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dc.contributor.authorJirayut Poomontre
dc.contributor.authorPisal Setthawong
dc.identifier.citation7th International Conference on Information Science and Application (ICISA) 2016 at Ho Chi Minh City, Vietnam: iCaste/Springer Published in Springer LNEEen_US
dc.description.abstractThis research proposes an extension to the prediction system of socio-economic status (SES) by using asset ownership data, that the authors proposed previously on subjects based in Bangkok, to include Thai upcountry urban subjects. The prediction system is based on the standardized SES classification that is proposed by the Thailand Marketing Research Society (TMRS) and widely adopted by marketing research firms in Thailand. The paper describes the TMRS SES classification briefly, proposes a prediction system for Thai upcountry urban subjects based on asset ownership data, and evaluate the performance of the predictor. A mobile application was created for the prediction system.en_US
dc.format.extent10 pagesen_US
dc.subjectSocio-economic statusen_US
dc.subjectPrediction systemen_US
dc.subjectStatistical multivariate analysisen_US
dc.subjectFactor analysisen_US
dc.subjectCluster analysisen_US
dc.titleExtending the Socio-Economic Status (SES) Prediction System Based on the Thailand Marketing Research Society (TMRS) Standardized SES Classification for Thai Upcountry Urban Subjectsen_US
dc.rights.holderJirayut Poomontreen_US
dc.rights.holderPisal Setthawong
mods.genreConference Paperen_US[Full Text] (

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