Social Structures and Reputation in Expert Review Systems

We model an expert review system where two producers competing for market share each are evaluated by two raters. Employing economics experiments, the paper examines how the rater’s incentive to provide objective feedback can be distorted in the presence of social ties and different penalty structures for assigning unobjective ratings. The results reject the self-interested model. We find that raters assign more biased ratings to help the producer they know compete, and this distortion is exacerbated when the reputation cost for rating unobjectively is lowered. Counterintuitively, when both of the raters know the same producer, the likelihood of biased ratings drops significantly. To explain the empirical regularities, we develop a behavioral economics model and show that the rater’s utility function should account not only for social preferences toward the producer, but also the rater’s psychological aversion toward favoring a producer more than the other rater. Our findings demonstrate that it is critical for policymakers to be cognizant of the nonpecuniary factors that can influence behavior in expert review systems. This paper was accepted by John List, behavioral economics.

• 저널Management Science · 66(7) · 3249–3276
• 토픽Experimental Behavioral Economics Studies · Safety Research
• DOI10.1287/mnsc.2019.3347
• 저자Kevin Chung, Keehyung Kim, Noah Lim