The effect of logistics and policy service quality on customer trust, satisfaction, and loyalty in quick commerce: A multigroup analysis of generation Y and generation Z
Bibliographic record
Abstract
This study investigated the effect of logistics and policy service quality on customer trust, satisfaction, and loyalty within the quick commerce landscape in Jordan, with a particular focus on generational differences between generation Y (Gen Y) and generation Z (Gen Z) users. A survey of 719 active Q-commerce users revealed that logistics service quality (personal contact quality, shipment condition, product availability, timely product delivery, and order accuracy) significantly affected customer satisfaction, with order accuracy being the most impactful factor. Additionally, both cash on delivery and order discrepancy handling significantly affected customer trust. Finally, customer satisfaction and trust affected customer loyalty, though in multigroup analysis, their relative importance varies between generations. Gen Z prioritizes speed of delivery and less concern on personal contact with delivery personnel. On the other hand, Gen Y values product availability and cash on delivery more than the younger generation. These findings offer valuable insights for Q-commerce platforms to tailor their strategies to the distinct priorities of each generation and enhance customer trust, satisfaction, and loyalty.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".