A Competitive Model of Ranking Agencies

Abstract

This paper investigates the discrepancy among the multiple ranking lists of the same performers. It treats ranking lists as some well-positioned information products rather than the repetitive measures of performance. Hence, discrepancy stems from the differentiation rather than the measure errors. In the model, two ranking agencies have each compiled a list that ranks a set of performers for an audience. The audience weighs the two ranking lists by how much each list is promoted aggregately by the performers, and formulates a perceived ranking for each performer. In order to boost their perceived rankings, performers decide which ranking list to promote, and how much to promote. Each agency decides on the rankings to maximize the aggregate promotion devoted to its own list. In equilibrium, both ranking agencies will choose the top-bottom approach, i.e., ranking the top-ranked performer on the competing list at the bottom of its own list, to maximize the biggest ranking difference for some performers. In response, only those performers enjoying the biggest ranking difference will promote the corresponding list, while the other performers will free ride their promotion.