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Experiments show improved performance over baseline methods, with feature contribution and partial dependence analyses used to interpret relationships. Key factors include VC investor count in the syndicate and social capital relevance, while patent numbers provide limited signal for early-stage valuation.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/application-of-machine-learning-techniques-to-predict-entrepreneurial-firm-valuation-research-article/290738/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/application-of-machine-learning-techniques-to-predict-entrepreneurial-firm-valuation-research-article/290738.png","ImageObject",300,407,{"name":42,"@type":43},"Miles","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-11-10","2026-09-17",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",18,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"Why is predicting early-stage entrepreneurial firm valuation challenging?","Question",{"text":63,"@type":64},"Early-stage VC investors face valuation obstacles because entrepreneurial firms lack operational performance records, and information asymmetry exists between them.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What method does the paper propose for valuation prediction?",{"text":68,"@type":64},"The paper proposes an integrated differential evolution algorithm with an adaptive moment estimation method scheme called Adam-ENN to predict entrepreneurial firm valuation.",{"name":70,"@type":61,"acceptedAnswer":71},"Which features are found to be most important in the prediction model?",{"text":72,"@type":64},"Feature contribution analysis indicates that the number of VC investors in the funding syndicate is the most important feature, and VC investors' social capital also significantly affects prediction results.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},290738,1789642477,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,115,120,123,127],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":112,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":113,"slug":114},8,30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":97,"slug":130},19,"General","general",{"code":4,"msg":82,"data":132},{"doc_id":79,"user_id":133,"nickname":42,"user_avatar":134,"doc_module":4,"category_id":112,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":140,"language":141,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":12,"update_tm":80,"read_time":145,"preview_page_count":4},13056703019404,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","University of Groningen  \nApplication of machine learning techniques to predict entrepreneurial firm valuation  \nZhang, Ruling; Tian, Zengrui; McCarthy, Killian J. ; Wang, Xiao; Zhang, Kun  \nPublished in:  \nJournal of Forecasting  \nDOI:  \n10.1002/for.2912  \nIMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.  \nDocument Version  \nPublisher's PDF, also known as Version of record  \nPublication date: 2023  \nLink to publication in University of Groningen/UMCG research database  \nCitation for published version (APA):  \nZhang, R. , Tian, Z. , McCarthy, K. J. , Wang, X. , & Zhang, K. (2023) . Application of machine learning techniques to predict entrepreneurial firm valuation. Journal of Forecasting , 42(2), 402-417.  \n[https://doi.org/10.1002/for.2912](https://doi.org/10.1002/for.2912)  \nCopyright  \nOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons) .  \nThe publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: [https://www.rug.nl/library/open-access/self-archiving-pure/taverne](https://www.rug.nl/library/open-access/self-archiving-pure/taverne)amendment.  \nTake-down policy  \nIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.  \nDownloaded from the University of Groningen/U MCG research database (Pure): [http://www.rug. nl/research/portal. For technical reasons the](http://www.rug. nl/research/portal. For technical reasons the)[ ](http://www.rug. nl/research/portal. For technical reasons the)[number of authors shown on this cover page is limited to 10 maximum.](number of authors shown on this cover page is limited to 10 maximum.)  \nDownload date: 28-12-2025  \nReceived: 7 March 2022 Revised: 19 August 2022 Accepted: 25 September 2022  \nDOI: 10.1002/for.2912  \nRESE ARCH ARTICL E  \nApplication of machine learning techniques to predict entrepreneurial firm valuation  \nRuling Zhang 1,2  | Zengrui Tian 1 | Killian J. McCarthy 2 | Xiao Wang 3 | Kun Zhang 4  \n1Glorious Sun School of Business and Management, Donghua University, Shanghai, China  \n2Faculty of Economics and Business, University of Groningen, Groningen, Netherlands  \n3International Business School Suzhou, Xi'an Jiaotong-Liverpool University, Suzhou, China  \n4School of Naval Architecture, Ocean, and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China  \nCorrespondence  \nZengrui Tian, Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China.  \nEmail: [2150937@mail.dhu.edu.cn](2150937@mail.dhu.edu.cn)  \nFunding information  \nChina Scholarship Council, Grant/Award Number: 201806630043  \nAbstract  \nVenture capital (VC) is the main contributor to entrepreneurial firms' funding and thus plays a crucial role in their sustainable development and rapid growth. However, early-stage VC investors often face valuation obstacles to predict firm valuation since entrepreneurial firms lack operational performance records and information asymmetry exists between them. In this paper, an integrated differential evolution algorithm and adaptive moment estimation method scheme (Adam-ENN) is proposed for early-stage VC investors to predict entrepreneurial firm valuation. Experimental results show that the proposed machine learning method outperforms the baseline methods. The feature contribution analysis and partial dependence plots were performed to open up the black box of the relationships between entrepreneurial firm valuation and its features. Results indicate that the number of VC inves","cbCaiqqkb3C5MFDz","https://ap.wps.com/l/cbCaiqqkb3C5MFDz","pdf",2001537,17,"English","# Abstract\n# Introduction\n## Background on entrepreneurial survival and funding constraints\n## Role of venture capital in valuation\n# Methods and model interpretation\n## Differential evolution and Adam-ENN approach\n## Feature contribution analysis and partial dependence plots","[{\"question\":\"Why is predicting early-stage entrepreneurial firm valuation challenging?\",\"answer\":\"Early-stage VC investors face valuation obstacles because entrepreneurial firms lack operational performance records, and information asymmetry exists between them.\"},{\"question\":\"What method does the paper propose for valuation prediction?\",\"answer\":\"The paper proposes an integrated differential evolution algorithm with an adaptive moment estimation method scheme called Adam-ENN to predict entrepreneurial firm valuation.\"},{\"question\":\"Which features are found to be most important in the prediction model?\",\"answer\":\"Feature contribution analysis indicates that the number of VC investors in the funding syndicate is the most important feature, and VC investors' social capital also significantly affects prediction results.\"}]","Application of machine learning techniques to predict entrepreneurial firm valuation - Research article | PDF",43]