Incentives and Problem Uncertainty in Innovation Contests: An Empirical Analysis

Kevin J. Boudreau; Nicola  Lacetera; Karim R. Lakhani

Article | Management Science | May 2011

Incentives and Problem Uncertainty in Innovation Contests: An Empirical Analysis

by Kevin J. Boudreau, Nicola Lacetera and Karim R. Lakhani

Abstract

Contests are a historically important and increasingly popular mechanism for encouraging innovation. A central concern in designing innovation contests is how many competitors to admit. Using a unique data set of 9,661 software contests, we provide evidence of two coexisting and opposing forces that operate when the number of competitors increases. Greater rivalry reduces the incentives of all competitors in a contest to exert effort and make investments. At the same time, adding competitors increases the likelihood that at least one competitor will find an extreme-value solution. We show that the effort-reducing effect of greater rivalry dominates for less uncertain problems whereas the effect on the extreme value prevails for more uncertain problems. Adding competitors thus systematically increases overall contest performance for high-uncertainty problems. We also find that higher uncertainty reduces the negative effect of added competitors on incentives. Thus uncertainty and the nature of the problem should be explicitly considered in the design of innovation tournaments. We explore the implications of our findings for the theory and practice of innovation contests.

Keywords: Motivation and Incentives; Problems and Challenges; Risk and Uncertainty; Innovation and Invention; Management Analysis, Tools, and Techniques; Value; Software; Competition; Performance; Theory; Practice;

Format: Print

21 pages

Find at Harvard

Citation:

Boudreau, Kevin J., Nicola Lacetera, and Karim R. Lakhani. "Incentives and Problem Uncertainty in Innovation Contests: An Empirical Analysis." Management Science 57, no. 5 (May 2011): 843–863.

True North was a private equity fund that specialized in the growth and buyout of mid-market, India-centric companies. The leadership team initially believed that technology was not core to traditional businesses and steered clear of new age technology-oriented businesses. Then, in 2007, True North invested in Meru Cabs, a ride-sharing service with a growing fleet of cabs that had to change its business model with the launch of tech-based platforms like Uber. This experience led True North to significantly alter its stance on the importance of technology-powered business models. The team learned that all businesses needed to effectively become technology businesses to remain relevant. True North initiated the “Analytics, Algorithms and Artificial Intelligence” (3A) project. A system, Kelp, was designed and developed internally to facilitate the transformation of True North into an AI-first firm based on the introduction of data-driven decision making and productivity-enhancing digital tools. In 2020, as different elements of Kelp were launched, the leadership team met to discuss the future of this technology.

Faculty & Research

Incentives and Problem Uncertainty in Innovation Contests: An Empirical Analysis

Abstract

Citation:

About the Author

More from the Author