Now showing items 1-3 of 3

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    Extending the Socio-Economic Status (SES) Prediction System Based on the Thailand Marketing Research Society (TMRS) Standardized SES Classification for Thai Upcountry Urban Subjects 

    Jirayut Poomontre; Pisal Setthawong (2016)

    This 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 ...
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    A Prediction System Based on the TMRS Standardized Socio-Economic Status (SES) Classification of Bangkok and Metropolian Subjects 

    Jirayut Poomontre; Pisal Setthawong (2015-01)

    The paper proposes a prediction system for socio-economic status (SES) classification of Bangkok and metropolitan subjects. The SES classification is based on the standardized SES classification that was proposed by the Thailand Marketing Research Society (TMRS) with the support of the National Statistical Office (NSO), and widely adopted by local marketing research firms. Extending the author’s previous work on the standardized TMRS SES classification, the paper describes a prediction system that was developed to classify Bangkok and ...
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    Thai hotel classification: a cluster analysis based on entrepreneurial marketing characteristics 

    Charnsid Leelakasemsant; Pattana Boonchoo (Assumption University Press, 2017)

    This paper seeks to explore whether there is any meaningful clusters of Thai hotels based on entrepreneurial marketing variables and the demographic characteristics of hotels and their managers. Exploratory two-step cluster analysis was adopted since it can deal with both categorical and continuous data simultaneously. The analysis resulted in nine clusters, each with its own unique characteristics. The findings indicated that three major characteristics of hotel and hotel managers —hotel size, gender, and types of manager (owner vs. non-owner) ...