{"title":"The impact of 'messy' data on group decision-making","authors":"Douglas R. Vogel","doi":"10.1109/HICSS.1988.11913","DOIUrl":null,"url":null,"abstract":"The author presents results from research examining the impact of the integration of external data of varying degrees of messiness in conjunction with use of an established group decision-support system. Messiness in this sense refers to the degree that the data comes from a large number of fragmented sources of varying degrees of objectivity across a broad spectrum of formats and contexts in environments with difficult and complex data interrelations. External data of varying degrees of messiness were provided in conjunction with the group's efforts to identify and assign priorities to key issues of a complex problem involving metropolitan land use and transportation planning. Research data were recorded on strategies of use and impact on decision-making as a function of external data messiness.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HICSS.1988.11913","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
The author presents results from research examining the impact of the integration of external data of varying degrees of messiness in conjunction with use of an established group decision-support system. Messiness in this sense refers to the degree that the data comes from a large number of fragmented sources of varying degrees of objectivity across a broad spectrum of formats and contexts in environments with difficult and complex data interrelations. External data of varying degrees of messiness were provided in conjunction with the group's efforts to identify and assign priorities to key issues of a complex problem involving metropolitan land use and transportation planning. Research data were recorded on strategies of use and impact on decision-making as a function of external data messiness.<>
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