Please use this form to submit your study for inclusion into our database. It will be checked by a member of the Innovation Growth Lab team, who may be in contact to ask for more information. Your email address * Your name * Title * The name of the study Short summary In the context of an online software development tournament, intermediate disclosure policy increased information and signaling in the innovation environment. Final disclosure promoted higher levels of entry and effort and independent experimentation; while it generated a diversity of approaches, this led to considerable effort devoted to suboptimal approaches and overall performance achieved. A brief description of the project's goals and its current state Abstract <p>Most of society’s innovation systems – academic science, the patent system, open source, etc. – are “open”in the sense that they are designed to facilitate knowledge disclosure among innovators. An essential difference across innovation systems is whether disclosure is of intermediate progress and solutions or of completed innovations. We theorize and present experimental evidence linking intermediate versus final disclosure to an ‘incentives-versus-reuse’ tradeoff and to a transformation of the innovation search process. We find intermediate disclosure has the advantage of efficiently steering development towards improving existing solution approaches, but also has the effect of limiting experimentation and narrowing technological search. We discuss the comparative advantages of intermediate versus final disclosure policies in fostering innovation.</p> The full abstract of the study, if available Links http://ac.els-cdn.com/S0048733314001425/1-s2.0-S0048733314001425-main.pdf Links to any published papers and related discussions Authors * Affiliations Academic and other institutes that the authors of the study are members of Delivery partner Organisations involved in delivering the trial, if appropriate Year Year Year199419951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026 Month MonthJanFebMarAprMayJunJulAugSepOctNovDec Day Day12345678910111213141516171819202122232425262728293031 Journal Journal publishing the study, if available Publication stage * Working Paper Published Ongoing Research Forthcoming Discussion Paper Research theme * Entrepreneurship Innovation Business Growth Country Country or countries where this study took place. Topics What sort of topics does the study cover? Sample attributes Hypotheses / research question Prediction 1: Implementing an intermediate rather than final disclosure policy leads to lower incentives but greater follow-on reuse. Prediction 2: Implementing an intermediate rather than final disclosure policy leads innovators to tend to converge towards successful solution approaches and to engage in a lesser degree of independent experimentation. Sample Trial population and sample selection Subjects were recruited from the TopCoder platform’s existing membership of software and algorithm programmers. The posting indicated that the challenge would feature an algorithmic optimisation solution related to genomics, the solution to which was sought by Harvard Medical School (from which the problem had been sourced), that the total prize pool would be $6,000.00 and that the exercise was also being used for research purposes. The call for participation did not describe what particular problem would be solved. 733 TopCoder members signed up for the experiment. 44% were professionals, the remainder were students. Participants from India (20%), the United States (16%), China (9%) and Russia (9%) accounted for more than half of a pool that represented 69 countries. Number of treatment groups Size of treatment groups Intermediate disclosure: 245; Final disclosure: 244 Size of control group Unit of analysis Clustered? Yes No Cluster details Trial attributes Treatment description Final disclosure group: no interactions of participants competing in the project were enabled on the platform, and competitors were told interactions off the platform would result in immediate disqualification of all involved. Intermediate disclosure group: all solutions submitted by subjects in the trial-and-error development process were immediately disclosed to other participants in the group. All submitted intermediate solutions were listed and available to participants in their entirety. Mixed regime group: the first week followed the rules and procedures of Final Disclosure; the second week followed the rules and procedures of Intermediate Disclosure. Rounds of data collection Baseline data collection and method TopCoder members voluntarily signed up to participate in the contest. TopCoder collects demographic information on members as well as their historical quality of performance and volume of submissions in TopCoder's other contests. Data collection method and data collected Evaluation Outcome variables <p>Effort and incentives: Active participation rate, number of submissions per active participant. Reuse of intermediate solutions: Number of active and inactive participants who examined submissions, number of examinations of intermediate submissions by active and inactive participants.</p> Results <p>Effort and incentives: Under intermediate disclosure, participation (number of active participants) and effort (number of submissions) were lower than under final disclosure by 26% and 56%, respectively. Reuse of intermediate solutions: Disclosure and reuse in intermediate disclosure (where disclosure and reuse is permitted by definition) was widespread and frequent. Many subjects, both active and inactively participating examined high numbers of intermediate submissions. Performance patterns and trajectories: Under Final disclosure, performance patterns are less stable. Under Intermediate disclosure, patterns of performance smoothly rise over time and eventually cluster on maximal performance. Diversity of solution approaches: Fewer solutions approaches were tried by submitters in Intermediate Disclosure.</p> Intervention costs Total costs not available. Cost of the total tournament prize pool: $18,000.00. Cost benefit ratio Reference Boudreau, K., & Lakhani, K., 2015. ''Open' Disclosure of Innovations, Incentives and Follow-on Reuse: Theory on Processes of Cumulative Innovation and a Field Experiment in Computational Biology'. Research Policy vol. 44(1), pages 4–19. Citation for use in academic references
