Linking Supply Chain Gaps to Consumer Inhibitors: A Data-Driven Study of Rural E-Commerce in Saudi Arabia
Bibliographic record
Abstract
This study investigates how supply chain infrastructure gaps constrain e-commerce growth in rural Saudi Arabia through the use of postal data, geospatial mapping, and consumer surveys. Results reveal significant regional disparities, with Jazan and Najran recording 4–5 postal facilities per 100,000 residents compared with only 0.7 in Riyadh. Key inhibitors include unclear regulations (66%), inability to inspect products (58%), lack of trust (39%), and limited home delivery (35%), reflecting persistent weaknesses in last-mile logistics. Correlation analysis (r=0.69, p>0.05) indicates a positive but statistically insignificant relationship between postal coverage and perceived delivery reliability. Overall, inadequate supply chain connectivity remains a major barrier to rural digital inclusion. Expanding postal and logistics infrastructure is therefore essential to strengthen consumer trust and achieve equitable e-commerce growth in line with Saudi Arabia’s Vision 2030.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".