Research on the Evolutionary Mechanism of University Faculty Engagement in Multi-agent Collaborative Innovation

Research on the Evolutionary Mechanism of University Faculty Engagement in Multi-agent Collaborative Innovation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Research on the Evolutionary Mechanism of University Faculty Engagement in Multi-agent Collaborative Innovation Feng Zhang, Jingdan Hao, Zhihan Zhang, Yunqi Chang, Xin Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7229474/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Multi-agent collaborative innovation catalyses scientific progress and fuels sustainable economic and social development. Its effectiveness depends on close cooperation among university faculty, government, and enterprises. As key knowledge producers, university faculty play a pivotal role in this process. Employing innovation ecosystem theory, this study constructs a multi-agent evolutionary game model involving government, enterprises, and university faculty to explore both their engagement in collaborative innovation and factors shaping their participation. Furthermore, it applies computer simulation as its main approach, complemented by case analysis to validate the results. The study found that: 1. Collaborative innovation remains stable only when the government, enterprises, and university faculty align their strategies. Any deviation by one party can lead to system degradation. 2. Government incentives alone are not sufficient; the evolution of the system hinges on the precision, credibility, and strength of their feedback effects. 3. University faculty’s research behaviour reflects both internal drivers and external influences. Despite favourable policy and trust conditions, individual differences in motivation, ability, and institutional perception can lead to divergent and stable behavioural outcomes. This study applies evolutionary game theory to elucidate the logic of university faculty participation in multi-agent collaborative innovation, provides policy implications to foster their active engagement and advances the understanding of collaborative innovation system. Physical sciences/Mathematics and computing Social science/Science technology and society university faculty Collaborative innovation Innovation ecosystem Evolutionary game model Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 22 Dec, 2025 Reviews received at journal 09 Oct, 2025 Reviews received at journal 06 Oct, 2025 Reviews received at journal 03 Oct, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviewers agreed at journal 28 Sep, 2025 Reviewers agreed at journal 28 Sep, 2025 Reviewers invited by journal 28 Sep, 2025 Editor assigned by journal 23 Sep, 2025 Editor invited by journal 17 Sep, 2025 Submission checks completed at journal 28 Aug, 2025 First submitted to journal 28 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7229474","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":526317540,"identity":"018d5911-d84d-490e-a3b1-cc2fdd51a143","order_by":0,"name":"Feng Zhang","email":"","orcid":"","institution":"Beijing Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Zhang","suffix":""},{"id":526317543,"identity":"f95336f8-dfcc-438b-9e66-b3a07c943a51","order_by":1,"name":"Jingdan 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