The Determinants of Digital Piracy Behaviour in Malaysia
Bibliographic record
Abstract
The advancement of technology has facilitated sustainable and significant development in supporting digitalisation of business operations, including but not limited to electronic commerce, but also resulting in a significant increase in digital crimes, particularly online piracy. Many consumers seek out pirated content and the majority of them do not perceive it as something that could eventually harm the creative industry or perceive it as a wrong practice. Therefore, the problem of online piracy becomes rampant. This research investigates the direct and indirect relationships between deviant peer associations, perceived benefits, attitude towards digital piracy, subjective norms, self-efficacy, digital piracy intention and actual digital piracy behaviour. A total of 450 samples were gathered via an online self-administered questionnaire survey. The data was evaluated by structural equation modeling (PLS-SEM) and statistical package for social sciences (SPSS). According to the statistical findings, all of the direct and indirect relationships among the seven variables are significantly supported. This study provides theoretical and managerial implications by demonstrating that digital piracy intention has a significant relationship on actual digital piracy behaviour as well as deviant peer associations have a significant relationship on an individual’s attitude towards digital piracy. This study concludes with some limitations and recommendations for the future digital piracy research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".