Lijia "Karen" Xie, PhD
Joy Burns Center 331
Assistant Professor
Fritz Knoebel School of Hospitality Management
Lijia "Karen" Xie

Biography at a Glance

Karen Xie is an Assistant Professor of Hospitality Analytics at the Daniels College of Business, University of Denver. Her research interests focus on the use of technology and data analytics to solve business problems. Her work relies primarily on econometrics and machine learning using large-scale business data.

Prior to pursuing her academic career, Karen worked as an analyst at the strategy consulting group of Accenture. During her tenure at DU, she has been an analytics researcher/consultant for industry leaders, including Expedia, Sage Hospitality, UBS, Unilever, Denver City Council, Smith Travel Research, Stonebridge Hotel Management Companies, Globus Family of Brands, Street Source Marketing, Aparium Hotel Group, Holiday Inn Express, Restaurant Solutions, Callan Associate, and Mars, Incorporated. Karen has extensive experience working internationally and is a keen observer of the Silicon Valley and the tech industry in China.

Karen is an active scholar in both information systems and hospitality. Her interdisciplinary work has been published at Journal of Management Information Systems (FT50), International Journal of Hospitality Management, International Journal of Contemporary Hospitality Management, Journal of Hospitality & Tourism Research, Cornell Hospitality Quarterly, among others. She is an active reviewer for Management Science, Information Systems Research, Journal of Management Information Systems, among others.

Outside of work, Karen is an enthusiast for ski. During the winter, she is often found on double-diamond ski runs in Colorado’s epic mountains. Karen holds a Ph.D. from Temple University Fox School of Business, an M.Phil from the Hong Kong Polytechnic University, and a Bachelor from Fudan University in Shanghai.


Areas of Work

  • Digital Transformations in the Service Industry
  • Peer-to-peer Markets
  • FinTech
  • Business Analytics with Statistics and Econometrics
  • Machine Learning for Predictive Modeling
  • Visualization using Big Data