We investigate the factors driving workers’ decisions to generate public goods inside an organization through a randomized solicitation of workplace improvement proposals in a medical center with 1200 employees. We find that pecuniary incentives, such as winning a prize, generate a threefold increase in participation compared to non-pecuniary incentives alone, such as prestige or recognition. Participation is also increased by a solicitation appealing to improving the workplace. However, emphasizing the patient mission of the organization led to countervailing effects on participation. Overall, these results are consistent with workers having multiple underlying motivations to contribute to public goods inside the organization consisting of a combination of pecuniary and altruistic incentives associated with the mission of the organization.
InnoCentive.com enables clients to tap into internal and external solver networks to address various business issues. In 2008, InnoCentive introduced "InnoCentive@Work" (lC@W), which recognized clients' reluctance to share problems and solutions with an external network. Instead, IC@W enabled clients to foster open collaboration amongst its own employees. IC@W became the fastest growing product in InnoCentive's portfolio. In 2010, InnoCentive added "team project rooms" which allowed small groups of solvers from InnoCentive's community to openly add posts and discussion threads after agreeing to the confidentiality and IP transfer requirements of the client. The case raises the questions of how the team room concept could be improved and how clients could be convinced of its benefits.
In summary, we show that a prize-based contest on a commercial platform can effectively recruit skilled individuals to apply their knowledge to a big-data biomedical problem. Deconstruction and transformation of problems for a heterogeneous solver community coupled with adequate data to produce and validate results can support solution diversity and minimize the risk of sub-optimal solutions that may arise from limited searches. In addition to the benefits of generating new knowledge, this strategy may be particularly useful in situations where the computational or algorithmic problem, or potentially any science problem, represents a barrier to rapid progress but where finding the solution is not itself the major thrust of the investigator’s scientific effort. The America Competes Act passed by the US Congress provides funding agencies with the authority to administer their own prize-based contests and paves the way for establishing how grant recipients might access commercial prize platforms to accelerate their own research.
The public phase of a capital campaign is typically launched with the announcement of a large seed donation. Andreoni (1998) argues that such a fundraising strategy may be particularly effective when funds are being raised for projects that have fixed production costs. The reason is that when there are fixed costs of production simultaneous giving may result in both positive and zero provision equilibria. Thus absent announcements donors may get stuck in an equilibrium that fails to provide a desirable public project. Andreoni (1998) demonstrates that such inferior outcomes can be eliminated when the fundraiser initially secures a sufficiently large seed donation. We investigate this model experimentally to determine whether announcements of seed money eliminate the inefficiencies that may result under fixed costs and simultaneous provision. To assess the strength of the theory we examine the effect of announcements in both the presence and absence of fixed costs. Our findings are supportive of the theory for sufficiently high fixed costs.
This supplementary case follows up on an innovative R&D approach by Beiersdorf,a skin care and cosmetics company. The case relates what happened to the product launched by Beiersdorf, to its Nivea line, following the events of the A case, and how the commercial success of the product informed thinking by leaders in R&D for the future.
We report results of a natural field experiment conducted at a medical organization that sought contribution of public goods (i.e., projects for organizational improvement) from its 1200 employees. Offering a prize for winning submissions boosted participation by 85 percent without affecting the quality of the submissions. The effect was consistent across gender and job type. We posit that the allure of a prize, in combination with mission-oriented preferences, drove participation. Using a simple model, we estimate that these preferences explain about a third of the magnitude of the effect. We also find that these results were sensitive to the solicited person’s gender.
This case presents the Myelin Repair Foundation's accelerated research collaboration model for drug discovery. It highlights the challenges of building a multi-disciplinary and multi-institutional research collaboration that is attempting to create a treatment for multiple sclerosis based on a novel scientific approach. The case provides details on how norms of academic research and intellectual property had to be updated to enable collaboration. The current dilemma facing the CEO and COO of the foundation relates to setting strategic priorities for research so that a treatment for MS can be ready in the next ten years. The strategic choices need to account for the complexities of drug discovery, the uncertainty of commercial partners' interest in the therapeutic approach and the constrained donor-based fundraising environment.
Scientists typically self-organize into teams, matching with others to collaborate in the production of new knowledge. We present the results of a field experiment conducted at Harvard Medical School to understand the extent to which search costs affect matching among scientific collaborators. We generated exogenous variation in search costs for pairs of potential collaborators by randomly assigning individuals to 90-minute structured information-sharing sessions as part of a grant funding opportunity for biomedical researchers. We estimate that the treatment increases the baseline probability of grant co-application of a given pair of researchers by 75% (increasing the likelihood of a pair collaborating from 0.16 percent to 0.28 percent), with effects higher among those in the same specialization. The findings indicate that matching between scientists is subject to considerable frictions, even in the case of geographically-proximate scientists working in the same institutional context with ample access to common information and funding opportunities.
The case describes Siemens, a worldwide innovator in the Energy, Healthcare, Industry, and Infrastructure & Cities sectors, and its efforts to develop and commercialize new R&D through open innovation, including internal and external crowdsourcing contests. Emphasis is placed on exploring actual open innovation initiatives within Siemens and their outcomes. These include creating internal social- and knowledge-sharing networks and utilzing third party platforms to host internal and external contests. Industries discussed include energy, green technology, infrastructure and cities, and sustainability. In addition, the importance of fostering a collaborative online environment and protecting intellectual property is explored.
This paper discusses several challenges in designing field experiments to better understand how organizational and institutional design shapes innovation outcomes and the production of knowledge. We proceed to describe the field experimental research program carried out by our Crowd Innovation Laboratory at Harvard University to clarify how we have attempted to address these research design challenges. This program has simultaneously solved important practical innovation problems for partner organizations, like NASA and Harvard Medical School (HMS), while contributing research advances, particularly in relation to innovation contests and tournaments. We conclude by proceeding to highlight the opportunity for the scholarly community to develop a “science of innovation” that utilized field experiments as means to generate knowledge.
Teaching Note for HBS Case 608-170
InnoCentive.com, a firm connecting R&D labs of large organizations to diverse external solvers through innovation contests, has to decide if it will enable collaboration in its community. Case covers the basics of a distributed innovation system works and the advantages of having external R&D. Links how concepts of open source are applied to a non-software setting. Describes the rationale for participation by solvers in innovation contests and the benefits that accrue to firms. Raises the issue if a community can be shifted to collaboration when competition was the basis of prior interaction.
The case describes the efforts of Beiersdorf, a worldwide leader in the cosmetics and skin care industries, to generate and commercialize new R&D through open innovation using external crowds and "netnographic" analysis. Beiersdorf, best known for its consumer brand Nivea, has a rigorous R&D process that has led to many successful product launches, but are there areas of customer need that are undervalued by the traditional process? A novel online customer analysis approach suggests untapped opportunities for innovation, but can the company justify a launch based on this new model of research?
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.