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Customer Segmentation Based on Dining Preferences in Full-Service Restaurants

机译:基于全方位服务餐厅中用餐偏好的客户细分

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This study was designed to identify the factors affecting five groups pruned by customer decision factors (menu, atmosphere, price, health, and brand reputation) that customers consider when selecting a full-service restaurant. The analytical method applied in this study was Decision Tree Analysis. As Decision Tree Analysis enables a researcher to identify and target desirable customer groups, it is an ideal analysis to identify differences between groups. A total of 390 questionnaires were used for the data analysis. The result indicated that depending on the group, classifying variables were different. That is, five groups have their own unique attributes. The results of this research would be valuable for marketers or managers in the restaurant industry to understand targeting customer segmentation.View full textDownload full textKeywordssegmentation, customer attributes, classifying variable, Decision Tree Analysis, CHAIDRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/15378020.2012.706180
机译:本研究旨在确定影响五组的因素,这些因素由客户在选择提供全方位服务的餐厅时要考虑的客户决策因素(菜单,氛围,价格,健康状况和品牌声誉)所修剪。本研究中使用的分析方法是决策树分析。由于决策树分析使研究人员能够识别和定位所需的客户群,因此,这是识别群体之间差异的理想分析。总共使用了390个问卷进行数据分析。结果表明,取决于组,分类变量是不同的。也就是说,五个组具有自己的独特属性。这项研究的结果对于餐饮业的营销人员或经理们来说,对于了解针对客户细分的目标将是有价值的。查看全文下载全文关键词细分,客户属性,分类变量,决策树分析,CHAID ”,services_compact:“ citeulike,netvibes,twitter,technorati,可口,linkedin,facebook,stumbleupon,digg,google,更多”,发布:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/15378020.2012.706180

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