Unravelling SMEs’ participation and success in public procurement
Why this work is in the frame
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Bibliographic record
Abstract
Purpose This paper aims to investigate the role of micro, small and medium enterprises (MSMEs) within the Canadian public procurement, by seeking to identify barriers and supporting factors of MSMEs’ participation and success in public tenders. Design/methodology/approach The empirical analysis builds on a unique survey run by the Canadian federal government, which addressed firms either participating or not participating in public tenders. Model estimation on the survey data relies on sample selection methodologies, which allow separating determinants of MSMEs’ decision to participate from determinants of success. Findings Results provide evidence that costs stemming from asset specificity and uncertainty (e.g. costs of bidding, requirements for participation, bundling of contracts and award rules based on minimum price) affect participation in public procurement. Within MSMEs, micro-firms are the most discouraged from participating. However, after controlling for factors affecting participation, micro-firms emerge as having a higher success rate, possibly because of high specialization and joint participation with larger firms. Research limitations/implications Because of the cross-sectional nature of the data used for hypotheses testing, endogeneity may arise if ex post variables affect ex ante decisions. This may apply if participation in procurement feeds on success in past tenders. Social implications Findings may inform policies for the inclusion of smaller firms in the public marketplace. Originality/value To the best of the authors’ knowledge, this study is the first attempting to disentangle determinants of participation in public tenders from determinants of success. Separating the two aspects helps fine-tune SME-friendly public procurement policies, by identifying actions that effectively facilitate success of MSMEs in public tenders.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it