Person: Boudreau, Kevin
Loading...
Email Address
AA Acceptance Date
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Boudreau
First Name
Kevin
Name
Boudreau, Kevin
6 results
Search Results
Now showing 1 - 6 of 6
Publication Cumulative Innovation & Open Disclosure of Intermediate Results: Evidence from a Policy Experiment in Bioinformatics(2014-01-13) Boudreau, Kevin; Lakhani, KarimRecent calls for greater openness in our private and public innovation systems have particularly urged for more open disclosure and granting of access to intermediate works–early results, algorithms, materials, data and techniques–with the goals of enhancing overall research and development productivity and enhancing cumulative innovation. To make progress towards understanding implications of such policy changes we devised a large-scale field experiment in which 733 subjects were divided into matched independent subgroups to address a bioinformatics problem under either a regime of open disclosure of intermediate results or, alternatively, one of closed secrecy around intermediate solutions. We observe the cumulative innovation process in each regime with fine-grained measures and are able to derive inferences with a series of cross-sectional comparisons. Open disclosures led to lower participation and lower effort but nonetheless led to higher average problem-solving performance by concentrating these lesser efforts on the most performant technical approaches. Closed secrecy produced higher participation and higher effort, while producing less correlated choices of technical approaches that participants pursued, resulting in greater individual and collective experimentation and greater dispersion of performance. We discuss the implications of such changes to the ongoing theory, evidence and policy considerations with regards to cumulative innovation.Publication From Crowds to Collaborators: Initiating Effort & Catalyzing Interactions Among Online Creative Workers(2014-04-24) Boudreau, Kevin; Gaule, Patrick; Lakhani, Karim; Riedl, Christoph; Woolley, Anita WilliamsOnline collaborative platforms have emerged as a complementary approach to traditional organizations for coordinating the collective efforts of creative workers. However, it is surprising that they result in any productive output as individuals often work without direct monetary incentives while collaborating with unknown others. In this paper, we distinguish the conditions necessary for eliciting effort from those affecting the quality of interdependent teamwork. We consider the role of incentives versus social processes in catalyzing collaboration. We test our hypotheses using a unique data set of 260 individuals randomly assigned to 52 teams tasked with developing working solutions to a complex innovation problem over 10 days, with varying monetary incentives. We find that levels of effort are driven by cash incentives and the presence of other interacting teammates. The level of collaboration, by contrast, was not sensitive to cash incentives. Instead, individuals increased their communication if teammates were also actively participating. Additionally, team performance is uniquely driven by the level of emergent interdependence, as indexed by the diversity of topics discussed and the temporal coordination of activity in short focused time periods. Our results contribute to the literature on how alternative organizational forms can be designed to solve complex innovation tasks.Publication Performance Responses to Competition Across Skill-Levels in Rank Order Tournaments: Field Evidence and Implications for Tournament Design(2014-01-13) Boudreau, Kevin; Lakhani, Karim; Menietti, MichaelTournaments are widely used in the economy to organize production and innovation. We study individual contestant-level data from 2,796 contestants in 774 software algorithm design contests with random assignment. Precisely conforming to theory predictions, the performance response to added contestants varies non-monotonically across contestants of different abilities, most respond negatively to competition, and highest-skilled contestants respond positively. In counterfactual simulations, we interpret a number of tournament design policies (number of competitors, prize allocation and structure, divisionalization, open entry) as a means of reconciling non-monotonic incentive responses to competition, effectively manipulating the number and skills distribution of contestants facing one another.Publication Field Evidence on Individual Behavior & Performance in Rank-Order Tournaments(2012-09-04) Boudreau, Kevin; Helfat, Constance E.; Lakhani, Karim; Menietti, MichaelEconomic analysis of rank-order tournaments has shown that intensified competition leads to declining performance. Empirical research demonstrates that individuals in tournament-type contests perform less well on average in the presence of larger number of competitors in total and superstars. Particularly in field settings, studies often lack direct evidence about the underlying mechanisms, such as the amount of effort, that might account for these results. Here we exploit a novel dataset on algorithmic programming contests that contains data on individual effort, risk taking, and cognitive errors that may underlie tournament performance outcomes. We find that competitors on average react negatively to an increase in the total number of competitors, and react more negatively to an increase in the number of superstars than non-superstars. We also find that the most negative reactions come from a particular subgroup of competitors: those that are highly skilled, but whose abilities put them near to the top of the ability distribution. For these competitors, we find no evidence that the decline in performance outcomes stems from reduced effort or increased risk taking. Instead, errors in logic lead to a decline in performance, which suggests a cognitive explanation for the negative response to increased competition. We also find that a small group of competitors, who are at the very top of the ability distribution (non-superstars), react positively to increased competition from superstars. For them, we find some evidence of increased effort and no increase in errors of logic, consistent with both economic and psychological explanations.Publication Colocation and Scientific Collaboration: Evidence from a Field Experiment(2012-09-04) Boudreau, Kevin; Ganguli Prokopovych, Ina; Gaule, Patrick; Guinan, Eva; Lakhani, KarimWe present the results of a field experiment conducted within the Harvard Medical School system of hospitals and research centers to understand how colocation impacts the likelihood of scientific collaboration. We introduce exogenous colocation and face-to-face interactions for a random subset of biomedical researchers responding to an opportunity to apply for a research grant. While the overall baseline likelihood of any two researchers collaborating is small, we find that random colocation significantly increases the likelihood of pair-level co-application by almost 70%. The effect of exogenous colocation on subsequent collaboration was greater for previous coauthors, pairs including a woman, and pairs researching similar clinical areas. Our results suggest that matching between scientists may be subject to considerable frictions—even among those in relatively close geographic proximity and in the same organizational system. At the same time, even a brief and focused intervention facilitating face-to-face interactions can provide information that impacts the formation of scientific collaborations.Publication The Novelty Paradox & Bias for Normal Science: Evidence from Randomized Medical Grant Proposal Evaluations(2012-12-06) Boudreau, Kevin; Guinan, Eva; Lakhani, Karim; Riedl, ChristophCentral to any innovation process is the evaluation of proposed projects and allocation of resources. We investigate whether novel research projects, those deviating from existing research paradigms, are treated with a negative bias in expert evaluations. We analyze the results of a peer review process for medical research grant proposals at a leading medical research university, in which we recruited 142 expert university faculty members to evaluate 150 submissions, resulting in 2,130 randomly-assigned proposal-evaluator pair observations. Our results confirm a systematic penalty for novel proposals; a standard deviation increase in novelty drops the expected rank of a proposal by 4.5 percentile points. This discounting is robust to various controls for unobserved proposal quality and alternative explanations. Additional tests suggest information effects rather than strategic effects account for the novelty penalty. Only a minority of the novelty penalty could be related to perceptions of lesser feasibility of novel proposals.