Researcher
Richard Davidson PhD Candidate, Daniels College of Business, University of Denver
Richard brings more than 25 years of experience in government procurement, spanning roles inside government and on the vendor side. He has led proposal strategy and managed more than twenty major technology RFP responses across federal, state, and local government markets.
Research Evolution
| Phase | Period | Description |
|---|---|---|
| V1 Pilot | 2025 | USAspending data, cross-sectional analysis, proxy treatment classification |
| V2 Analysis | 2025-2026 | Omari et al. (2025) FPDS dataset, difference-in-differences design, 654,307 awards |
| Dissertation | Fall 2026+ | University of Denver Executive PhD, Daniels College of Business |
Publication Portfolio
| Paper | Title | Target Journal | Status |
|---|---|---|---|
| 1 | The Policy Shock That Didn’t Shock | Journal of Public Procurement | Draft Complete |
| 2 | Transaction Costs as Moderators | JPART | Draft Complete |
| 3 | International Procurement Comparison | IJPA | Draft Complete |
| 4 | Single-Bid Awards | PPMR | Draft Complete |
| 5 | The Source Selection Evidence Gap | Journal of Public Procurement | Draft Complete |
Committee
Committee will be formed upon program enrollment (Fall 2026).
About This Site
This site is the most comprehensive public resource on procurement source selection research. It contains:
- Five empirical research papers analyzing 654,307 federal contract awards
- Literature database with 100+ annotated scholarly articles and automated daily discovery
- Federal procurement data analysis using the Omari et al. (2025) FPDS dataset
- International procurement comparison across 12 countries plus the EU
- Vendor journey cost analysis documenting $30K-$1.1M+ US entry barriers
- Profiles of 25 key scholars and practitioners in procurement
Tools & Technology
- Website: Hugo static site generator, GitHub Pages
- Data: Python (pyarrow, pandas) processing the Omari et al. (2025) Parquet dataset
- Analysis: Python (statsmodels, scipy, sklearn) for DiD estimation and robustness checks
- Papers: python-docx for automated paper generation from analysis results
- Articles: OpenAlex + Semantic Scholar automated daily discovery (439+ articles)