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题目:The Effect of Images on Airbnb Occupancy: An Integration of Deep Learning and Econometric Analysis
时间:6月26日下午2:30
地点:经济与管理学院学术报告厅(南校区信远楼2区 324)
报告人:Anol Bhattacherjee  教授
 
报告人简介
Anol Bhattacherjee is a Professor of Information Systems and Exide Professor of Business Ethics at the University of South Florida. In a research career spanning 20 years, Anol has published over 100 publications, including 60 refereed journal papers.  His free textbook on research methods titled Social Science Research: Principles, Methods, and Practices has been downloaded over 650,000 times since its publication in 2011, used in 209 countries, and is available in seven languages. Anol’s research focuses on creativity and innovations, healthcare informatics, and ICT for development. He served on the editorial board of MIS Quarterly for four years and served as a senior editor at Journal of the AIS.  He holds PhD and MBA degrees from the University of Houston, and MS and BS degrees from Indian Institute of Technology, and had prior faculty appointments at Arizona State University and the University of Colorado at Denver.
 
报告内容
This paper examines the effect of images on transactions on sharing economy platforms. Specifically, it considers how image count, category, and entropy on Airbnb listings influence listing occupancy. A deep learning convolutional neural network model is used to classify images into indoor versus outdoor categories. We then compute the amount of uncertainty (entropy) in images, and employ an econometric model to test the effects of the count of indoor and outdoor images, the category of the primary image (indoor or outdoor), and image entropy on subsequent occupancy, while controlling for possible confounds. Our analysis indicate that presenting outdoor image as the primary image reduces Airbnb occupancy relative to listings with indoor images as their primary image. Increasing the number of indoor and outdoor images negatively impact listing occupancy, and lower entropy of the primary image negatively impact occupancy on Airbnb.
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