivity analysis revealed that efficiency rankings are robust to alterations in the decomposition weight restrictions. This is the first study that uses DEA to incorporate the noise-pollution problem in railway efficiency measurement.
Publication DOI: | https://doi.org/10.1016/j.trd.2021.102980 |
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Divisions: | College of Business and Social Sciences > Aston Business School > Operations & Information Management College of Business and Social Sciences > Aston Business School |
Additional Information: | © 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Uncontrolled Keywords: | Network DEA,Undesirable output,Efficiency decomposition,Railways,Noise pollution |
Publication ISSN: | 1361-9209 |
Last Modified: | 13 Dec 2024 17:43 |
Date Deposited: | 10 Aug 2021 08:32 |
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Related URLs: |
https://linking ... 361920921002789
(Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2021-09-01 |
Published Online Date: | 2021-08-06 |
Accepted Date: | 2021-07-08 |
Authors: |
Michali, Maria
Emrouznejad, Ali ( 0000-0001-8094-4244) Dehnokhalaji, Akram ( 0000-0002-2751-0719) Clegg, Ben ( 0000-0001-7506-5237) |
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