Minimization of empty container truck trips: insights into truck-sharing constraints
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
Purpose The issue of empty truck trips is largely ignored in the current literature. In order to cover this important research gap, the purpose of this paper is to explore, describe, categorize and rank the potential truck-sharing constraints for container trucks traveling empty around the port gates. Design/methodology/approach In order to contribute empirically to the current body of knowledge and understandings of truck-sharing constraints, this paper adopts a multi-method empirical approach involving both qualitative interviews and quantitative questionnaire surveys. Findings Among many key constraints that influence the future of truck-sharing opportunities, the authors determine, for example, that a carrier’s ability to earn the trust of its competitors is one of the top most important factors of success for a fruitful truck-sharing event. The problem is, perhaps, further complicated because of the increasing competitive environment in the container transport industry, as well as the lack of effective coordination between the key parties involved. Research limitations/implications None of the earlier studies has provided a broad understanding and ranking of the truck-sharing constraints that should be considered in truck-sharing events, although the empty trips issue has been limitedly mentioned in the recent academic literature. Practical implications Empty truck trips are wasted miles. Wasted empty miles decrease transport capacity in the container distribution chain along with causing an increase in carbon emission, traffic congestion, fuel consumption and environmental pollution. The research results can be used by policy makers to underpin effective measures to prevent the low utilization of trucks. Originality/value This study addresses an important gap. To the authors’ knowledge, this is the first study in the area that ranks truck-sharing constraints to reduce empty trucks trips.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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