{"title":"Multicriteria Market Segmentation: An Outranking Approach","authors":"J. C. López, D. A. G. Chavira","doi":"10.1109/ISKE47853.2019.9170388","DOIUrl":null,"url":null,"abstract":"In this article, we offer a novel multicriteria decision analysis method for the segmentation of the market. The proposed method combines the analysis of preferences of the customer and the application of decision aiding on the segmentation problem. To explore the preferences of each customer in a strong way, the method applies the aggregation-disaggregation paradigm and a genetic algorithm to derive multiple sets of preference parameters of the ELECTRE III method compatible with the preference information supplied by each customer. Next, the preferences of each customer are characterized by the dispersion of potential rankings of products by applying the derived valued outranking relations. A novel metric is used to quantify the similitude among preferences of diverse customers, and a procedure of clustering is established to complete the segmentation of the market.","PeriodicalId":399084,"journal":{"name":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE47853.2019.9170388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this article, we offer a novel multicriteria decision analysis method for the segmentation of the market. The proposed method combines the analysis of preferences of the customer and the application of decision aiding on the segmentation problem. To explore the preferences of each customer in a strong way, the method applies the aggregation-disaggregation paradigm and a genetic algorithm to derive multiple sets of preference parameters of the ELECTRE III method compatible with the preference information supplied by each customer. Next, the preferences of each customer are characterized by the dispersion of potential rankings of products by applying the derived valued outranking relations. A novel metric is used to quantify the similitude among preferences of diverse customers, and a procedure of clustering is established to complete the segmentation of the market.