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This paper sets out to develop a unified theoretical framework integrating von Hippel user innovation and Schumpeterian industrial dynamics through a relatively simple agent-based model (ABM). The model reproduces known stylised facts, and it also generates some important theoretical results to explain the transition from community-phase to market-phase innovation, that neither paradigm addresses on its own. In our model, as user innovators develop the technology for their own use, complementary interactions with producers also begin to form. These firms seek market opportunity and require a certain minimum scale of operations before they enter. Where firms enter, they bring scale and often further innovate, which in turn, recursively feeds back into user innovation. In this way, von Hippel and Schumpeterian innovation co-evolve. Our ABM provides a formal and endogenous framework to understand these coevolutionary processes, generating theoretical results about the conditions under which it occurs. Specifically, the model simulations explore how two structural key parameters: users' attribute requirement thresholds and the degree of local sticky information , shape this co-evolutionary process. The simulations show that: (i) community fragmentation driven by high information stickiness may impede viable producer entry even when user demand exists; (ii) medium values for user attribute requirement thresholds generate a competitive advantage for pioneering firms landed at the center of the attribute space and; (iii) the industrial dynamics that emerge from user communities reproduce the Schumpeterian stylised facts, thereby providing a unifying bridge between the two paradigms. These theoretical findings have direct implications for innovation policy: (i) policy should monitor community coherence as an early signal for specific viable commercialization; (ii) a policy model that addresses information stickiness will be necessarily context-dependent and, (iii) the attribute requirement threshold suggests that producer entry strategies should be attuned to the distribution of user requirement heterogeneity.
Almudí et al. (Tue,) studied this question.