Recall that today the dominant pattern in household sector innovation is that all innovation process steps are completed by a single individual. As table 2.6 documents, studies of household sector innovation in the United Kingdom, the United States, and Japan have shown that in those countries about 90 percent of innovations are made by individuals acting alone. In Finland and South Korea, 72 percent of innovations by consumers are made by individuals acting alone, with the remainder being collaborative efforts.
As was discussed earlier, an individual acting alone may be well prepared in terms of personality traits to succeed at one innovation stage but less well prepared for the next stage, where the identical traits are less helpful. When innovation is collaborative, it may be possible to solve this problem: Collectively the collaborators may have all the personality traits needed to successfully complete all three stages of innovation. A start-up firm uses this strategy when it puts different types of people on a team. When a new business venture is created to develop, produce, and market an innovation, it is a common prescription for success to recruit a group of individuals who collectively have expertise in all tasks relevant to the project (Akgun, Keskin, and Byrne 2010; Ensley and Hmieleski 2005; Vissers and Dankbaar 2002). The same strategy is often used by the personnel departments of larger firms (Muchinsky and Monahan 1987; Kristof 1996).
Innovations developed collaboratively also diffuse more frequently than do innovations developed by single individuals. The difference can be quite striking, as was noted in chapter 5. Thus, recall that Ogawa and Pongtanalert (2013) found that when individuals belonged to communities with a shared interest in the innovation they developed, the adoption rate by peers was 48.5 percent. When innovators did not belong to such communities, the adoption rate was only 13.3 percent. Other literature supports these patterns. For example, it is clear that innovators participating in communities tend to share information, including information about innovations they have developed, with other members (Morrison, Roberts, and von Hippel 2000; Raasch, Herstatt, and Lock 2008).
In view of the evidence of the benefits associated with collaborative innovation, policymakers and practitioners may wish to explore ways to increase the proportion of collaborative projects in the household sector. Increasing the availability of innovation facilities such as makerspaces is one potentially useful practical step. Such facilities offer access to sophisticated prototyping tools; they also enable potential collaborators to congregate and to discover one another. Also likely to be helpful are online community forums in which people can post their innovation-related interests and find one another at low cost. One excellent example of such a forum is https://patient-innovation. com/, a non-profit website that provides a collection point for information on patient-developed innovations (Patient Innovation 2016). That website is also designed to support online discussion and sharing of innovation-related information by medical patients and people interested in helping them (Habicht, Oliveira, and Shcherbatiuk 2012). More generally, of course, inexpensive Internet access and toolkits for collaborative design, such as those supplied by and for open source software development communities, can support collaboration at a distance.