{"title":"预测协作业务流程中的变更传播影响","authors":"W. Fdhila, S. Rinderle-Ma","doi":"10.1145/2554850.2554966","DOIUrl":null,"url":null,"abstract":"During the life cycle of a Business-to-Business (B2B) collaboration, companies may need to redesign or change parts of their service orchestrations. A change request proposed by one partner will, in most cases, result in changes to other partner orchestration. An accurate prediction of the behavior of a change request and an analysis of its impacts on the collaboration allows to avoid significant costs related to unsuccessful propagation, e.g. negotiation fail. This paper focuses on predicting the likelihood of a change request propagation as well as its ripple effects on the overall collaboration. To estimate these values, the approach analyses the collaboration structure through a priori analysis. We will show how the prediction models can be specified and implemented within a proof-of-concept prototype. Discussion will be provided on visualization possibilities and model validation.","PeriodicalId":285655,"journal":{"name":"Proceedings of the 29th Annual ACM Symposium on Applied Computing","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Predicting change propagation impacts in collaborative business processes\",\"authors\":\"W. Fdhila, S. Rinderle-Ma\",\"doi\":\"10.1145/2554850.2554966\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"During the life cycle of a Business-to-Business (B2B) collaboration, companies may need to redesign or change parts of their service orchestrations. A change request proposed by one partner will, in most cases, result in changes to other partner orchestration. An accurate prediction of the behavior of a change request and an analysis of its impacts on the collaboration allows to avoid significant costs related to unsuccessful propagation, e.g. negotiation fail. This paper focuses on predicting the likelihood of a change request propagation as well as its ripple effects on the overall collaboration. To estimate these values, the approach analyses the collaboration structure through a priori analysis. We will show how the prediction models can be specified and implemented within a proof-of-concept prototype. Discussion will be provided on visualization possibilities and model validation.\",\"PeriodicalId\":285655,\"journal\":{\"name\":\"Proceedings of the 29th Annual ACM Symposium on Applied Computing\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 29th Annual ACM Symposium on Applied Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2554850.2554966\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 29th Annual ACM Symposium on Applied Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2554850.2554966","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predicting change propagation impacts in collaborative business processes
During the life cycle of a Business-to-Business (B2B) collaboration, companies may need to redesign or change parts of their service orchestrations. A change request proposed by one partner will, in most cases, result in changes to other partner orchestration. An accurate prediction of the behavior of a change request and an analysis of its impacts on the collaboration allows to avoid significant costs related to unsuccessful propagation, e.g. negotiation fail. This paper focuses on predicting the likelihood of a change request propagation as well as its ripple effects on the overall collaboration. To estimate these values, the approach analyses the collaboration structure through a priori analysis. We will show how the prediction models can be specified and implemented within a proof-of-concept prototype. Discussion will be provided on visualization possibilities and model validation.