My fourth challenge is to find which values must be manipulated to allow a university to achieve their potential research output. To calculate the research output potential at a university, I must first create aggregate variables - variables that use proportions to include multiple variables. Aggregates allow for easy comparison of funding, student and curriculum quality, and the amount of faculty dedication to research at leading U.S. universities. As shown in Table 2, each variable has a specific weight based on its significance. To select these weights, correlations from Table 1 are essential: the higher the correlation between the independent variable and the research output, the greater weight it held in the aggregate. The aggregate for research output consists of 50% awards, 30% citations, and 20% increase in citations index.
The correlation between the research output aggregate and the independent variables shows the significance of each variable to publications and citations and helps determine weights for the aggregates for funding, student quality, and faculty dedication. As shown in Table 2, the aggregate for funding (X-A) consists of 50% federal funding, 20% non-federal funding, 20% increase in funding, and 10% endowment funding. The aggregate for student quality (X-B) is made up of 30% percentage of STEM graduates, 30% national math ranking, 20% SAT median, and 20% percentage of National Merit scholars in the incoming class. The aggregate for faculty dedication (X-C) contains 30% number of research centers, 20% percentage of faculty in the National Academy, 40% doctorate-to-faculty-ratio, and 10% percentage of faculty with awards from the Howard Hughes Medical Institute. ...
... middle of paper ...
...ersities. I am now starting to understand how all the innovation and technological progress can develop in so many outstanding institutions. But I also believe that administrators and researchers need to review their own portfolios to assess how well their existing factor resources are being deployed and where better synergies could be created. Princeton University appears to be one great example where research output could be doubled over the next five years with a renewed emphasis on STEM resources. In the end, I found that, overall, federal funding, nonfederal funding, and endowment funding most significantly affect the funding for the university, the percentage STEM graduates and the math ranking most greatly affect student qualifications, and the percentage of the faculty in the National Academy most significantly impacted the faculty’s dedication to research.
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