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数据科学与管理工程学系学术讲座No.18

发布时间:2017-06-12 09:51:59 来源:数据科学与管理工程学系 浏览次数:

 How Online Information Influences Offline Transactions: The Case of Zillow and the Real Estate Market

 

时 间:2017年6月15日(周四)下午 14:00-15:00

地 点:浙江大学紫金港校区行政楼1002会议室

主讲人:Prof. Zhengrui JIANG, 爱荷华州立大学

主持人:王明征教授,浙江大学管理学院

摘 要:

The Internet is having a profound impact on how information flows and how transactions are conducted in the business world; the real estate market is no exception. Recent studies show that most home buyers now rely on online websites as their primary information source, and are more likely to find their homes from the Internet than from any other source. Using data collected from the most dominant online real estate platform, Zillow.com, we study how online property information affects offline sale prices. Our results reveal that property information on Zillow has a larger influence on the sale price of uncommon properties, i.e., those valued lower than 70% or higher than 130% of their neighborhood average, than on the price of common properties, i.e., those valued between 70% and 130% of their neighborhood average. Specifically, we find that the length of the property description and the number of photos on Zillow have a significant and positive impact on the price of uncommon houses, while their impact on common houses is not significant. Although the save-per-view ratio, i.e., the percentage of online viewers who have saved a property, has a significant and positive impact on the sale price of both common and uncommon properties, the coefficient of this impact for uncommon properties is more than 250% that for common properties. Furthermore, we find that Zestimate, the property value assessment provided by Zillow, influences the sale price of both types of properties; but the accuracy of Zestimate, which varies across areas, does not have a significant impact on property price. Finally, our results indicate that sellers and real estate professionals are willing to provide more property information when the property value is higher, when the property is less comparable to surrounding ones, or when the seller’s asking price is significantly higher than the estimated property value. These findings shed light on how online property information are used by home buyers and sellers for different types of properties, and can help real estate professionals and online real estate platforms better utilize the Internet and improve the efficiency of the real estate market.

主讲人简介:

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Prof. Zhengrui JIANG is the Thome Professor in Business and associate professor of information systems at the College of Business, Iowa State University. He received his PhD in Management Science/Information Systems from the University of Texas at Dallas. His primary research interests include business intelligence/analytics, diffusion of innovations, and economics of information goods. He has published in leading academic journals including Management Science, MIS Quarterly, Information Systems Research, IEEE Transactions on Knowledge and Data Engineering, INRORMS Journal on Computing, and Journal of Management Information Systems. His research has been funded by U.S. Agency for International Development, and National Natural Science Foundation of China. He currently serves as an associate editor for MIS Quarterly. He previously served as guest editors for Production and Operations Management and IEEE Transactions on Management Information Systems. He also served as a program co-chair for the 2014 Midwest Association of Information Systems Conference and the 2015 Big XII+ MIS Research Symposium. He will be co-chairing the 2018 Workshop on Information Technology and Systems.

 

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