Paper Type
Complete
Paper Number
PACIS2025-1650
Description
The aging population in China intensifies pressure on healthcare systems, prompting the adoption of smart aged care service platforms to enhance service quality and efficiency. However, challenges like data security, collaboration gaps, and stakeholder conflicts hinder progress. The study employs a quadrilateral evolutionary game model to analyze data-sharing strategies among government agencies, platform managers, service providers, and recipients. Numerical simulations reveal that a robust value co-creation ecosystem can reduce reliance on regulatory enforcement, while preventing improper behavior by service providers is crucial for maintaining trust. Dynamic subsidy and punishment mechanisms further support sustainable platform development. The findings offer a theoretical framework and practical recommendations for optimizing data-sharing strategies, aiding policymakers and platform managers in fostering a resilient and efficient smart aged care ecosystem.
Recommended Citation
Liu, Tianchang; Zeng, Pengxiang; and Zhu, Qinghua, "The Data Sharing Strategies for Smart Aged Care Service Platforms: A Quadrilateral Evolutionary Games" (2025). PACIS 2025 Proceedings. 3.
https://aisel.aisnet.org/pacis2025/dig_plat/di/3
The Data Sharing Strategies for Smart Aged Care Service Platforms: A Quadrilateral Evolutionary Games
The aging population in China intensifies pressure on healthcare systems, prompting the adoption of smart aged care service platforms to enhance service quality and efficiency. However, challenges like data security, collaboration gaps, and stakeholder conflicts hinder progress. The study employs a quadrilateral evolutionary game model to analyze data-sharing strategies among government agencies, platform managers, service providers, and recipients. Numerical simulations reveal that a robust value co-creation ecosystem can reduce reliance on regulatory enforcement, while preventing improper behavior by service providers is crucial for maintaining trust. Dynamic subsidy and punishment mechanisms further support sustainable platform development. The findings offer a theoretical framework and practical recommendations for optimizing data-sharing strategies, aiding policymakers and platform managers in fostering a resilient and efficient smart aged care ecosystem.
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