How different rewards tend to influence employee non-compliance with information security policies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose To help reduce the increasing number of information security breaches that are caused by insiders, past research has examined employee non-compliance with information security policy. However, existent studies have observed mixed results, which suggest that an interaction is likely to exist among the variables that explain employee non-compliance. In an effort to provide evidence for this possibility, this paper aims to better explain why employees routinely engage in non-compliant behaviors by examining the direct and interactive effects of employees’ perceived costs and rewards of compliance and non-compliance on their routinized non-compliant behaviors. Design/methodology/approach Based on rational choice theory, this study used 16 hypothetical scenarios in an experimental survey, collecting data from 326 respondents and analyzing them via structural equation modeling and a four-way factorial experiment. Findings The results suggest that routinized non-compliance of employees is more strongly influenced by the rewards than the costs they perceive in their non-compliance. Further, employees’ routinized non-compliance behavior was found to be positively influenced by an interactive effect of perceived rewards of compliance when their perceptions of their non-compliance costs and rewards were both high and low. Originality/value This paper’s key contribution is to suggest that non-compliance behavior is influenced by direct and interactive effects of perceived rewards of compliance and non-compliance.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.014 |
| Open science | 0.001 | 0.001 |
| 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 it