Keywords

Balanced scorecard, system dynamics, causal loops, portfolio management, federal funding

Abstract

The University of Central Florida has many successful measures to reflect on as it celebrates its 50th year in 2013. It is the university with the 2nd largest student population in the U. S. and its overall ranking in the U.S. News & World Report has improved 4 years in a row. However, with respect to research, the federally funded research and development for the University of Central Florida (UCF) has remained flat. In addition, when compared to other schools, its portion of those federal research dollars is small. This thesis lays the groundwork for developing a model for improving the federally financed academic research and development. A systems approach using the balanced scorecard methodology was used to develop causal loop relationships between the many factors that influence the federal funding process. Measures are proposed that link back to the objectives and mission of the university. One particular measure found in the literature was refined to improve its integration into this model. The resulting work provides a framework with specific measures that can be incorporated at the university to improve their share of the federally financed research and development. Although developed for UCF this work could be applied to any university that desires to improve their standing in the federal financed academic research and development market.

Notes

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Graduation Date

2013

Semester

Fall

Advisor

Rabelo, Luis

Degree

Master of Science (M.S.)

College

College of Engineering and Computer Science

Department

Industrial Engineering and Management Systems

Degree Program

Industrial Engineering; Engineering Management

Format

application/pdf

Identifier

CFE0005069

URL

http://purl.fcla.edu/fcla/etd/CFE0005069

Language

English

Release Date

December 2013

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic

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