Searching together versus searching apart: Evidence from Kaggle

Abstract

How does the mode of search—independently or jointly—affect collective search, a central component of organizational adaptation and innovation? Using naturally occurring data from a strongly incentivized online competition platform, we find that compared to their counterfactuals that search apart, groups searching together exhibit less exploration in their search outcomes as noted in prior experimental and computational modeling studies. However, groups searching together stimulate a greater number of search attempts from their members than groups searching apart, an effect that has so far remained unnoticed. Further, both search attempts and exploration contribute positively to search performance. This suggests that the choice of search mode should depend on the demands of strategic contexts that make either the variety or volume of solutions relatively more important for collective search. Managerial Summary How members of a team interact when looking for solutions to problems shapes their success. Using evidence from online machine learning competitions, we find that looking for solutions together encourages members to examing more alternatives but narrows the range of these ideas, while working independently generates greater variety but fewer alternatives being examined. We propose that the choice between the two depends on context. When innovation requires novel, distinctive solutions, as in early‐stage R&D, independent work may be more effective. When speed and volume matter, as in patent races or crowded digital markets, searching for solutions together delivers faster iteration. Managers can improve innovation outcomes by aligning the mode of teamwork with the strategic demands of the problem.