The Role of Problem Specification in Crowdsourcing Contests for Design Problems: A Theoretical and Empirical Analysis

This paper studies the role of seekers' problem specification in crowdsourcing contests for design problems. Platforms hosting design contests offer detailed guidance for seekers to specify their problems when launching a contest. Yet, problem specification in such crowdsourcing contests is something the theoretical and empirical literature has largely overlooked. We aim to fill this gap by offering an empirically-validated model to generate insights for the provision of information at contest launch. We develop a game-theoretic model featuring different types of information (categorized as “conceptual objectives” or “execution guidelines”) conveyed in problem specifications, and assess their impact on design processes and submission qualities. Real-world data is used to empirically test hypotheses and policy recommendations generated from the model, and a quasi-natural experiment provides further empirical validation. We show theoretically and verify empirically that, with more conceptual objectives disclosed in the problem specification, the number of participants in a contest eventually decreases; with more execution guidelines in the problem specification, the trial effort provision by each participant increases; and the best solution quality always increases with more execution guidelines, but eventually decreases with more conceptual objectives. We find that, to maximize the best solution quality in crowdsourced design problems, seekers should always provide more execution guidelines, and only a moderate number of conceptual objectives.