A comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of Sweden
This study analyses the trends in energy use and CO2 emissions in the manufacturing industry and service sector. Using data at the two-digit aggregation level for the Swedish manufacturing and service industries, this empirical study intends to examine energy use, energy efficiency and CO 2 emission...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2013
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/24332
- Acceso en línea:
- https://doi.org/10.1504/IJADS.2013.053275
https://repository.urosario.edu.co/handle/10336/24332
- Palabra clave:
- Dea
Manufacturing industries
Panel data models
Service sectors
Sweden
Data envelopment analysis
Energy efficiency
Investments
Manufacture
Taxation
Telecommunication industry
Carbon dioxide
Data envelopment analysis
Dea
Energy efficiency
Manufacturing industry
Panel data model
Service sector
Sweden
- Rights
- License
- Abierto (Texto Completo)
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11b149ec-e823-4984-9f05-b74f619e4a75-12020-05-26T00:11:47Z2020-05-26T00:11:47Z2013This study analyses the trends in energy use and CO2 emissions in the manufacturing industry and service sector. Using data at the two-digit aggregation level for the Swedish manufacturing and service industries, this empirical study intends to examine energy use, energy efficiency and CO 2 emissions using data envelopment analysis (DEA) and panel data techniques. DEA is applied to assess energy efficiency within a production framework. Panel data techniques are used to determine which variables influence energy efficiency. The results from the DEA reveal significant variations in energy efficiency across the manufacturing and service industries. The results for these sectors also indicate that technical efficiency and energy efficiency have increased while CO2 emissions have decreased, especially in recent years. The results of the panel data techniques demonstrate that increased energy taxes, electricity consumption, investments and labour productivity generate higher energy efficiency, while higher fossil fuel consumption leads to lower energy efficiency. All of the findings of this study are important for developing effective energy policies that encourage better energy use and management in the industrial sector. Copyright © 2013 Inderscience Enterprises Ltd.application/pdfhttps://doi.org/10.1504/IJADS.2013.0532751755808517558077https://repository.urosario.edu.co/handle/10336/24332eng116No. 297International Journal of Applied Decision SciencesVol. 6International Journal of Applied Decision Sciences, ISSN:17558085, 17558077, Vol.6, No.2 (2013); pp. 97-116https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885090474&doi=10.1504%2fIJADS.2013.053275&partnerID=40&md5=a5a2849dc37fb4bc4e09fa842658e8d2Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURDeaManufacturing industriesPanel data modelsService sectorsSwedenData envelopment analysisEnergy efficiencyInvestmentsManufactureTaxationTelecommunication industryCarbon dioxideData envelopment analysisDeaEnergy efficiencyManufacturing industryPanel data modelService sectorSwedenA comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of SwedenarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Martínez C.I.P.10336/24332oai:repository.urosario.edu.co:10336/243322022-05-02 07:37:14.883596https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
A comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of Sweden |
title |
A comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of Sweden |
spellingShingle |
A comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of Sweden Dea Manufacturing industries Panel data models Service sectors Sweden Data envelopment analysis Energy efficiency Investments Manufacture Taxation Telecommunication industry Carbon dioxide Data envelopment analysis Dea Energy efficiency Manufacturing industry Panel data model Service sector Sweden |
title_short |
A comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of Sweden |
title_full |
A comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of Sweden |
title_fullStr |
A comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of Sweden |
title_full_unstemmed |
A comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of Sweden |
title_sort |
A comparative analysis of energy use and CO2 emissions in the manufacturing and service industries of Sweden |
dc.subject.keyword.spa.fl_str_mv |
Dea Manufacturing industries Panel data models Service sectors Sweden Data envelopment analysis Energy efficiency Investments Manufacture Taxation Telecommunication industry Carbon dioxide Data envelopment analysis Dea Energy efficiency Manufacturing industry Panel data model Service sector Sweden |
topic |
Dea Manufacturing industries Panel data models Service sectors Sweden Data envelopment analysis Energy efficiency Investments Manufacture Taxation Telecommunication industry Carbon dioxide Data envelopment analysis Dea Energy efficiency Manufacturing industry Panel data model Service sector Sweden |
description |
This study analyses the trends in energy use and CO2 emissions in the manufacturing industry and service sector. Using data at the two-digit aggregation level for the Swedish manufacturing and service industries, this empirical study intends to examine energy use, energy efficiency and CO 2 emissions using data envelopment analysis (DEA) and panel data techniques. DEA is applied to assess energy efficiency within a production framework. Panel data techniques are used to determine which variables influence energy efficiency. The results from the DEA reveal significant variations in energy efficiency across the manufacturing and service industries. The results for these sectors also indicate that technical efficiency and energy efficiency have increased while CO2 emissions have decreased, especially in recent years. The results of the panel data techniques demonstrate that increased energy taxes, electricity consumption, investments and labour productivity generate higher energy efficiency, while higher fossil fuel consumption leads to lower energy efficiency. All of the findings of this study are important for developing effective energy policies that encourage better energy use and management in the industrial sector. Copyright © 2013 Inderscience Enterprises Ltd. |
publishDate |
2013 |
dc.date.created.spa.fl_str_mv |
2013 |
dc.date.accessioned.none.fl_str_mv |
2020-05-26T00:11:47Z |
dc.date.available.none.fl_str_mv |
2020-05-26T00:11:47Z |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1504/IJADS.2013.053275 |
dc.identifier.issn.none.fl_str_mv |
17558085 17558077 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/24332 |
url |
https://doi.org/10.1504/IJADS.2013.053275 https://repository.urosario.edu.co/handle/10336/24332 |
identifier_str_mv |
17558085 17558077 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationEndPage.none.fl_str_mv |
116 |
dc.relation.citationIssue.none.fl_str_mv |
No. 2 |
dc.relation.citationStartPage.none.fl_str_mv |
97 |
dc.relation.citationTitle.none.fl_str_mv |
International Journal of Applied Decision Sciences |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 6 |
dc.relation.ispartof.spa.fl_str_mv |
International Journal of Applied Decision Sciences, ISSN:17558085, 17558077, Vol.6, No.2 (2013); pp. 97-116 |
dc.relation.uri.spa.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885090474&doi=10.1504%2fIJADS.2013.053275&partnerID=40&md5=a5a2849dc37fb4bc4e09fa842658e8d2 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.acceso.spa.fl_str_mv |
Abierto (Texto Completo) |
rights_invalid_str_mv |
Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
institution |
Universidad del Rosario |
dc.source.instname.spa.fl_str_mv |
instname:Universidad del Rosario |
dc.source.reponame.spa.fl_str_mv |
reponame:Repositorio Institucional EdocUR |
repository.name.fl_str_mv |
Repositorio institucional EdocUR |
repository.mail.fl_str_mv |
edocur@urosario.edu.co |
_version_ |
1814167690474946560 |