{"title":"衡量政府采购复杂信息系统时系统工程的有效性","authors":"Steven Doskey, T. Mazzuchi, S. Sarkani","doi":"10.1109/SysCon.2013.6549873","DOIUrl":null,"url":null,"abstract":"In this paper, the authors present an innovative means of gauging systems engineering effectiveness. This research uses a Bayesian Belief Network to model causal relationships present in government acquisitions of complex information systems and to create a Systems Engineering relative effectiveness index model that can be used to identify and analyze Systems Engineering patterns and subsequently predict possible areas of SE performance risk.","PeriodicalId":218073,"journal":{"name":"2013 IEEE International Systems Conference (SysCon)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A measure of systems engineering effectiveness in government acquisition of complex information systems\",\"authors\":\"Steven Doskey, T. Mazzuchi, S. Sarkani\",\"doi\":\"10.1109/SysCon.2013.6549873\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the authors present an innovative means of gauging systems engineering effectiveness. This research uses a Bayesian Belief Network to model causal relationships present in government acquisitions of complex information systems and to create a Systems Engineering relative effectiveness index model that can be used to identify and analyze Systems Engineering patterns and subsequently predict possible areas of SE performance risk.\",\"PeriodicalId\":218073,\"journal\":{\"name\":\"2013 IEEE International Systems Conference (SysCon)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Systems Conference (SysCon)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SysCon.2013.6549873\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Systems Conference (SysCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SysCon.2013.6549873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A measure of systems engineering effectiveness in government acquisition of complex information systems
In this paper, the authors present an innovative means of gauging systems engineering effectiveness. This research uses a Bayesian Belief Network to model causal relationships present in government acquisitions of complex information systems and to create a Systems Engineering relative effectiveness index model that can be used to identify and analyze Systems Engineering patterns and subsequently predict possible areas of SE performance risk.