ArticleHeliyon2024
Game analysis of enterprise data sharing from a supply chain perspective.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
[Research Purpose] In the era of the digital economy, there is an urgent need to explore solutions to various problems faced by enterprises in their digital transformation, such as the lack of data resources, data silos, and information asymmetry within supply chains. [Method/Contribution] Leveraging evolutionary game theory and adopting a supply chain perspective, this study integrates the government and upstream/downstream enterprises into a unified analysis framework. In this study, a three-party evolutionary game model under government coordination aimed at fostering data openness and sharing among supply chain enterprises is constructed. Simulation analyses are conducted on decision-making strategies concerning data sharing between the government and supply chain enterprises across different scenarios. [Research Conclusion] It is observed that the high level of benefits and low costs associated with data sharing incentivize supply chain enterprises to actively open and share their data. Notably, government incentives significantly encourage data openness among these enterprises by subsidizing the cost of data sharing, "especially evident when the incentive coefficient exceeds 0.6," thereby guiding them toward collaborative data-sharing initiatives. Finally, it is also found that data sharing further promotes the digital transformation of the supply chain, optimizing decision-making processes, resource allocation, and operational efficiency. Through data sharing, better forecasting, inventory management, and risk mitigation strategies can be implemented. Moreover, data sharing fosters collaboration among supply chain partners enhances transparency and trust, and makes the supply chain more synchronized and responsive, which leads to value cocreation within the supply chain, with downstream enterprises being more incentivized than upstream enterprises by this value cocreation.
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Registered trials
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