Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14622
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSHEN, Yongjun-
dc.contributor.authorHERMANS, Elke-
dc.contributor.authorBRIJS, Tom-
dc.contributor.authorWETS, Geert-
dc.contributor.authorVANHOOF, Koen-
dc.date.accessioned2013-03-05T09:21:55Z-
dc.date.available2013-03-05T09:21:55Z-
dc.date.issued2013-
dc.identifier.citationWang, Wuhong; Wets, Geert (Ed.). Computational Intelligence for Traffic and Mobility, p. 223-242-
dc.identifier.isbn978-94-91216-79-4-
dc.identifier.issn1875-7650-
dc.identifier.urihttp://hdl.handle.net/1942/14622-
dc.description.abstractRoad transport is vital to the economic development, trade and social integration. However, it is also responsible for the majority of negative impacts on environment and society. To achieve sustainable development, there is a growing need for a country to assess its undesirable costs so as to determine its road transport policy. In this study, total energy consumption, greenhouse gase missions, as well as safety issues in European road transport are selected representing the level of sustainable development in each member state of the European Union (EU). With data from the period of 1995-2007, the extent to which the 27 EU countries have improved their 'productivity' on sustainable road transport is evaluated based on data envelopment analysis (DEA) and the Malmquist productivity index. In particular, an adjusted DEA-based Malmquist productivity index is proposed to measure the changes in the undesirable impacts over time, which further decomposes into two components: the change in efficiency and the technical change. The results show a considerable progress towards sustainable road transport in Europe during this period. However, the development indifferent countries were unbalanced. Some of them were even deteriorating. For those underperforming countries, specific benchmarks are indicated based on the model results, and challenging targets are assigned by learning from their benchmarks. Moreover, the decomposition into the two components further reveals that the bulk of the improvement was attained through the adoption of productivity-enhancing new technologies throughout the road transport sector, rather than through the relatively inefficient countries catching up with those efficient ones. In addition, the growth in both two aspects slowed down in 2007, which implies that the momentum of further improvement is in danger of being lost so that new impetus is needed.-
dc.language.isoen-
dc.publisherAtlantis Press-
dc.titleInvestigating the Progress towards Sustainable Road Transport in Europe: Lessons Learned from a DEA-based Malmquist Productivity Index-
dc.typeBook Section-
local.bibliographicCitation.authorsWang, Wuhong-
local.bibliographicCitation.authorsWets, Geert-
dc.identifier.epage242-
dc.identifier.spage223-
local.bibliographicCitation.jcatB2-
local.type.refereedRefereed-
local.type.specifiedBook Section-
local.relation.ispartofseriesnr8-
local.identifier.vabbc:vabb:343951-
dc.identifier.doi10.2991/978-94-91216-80-0_12-
dc.identifier.urlhttp://link.springer.com/chapter/10.2991%2F978-94-91216-80-0_12-
local.bibliographicCitation.btitleComputational Intelligence for Traffic and Mobility-
item.fulltextWith Fulltext-
item.accessRightsRestricted Access-
item.contributorBRIJS, Tom-
item.contributorWETS, Geert-
item.contributorSHEN, Yongjun-
item.contributorHERMANS, Elke-
item.contributorVANHOOF, Koen-
item.fullcitationSHEN, Yongjun; HERMANS, Elke; BRIJS, Tom; WETS, Geert & VANHOOF, Koen (2013) Investigating the Progress towards Sustainable Road Transport in Europe: Lessons Learned from a DEA-based Malmquist Productivity Index. In: Wang, Wuhong; Wets, Geert (Ed.). Computational Intelligence for Traffic and Mobility, p. 223-242.-
item.validationvabb 2015-
Appears in Collections:Research publications
Files in This Item:
File Description SizeFormat 
book chapter-shen.pdf
  Restricted Access
321.19 kBAdobe PDFView/Open    Request a copy
Show simple item record

Page view(s)

62
checked on Jul 3, 2022

Download(s)

48
checked on Jul 3, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.