{"title":"可持续商业实践中风险排序的智能方法","authors":"Mahmoud Ibrahim, Mahmoud Ismail","doi":"10.54216/jsdgt.030102","DOIUrl":null,"url":null,"abstract":"In an era marked by increasing global interconnectivity and multifaceted risks, the imperative for effective risk management in international business administration has never been more pronounced. This paper presents a novel and sustainable approach to ranking risks within this dynamic landscape. Leveraging the power of the Multinomial Naive Bayes classifier, our method empowers organizations to systematically assess and prioritize risks while embracing sustainability principles. Through meticulous experimentation and analysis, we demonstrate the method's efficacy and its capacity to enhance decision-making processes for businesses operating on an international scale. Our experiments validate the method's robustness and applicability, contributing to the fields of international business administration and risk management. The findings underscores the critical importance of intelligent, data-driven risk assessment and mitigation in an interconnected world. It not only contributes to the fields of international business administration and risk management but also offers a blueprint for harmonizing economic success with environmental and social responsibility.","PeriodicalId":117695,"journal":{"name":"Journal of Sustainable Development and Green Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intelligent Method for Ranking the Risks in Sustainable Business Practices\",\"authors\":\"Mahmoud Ibrahim, Mahmoud Ismail\",\"doi\":\"10.54216/jsdgt.030102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In an era marked by increasing global interconnectivity and multifaceted risks, the imperative for effective risk management in international business administration has never been more pronounced. This paper presents a novel and sustainable approach to ranking risks within this dynamic landscape. Leveraging the power of the Multinomial Naive Bayes classifier, our method empowers organizations to systematically assess and prioritize risks while embracing sustainability principles. Through meticulous experimentation and analysis, we demonstrate the method's efficacy and its capacity to enhance decision-making processes for businesses operating on an international scale. Our experiments validate the method's robustness and applicability, contributing to the fields of international business administration and risk management. The findings underscores the critical importance of intelligent, data-driven risk assessment and mitigation in an interconnected world. It not only contributes to the fields of international business administration and risk management but also offers a blueprint for harmonizing economic success with environmental and social responsibility.\",\"PeriodicalId\":117695,\"journal\":{\"name\":\"Journal of Sustainable Development and Green Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Sustainable Development and Green Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54216/jsdgt.030102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Sustainable Development and Green Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54216/jsdgt.030102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent Method for Ranking the Risks in Sustainable Business Practices
In an era marked by increasing global interconnectivity and multifaceted risks, the imperative for effective risk management in international business administration has never been more pronounced. This paper presents a novel and sustainable approach to ranking risks within this dynamic landscape. Leveraging the power of the Multinomial Naive Bayes classifier, our method empowers organizations to systematically assess and prioritize risks while embracing sustainability principles. Through meticulous experimentation and analysis, we demonstrate the method's efficacy and its capacity to enhance decision-making processes for businesses operating on an international scale. Our experiments validate the method's robustness and applicability, contributing to the fields of international business administration and risk management. The findings underscores the critical importance of intelligent, data-driven risk assessment and mitigation in an interconnected world. It not only contributes to the fields of international business administration and risk management but also offers a blueprint for harmonizing economic success with environmental and social responsibility.