The United States does best when it continuously grows and adapts to further its position in world leadership. That adaptation can be organic in nature or intentionally constructed. Either way it should seek to create new products and when possible whole new industries that expand and create emerging markets. Innovative clusters provide an opportunity to speed industry innovation through complementary stakeholders that seek to systematically solve larger product innovation challenges. Solving market problems leads to global economic expansion and the secondary benefits of influence.
The U.S. will need rapid innovation to maintain competitiveness and thus might seek to enhance its scientific capacity by creating social and economic strengths. The pressure to try new ideas is rising and the Transactional Rapid Innovation Cluster (TRIC) Model may help in sparking adaptive economic lift. While the method is somewhat in its initial stages there is some hope that the long tail of development leads to improved economic innovation and capacity.
What is a Cluster?
It is hard to gain a grasp of something complex that contains within it millions of smaller moving parts unless one has a working definition that can encompass the whole. In science, definitions often change as new insights from discoveries are brought forward in such as way as to improve the perceptual forming of ideas. While the definition is in a constant state of refinement, one can consider clusters broadly as,
Clusters are connections of similar businesses that share knowledge to improve innovation. Innovation leads to new products and eventually economic growth. The Transactional Rapid Innovative Cluster model (TRIC) discussed in this book, focuses on a very similar model. Complementary companies can hedge their differences to raise the total value economic and social outputs of the area through research & development partnerships to foster a pro-growth innovative environment.
What does the TRIC do?
To better understand how the TRIC impacts economic innovation one might think of how complementing research discoveries around similar goal(s) are adapted quickly to use through advanced worker skills (human capital). The TRIC is a more applied working research model designed to help industries put to use new discoveries directly to the market by removing informational barriers often found in siloed research & development and the insulated labs of universities.
For example, let us say that you desire to improve robotics and AI for productive use in space flight, firefighting/first responding, or the military. An initial prototype could be built by partnering industry stakeholders around desired cluster goals. To build something complex requires putting advanced industry and human capital skills in the same locality with specific objectives around research agendas (virtually and physically). Companies can be selected and encouraged to participate based on their contributory value and potential developmental benefits of achieving cluster goals.
Are Clusters Measurable?
Just like one can construct an algorithm to study linkages between companies one can also create algorithms to calculate cross linkages of complementary industries. Assessing how clusters are formed and how they connect to create innovation is part of the process of maximizing economic growth. Economic systems are made up of things that range from human motivation all the way over resource usage. In the case of clusters, the goal is to understand the specific data markers that improve adaptations in multiples industries and learn how to repeat that in other places for national advantage.
How the Research Started?
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| The Tuna Industry Picture |
The central questions at the time were how to increase fish stocks, improve opportunities for smaller businesses while maintaining ecosystem health. One long term solution I found beyond changing regulations was to innovate the environment and all that was within that environment to produce and harvest more fish while still maximizing long term sustainability. In my preliminary model I thought of all the pieces that might create an embedded robotic fish steward that studies, helps, and monitors large fish schools (i.e. over fishing, regulation violations or reports pollution sources). Then I pondered how many other industries would be impacted not only by my fish robot example but also all the patents needed to create and produce such fish robots. A real problem with a hypothetical solution would require innovative jumps that are becoming more possible with AI, energy and robotic advancements.
Potential National Benefits
The benefits of developing expanding transactional clusters across many industries are potentially. We might consider the butterfly effects of multiple innovations influencing multiple industries with a new discovery that leads to new products. Innovative discoveries that have significant industry value means that exports by American made products will rise and the nation's GDP will expand. Further that with possible improvements in wages for highly skilled workers within clusters, depending on how we allocate under a broader based capitalism, and you have benefits impacting a wider group of stakeholders.
We should also not forget that other industries such as the military, space industry, tools, etc. tied to a cluster's design are likely to benefit from such rapid innovation to develop additional competitive advantages.
Key Points:
-Complementary clusters create broader innovations versus primarily deeper innovations.
-The TRIC model may have significant research and investment advantages for participating industries.
-The Transactional Rapid Innovative Cluster model (TRIC) model seeks to improve innovation across multiple industries to speed national development.
-Creation of important prototypes leads to new patents and multi industry adaptations that leads to butterfly effects across many networks.
Delago, M., Porter, M. & Stern, S. (August 2014). Defining Clusters of Related Industries. National Bureau of Economic Research. https://www.nber.org/papers/w20375
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