드론 음식배달 서비스에서 기대편익에 관한 시장세분화 연구: 의사결정나무 CHAID 알고리즘 분석을 중심으로
A Study on the Market Segmentation of Drone Food Delivery Services by Expected Benefits: Focusing on the Analysis of Answertree CHAID Algorithm
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In the Fourth Industrial Revolution, drone food delivery services are attracting attention due to its great advantages. However, there is no existing research on market segmentation in the context of drone food delivery services. Therefore, the purpose of this research was to segment sub-groups based on five sub-dimensions of perceived benefits, and identify the differences in the sub-groups according to demographic factors using the Answertree method. A total of 720 samples were used for analysis. As a result of the analysis for each expected benefit type, the split node of Answertree was created according to convenience, emotion, and compatibility, and significant market segmentation results were confirmed according to gender, age, education level, and marital status for each model. The risk estimates for each model are .392, .418, and .428, which implies a model accuracy of 60.8%, 58.2%, and 57.2%.
Abstract
In the Fourth Industrial Revolution, drone food delivery services are attracting attention due to its great advantages. However, there is no existing research on market segmentation in the context of drone food delivery services. Therefore, the purpose of this research was to segment sub-groups based on five sub-dimensions of perceived benefits, and identify the differences in the sub-groups according to demographic factors using the Answertree method. A total of 720 samples were used for analysis. As a result of the analysis for each expected benefit type, the split node of Answertree was created according to convenience, emotion, and compatibility, and significant market segmentation results were confirmed according to gender, age, education level, and marital status for each model. The risk estimates for each model are .392, .418, and .428, which implies a model accuracy of 60.8%, 58.2%, and 57.2%.
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