Incentive and Supervision Mechanism for Operation and Maintenance of Mega Railway Infrastructure Based on Principal-Agent Theory.
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| Title: | Incentive and Supervision Mechanism for Operation and Maintenance of Mega Railway Infrastructure Based on Principal-Agent Theory. |
|---|---|
| Authors: | Liu, Kai1 (AUTHOR) kailiuyy@bjtu.edu.cn, Kou, Yuanyuan2 (AUTHOR), Liu, Yuming1 (AUTHOR), Yang, Xiaoxu1 (AUTHOR) |
| Source: | Engineering Management Journal. 2025, Vol. 37 Issue 2, p183-194. 12p. |
| Subjects: | Infrastructure (Economics), Incentive (Psychology), Expected utility, Government corporations, Railroad design & construction |
| Abstract: | This study incorporates fairness preference theory into the principal-agent model to address the challenges arising from information asymmetry between the government and railway infrastructure operation and maintenance (O&M) companies. It develops an incentive and supervision model for the management of mega railway infrastructure operations and maintenance, considering two perspectives: full rationality and fairness preference. The models are compared and analyzed, exploring the costs of government supervision and the changes in expected benefits when equity preference is taken into account. The conclusions are supported by numerical examples and visual analysis, illustrating the impact of different variable parameters on the behavioral strategies of the government and O&M companies. The findings demonstrate that a well-designed incentive and supervision mechanism can effectively regulate the behavior of railway infrastructure O&M companies. The effort level of O&M companies is positively correlated with the intensity of government incentives and supervision. Moreover, from the perspective of fairness preference, transferring some financial benefits from the government to O&M companies not only increases their extra effort but also reduces government's supervision costs, while the government's expected utility gain depends on the strength of "reciprocity" exhibited by O&M companies. [ABSTRACT FROM AUTHOR] |
| Copyright of Engineering Management Journal is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 184490851 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Incentive and Supervision Mechanism for Operation and Maintenance of Mega Railway Infrastructure Based on Principal-Agent Theory. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Liu%2C+Kai%22">Liu, Kai</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> kailiuyy@bjtu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Kou%2C+Yuanyuan%22">Kou, Yuanyuan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Yuming%22">Liu, Yuming</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yang%2C+Xiaoxu%22">Yang, Xiaoxu</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Engineering+Management+Journal%22">Engineering Management Journal</searchLink>. 2025, Vol. 37 Issue 2, p183-194. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Infrastructure+%28Economics%29%22">Infrastructure (Economics)</searchLink><br /><searchLink fieldCode="DE" term="%22Incentive+%28Psychology%29%22">Incentive (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Expected+utility%22">Expected utility</searchLink><br /><searchLink fieldCode="DE" term="%22Government+corporations%22">Government corporations</searchLink><br /><searchLink fieldCode="DE" term="%22Railroad+design+%26+construction%22">Railroad design & construction</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study incorporates fairness preference theory into the principal-agent model to address the challenges arising from information asymmetry between the government and railway infrastructure operation and maintenance (O&M) companies. It develops an incentive and supervision model for the management of mega railway infrastructure operations and maintenance, considering two perspectives: full rationality and fairness preference. The models are compared and analyzed, exploring the costs of government supervision and the changes in expected benefits when equity preference is taken into account. The conclusions are supported by numerical examples and visual analysis, illustrating the impact of different variable parameters on the behavioral strategies of the government and O&M companies. The findings demonstrate that a well-designed incentive and supervision mechanism can effectively regulate the behavior of railway infrastructure O&M companies. The effort level of O&M companies is positively correlated with the intensity of government incentives and supervision. Moreover, from the perspective of fairness preference, transferring some financial benefits from the government to O&M companies not only increases their extra effort but also reduces government's supervision costs, while the government's expected utility gain depends on the strength of "reciprocity" exhibited by O&M companies. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Engineering Management Journal is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=184490851 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/10429247.2024.2388460 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 183 Subjects: – SubjectFull: Infrastructure (Economics) Type: general – SubjectFull: Incentive (Psychology) Type: general – SubjectFull: Expected utility Type: general – SubjectFull: Government corporations Type: general – SubjectFull: Railroad design & construction Type: general Titles: – TitleFull: Incentive and Supervision Mechanism for Operation and Maintenance of Mega Railway Infrastructure Based on Principal-Agent Theory. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liu, Kai – PersonEntity: Name: NameFull: Kou, Yuanyuan – PersonEntity: Name: NameFull: Liu, Yuming – PersonEntity: Name: NameFull: Yang, Xiaoxu IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10429247 Numbering: – Type: volume Value: 37 – Type: issue Value: 2 Titles: – TitleFull: Engineering Management Journal Type: main |
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