Pathways for enhancing university technology transfer efficiency via digital innovation ecosystems: a university-based comparative perspective

Pathways for enhancing university technology transfer efficiency via digital innovation ecosystems: a university-based comparative perspective | 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 Research Article Pathways for enhancing university technology transfer efficiency via digital innovation ecosystems: a university-based comparative perspective Qian Luo, Shuying Li, Yixin Chen, Yung-ho Chiu, Lina Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6543320/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Technology transfer and innovation diffusion are not only means for economic growth but also crucial for promoting social equity and sustainable development. This study evaluates China's university technology transfer (UTT) efficiency using a dynamic two-stage Data Envelopment Analysis model. Using dynamic QCA, it explores the impacts of digital innovation ecosystems (DIE) from component and spatial heterogeneity perspectives. The key findings are: (1) From 2013–2018, UTT efficiency in China rose, dropped in 2019–2020 due to COVID-19, and rebounded in 2021. Spatial disparities were clear, with the eastern region leading and the northeastern region trailing. (2) The inter-group consistency analysis revealed that before 2018, configuration III (The value co-creation-driven type guided by the government) was most effective in achieving high UTT efficiency, while after 2018, market-dominant paths, especially configuration IV (The value co-creation-driven type guided by the market), became more prominent. The within-group analysis revealed that a regional effect for configuration I-IV, highlighting the importance of considering spatial heterogeneity. (3) Policy recommendations include promoting digital development, formulating region-specific policies, and improving the digital economy governance system to enhance UTT efficiency. These findings highlight the importance of a dynamic, region-specific approach for optimizing UTT efficiency through the development of digital innovation ecosystems. University technology transfer efficiency Digital innovation ecosystem Dynamic QCA Data Envelopment Analysis Regional disparities Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-6543320","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":451181375,"identity":"061a1eb3-acb9-4733-a3ad-77ee4235acdf","order_by":0,"name":"Qian Luo","email":"","orcid":"","institution":"Jinling Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Luo","suffix":""},{"id":451181376,"identity":"42f78df1-c1be-42ed-b83e-cec57fb82c8e","order_by":1,"name":"Shuying Li","email":"","orcid":"","institution":"Hohai University","correspondingAuthor":false,"prefix":"","firstName":"Shuying","middleName":"","lastName":"Li","suffix":""},{"id":451181377,"identity":"e6619cdd-52ff-48b8-aaa3-1e116adf554e","order_by":2,"name":"Yixin Chen","email":"","orcid":"","institution":"Hohai University","correspondingAuthor":false,"prefix":"","firstName":"Yixin","middleName":"","lastName":"Chen","suffix":""},{"id":451181378,"identity":"0776f6e1-9836-4f1a-bfd9-77979bd6696a","order_by":3,"name":"Yung-ho Chiu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtUlEQVRIiWNgGAWjYFACHoYDDBUQpgQJWs7AtRgQp4WBsY0ULfzsZw8e5p1XJ29wgPngbR6GP4kNhLRI9uQlHObddthwwwG2ZGseBgPCWgxu8BgAtRxIMDjAYyYN1JJLUIs9WMucOqAW/m/EaTGQAGlpYAbZwkacFokzOQYH5xw7bDjzMJux5RwD43qCWvjbzxh/eFNTJ893vPnhjTcVcsaEdCABZrA7SdAwCkbBKBgFowA3AAB5UTb2v/9oxAAAAABJRU5ErkJggg==","orcid":"","institution":"Soochow University","correspondingAuthor":true,"prefix":"","firstName":"Yung-ho","middleName":"","lastName":"Chiu","suffix":""},{"id":451181379,"identity":"58cc75aa-120c-4ff8-ba28-181f40ca1f53","order_by":4,"name":"Lina Zhang","email":"","orcid":"","institution":"Hohai University","correspondingAuthor":false,"prefix":"","firstName":"Lina","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-04-28 03:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6543320/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6543320/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86566099,"identity":"eb3be06c-7401-48cb-8c4f-4e06d45b10fa","added_by":"auto","created_at":"2025-07-12 11:46:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":806684,"visible":true,"origin":"","legend":"","description":"","filename":"manusciptno.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6543320/v1_covered_b2a364c3-e482-4a32-955f-f54fa540539b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pathways for enhancing university technology transfer efficiency via digital innovation ecosystems: a university-based comparative perspective","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"University technology transfer efficiency, Digital innovation ecosystem, Dynamic QCA, Data Envelopment Analysis, Regional disparities","lastPublishedDoi":"10.21203/rs.3.rs-6543320/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6543320/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTechnology transfer and innovation diffusion are not only means for economic growth but also crucial for promoting social equity and sustainable development. This study evaluates China's university technology transfer (UTT) efficiency using a dynamic two-stage Data Envelopment Analysis model. Using dynamic QCA, it explores the impacts of digital innovation ecosystems (DIE) from component and spatial heterogeneity perspectives. The key findings are: (1) From 2013\u0026ndash;2018, UTT efficiency in China rose, dropped in 2019\u0026ndash;2020 due to COVID-19, and rebounded in 2021. Spatial disparities were clear, with the eastern region leading and the northeastern region trailing. (2) The inter-group consistency analysis revealed that before 2018, configuration III (The value co-creation-driven type guided by the government) was most effective in achieving high UTT efficiency, while after 2018, market-dominant paths, especially configuration IV (The value co-creation-driven type guided by the market), became more prominent. The within-group analysis revealed that a regional effect for configuration I-IV, highlighting the importance of considering spatial heterogeneity. (3) Policy recommendations include promoting digital development, formulating region-specific policies, and improving the digital economy governance system to enhance UTT efficiency. 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