{"title":"人工神经网络在企业社会责任决策中的应用","authors":"Nguyen Thi Thanh Binh","doi":"10.1002/isaf.1542","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Neural networks in deep learning are changing the way we interact with the world. This paper focuses on building a logit artificial neural network (ANN) and through it finds out the factors affecting the decision to join corporate social responsibility (CSR) of firms. This study contributes to suggesting new directions for research in the artificial intelligence (AI) era on the relationship between corporate governance and CSR. The dataset of 817 Taiwanese electronic firms is analyzed for the period 2014–2020. The empirical results show that when the power of the board of directors, supervisors, and CEOs are higher, firms do not choose to participate in CSR. The independent board has not yet promoted its corporate oversight of CSR participation. The decision not to participate in CSR of the firms is made when they are more equipped with the background of accounting, finance, and law. Only firms with higher debt, asset value, and profitability are willing to join CSR. These research results suggest some important points for future policy reforms towards sustainability.</p>\n </div>","PeriodicalId":53473,"journal":{"name":"Intelligent Systems in Accounting, Finance and Management","volume":"31 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An application of artificial neural networks in corporate social responsibility decision making\",\"authors\":\"Nguyen Thi Thanh Binh\",\"doi\":\"10.1002/isaf.1542\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>Neural networks in deep learning are changing the way we interact with the world. This paper focuses on building a logit artificial neural network (ANN) and through it finds out the factors affecting the decision to join corporate social responsibility (CSR) of firms. This study contributes to suggesting new directions for research in the artificial intelligence (AI) era on the relationship between corporate governance and CSR. The dataset of 817 Taiwanese electronic firms is analyzed for the period 2014–2020. The empirical results show that when the power of the board of directors, supervisors, and CEOs are higher, firms do not choose to participate in CSR. The independent board has not yet promoted its corporate oversight of CSR participation. The decision not to participate in CSR of the firms is made when they are more equipped with the background of accounting, finance, and law. Only firms with higher debt, asset value, and profitability are willing to join CSR. These research results suggest some important points for future policy reforms towards sustainability.</p>\\n </div>\",\"PeriodicalId\":53473,\"journal\":{\"name\":\"Intelligent Systems in Accounting, Finance and Management\",\"volume\":\"31 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligent Systems in Accounting, Finance and Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/isaf.1542\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Systems in Accounting, Finance and Management","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/isaf.1542","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
An application of artificial neural networks in corporate social responsibility decision making
Neural networks in deep learning are changing the way we interact with the world. This paper focuses on building a logit artificial neural network (ANN) and through it finds out the factors affecting the decision to join corporate social responsibility (CSR) of firms. This study contributes to suggesting new directions for research in the artificial intelligence (AI) era on the relationship between corporate governance and CSR. The dataset of 817 Taiwanese electronic firms is analyzed for the period 2014–2020. The empirical results show that when the power of the board of directors, supervisors, and CEOs are higher, firms do not choose to participate in CSR. The independent board has not yet promoted its corporate oversight of CSR participation. The decision not to participate in CSR of the firms is made when they are more equipped with the background of accounting, finance, and law. Only firms with higher debt, asset value, and profitability are willing to join CSR. These research results suggest some important points for future policy reforms towards sustainability.
期刊介绍:
Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.