Effects of Organization Insiders' Self-Control and Relevant Knowledge on Participation in Information Systems Security Deviant Behavior
Bibliographic record
Abstract
Disastrous consequences tend to befall organizations whose employees participate in information systems security deviant behavior (ISSDB) (e.g., connecting computers to the Internet through an insecure wireless network and opening emails from unverified senders). Although organizations recognize that ISSDB poses a serious problem, understanding what motivates its occurrence continues to be a key concern. While studies on information technology (IT) misuse abounds, research specifically focusing on the drivers of ISSDB remains scant in the literature. Using self-control theory, augmented with knowledge of relevant factors, this study examined the effects of employees' self-control, knowledge of computers/IT, and information systems (IS) security threats and risks on participation in ISSDB. A research model, including the aforementioned factors, was proposed and tested using the partial least squares technique. Data was collected from a survey of Canadian professionals. The results show that low self-control and lower levels of knowledge of computers/IT are related to employees' involvement in ISSDB. The data did not provide a meaningful relationship between employees' knowledge of IS security threats/risks and desire to participate in ISSDB.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 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".