The effect of e-store website quality in terms of consumer rights on the reliability and respon-siveness of the e-customer
Bibliographic record
Abstract
E-consumer rights aim to provide consumers and sellers a fair opportunity when dealing online, which requires both parties to know their rights and ethics. Therefore, the purpose of this study is to verify the impact of consumer rights available on reputed online store websites in Saudi Arabia (KSA) on the customer service, using expectation confirmation theory (ECT). A random sampling technique was used for primary data collection from a sample size of 152 faculty members. IBM Software Package for Social Sciences SPSS-26 and structural equation modeling (SEM) LISREL software programs were used for data analysis. The findings show that e-consumer rights have positive and significant effects on customers’ e-reliability and e-responsiveness. In addition, consumers’ income significantly influences their e-responsiveness, while the number of e-dealings per month significantly influences both e-reliability and e-responsiveness. The results of the study also provide an inventory of eight reasons why consumers prefer to deal with local electronic stores over foreign ones. Based on these findings, theoretical importance, practical implications, and suggestions for future research are discussed.
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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 | 0.007 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".