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Determinants of sustainability performance of manufacturing companies using two-stage data envelopment analysis

2025Artigo científico Acesso aberto
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datacite.subject.fosCiências Sociais::Economia e Gestão
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
dc.contributor.authorSutiene, Kristina
dc.contributor.authorVaz, Clara B.
dc.contributor.authorVaitiekuniene, Raminta
dc.contributor.authorVaz, Clara B.
dc.date.accessioned2026-02-13T12:08:57Z
dc.date.available2026-02-13T12:08:57Z
dc.date.issued2025
dc.description.abstractThe investigation of business performance via the lens of sustainability has become an increasingly attractive topic among scholars. This study contributes to the field by proposing a two-stage methodology. First, to assess companies’ efficiency in terms of sustainability, their scores of the environmental, social and governance (ESG) pillars are combined into the single weighted sustainability performance indicator using the ‘Benefit of the Doubt’ model, which is maximized for each company by comparing it against the best performers in terms of ESG scores based on Data Envelopment Analysis. Then, in the second stage, the significant determinants are identified after efficiency estimates are regressed on company performance indicators using Tobit panel regression. To demonstrate this approach, we selected 559 companies from the manufacturing sector, as this industry continues to face challenges to reduce environmental impact, improve resource efficiency, and promote social responsibility. The main findings include the examination of the best performers and underperforming companies in terms of sustainability, along with key financial indicators identified in the study.por
dc.description.sponsorshipThis research has received funding from the Research Council of Lithuania (LMTLT), agreement No. S-PD-22-23. This work was also supported by national funds through FCT/MCTES (PIDDAC): CeDRI, UIDB/05757/2020 (DOI: 10.54499/UIDB/05757/2020) and UIDP/05757/2020 (DOI: 10.54499/UIDP/05757/2020); and SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020).
dc.identifier.citationSutiene, Kristina; Vaz, Clara B.; Vaitiekuniene, Raminta ( 2025). Determinants of sustainability performance of manufacturing companies using two-stage data envelopment analysis. Environmental and Ecological Statistics. ISSN 1352-8505.32:2. p. 675-706
dc.identifier.doi10.1007/s10651-025-00659-5
dc.identifier.eissn1573-3009
dc.identifier.issn1352-8505
dc.identifier.urihttp://hdl.handle.net/10198/35742
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
dc.relation.ispartofEnvironmental and Ecological Statistics
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectESG
dc.subjectManufacturing companies
dc.subjectSustainability
dc.subjectTobit panel regression
dc.subjectTwo-stage DEA
dc.titleDeterminants of sustainability performance of manufacturing companies using two-stage data envelopment analysis
dc.typejournal article
dspace.entity.typePublication
oaire.awardNumberUIDB/05757/2020
oaire.awardNumberUIDP/05757/2020
oaire.awardNumberLA/P/0007/2020
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.citation.issue2
oaire.citation.titleEnvironmental and Ecological Statistics
oaire.citation.volume32
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameVaz
person.givenNameClara B.
person.identifierR-001-FQC
person.identifier.ciencia-id9611-3386-E516
person.identifier.orcid0000-0001-9862-6068
person.identifier.ridF-1519-2016
person.identifier.scopus-author-id56352045500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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relation.isAuthorOfPublication.latestForDiscovery34bc350c-28d9-4b06-9874-b2b0dba58d1d
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