{"title":"策略研究中的机器学习方法","authors":"Mike H. M. Teodorescu","doi":"10.2139/ssrn.3012524","DOIUrl":null,"url":null,"abstract":"Numerous applications of machine learning have gained acceptance in the field of strategy and management research only during the last few years. Established uses span such diverse problems as strategic foreign investments, strategic resource allocation, systemic risk analysis, and customer relationship management. This survey article covers natural language processing methods focused on text analytics and machine learning methods with their applications to management research and strategic practice. The methods are presented accessibly, with directly applicable examples, supplemented by a rich set of references crossing multiple subfields of management science. The intended audience is the strategy and management researcher with an interest in understanding the concepts, the recently established applications, and the trends of machine learning for strategy research.","PeriodicalId":406435,"journal":{"name":"CompSciRN: Other Machine Learning (Topic)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Machine Learning Methods for Strategy Research\",\"authors\":\"Mike H. M. Teodorescu\",\"doi\":\"10.2139/ssrn.3012524\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Numerous applications of machine learning have gained acceptance in the field of strategy and management research only during the last few years. Established uses span such diverse problems as strategic foreign investments, strategic resource allocation, systemic risk analysis, and customer relationship management. This survey article covers natural language processing methods focused on text analytics and machine learning methods with their applications to management research and strategic practice. The methods are presented accessibly, with directly applicable examples, supplemented by a rich set of references crossing multiple subfields of management science. The intended audience is the strategy and management researcher with an interest in understanding the concepts, the recently established applications, and the trends of machine learning for strategy research.\",\"PeriodicalId\":406435,\"journal\":{\"name\":\"CompSciRN: Other Machine Learning (Topic)\",\"volume\":\"117 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CompSciRN: Other Machine Learning (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3012524\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CompSciRN: Other Machine Learning (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3012524","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Numerous applications of machine learning have gained acceptance in the field of strategy and management research only during the last few years. Established uses span such diverse problems as strategic foreign investments, strategic resource allocation, systemic risk analysis, and customer relationship management. This survey article covers natural language processing methods focused on text analytics and machine learning methods with their applications to management research and strategic practice. The methods are presented accessibly, with directly applicable examples, supplemented by a rich set of references crossing multiple subfields of management science. The intended audience is the strategy and management researcher with an interest in understanding the concepts, the recently established applications, and the trends of machine learning for strategy research.