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Pei Xu

Pei  Xu


position: Assistant Professor
dept: Department of Systems and Technology
phone: (334) 844-6513
e-mail: pzx0002@auburn.edu
office: 420 Lowder Hall
c.v.: click here


Pei Xu is an Assistant professor in the area of Business Analytics. She received her Ph.D. degree in Decision Science and Information Systems from the University of Kentucky in 2014. Her research focus is on understanding the economic and social impact of emerging information technology, in areas including online user-generated content, crowdsourcing, social media for e-commerce and healthcare, and emerging financial technology. In her research, a variety of quantitative approaches (e.g., econometrics, statistics, machine learning) are leveraged to discover insights from corporate datasets. Her research has been published in high-quality journals and presented at conferences. 

She teaches two Business Analytics major courses, Business Analytics II and Predictive Modeling II. The latter aims to go beyond the traditional regression approaches and to provide an overview of those modern predictive methods (e.g., Neural Network and Deep Learning, Random Forest, Boosting and Bagging) in the context of marketing, finance, and other essential business decisions.


Selected Publications

  1. “Understanding the Impact of Crowd Voting on Participation in Crowdsourcing Contests.” Journal of Management Information Systems, 2020 forthcoming.
  2. “Employee satisfaction trajectories and their effect on customer satisfaction and repatronage intentions”, Journal of the Academy of Marketing Science, Volume 47, no. 5 (2019): Pages 815-836. 
  3. "Product Engagement and Identity Signaling: The Role of Likes in Social Commerce for Fashion Products." Information & Management, Volume 56, no. 2 (2019): Pages 143-154.
  4. “The Impact of Online Incivility on Perceptions of Justice”, Journal of Interactive Marketing, Volume 44, (2018), Pages 60-81. 
  5. “Will video be the next generation of e-commerce product reviews? Presentation format and the role of product type”, Decision Support Systems, Volume 73, (2015), Pages 85-96.
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