{"title":"自愿性信息披露的决定因素:整合极端梯度提升(XGBoost)和可解释人工智能(XAI)技术","authors":"","doi":"10.1016/j.irfa.2024.103577","DOIUrl":null,"url":null,"abstract":"<div><p>Financial information transparency is vital for the various users of financial statements. This study employs the Explainable Artificial Intelligence (XAI) approach, utilizing eXtreme Gradient Boost (XGBoost) to explore management's motivations for voluntary disclosure. By transforming financial data into various plots, we introduce a voluntary disclosure model that enhances interpretability through Shapley Additive exPlanations (SHAP) techniques. These XAI methods aim to clarify different results in the voluntary disclosure literature, addressing the ongoing debate within the financial research community regarding voluntary disclosure. This research marks a significant advancement in voluntary disclosure by merging the transparency of XAI with effective voluntary disclosure prediction, offering a more comprehensive understanding of the determinants of voluntary disclosure.</p></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":null,"pages":null},"PeriodicalIF":7.5000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The determinants of voluntary disclosure: Integration of eXtreme gradient boost (XGBoost) and explainable artificial intelligence (XAI) techniques\",\"authors\":\"\",\"doi\":\"10.1016/j.irfa.2024.103577\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Financial information transparency is vital for the various users of financial statements. This study employs the Explainable Artificial Intelligence (XAI) approach, utilizing eXtreme Gradient Boost (XGBoost) to explore management's motivations for voluntary disclosure. By transforming financial data into various plots, we introduce a voluntary disclosure model that enhances interpretability through Shapley Additive exPlanations (SHAP) techniques. These XAI methods aim to clarify different results in the voluntary disclosure literature, addressing the ongoing debate within the financial research community regarding voluntary disclosure. This research marks a significant advancement in voluntary disclosure by merging the transparency of XAI with effective voluntary disclosure prediction, offering a more comprehensive understanding of the determinants of voluntary disclosure.</p></div>\",\"PeriodicalId\":48226,\"journal\":{\"name\":\"International Review of Financial Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.5000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Review of Financial Analysis\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S105752192400509X\",\"RegionNum\":1,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Financial Analysis","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S105752192400509X","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
The determinants of voluntary disclosure: Integration of eXtreme gradient boost (XGBoost) and explainable artificial intelligence (XAI) techniques
Financial information transparency is vital for the various users of financial statements. This study employs the Explainable Artificial Intelligence (XAI) approach, utilizing eXtreme Gradient Boost (XGBoost) to explore management's motivations for voluntary disclosure. By transforming financial data into various plots, we introduce a voluntary disclosure model that enhances interpretability through Shapley Additive exPlanations (SHAP) techniques. These XAI methods aim to clarify different results in the voluntary disclosure literature, addressing the ongoing debate within the financial research community regarding voluntary disclosure. This research marks a significant advancement in voluntary disclosure by merging the transparency of XAI with effective voluntary disclosure prediction, offering a more comprehensive understanding of the determinants of voluntary disclosure.
期刊介绍:
The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.