基于共享经济平台在线信息的消费者决策分析  

Consumer decision analysis of online reviews based on sharing economic platform

作　　者：赵建欣[1] 朱阁[1] 宋玲玉 ZHAO Jianxin;ZHU Ge;SONG Lingyu(School of Information Management, Beijing Information Science ＆ Technology University, Beijing 100192, China)

机构地区：[1]北京信息科技大学信息管理学院,北京100192

出　　处：《北京信息科技大学学报（自然科学版）》2017年第6期14-19,共6页Journal of Beijing Information Science and Technology University

基　　金：国家自然科学基金资助项目(71701020)

摘　　要：为研究共享经济背景下在线信息对实际销售的影响,从旅行房屋租赁社区Airbnb网站上选取了中美两国6个城市的1014条房源在线数据,建立多元回归模型研究影响短租销量的可能因素。对价格、收藏数量、总体评分及地区差异等因素的层次回归分析显示该模型对因变量有较高解释度(调整R2为0.553)。结果表明,房间价格在2个地区对房源销量均为显著负相关;收藏数量对房源销量有显著正相关,且系数较高;总体评分仅在中国地区对房源销量呈显著正相关;收藏数量对房源销量的影响程度受到地区差异的显著调节作用。该研究结果对中美两国短租平台的发展提供了一定的理论指导和实践意义。In order to study the impact of online information on the actual sales in the context of sharing economy, 1014 panel data from six cities in China and the United States were collected on the Airbnb website. The multiple regression model was established to study the possible factors （ such as the price, the wish list, the overall score and the regional difference） that affect the sales. The regression analysis showed that the model had a higher degree of interpretation of the dependent variable （ adjusted R2was 0. 553 ）. The results show that the room price is negatively correlated with the sales volume in both regions. The number of collections has a significant positive correlation with the sales volume and the coefficient is high. The overall score has a significant positive correlation with the sales volume in China. The impact of the number of collections on the sales volume is significantly regulated by the regional differences. The results of this study may provide theoretical guidance and practical significance for the development of short-term rent platform in China and the United States.

关 键 词：在线评论 回归模型 共享经济 Airbnb.com 

分 类 号：F59[经济管理—旅游管理]