Faculty Details

Photo of Yan  Huang

Yan Huang

PhD Candidate

PhD Candidate

PhD Job Market Candidate

Office: HBH3003
Voice: 412-268-7848
Email: yanhuang@andrew.cmu.edu
Personal Website

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Yan Huang is a graduating PhD student, and as of July 2013, she will be an Assistant Professor of Technology and Operations at the Stephen M. Ross School of Business, University of Michigan.

Yan is a quantitative modeler interested in problems related to technological innovation. Her research addresses the problems facing practitioners as they leverage crowdsourcing and social media internally and externally to improve their productivity and profitability. Her work is among the first to look into the economic processes that shape participants’ behavior in various forms of enterprise social media and crowdsourcing initiatives. She applies structural and Bayesian modeling methods to analyze issues related to technological innovation, simulates effects of changes in the platform design and introduction of new policies, and recommends policies that should lead to greater effectiveness in enterprise use of social media.  

Research Interest(s)

Topics: Crowdsourcing, Enterprise Social Media, Digital Goods, Online Marketing Methodologies: Economic Theories, Econometrics, Structural Modeling, Bayesian Modeling


B.Sc. in Information Systems and Management
Tsinghua University (2009)

Ph.D. in Information Systems and Management
Carnegie Mellon University (2013)

Media Mentions



Working Papers


A Structural Model of Employee Behavioral Dynamics in Enterprise Social Media, with Param Vir Singh and Anindya Ghose, under third round review at Management Science.


Digital Music

An Empirical Analysis of Digital Music Bundling Strategy, with Brett Danaher, Michael D. Smith and Rahul Telang, under first round review at Management Science.


The Negative Impact of Groupon Usage on Store Review: An Analytical Analysis, with Param Vir Singh and Kannan Srinivasan.

Ideastorm Paper

Crowdsourcing New Product Ideas under Consumer Learning, with Param Vir Singh and Kannan Srinivasan, under preparation for second round review at Management Science.



 Crowdsourcing Contests: A Dynamic Structural Model of the Impact of Incentive Structure on Solution Quality, with Param Vir Singh and Tridas Mukhopadhyay.


 Learning to Win in Crowdsourcing Contests: A Dynamic Structural Analysis, with Anindya Ghose and Param Vir Singh