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Yili (Kevin) Hong

Yili (Kevin) Hong

Assistant Professor
Information Systems

Department
Contact
Office:BA 319G
Mailing Address:
Main Campus
PO BOX 874606
Tempe, AZ 85287-4606

Phone: 480-727-4003
Fax: 480-727-0881
Email: hong@asu.edu

View Vita

Job Title(s)
Assistant Professor 

Education
Ph.D. in Management Information Systems, Temple University, 2014;

B.A. in Management, Beijing Foreign Studies University, 2009;

B.A. in English, Beijing Foreign Studies University, 2009. 

Research Areas
Online Labor Markets, Product Fit Uncertainty, Mobile, Social Media

Preferred Methodology
Econometrics, field experimentation

Recent Consulting
Freelancer.com, Kamino Labs, fits.me

Current Projects
Open Versus Sealed Bid Auctions: Empirical Evidence from Online Labor Markets

Is the World Truly “Flat”? Evidence from Online Labor Markets

Measuring Product Type with Dynamics of Online Product Review Variances: A Theoretical Model and Empirical Applications

What Happens when Word-of-Mouth Goes Mobile? 

The Nature and Effects of Distance Bias in Consumer Evaluation

On Bid Similarity and Evaluation Costs: Evidence from Online Labor Auctions

Academic Positions Held
Arizona State University: 2014-present. 

Career and Recent Professional Awards; Teaching Awards

Best Conference Paper (nominated), International Conference on Information Systems (2014)

Best Dissertation Award (first place), Fox School of Business, Temple University, 2014

Best Conference Paper (runner up), International Conference on Information Systems (2012)

Best Conference Paper (runner up), America's Conference on Information Systems (2012)

Doctoral Consortium Member, International Conference on Information Systems (2013)

Best Teaching Award, Temple University (2013)

 

Representative Publications

Hong, Y. and P. A. Pavlou (2014). “Product Fit Uncertainty in Online Markets: Nature, Effects, and Antecedents.” Information Systems Research 25(2), pp. 328-344.

Dimoka, A., Y. Hong and P. A. Pavlou (2012). “On Product Uncertainty in Online Markets: Theory and Evidence”, MIS Quarterly 32(3), pp. 395-426.