Effects of Individual and Organization Based Beliefs and the Moderating Role of Work Experience on Insiders' Good Security Behaviors
Bibliographic record
Abstract
This research aims to identify the factors that drive an employee to comply with requirements of the Information Security Policy (ISP) with regard to protecting her organizationpsilas information and technology resources. Two different research models are proposed for an employeepsilas individual based beliefs and organization based beliefs. An employeepsilas attitude is traced to its underlying foundational beliefs in each model, namely, benefit of compliance, cost of non-compliance, and cost of compliance, which are beliefs that represent the perceived effects of compliance or non-compliance. It is also postulated that these beliefs along with an employeepsilas attitude are affected by her Information Security Awareness (ISA). Besides the structural model testing of individual and organizational models of compliance, the moderating role of an employeepsilas work experience is investigated. Our results show that, while individual benefit of compliance and cost of compliance are not significant in the low experience group, all individual based beliefs are significant in the high experience group. Similarly, organizational benefit of compliance is not significant in the low experience group, while all organization based beliefs are significant in the high experience group. Furthermore, ISA is found to affect an employeepsilas attitude and all her individual and organization based beliefs. As organizations strive to get their employees to follow their information security rules and regulations, our study mainly sheds light on the moderating role of an employeepsilas work experience in changing the strength of individual and organization based beliefs on employeespsila attitude as well as her ISA.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".