It is the dirty little secret of innovation economics and policy that we do not know if it works. Here I propose that the tenuous link between innovation policies and innovative outputs are at least partly due to what I call the ‘innovation fallacy’. I argue that innovation policy is only solving half of the problem that it seeks to ameliorate.
The conventional economic ‘innovation problem’ is what supposedly provides the rationale for innovation policy. The story is that in a free market there are fewer resources dedicated to innovative activities than what is deemed to be some optimal ‘socially desirable’ level. That is, we do not have enough research and development (R&D) and that research and development is good.
The familiar diagnosis given here is one of ‘market failure‘. As we well know the faint allure of market failure is swiftly followed by calls for some state-based cure. ‘Market failure’ and ‘the need for state intervention’ are not inextricably coupled; rather they are very separate claims (this is a story for a separate post).
What I wish to clarify here is the underlying innovation problem that innovation policy is trying to solve has two parts. The first part takes the form of a technical or scientific problem. This is where investments in new technology are important and is usually the task of engineers, scientists, or hackers. This is also where innovation policy focuses.
But there is also another part of the problem that is often ignored. This is is problem the entrepreneur faces in acquiring and applying information about the catalytic economy to a new technology. This is an extremely uncertain task.
Entrepreneurs need information about: who wants the technology; how they will use it; what price points; under what conditions; in which jurisdictions; under what regulatory regime; complementary investment possibilities; what constellation of comparative advantages; potential economic externalities and so on and so on.
This entrepreneurial information about market opportunities is costly, distributed and shrouded in uncertainty.
Thus innovation is not simply about creating new things. Innovation — and the entrepreneurial process — is about creating new things that the market wants to buy. This is the distinction between an invention and an innovation. We may have as many inventions as we wish, but if they do not seek the demand of the market then that invention fails to provide the the very societal transformations we care about.
Innovation policy seems to rest on this innovation fallacy: that the innovation problem is solved once the technical phase is completed. This is tantamount to claiming that the recognition of market opportunities and the adoption and diffusion of innovation — the second phase — just occurs in some costless and frictionless process. This is clearly not the case. The bits of information I describe above are costly to produce, are generally learnt only through experience, and are largely contextual about a particular technology.
If the innovation fallacy is understood, where does the state sit in this process? This is an ambiguous and open question. I am not suggesting that an understanding of the innovation fallacy will somehow fix innovation policy. However it certainly will not break it. What is important for policy makers to understand is that more innovation policy does not necessarily generate more innovation because the underlying assumptions suffer from a fallacy.
This post is partly based on an upcoming conference paper which I will place up on SSRN soon. It outlines my PhD and presents a potential solution to the innovation problem that emerged from civil society institutions, not from state coercion: The Innovation Commons. See:
Allen, D. and Potts, J. 2015. ‘The innovation commons — why it exists, what it does, who it benefits, and how.’ A paper to be presented at the International Association for the Study of the Commons biannual global conference.