Abstract
Engineering education pushes the creation of new technology to solve community problems. The process of technology transfer promotes educational innovation in universities, a vital process that can improve citizens’ quality of life in cities and rural communities. As a result, university technology transfer offices (TTOs) have to create strategies that motivate students and researchers to generate technology. Thus, a primary challenge that TTOs face is to know and communicate the income potential compared to their much more predictable and limited expense budgets. Institutional budgeting for a TTO’s growth would be simplified if the office were on a solid financial footing, i.e., breaking even or making a financial return. Many offices assume that income is unpredictable, that it is a lottery, luck, and more stakes in the fire improve the odds of hitting a winner, etc. These common assumptions or beliefs provide only a vague insight into how to move an intellectual property (IP) portfolio strategy forward. How can a TTO be assessed for quantitative value and not just be a cost center adding qualitative value? This paper illustrates the first steps to understanding how to project potential income versus a much more predictable expense budget, which would allow universities to improve their technology transfer strategy and results. As a result, TTOs would operate under a more sustainable IP portfolio strategy, promote educational innovation in universities, and generate a more significant community impact.
Highlights
Moving from research projects to technological development is not always easy since some university–industry relationships are not sufficiently communicative about the research areas that the industries are investigating
If one could tease out an underlying probability distribution from historical income To gain insight into technology transfer offices (TTOs) intellectual property (IP) portfolios’ potential, we developed a model b data, one could explore modeling income and strategies to improve a TTO’s financial historical income, distributions techniques performance
This paper shows how the historical data of technology transfer offices can be used for modeling the technology transfer office’s portfolio income using the power-law probability distributions and Monte Carlo methods
Summary
Moving from research projects to technological development is not always easy since some university–industry relationships are not sufficiently communicative about the research areas that the industries are investigating. Universities could prepare students and researchers to improve the new technology and consider developing a startup business plan. If one could tease out an underlying probability distribution from historical income To gain insight into TTO IP portfolios’ potential, we developed a model b data, one could explore modeling income and strategies to improve a TTO’s financial historical income, distributions techniques performance. This kind of modeling/simulation enables prob primarily based on historical data, is the first step to understanding the income potential assessment buthelp notdefine pointand predictions This does modelnot pre does notincome forecast future incometime but the statistical without probability income generation year’s or shorter horizons;. A of detailed cash flowbased history, es on a TTO’s historical results This kind of modeling/simulation enables probabilistic year’s income is highly unlikely to be an accurate or reliable prediction. This model can illustrate the portfolio’s probability of returning future positive cash flows
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