Dominant communities and dominant designs: Community-based innovation in the context of the technology life cycle

Abstract

Online community-based innovation-whether through self-organized communities, firm-community collaborations, or innovation contests and crowdsourcing-is increasingly used as a source of technological advances, yet studies in this domain are often detached from considering the dynamics of technological evolution itself. Where technological advances reside (knowledge distribution), the degree to which innovation tasks can be specified (task decomposition) and the rate of technological progress (performance trajectory) all vary dramatically over the technology life cycle. These factors have implications for what forms of online crowds and communities are most likely to contribute technological advances. We provide a dynamic model of the expected "dominant communities" for technological advances at each phase of the life cycle, and we draw on examples from open-source software and consumer three-dimensional printing to illustrate the model. Our objectives are to determine how different forms of community-based innovation dominate at different times, to ground innovation models more firmly in material technological advances, and to provide focus for future research in this domain.

Open strategy-making with crowds and communities: Comparing Wikimedia and Creative Commons

“…With regard to potential implications for practice, we could see a benefit in developing and marketing tools with a clear focus on either crowds or communities. Actually, current tools for open innovation or strategy such as the ones used in the case described by Stieger et al (2012) already implicitly cater more to either crowds or communities (see also Seidel et al, 2017). The more such tools allow their users to access and review peer contributions, the more these cater to communities (see also Seidel and Stewart, 2011).…”

“…Hautz et al (2017), in their typology of tensions, or 'dilemmas' as they call it, argue that the complications and challenges associated with open strategy-making are always coupled to potential advantages. Building upon these works, we intend to show that tensions have an impact not only on the organization opening up its strategy-making, but also, and possibly more importantly, are related to the group of actors targeted or invited for taking part in strategy-making (for a similar endeavor in the realm of innovation see Seidel et al, 2017).…”

“…Although crowds and communities both reside outside the formal organization, they differ with respect to their specific relational setup: while communities are networks of interrelated actors, who may engage in interpersonal exchange and share social ties or a common identity outside an open strategy-making process, crowds mostly comprise actors who do not share interpersonal ties but are mainly related to the organization in some form or another (e.g. being a client, supplier or interested individual; see also Seidel et al, 2017). While this distinction between crowds and communities is implicitly present in the literature on open strategy-making, so far no specific research efforts have been undertaken to analyze whether it actually matters for understanding open strategy-making and, if so, how it relates to the practices and tensions emerging from 'opening up' organizational strategy-making.…”

Game Simulation Analysis of Radical Innovation Processes of High-tech Enterprises based on WoO-EGT Model

“…The period called later maturity is regarded as the market timing of RIP, and it is regarded as the WoO of RIP. Given that the later-maturity period of existing technologies in the market is limited to the incremental innovation of existing locking technologies, and considering that their technological potentials have been fully mined in the growth stage, the performance of technology products will have no substantial changes in this stage [27]. However, if the breakthrough technology can be introduced to the market at this stage, then either the performance of products can be remarkably improved or new performance products may be provided, which can increase the acceptance probability of products [28].…”

The Open Innovation Research Landscape: Established Perspectives and Emerging Themes across Different Levels of Analysis

“…Moreover, crowdfunding can be a good setting to study failure in the context of OI, based on the data on unsuccessful projects. Recent work suggests that crowdsourcing may be more appropriate at later stages of the technological lifecycle (Seidel, Langner, and Sims 2016), and is subject to other contingencies including the context of networks, industry and geography (Agrawal, Catalini, and Goldfarb 2011;Mollick 2014;Dushnitsky et al 2016). …”