The impact of attitude, subjective norms, perceived behavioral control, and perceived risks on intention in online shopping in Jordan
Bibliographic record
Abstract
Previously, studies reported inconclusive findings while analyzing the influence of factors affecting online purchase intention. Also, most studies were conducted in the context of developed countries, limiting us to a specific context. Hence, for comprehensive understanding, this study aims at examining the factors affecting the online purchase intention in the e-commerce industry of Jordan. The survey was conducted to collect data from university students in Jordan. Structural equation modeling was employed to analyze the data. Findings show that attitude, subjective norms, perceived behavioral control are positively associated with online purchase intention. However, perceived risks are negatively associated with online purchase intention. Although all factors are significantly related to online purchase intention, the attitude has a greater influence. This study adds value to the theory of planned behavior and consumer behavior by examining attitude, subjective norm, perceived behavioral control, and perceived risks as important predictors of online purchase intention. Besides, this study suggests that online retailers must keep their commitments, promises, and customers’ interests in mind while developing e-commerce strategies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".