Article Details

Abstract

This study employs agent-based modeling and computational experiments to explore the complex evolutionary mechanisms of university social service innovation. It identifies three typical evolutionary pathways including policy-driven, trust-accumulation, and platform-enabled, and systematically analyzes their formation mechanisms and comprehensive performance differences. The results indicate that the evolution of university social service systems exhibits multi-stability, with policy intensity, trust foundation, and platform efficiency serving as three key control variables that drive path divergence. The three types of pathways show significant performance trade-offs across dimensions such as efficiency, effectiveness, resilience, and fairness, with the trust-accumulation pathway demonstrating the strongest comprehensive capacity for sustainable development. Based on these findings, this study proposes a series of recommendations: establishing a long-term trust cultivation mechanism, promoting platform algorithm governance, and implementing differentiated policies based on regional endowments, which provide scientific decision-making support for regional innovation systems to move from “path discovery” to “adaptive governance”.

Keywords

university social service; evolutionary path; agent-based modeling; computational experiment; adaptive governance; computational social science; complex system

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Funding

2025 Wuxi Philosophy and Social Sciences Tendering Project (Social Education Development Special Project) "Research on Innovative Paths of Social Service Functions in Wuxi Universities from the Perspective of Government Enterprise School Collaboration" (WXSK25-JY-B02); 2023 Jiangsu Province Education Science Planning Project: "Research on the Construction and Practice of Agile Teaching System for Sustainable Competitiveness" (B/2023/02/60)

About the authors

Zhu Jianjun (1976-), male, Han ethnicity, from Rudong, Jiangsu, associate professor, master's degree, research direction: vocational education and data modeling; Nie Wanqin (1994-), female, Han ethnicity, from Qianjiang, Hubei Province, lecturer, master's degree, research direction: smart logistics and supply chain, as well as low altitude logistics; Xu Nanying (1997-), female, Han ethnicity, from Nanjing, Jiangsu, teaching assistant, master's degree, research direction: vocational education and cross-border e-commerce.