For decades researchers have studied various aspects of the technology transfer and commercialization process in universities in hopes of discovering effective methods for enabling more research to leave the university as technologies that benefit society. However, this effort has fallen short, as only a very small percentage of applied research finds its way to the marketplace through licenses to large companies or to new ventures. Furthermore, the reasons for this failure have yet to be completely explained.
In some respects, this appears to be an ontological problem. In their effort to understand the phenomenon of university commercialization, researchers tend to reduce the process into its component parts and study each part in isolation. The result is conclusions that ignore a host of variables that interact with the part being studied and frameworks that describe a linear process from invention to market rather than a complex system. To understand how individuals in the technology commercialization system make strategic choices around outcomes, studies have been successful in identifying some units of analysis (the tech transfer office, the laboratory, the investment community, the entrepreneurship community); but they have been less effective at integrating the commercialization process, contexts, behaviors, and potential outcomes to explain the forces and reciprocal interactions that might alter those outcomes.
The technology commercialization process that leads to new technology products and entrepreneurial ventures needs to be viewed as a complex adaptive system that operates under conditions of risk and uncertainty with nonlinear inputs and outputs such that the system is in a constant state of change and reorganization. There is no overall project manager managing tasks and relationships; therefore, the individuals in the system act independently and codependently. No single individual is aware of what is going on in any other part of the system at any point in time, and each individual has a different agenda with different metrics on which their performance is judged. What this means is that a small number of decision makers in the university commercialization system can have a disproportionate impact on the effectiveness and success of the entire system and its research outcomes.
Critics of reductionist research propose that understanding complex adaptive systems, such as university technology commercialization, requires a different mode of thinking—systems thinking—which looks at the interrelationships and dependencies among all the parts of the system. Combined with real options reasoning, which enables resilience in the system to mitigate uncertainty and improve decision-making, it may hold the key to better understanding the complexity of the university technology commercialization process and why it has not been as effective as it could be.