Many billions of dollars each year are spent in pursuit of economic and social development goals. The field of program evaluation aims to measure the efficacy of these programs and allocate funds to achieve optimal results. However, current research on program design and evaluation tends to focus on determining causality through complex statistical methods, neglecting intermediate measures of data, such as network metrics. Similarly, research in computational social science has focused on generating hypotheses and validating theory rather than economic development applications. This thesis develops a novel technique for using computational social science to design and evaluate social and economic programs. A framework for program design and evaluation using network metrics is presented, along with two case studies that illustrate the use of this technique. In the first, we consider Start-Up Chile, an economic development program whose goal is to foster networks between Chileans and international entrepreneurs, using network metrics to evaluate its ability to facilitate connection between Chilean and non- Chilean entrepreneurs. Second, an agent-based model for designing entrepreneurial incubators is developed, with novel conclusions for more efficient design of economic development programs.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:712061 |
| Date | January 2015 |
| Creators | Richman, Jessica |
| Contributors | Scott, Linda |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://ora.ox.ac.uk/objects/uuid:6b454558-e7db-4e40-ac90-2fce912c916f |
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