[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124076-en":3,"doc-seo-124076-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124076,687197207639,"Asher","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","What makes companies zombie - Detecting the most important zombification feature using tree-based machine learning","Tree-based machine learning models are used to identify the key factors behind company zombification that earlier studies often treat as secondary to general determinants. The work applies machine-learning feature analysis to three feature-set constructions, then evaluates them with four tree-based algorithms. Across experiments, Debt and ROA emerge with the highest feature scores for predicting zombie firms. Lasso-based feature sets yield the strongest evaluation metrics through a two-step filtering process, improving predictive accuracy for early warning monitoring.","What makes companies zombie? : Detecting the most important zombification feature using tree-based machine learning  \nBrahmana, R. K .  \nPublished PDF deposited in Coventry University’s Repository  \nOriginal citation:  \nBrahmana, RK 2025, 'What makes companies zombie? : Detecting the most important zombification feature using tree-based machine learning', Expert Systems with Applications, vol. 270, 126538. [https://doi.org/10.1016/j.eswa.2025.126538](https://doi.org/10.1016/j.eswa.2025.126538)  \n[DOI 10.1016/j.eswa.2025.126538](DOI 10.1016/j.eswa.2025.126538)[ ](DOI 10.1016/j.eswa.2025.126538)[ISSN 0957-4174](ISSN 0957-4174)  \n[ESSN 1873-6793](ESSN 1873-6793)  \nPublisher: Elsevier  \n© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( [http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/) ).  \nExpert Systems With Applications 270 (2025) 126538  \nContents lists available at ScienceDirect  \nExpert Systems With Applications  \njournal [homepage: www.elsevier.com/locate/eswa](homepage: www.elsevier.com/locate/eswa)  \n| What makes companies zombie? Detecting the most important zombification feature using tree-based machine learning |  |  |  |\n| --- | --- | --- | --- |\n| Rayenda Khresna Brahmana \u003Cbr>School of Economics, Finance, and Accounting, Coventry University, Coventry CV1 5DL United Kingdom |  |  |  |\n| A R T I C L E I N F O |  | A B S T R A C T |  |\n| Keywords:\u003Cbr>Zombie Companies\u003Cbr>Firm Characteristics Feature Analysis Machine Learning Tree-based models |  | Tree-based machine learning models are crucial for identifying key features of company zombification, which remain underexplored in current literature focused solely on determinants. This study addresses this gap by employing machine learning feature analysis to identify and analyze the critical factors driving zombification, offering a fresh and data-driven perspective on the issue. Three different feature sets are examined: (i) Feature Zoo,(ii) Logistic regression-based, and (iii) Lasso-based features, focusing on critical internal characteristics of firms. These feature sets are applied to four tree-based algorithms—Decision Tree, Random Forest, Gradient Boosting Model, and XGBoost—chosen for their white model capabilities, allowing the feature extractions. The results indicate that Debt and ROA consistently have the highest feature scores, suggesting they are crucial for predicting zombie companies. Additionally, the Lasso-based feature sets provide the best evaluation metrics, indicating that the two-step filtering process effectively improves the predictive model for zombie companies. The study enriches the literature by extending the anatomy of zombie companies with a more advanced approach. The results also address Debt and ROA as the most significant features for identifying zombie firms. Managers and policymakers should prioritize monitoring Debt and ROA as early warning indicators for company zombification. |  |\n\n1. Introduction  \nAs walking dead entities, zombie companies operate solely to cater to their going concerns, often surviving through government incentives (Liu et al., 2019; Ahearne & Shinada, 2005). Consequently, their existence distorts healthy market competition (Qiao et al., 2022; Zhang & Huang, 2022; Caballero et al., 2008), infecting healthy companies with insolvency (Yu et al., 2021; Caballero et al., 2008), depressing the national economy with resource misallocation (Mao & Xu, 2024; Liu et al., 2019), and serving long-run global stagflation (Krugman, 2020; Ahearne & Shinada, 2005).  \nOne theoretical gap in this area is identifying the most important features of zombie companies. Several attempts have been made, but it is more on exploration and theoretical rather than empirical with a robust approach. For instance, El Ghoul et al. (2021) descriptively identified 10 % of zombie companies from 79 countries from 2005 to 2016. Then, Banerjee and Hofmann (2022","cbCaioa6VLvYe84F","https://ap.wps.com/l/cbCaioa6VLvYe84F","pdf",3894067,1,18,"English","en",105,"# Introduction\n## Research gap and motivation\n## Approach using machine learning feature analysis","[{\"question\":\"What is the main research goal of the paper?\",\"answer\":\"To detect the most important features driving company zombification using tree-based machine learning feature analysis.\"},{\"question\":\"Which firm characteristics are identified as most important for predicting zombie companies?\",\"answer\":\"Debt and ROA consistently receive the highest feature scores across the evaluated models.\"},{\"question\":\"How do the feature-set methods affect model performance?\",\"answer\":\"Lasso-based feature sets provide the best evaluation metrics, and the paper attributes the improvement to a two-step filtering process that enhances predictive power.\"}]","What makes companies zombie - Detecting the most important zombification feature using tree-based machine learning | PDF",1785820207,45,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"what-makes-companies-zombie-detecting-the-most-important-zombification-feature-using-tree-based-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/what-makes-companies-zombie-detecting-the-most-important-zombification-feature-using-tree-based-machine-learning/124076/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main research goal of the paper?","Question",{"text":75,"@type":76},"To detect the most important features driving company zombification using tree-based machine learning feature analysis.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which firm characteristics are identified as most important for predicting zombie companies?",{"text":80,"@type":76},"Debt and ROA consistently receive the highest feature scores across the evaluated models.",{"name":82,"@type":73,"acceptedAnswer":83},"How do the feature-set methods affect model performance?",{"text":84,"@type":76},"Lasso-based feature sets provide the best evaluation metrics, and the paper attributes the improvement to a two-step filtering process that enhances predictive power.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]