Determinants of intention to use e-commerce in Saudi Arabia
Bibliographic record
Abstract
This study investigates the key factors influencing intention to use e-commerce in an emerging market context, focusing on individuals residing in Saudi Arabia. A quantitative research approach was adopted, and data were collected using a structured questionnaire from 281 respondents through a convenience sampling technique. Data were analyzed using structural equation modeling with SmartPLS to test the hypothesized relationships. The results revealed that attitude, subjective norms, self-efficacy, and trust all had significant positive effects on intention to use e-commerce. Moreover, trust in e-commerce was found to influence attitude, which in turn mediated the relationship between trust and intention, highlighting the importance of trust as both a direct and indirect driver of online purchasing behavior. The R-square values indicated that 47.9% of the variance in attitude and 65.4% of the variance in intention were explained by the model, confirming strong explanatory power. The study concludes that trust, confidence, social influence, and positive attitudes are crucial for enhancing consumers’ willingness to engage in e-commerce. The study delivers essential information which helps e-commerce companies and marketing professionals and government officials to enhance consumer trust and digital shopping experience and build favorable digital commerce attitudes in Saudi Arabia.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".