Shipper Willingness to Pay to Increase Environmental Performance in Freight Transportation
Bibliographic record
Abstract
Reduction of the environmental impact of freight transport becomes more crucial as the worldwide volume of freight transport increases. Not only technological improvements are needed but also organizational and operational changes designed to optimize logistic chains, including the allocation of goods to transport modes. Such changes often imply an increase in transport prices and are therefore realistic only if an explicit demand of shippers for environmental improvements can be observed. A shipper survey was administered in Switzerland to evaluate relevant factors in shipper demand for land transport services (including the role of freight transport's environmental performance). The survey included stated-choice experiments based on real-world transport chains. A set of logit models was estimated to quantify shippers' willingness to pay for reducing the environmental impact of their shipments. Special focus was given to differences between types of commodities shipped and to the impact on choice behavior of conventional quality aspects (on-time reliability, transit time, etc.). Results support the hypothesis that the closer a shipper is linked to the end consumer, the higher the sensitivity to environmental concerns.
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.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".