Interplay between humanitarian procurement operations and fundraising
Bibliographic record
Abstract
Procuring requested relief items, while ensuring an available budget, is an essential task in humanitarian logistics. Humanitarian organizations (HOs) are facing difficult decisions about procurement portfolios (i.e., prepositioning-versus-emergency procurement) and fundraising strategies. We develop a two-stage newsvendor model in the context of a leader-follower game between a representative HO (the leader and donors (the follower)to characterize their interactions. In our model, the HO decides on the prepositioning level for disaster preparedness under uncertainty, while the fundraising expense is determined on the disaster response phase. Our research compares a budget-constrained case with a budget-unconstrained benchmark case. Furthermore, we discuss the trade-off between the efficiency (i.e., maximizing HO’s expected budget) and effectiveness (i.e., maximizing expected demand fill rate) of procurement and fundraising operations. Our numerical analysis reveals that the budget-unconstrained environment would provide the HO with misleading managerial insights into procurement portfolios—overemphasis on prepositioning. Further, an effective fund-raise mechanism that could raise donors’ motivation for donations would reduce prepositioning. We also observe that prepositioning cannot guarantee to achieve the highest operational effectiveness (demand fill rate) due to the loss of fundraising opportunities. Research implications and managerial guidelines are proposed.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".