Investigating Influence of Trust on Repurchasing by Mediating Role of Customer Satisfaction in Online Stores
Bibliographic record
Abstract
Analyzing and investigating factors affecting trust and satisfaction creation and providing condition for creating these factors by online stores help them to perceive customers’ needs and lead to increasing loyalty level, intention for repurchasing and improving profitability level. Therefore, this paper investigates influence of trust on repurchasing by mediating role of customer satisfaction. Population of this paper were customers of online stores which have 2-star electronic trust symbol on the base of E-trade development center (Note 1) ranking and had shopping more than once. Data were gathered from 267 samples of customers by availability method and questionnaire tool and its reliability was confirmed by Cronbach's alpha with 82%. Considering analyzing data by SEM on LIZERAL software, findings show that trust has positive and significant influence on repurchasing and indirect influence of trust on repurchasing by mediating role of customers satisfaction is more than its direct influence which confirms mediating role of customers’ satisfaction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".