While learning quite a lot about Project Management from DavidT, I quite accidentally ran across his post on adoption .
"There are a couple of largely accepted theories that model or predict technology lifecycle and adoption patterns:- The Diffusion of Innovations theory offers a model for how a given technology gets accepted and spreads through markets. Its central point is that technologies spread by gradually addressing the needs of 4 types of users: innovators, early adopters, the early majority, and the late majority (a fifth category, the laggards, might just never get it)- The Technology Acceptance Model (TAM) offers some prediction to End User adoption. The key concept here is that individual users adopt a given technology based on its perceived usefulness and its perceived ease of use.To my knowledge, there isn't an established theory or framework that models evolution trends of Technologies.When looking at the history and evolution of web services, we seem to be in front of species that are spreading, adapting, and diverging much like finches in the Galapagos.The immediate thought that then comes to mind is whether Darwin's Theory of Evolution has some or any relevance to Technology.The theory of evolution defines three basic mechanisms of evolutionary change:. Natural Selection is a process by which traits that are more useful in a given environment become more common over time (because they give better chances of survival), while traits that are harmful become rarer. Gene Flow is the exchange of genes within and between populations, which translates in traits being transferred between populations and species.. Genetic Drift is a purely random shift of the frequency of traits within a population - traits become more or less common in a population because of the long-term statistical effect of the random distribution of genes in each generationHow could these mechanisms apply to technology?- Natural Selection is probably the mechanism most relevant to technology trending.The fitter a technology is to the needs of its market, the more likely it is to stick around, and potentially supersede other technologiesThis is why PCs are more likely to be found today than mainframes, why java is more often used than Fortran, and why soap-based web services have replaced xml-rpc.- Gene Flow is also common in the tech field (although we'd probably want to call it something else).Features and concepts are constantly exchanged between complementary or competing technologies.That's how C# got a memory garbage collection mechanism similar to the one in java, and how row-level locking made it in MS SQL Server after years of Oracle claiming it as a key differentiator.Gene flow is also at the root of hybridization, where traits of different species end-up being combined. This is what might be truly going on right now with REST - which is applying concepts of simpler web protocols, most notably HTTP and RSS, onto Web Services.- Genetic Drift seems at first least relevant to the tech field, but might in fact be the most interesting bit.The core concept in genetic drift is that the random distribution of genes in each generation can have a long-term effect on the frequency of traits in a population (because of the statistical law of large numbers, genetic drift is less likely to occur in large population than in smaller ones).What, if anything, could have a similar impact in the evolution of technologies? What type of mechanisms, if any, can have an effect on the evolution and adoption of a technology, without being connected to its intrinsic fit or value?Obviously there are a lot more forces that dictate the success or demise of technologies than just their core virtues.A strategic alliance with IBM propelled MS-DOS into market dominance; technology companies like Oracle spend millions trying to influence the market; and there is a whole ecosystem of media, analysts, and venture capitalists who strive on generating buzz (PointCast or Twitter come to mind).Who knows - if LISP had been able to be more hip, we might all be using more parenthesis today."
Again, my "meme theory" interest (obsession?) means I cannot but help notice 'one more case that fits'. Technology memes playing out their game of survival in the world....
The question is: How can I model, simulate, and more importantly - validate, prove....and Predict the future?