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University of Delaware - Alfred Lerner College of Business & Economics

Xiao Fang

Photograph Image of Xiao Fang
Title Professor of MIS, JPMorgan Chase Fellow
Email xfang@nospam5c6a495a96e79.udel.edu
Office 357 Purnell Hall
Phone (302) 831-3806
Biography

Education

  • Ph.D. in management information systems, University of Arizona
  • B.S., M.S. in management information systems, Fudan University, China

Select Publications

  • He, J., Fang, X., Liu, H., Li, X. 2018. Mobile App Recommendation: An Involvement-Enhanced Approach. MIS Quarterly, forthcoming.
  • Fang, X., and Hu, P. 2018. Top Persuader Prediction for Social Networks. MIS Quarterly 42 (1), pp. 63-82.
  • Li, Z., Fang, X., and O. R. Liu Sheng. 2018. A Survey of Link Recommendation for Social Networks: Methods, Theoretical Foundations, and Future Directions. ACM Transactions on Management Information Systems 9 (1) Lead Article.
  • Hu, P., Hu, H., and Fang, X. 2017. Examining the Mediating Roles of Cognitive Load and Performance Outcomes in User Satisfaction with a Website: A Quasi-Field Experiment. MIS Quarterly 41 (3), pp. 975-987.
  • Li, Z.*, Fang, X.*, Bai, X. and O. R. Liu Sheng. 2017. Utility-based Link Recommendation for Online Social Networks. Management Science, 63(6), pp. 1938-1952. (*Equal contribution).
  • Fang, X., Liu Sheng, O. R., and P. Goes. 2013. When Is the Right Time to Refresh Knowledge Discovered from Data? Operations Research, 61(1), pp. 32-44.
  • Fang, X., Hu, P., Li., Z., and W. Tsai. 2013. Predicting Adoption Probabilities in Social Networks. Information Systems Research, 24(1), pp. 128-145.
  • Fang, X. 2013. Inference-based Naive Bayes: Turning Naive Bayes Cost-sensitive. IEEE Transactions on Knowledge and Data Engineering, 25(10), pp. 2302-2313.
  • Fang, X., Hu, P., Chau, M., Hu, H., Yang, Z. and Liu Sheng, O. R. 2012. A Data-driven Approach to Measure Website Navigability. Journal of Management Information Systems, 29(2), pp.173-212.
  • Zhang, J., Fang, X., and Liu Sheng, O. R. 2007. Online Consumer Search Depth: Theory and New Findings. Journal of Management Information Systems, 23(3), pp. 71-95.
  • Fang, X., Chau, M., and Liu Sheng, O. R. 2007. ServiceFinder: A Method Towards Enhancing E-service Portals. ACM Transactions on Information Systems, 25(4) Article 17.
  • Fang, X., Liu Sheng, O. R., Gao, W., and Iyer, B. 2006. A Data Mining Based Prefetching Approach to Caching For Network Storage Systems. INFORMS Journal on Computing, 18(2), pp. 267-282.
  • Fang, X., and Liu Sheng, O. R. 2004. LinkSelector: A Web Mining Approach to Hyperlink Selection for Web Portals. ACM Transactions on Internet Technology, 4(2), pp. 209-237.

Awards & Honors

  • Lerner College Outstanding Scholar Award, 2017.
  • Accounting and MIS Department Faculty Excellence in Research Award, 2017.
  • INFORMS Design Science Award, 2016.
  • JPMorgan Chase Fellow, 2015–
  • David Eccles Emerging Scholar, University of Utah, 2013 – 2015
  • University Incentive Seed Grant, University of Utah, 2012
  • Outstanding Faculty, presented by the students of Operations and Information Systems, University of Utah, 2011
  • Most Influential Teacher, recognized by the Master of IS program, University of Utah, 2010
  • Outstanding Junior Researcher Award, College of Business Administration, University of Toledo, 2008
  • Robert Pearson Memorial Award for the Best Contribution to Theory, Northeast Decision Science Institute, 2008
  • University Summer Research Awards and Fellowships, University of Toledo, 2007

Curriculum Vitae

Download Xiao Fang’s CV (PDF)

Website

Visit Xiao Fang’s Personal Webpage