Screening in Multistage Contests

Problem definition: Firms seek to use the contest format to source solutions from a broader network of outside solvers. We study the application of the contest approach in multistage settings and show how and when screening of contestants between stages can produce improved contest outcomes. Methodology/results: We present an application-driven game-theoretic model to capture imperfections in screening using the true-positive rate (sensitivity) and the true-negative rate (specificity). Specifically, we consider a two-stage contest with a screening decision by the firm between the stages. Solvers face uncertainty about their probability of fit, and the final quality of the solution is dependent on the performance across both stages. We identify two mechanisms through which screening induces greater effort, namely the encouragement effect and the competitive contest effect, and characterize how screening should be tuned to the problem setting. We find that filtering out true negatives in contests with exogenous solvers’ probability of fit is optimal for solution-seeking firms. Our results indicate that in case of problems with endogenous probability of fit and less up-front complexity, coarse (imperfect) screening is beneficial in order to manage competition and stimulate greater effort, but it behooves the firm to resort to more accurate screening otherwise. We also derive nuanced results for the case when a seeker faces screening constraints and must balance screening sensitivity and specificity. Managerial implications: Our work provides firms an additional degree of freedom in terms of specific and sensitive screening to design and run contests and to better engage outside solvers. We derive actionable results and translate them into a managerial framework to help fine-tune the screening mechanism for improved contest performance.