Gender heterogeneity in couriers' mode choice behaviours: Crowd-shipping for E-groceries
Bibliographic record
Abstract
This paper examines the mode choice behaviour of occasional couriers providing crowd-shipping (CS) deliveries for e-groceries, with a particular focus on gender heterogeneity. Using a behavioural survey conducted in Kharkiv, Ukraine, in early 2021, combined with simulated travel attributes and discrete choice modelling based on random utility maximisation theory, this study explores how gender influences mode preferences and willingness to pay (WTP) across six transport modes within a crowd-shipping context. The results reveal significant gender-based differences in both mode choice and WTP. Female couriers consistently exhibit a higher WTP across all transport modes compared to their male counterparts. For instance, women's WTP for cycling (90 UAH/h) is substantially higher than men's (59.79 UAH/h), while for car-based deliveries, women's WTP reaches 87.16 UAH/h, compared to 54.94 UAH/h for men. These findings suggest that women require higher compensation, particularly for non-motorised modes, likely due to differences in physical effort required and perceived comfort.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".