{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T04:43:44Z","timestamp":1777697024509,"version":"3.51.4"},"reference-count":15,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T00:00:00Z","timestamp":1752451200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"The Special Undergraduate Course Project in the \"1112\" Teaching Engineering Construction Project of Shaanxi Fashion Engineering University","award":["2024TSKC067"],"award-info":[{"award-number":["2024TSKC067"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Intelligent Decision Technologies"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>\n                    With increasing climate change urgency and regulatory pressures, corporations are expected to adopt transparent and efficient environmental accounting practices. In China, where industrialization often outpaces sustainability, there is a need for intelligent tools to align business performance with environmental responsibility. Despite the existence of environmental key performance indicators (KPIs), many organizations struggle with adopting suitable environmental accounting strategies due to a lack of data-driven frameworks. Traditional approaches often overlook the complexity and industry-specific nature of sustainability data, leading to poor decision-making. This research proposes EcoStratClass, a machine learning-based framework for classifying Chinese corporations into appropriate Environmental Accounting Strategy types based on sustainability performance. Using the Smart Sustainability &amp; Environmental Accounting in Chinese Corporations (SSEC-ChiCorp) dataset, the methodology involves advanced data preprocessing, including attribute removal, target mean encoding, PCA for categorical reduction, ordinal mapping for audit frequency, and hybrid normalization techniques (Z-score, Min-Max, and Box-Cox). The Environmental Signature Score (ESS) quantifies overall sustainability impact, considering CO\n                    <jats:sub>2<\/jats:sub>\n                    emissions, energy usage, recycling, and renewable resource consumption. Feature selection employs the Environmental Signature Learning (ESL) method, combining Mutual Information, Chi-Square, ANOVA F-test, Recursive Feature Elimination (RFE), and models like LightGBM, Random Forest, and SVM. The classification model uses a stacked ensemble of LightGBM, Random Forest, and SVM, with Logistic Regression as the meta-learner. SHAP values improve model explainability by highlighting influential attributes. With an accuracy of 92.87%, the model achieves strong performance in various metrics (macro precision, recall, F1 score). EcoStratClass offers a reliable, interpretable decision-support system to guide corporations in selecting effective environmental accounting strategies, promoting ESG-aligned sustainable development.\n                  <\/jats:p>","DOI":"10.1177\/18724981251357820","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T06:55:31Z","timestamp":1752562531000},"page":"3003-3020","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Smart sustainability: Environmental accounting strategy for modern corporations using machine learning"],"prefix":"10.1177","volume":"19","author":[{"given":"Zhao","family":"Wenhua","sequence":"first","affiliation":[{"name":"School of Economics and Management, Shaanxi Fashion Engineering University, Xi\u2019an, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyun","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Economics and Management, Anhui Agriculture University, Hefei, Anhui, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junjie","family":"Ren","sequence":"additional","affiliation":[{"name":"PingAn Insurance, Hefei, Anhui, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,7,14]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/su15118643"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.3390\/su15118896"},{"key":"e_1_3_2_4_2","first-page":"1","article-title":"Navigating sustainable development: exploring the nexus of board attributes and environmental accounting information disclosure in China\u2019s construction industry","author":"Chang G","year":"2024","unstructured":"Chang G, Wiredu I, Boadu PK, et al. Navigating sustainable development: exploring the nexus of board attributes and environmental accounting information disclosure in China\u2019s construction industry. Environ Dev Sustainability 2024: 1\u201326. doi:\u00a010.1007\/s10668-024-05366-y","journal-title":"Environ Dev Sustainability"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.3390\/su14169964"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.3390\/su15097052"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.3390\/en15207633"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.3390\/electronics12092048"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.3390\/su16156334"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.24818\/EA\/2022\/59\/94"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2024.105499"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sftr.2022.100068"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.3390\/su151813493"},{"key":"e_1_3_2_14_2","first-page":"13","article-title":"AI For environmental sustainability: applications in resource management and conservation","volume":"1","author":"Yousaf H","year":"2024","unstructured":"Yousaf H. AI For environmental sustainability: applications in resource management and conservation. Artif Intell Multidiscip J Syst Appl 2024; 1: 13\u201326.","journal-title":"Artif Intell Multidiscip J Syst Appl"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.36713\/epra13325"},{"key":"e_1_3_2_16_2","first-page":"150","article-title":"The role of artificial intelligence in sustainable agriculture and waste management: towards a green future","volume":"2","author":"Hernandez D","year":"2024","unstructured":"Hernandez D, Pasha L, Yusuf DA, et\u00a0al. The role of artificial intelligence in sustainable agriculture and waste management: towards a green future. Int Trans Artif Intell 2024; 2: 150\u2013157.","journal-title":"Int Trans Artif Intell"}],"container-title":["Intelligent Decision Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18724981251357820","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/18724981251357820","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18724981251357820","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:21:38Z","timestamp":1777454498000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/18724981251357820"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,14]]},"references-count":15,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["10.1177\/18724981251357820"],"URL":"https:\/\/doi.org\/10.1177\/18724981251357820","relation":{},"ISSN":["1872-4981","1875-8843"],"issn-type":[{"value":"1872-4981","type":"print"},{"value":"1875-8843","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,14]]}}}