Team Composition and Incentive Design in Collaborative Product Development

Abstract

Choosing the right development team is crucial for companies. We investigate how project collaboration requirements and uncertainty levels affect the choice between “specialists” with higher levels of task-specific abilities and “generalists” with higher levels of collaboration skills. We also examine how these factors affect optimal team incentives. In addition to performance-enhancing helping, we consider another type of collaboration that has received less attention in the incentive literature: information-sharing, which can reduce uncertainty and lead to more compatible design decisions. In the case of helping, we show that if uncertainty is high then specialists might be preferred in order to reduce risk exposure—even if their task-specific abilities are only slightly better. Conversely, if information-sharing can significantly reduce uncertainty then generalists may be favored even if their task-specific abilities are much lower. Our study also reveals that task and collaboration incentives can be either complements or substitutes depending on the type of collaboration and level of project uncertainty: in projects that benefit from helping, firms will always substitute task incentives for collaboration incentives when selecting a team of specialists (rather than a team of generalists), yet this need not be the case with information-sharing. In such projects, it can be optimal to offer higher task incentives and also higher collaboration incentives to a team of specialists (than to a team of generalists) even though specialists’ collaboration skills are relatively lower.