The “self-organizing” of online crowds — or workers, more generally — into teams is a non-trivial problem of coordination and matching, in a context in which other parties are simultaneously competing for partners. Here, we experimentally investigate the capacity for workers in online crowds to self-organize into teams, within a scientific crowdsourcing contest. We compare matching outcomes and performance to those in a comparison group in which we eliminate the coordination and matching problem altogether (by directly assigning individuals to Pareto efficient teams). Online crowd members do remarkably well relative to the benchmark achieving 13% more functioning teams. Teams also tended to be more effective, by several measures. (We found no evidence these levels depending on the size of the self-organizing pool of workers.) Conditional on having formed, the self-organizing teams also benefit from several advantages in performance.
This article examines an experiment in open innovation applied to scientific research on Type 1 diabetes at Harvard Medical School. In the traditional research process in academic medicine, a single research team typically carries through each stage of the process — from generating the idea to carrying out the research and publishing the results. Harvard Catalyst, a pan-Harvard agency with a mission to speed biomedical research from the lab to patients' bedsides, modified the traditional grant proposal process as an experiment in bringing greater openness into every stage of research. Participation was successfully extended to nontraditional actors. With support from Dr. William Chin, the executive dean for research at Harvard Medical School and a former vice president of research at Eli Lilly (an early adopter of open innovation), Harvard Catalyst started with the front end of the innovation system by opening up the process of generating research questions. Instead of focusing on identifying individuals who might tackle a tough research problem, Harvard Catalyst wanted to allow an open call for ideas in the form of a prize-based contest to determine the direction of the academic research. This might lead to potentially relevant questions not currently under investigation or largely ignored by the Type 1 diabetes research community. Harvard Catalyst partnered with the InnoCentive online contest platform to initiate the idea generation process. Participants had to formulate well-defined problems and/or hypotheses to advance knowledge about Type 1 diabetes research in new and promising directions. In the end, 150 new hypotheses and research pathways were proposed. Teams were invited to propose projects on the 12 most promising of these; today, seven teams are carrying out the research. The Harvard Catalyst experience suggests that open-innovation principles can be adopted even within a well-established and experienced innovation-driven organization.
Teaching Note for HBS Case 610-032.
TopCoder's crowdsourcing-based business model, in which software is developed through online tournaments, is presented. The case highlights how TopCoder has created a unique two-sided innovation platform consisting of a global community of over 225,000 developers who compete to write software modules for its over 40 clients. Provides details of a unique innovation platform where complex software is developed through ongoing online competitions. By outlining the company's evolution, the challenges of building a community and refining a web-based competition platform are illustrated. Experiences and perspectives from TopCoder community members and clients help show what it means to work from within or in cooperation with an online community. In the case, the use of distributed innovation and its potential merits as a corporate problem solving mechanism is discussed. Issues related to TopCoder's scalability, profitability, and growth are also explored.