The Impact of Switching Costs on Vendor Financing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Empirical studies point to trade credit as an important continuing source of short term financing for small and medium-sized enterprises. We show that vendor financing appears in equilibrium as the result of repeated trade interactions between a buyer and a supplier when changing supplier is costly. The supplier is then able to extract a periodic rent from the buyer. The presence of switching costs is not, however, detrimental to the buyer because competition between suppliers for this rent forces them to offer a rebate before the relationship is initiated. This sequence of a rebate followed by high prices is similar to a long term financing structure. The role of switching costs is similar to that of a precommitment device that allows the buyer to borrow a limited amount of capital from the supplier in the first period and to roll over the debt until the end of the relationship. In the case of small business owners who have difficulty accessing financial markets, our model suggests that switching costs allows them to smooth their dividend income, albeit inefficiently, by using vendor financing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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