See also Intellectual Property.
I am especially interested in modeling how technology changes the rules of the game, as opposed to marginally changes some parameters; not, say residual stochastic shocks (in the “Real Business Cycle” models), or as the slope of a marginal cost of production curve (in textbook microeconomics). That is, technological innovation that leads to a qualitative, rather than incremental, change in the state of play —- respecting that a lot of marginal changes might in fact lead to major qualitative changes.
In recognition of that emphasis, I briefly called this entry “disruptive technology” instead of mere “innovation”, but then I felt like a TED speaker and woke up sweating in the night to change it.
This is at the very limit of modelability, surely?. The introduction of a new technology has many components, from social uptake, to supply chains, to the discovery process. The unexpected interactions with the other technologies out there. The internal combustion engine changed more than just transit times. The computer network altered more than just mail delivery times.
The cascade of effects from any one alteration is, it is likely, unknowable in advance, but might have some regularities, or at least some kind of underlying set of distributions as a stochastic process - some kind of branching process perhaps? Fixation processes, by analogy with evolutionary theory?
“Product space” model
Due originally to Hidalgo and Hausmann, and made purportedly more rigorous by Caldarelli et al.
Considers products and nations in a bipartite graph, and does various network statistics upon it.
Attempts to be predictive about the “natural level” of a country’s GDP.
(c.f. Felix Reed-Tsochas’ affinity for such graphs, har har) Note that there is an implicit third part in the graph, to whit “capabilities”, which represent infrastructure to manufacture products.
Frank Schweitzer et al have a similar notion of inter-firm R&D networks which may be related? See references.
Should mention this, despite nonverifiability etc.
Marginal returns on research
Moore’s law versus Eroom’s law governing trends in marginal research productivity. What does the paucity of new drugs mean?
Other interesting things to look at
So Loreto, Strogatz, and co have modified Polya’s urn model to account for the possibility that discovering a new color in the urn can trigger entirely unexpected consequences. They call this model “Polya’s urn with innovation triggering.” [..they] then calculate how the number of new colors picked from the urn, and their frequency distribution, changes over time. The result is that the model reproduces Heaps’ and Zipf’s Laws as they appear in the real world
Phillip Ball on What innovation really is
Mariana Mazzucato seems to be interesting
Will a journal of infrastructure complexity actually be good?
Source of the alarming graphic above.
Is it just me, or does this resemble a maximal statistic, or perhaps a rarefaction curve?
Thiel, P. A.(2014). Zero to one: notes on startups, or how to build the future (First edition.). New York: Crown Business.
Peter Thiel, what a problem that man is.
“Thiel begins with the contrarian premise that we live in an age of technological stagnation, even if we’re too distracted by shiny mobile devices to notice. Information technology has improved rapidly, but there is no reason why progress should be limited to computers or Silicon Valley. Progress can be achieved in any industry or area of business. It comes from the most important skill that every leader must master: learning to think for yourself.
Doing what someone else already knows how to do takes the world from 1 to n, adding more of something familiar. But when you do something new, you go from 0 to 1. The next Bill Gates will not build an operating system. The next Larry Page or Sergey Brin won’t make a search engine. Tomorrow’s champions will not win by competing ruthlessly in today’s marketplace. They will escape competition altogether, because their businesses will be unique.”
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