Is novelty trading off with practicality? In new research forthcoming in MIS Quarterly (1), Harris Kyriakou (ESSEC Business School) and his colleagues Jeffrey Nickerson (Stevens Institute of Technology) and Ann Majchrzak (University of Southern California) explored how novelty, and the structure of preexisting designs affect product development processes in online innovation communities.
What are online innovation communities?
Online innovation communities, rather than focusing on participants’ profiles, focus on the development of products. They’re distinguishable from other online knowledge production communities like Wikipedia and open source software forums in three key ways:
They don’t have one single production goal, with the content being evaluated based on its novelty, rather than the knowledge it includes
They are designed around artifacts made by individuals, not team-based projects
Novelty plays a crucial role in retaining and keeping participants engaged with the community
In online innovation communities, the term “design landscape” is used to refer to the place where the search for a design occurs (2). An array of artifacts forms this design landscape, and members of the community search the landscape for new designs and add their own. The idea is to add and identify artifacts that are novel in relation to other artifacts: novel artifacts capture people’s attention. However, past work has also suggested that novelty creates uncertainty, leading associated costs to increase (3, 4).
These communities are becoming increasingly popular, to the extent that some of the major intellectual property players like IBM, Microsoft, and Apple are getting in on the game by donating software, encouraging the participation of their employees, as well as using these communities as a source of inspiration in product development.
In these communities, participants are looking for novelty, which means looking for novel designs. Typically, novelty is examined and assessed unidimensionally. However, novelty can take different forms. Here, the researchers looked at both visual and verbal novelty. Visual novelty refers to how unique the shape of a newly created product design is compared to anything pre-existing, while verbal novelty relates to the uniqueness of the text associated with the newly developed products, which typically contain information about its purpose and function.
In this study, they also looked at the structure of the design landscape affecting what was being developed — how product designs were distributed, clustered, and organized. The level of structure impacts the search process, since it impacts how easy it is to find designs and identify gaps in the market. Since people process visual and verbal information differently, participants are likely to also process visual and verbal structure differently.
On one hand, highly-structured landscapes can inhibit creativity if participants feel like they can’t contribute a novel artifact, making it harder to develop verbally novel designs. On the other hand, since visual search is typically harder, having a more structured landscape can actually make it easier to identify a gap where a visually novel design can be contributed.
To better understand online innovation communities, the researchers conducted an analysis including over 35,000 Thingiverse design artifacts, Thingiverse is the largest 3D printing and open source hardware community to date. In Thingiverse, participants develop a wide range of product designs intended for 3D printing, including drones, robots, 3D printers, and sometimes even cars. They collected data for 4.5 years, including the 3D digital blueprints of products and their text descriptions.
The researchers provided strong evidence that visual and verbal novelty had distinct effects on both the consumption and production of product designs. Structure plays a role as well: it’s more likely that visually novel artifacts will be produced in highly-structured landscapes, whereas verbally novel artifacts are more likely to emerge from less-structured landscapes. Further, product designs associated with high visual novelty, or high verbal novelty, lead to higher rates of consumption and production. That said, when a product design exhibits high degrees of both visual and verbal novelty, its consumption and production tend to be lower. This finding underlines the need to consider different types of novelty separately, as their effects may be distinct, and their combination may prove undesirable.
Their findings also look at different aspects of the search process:
When participants search for new designs to consume, they learn about the landscape’s structure and how to identify gaps
When they contribute, they evaluate whether to reuse and update an existing product design using existing product designs — showcasing that it’s important to consider both consumption and production, as these processes are inherently intertwined
When participants add new designs, they alter the design landscape and its structure, affecting how participants perceive and interact with product designs moving forward.
By breaking down the search process in that way, we can see that understanding online innovation communities involves understanding the interrelationships between artifacts, individuals, and design landscapes. This research also highlights the fact that design attributes impact people’s activities in different ways, as verbal and visual novelty had distinct effects on consumption and production.
With the rise of online innovation communities and their increased use as a source of innovation for leading organizations, it’s becoming crucial for managers to understand how they tick. For managers that are moderating such communities, it’s worth advising participants that being novel on one attribute may be better than being novel on both, and developing systems that can encourage community participants to develop product designs that are very novel in one dimension. Understanding these relationships can also help managers and participants alike to predict more accurately which product designs are more likely to become highly successful. Finally, this research highlights the importance of studying design landscapes in general, rather than merely focusing on individual users or product designs.
Kyriakou, H., Nickerson, J. V., & Majchrzak, A. (2022). Novelty and the structure of design landscapes: A relational view of online innovation communities. MIS Quarterly, 46(3).
Baldwin, C., Hienerth, C., and Von Hippel, E. (2006). How user innovations become commercial products: A theoretical investigation and case study. Research Policy, 35(9), 1291-1313.
Arentze, T., and Timmermans, H. (2005). Information gain, novelty seeking and travel: A model of dynamic activity-travel behavior under conditions of uncertainty. Transportation Research Part A: Policy and Practice, 39, 125-145.
Boudreau, K. J., Guinan, E. C., Lakhani, K. R., and Riedl, C. (2016). Looking across and looking beyond the knowledge frontier: Intellectual distance, novelty, and resource allocation in science. Management Science, 62, 2765-2783.