Indika Dissanayake

Strategic effort allocation in online innovation tournaments

Abstract Online innovation tournaments, such as those hosted by crowdsourcing platforms (e.g., Kaggle), have been widely adopted by firms to evolve creative solutions to various problems. Solvers compete in these tournaments to earn rewards. In such competitive environments, it is imperative that solvers provide creative solutions with minimum effort. This article explores the factors that influence the solvers’ effort allocation decisions in a dynamic tournament setting. Specifically, comprehensive time variant data of teams that participated in crowdsourcing competitions on Kaggle were analyzed to gain insight into how solvers continually formulate strategies in light of performance feedback obtained through interim ranking. The results suggest that solvers strategically allocate their efforts throughout the contest to dynamically optimize their payoffs through balancing the probability of winning and the cost of expending effort. In particular, solvers tend to increase their efforts toward the end of tournaments or when they get closer to winning positions. Furthermore, our findings indicate that a last-minute surge in effort is more prevalent among high-skill solvers than in those with lower skill levels. In addition to providing insights that may help solvers develop strategies to improve their performance, the study has implications for the design of online crowdsourcing platforms, particularly in terms of incentivizing solvers to put forth their best effort.

Peer-recognition and Performance in Online Crowdsourcing Communities

Recent advances in information technology bring significant changes to the nature of social interactions and information exchange. Physical face-to-face communications are slowly replaced by online virtual communities. Motivated by this phenomenon, this research investigates how voluntary community involvement and self-disclosure behavior impact a members peer-recognition and task performance within a virtual crowd sourcing competition community. We collected secondary data from the discussion forums of a specialized crowd sourcing platform that focuses on data analytics projects. Our results reveal that a members community involvement improves both the peer-recognition of the member in the community and his/her performance ranking. Our findings have strategic implications to participants of virtual crowd sourcing communities and other professional online communities.