Full transparency or restricted visibility? Mechanisms of blockchain enabled data sharing in supply chain.
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| Title: | Full transparency or restricted visibility? Mechanisms of blockchain enabled data sharing in supply chain. |
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| Authors: | He, Yu1 (AUTHOR), Jiang, Cuiqing1 (AUTHOR), Dong, Junfeng1 (AUTHOR) jfdong4@hfut.edu.cn, Ding, Yong1 (AUTHOR), Chen, Bo1 (AUTHOR) |
| Source: | International Journal of Production Research. Feb2026, Vol. 64 Issue 4, p1227-1248. 22p. |
| Subjects: | Blockchains, Supply chain management, Data encryption, Disclosure, Demand forecasting, Incentive (Psychology), Privacy, Information sharing |
| Abstract: | This study examines values and adoption conditions of Blockchain Technology (BCT) in horizontal demand forecast sharing among retailer, focusing on the influence mechanism of transparency-restriction approaches and BCT's endogenous effects on firms' sharing incentives. We model a supply chain with one manufacturer and multiple retailers, comparing four BCT-enabled data-sharing regimes: open access (permissionless) versus no-open access (permissioned), with or without encryption. Results show that restricted transparency, combined with selective accessibility, aligns individual and collective incentives by curbing wholesale price inflation and improving forecast accuracy. Contrary to intuition, higher transparency does not universally benefit retailers; supplementary encryption can balance data utility and privacy, enabling Pareto-superior outcomes. We further demonstrate BCT can reduces moral hazards in horizontal sharing (e.g. sharing biased forecast), allowing retailers to leverage aggregated demand signals without inefficiently verification. However, excessive transparency in BCT can accelerates retailers' profit erosion, akin to perfect competition. These findings offer micro-foundations for adopting visibility-restriction technologies (e.g. Zero-Knowledge Proofs) and guide the design of context-specific BCT systems. By reconciling transparency-privacy tensions and demonstrating BCT's endogenous role in forecasting, this study advances strategies for enhancing supply chain resilience through BCT innovation. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Production Research 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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| Items | – Name: Title Label: Title Group: Ti Data: Full transparency or restricted visibility? Mechanisms of blockchain enabled data sharing in supply chain. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22He%2C+Yu%22">He, Yu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiang%2C+Cuiqing%22">Jiang, Cuiqing</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dong%2C+Junfeng%22">Dong, Junfeng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jfdong4@hfut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Ding%2C+Yong%22">Ding, Yong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Bo%22">Chen, Bo</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Feb2026, Vol. 64 Issue 4, p1227-1248. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Blockchains%22">Blockchains</searchLink><br /><searchLink fieldCode="DE" term="%22Supply+chain+management%22">Supply chain management</searchLink><br /><searchLink fieldCode="DE" term="%22Data+encryption%22">Data encryption</searchLink><br /><searchLink fieldCode="DE" term="%22Disclosure%22">Disclosure</searchLink><br /><searchLink fieldCode="DE" term="%22Demand+forecasting%22">Demand forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Incentive+%28Psychology%29%22">Incentive (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Privacy%22">Privacy</searchLink><br /><searchLink fieldCode="DE" term="%22Information+sharing%22">Information sharing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study examines values and adoption conditions of Blockchain Technology (BCT) in horizontal demand forecast sharing among retailer, focusing on the influence mechanism of transparency-restriction approaches and BCT's endogenous effects on firms' sharing incentives. We model a supply chain with one manufacturer and multiple retailers, comparing four BCT-enabled data-sharing regimes: open access (permissionless) versus no-open access (permissioned), with or without encryption. Results show that restricted transparency, combined with selective accessibility, aligns individual and collective incentives by curbing wholesale price inflation and improving forecast accuracy. Contrary to intuition, higher transparency does not universally benefit retailers; supplementary encryption can balance data utility and privacy, enabling Pareto-superior outcomes. We further demonstrate BCT can reduces moral hazards in horizontal sharing (e.g. sharing biased forecast), allowing retailers to leverage aggregated demand signals without inefficiently verification. However, excessive transparency in BCT can accelerates retailers' profit erosion, akin to perfect competition. These findings offer micro-foundations for adopting visibility-restriction technologies (e.g. Zero-Knowledge Proofs) and guide the design of context-specific BCT systems. By reconciling transparency-privacy tensions and demonstrating BCT's endogenous role in forecasting, this study advances strategies for enhancing supply chain resilience through BCT innovation. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Production Research 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/00207543.2025.2567503 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 1227 Subjects: – SubjectFull: Blockchains Type: general – SubjectFull: Supply chain management Type: general – SubjectFull: Data encryption Type: general – SubjectFull: Disclosure Type: general – SubjectFull: Demand forecasting Type: general – SubjectFull: Incentive (Psychology) Type: general – SubjectFull: Privacy Type: general – SubjectFull: Information sharing Type: general Titles: – TitleFull: Full transparency or restricted visibility? Mechanisms of blockchain enabled data sharing in supply chain. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: He, Yu – PersonEntity: Name: NameFull: Jiang, Cuiqing – PersonEntity: Name: NameFull: Dong, Junfeng – PersonEntity: Name: NameFull: Ding, Yong – PersonEntity: Name: NameFull: Chen, Bo IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 02 Text: Feb2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 00207543 Numbering: – Type: volume Value: 64 – Type: issue Value: 4 Titles: – TitleFull: International Journal of Production Research Type: main |
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