住宅商品房市场细分—基于A市居民购房意向调研
Residential Real Estate Market Segmentation—Based on Residents Purchase Intention Survey of A City

作者: 常思敏 , 费 宇 :云南财经大学,云南 昆明;

关键词: 聚类方法决策树方法房地产市场细分Clustering Method Decision Tree Method Residential Real Estate Market Segmentation

摘要:
为了更好地了解消费者的购房需求,细分住宅商品房市场,为房地产商制定精准的市场营销策略提供借鉴,本文将传统的统计学方法和机器学习的方法相结合定量分析了住宅商品房市场的需求状况。首先,文章结合以往研究经验选取房地产市场细分指标,通过问卷调查获取A市居民的购房意向与需求信息。然后,采用K-means聚类分析和决策树分类方法将消费者分为四类。最后,根据分类结果,运用频数分析、百分比分析、交叉列联分析方法得出了每一个类别的市场特征和需求倾向,为房地产开发商精准营销提供借鉴。同时,本文还得出了四类市场群体在住宅户型、购房关注点等方面的选择共性,为房地产开发商初期项目建设也有一定的指导意义。

Abstract: In order to better understand the housing demand of consumer, divide the residential real estate market, and provide reference for precise marketing strategies for real estate developers, this paper, combining the traditional statistical methods and machine learning method, analyzes the residential housing market demand in quantitative way. First of all, this paper bases previous re-search experience to select indicators for the real estate market segmentation, through the ques-tionnaire survey to obtain A city’s information about residential purchase intention and demand. Then, through using the K-means cluster analysis and decision tree classification method, it comes to the conclusion that consumers can be divided into four groups. Finally, according to the classi-fication results, and using frequency, percentage, cross contingency analysis methods, it shows demand characteristics and tendencies of each category. All of these provide reference for real estate developers in their project preparation stage.

文章引用: 常思敏 , 费 宇 (2016) 住宅商品房市场细分—基于A市居民购房意向调研。 现代市场营销, 6, 41-51. doi: 10.12677/MOM.2016.63006

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