Understanding DEA Efficiency Results in Energy Technologies: The Role of Non-Discretionary Inputs and Undesirable Outputs.
Saved in:
| Title: | Understanding DEA Efficiency Results in Energy Technologies: The Role of Non-Discretionary Inputs and Undesirable Outputs. |
|---|---|
| Authors: | Kapłan, Radosław1 (AUTHOR) |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 10, p2417. 17p. |
| Subject Terms: | *Data envelopment analysis, *Coal gasification, *Mathematical variables, *Energy consumption, *Waste products |
| Abstract: | Data Envelopment Analysis (DEA) is widely applied to evaluate technological efficiency in the energy sector, yet its results are often difficult to interpret, particularly when extended model specifications are used. This study investigates how alternative treatments of environmental conditions and undesirable outputs influence efficiency measurement in energy technologies. Four DEA specifications are compared: the classical CCR model, a model incorporating non-discretionary inputs (CCR-ND), a model including undesirable outputs (CCR-B), and a combined specification (CCR-ND-B). The empirical analysis is based on data describing coal gasification technologies and is supplemented with controlled hypothetical cases designed to isolate the effects of environmental parameters. The results show that incorporating non-discretionary inputs and undesirable outputs does not necessarily reduce efficiency scores but reshapes the geometry of the production possibility set and modifies the structure of benchmark technologies. The findings highlight the importance of careful classification of inputs and outputs and emphasize that DEA results should be interpreted in relation to the underlying modeling assumptions. Comparing alternative model specifications improves transparency and helps avoid treating DEA as a "black box", supporting more informed efficiency assessment in energy technology analysis. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: enr DbLabel: Energy & Power Source An: 194141532 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Understanding DEA Efficiency Results in Energy Technologies: The Role of Non-Discretionary Inputs and Undesirable Outputs. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kapłan%2C+Radosław%22">Kapłan, Radosław</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 10, p2417. 17p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Data+envelopment+analysis%22">Data envelopment analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22Coal+gasification%22">Coal gasification</searchLink><br />*<searchLink fieldCode="DE" term="%22Mathematical+variables%22">Mathematical variables</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br />*<searchLink fieldCode="DE" term="%22Waste+products%22">Waste products</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Data Envelopment Analysis (DEA) is widely applied to evaluate technological efficiency in the energy sector, yet its results are often difficult to interpret, particularly when extended model specifications are used. This study investigates how alternative treatments of environmental conditions and undesirable outputs influence efficiency measurement in energy technologies. Four DEA specifications are compared: the classical CCR model, a model incorporating non-discretionary inputs (CCR-ND), a model including undesirable outputs (CCR-B), and a combined specification (CCR-ND-B). The empirical analysis is based on data describing coal gasification technologies and is supplemented with controlled hypothetical cases designed to isolate the effects of environmental parameters. The results show that incorporating non-discretionary inputs and undesirable outputs does not necessarily reduce efficiency scores but reshapes the geometry of the production possibility set and modifies the structure of benchmark technologies. The findings highlight the importance of careful classification of inputs and outputs and emphasize that DEA results should be interpreted in relation to the underlying modeling assumptions. Comparing alternative model specifications improves transparency and helps avoid treating DEA as a "black box", supporting more informed efficiency assessment in energy technology analysis. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=194141532 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/en19102417 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 2417 Subjects: – SubjectFull: Data envelopment analysis Type: general – SubjectFull: Coal gasification Type: general – SubjectFull: Mathematical variables Type: general – SubjectFull: Energy consumption Type: general – SubjectFull: Waste products Type: general Titles: – TitleFull: Understanding DEA Efficiency Results in Energy Technologies: The Role of Non-Discretionary Inputs and Undesirable Outputs. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kapłan, Radosław IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 19 – Type: issue Value: 10 Titles: – TitleFull: Energies (19961073) Type: main |
| ResultId | 1 |
