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Record W2890296391

Using Cognitive Dissonance Theory to Explain Information Security Policy Violations

2018· article· en· W2890296391 on OpenAlexaff
Nasim Talebi, Mohsen Jozani, Tejaswini Herath, H. Raghav Rao

Bibliographic record

VenueJournal of the Association for Information Systems · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOpinion Dynamics and Social Influence
Canadian institutionsBrock University
Fundersnot available
KeywordsCognitive dissonanceComputer scienceSelf-perception theoryInformation securityInformation theoryCognitionComputer securityCognitive psychologyPsychologySocial psychologyMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

The use of sanctions has long been advocated to enforce information security policy (ISP) compliance to control malicious and non-malicious insider threat. The ISP literature is largely based on deterrence theory. However, findings are inconsistent and deterrence has not been a strong predictor especially when non-compliant behavior is the focus of the study. To better explain this phenomenon, scholars have integrated theories and introduced additional constructs. By integrating cognitive dissonance and extended deterrence theory, this study seeks to examine the moderating effect of the personality trait of inertia on the relationship between formal and informal sanctions with ISP non-compliance. More specifically, the focus of this study is on investigating the factors that impact non-compliance of insiders (employees). \\ \\ This paper revisits the role of formal and informal sanctions in ISP compliance literature through the lens of cognitive dissonance theory. Although certainty of getting caught as well as the severity and swiftness of penalties for engage in policy violating behavior along with subjective norm and their peer behavior have a negative effect on employees’ intention to show non-compliance behavior, inertia will strengthen this relationship. \\ \\ To test the research hypotheses, we plan to use a scenario-based survey instrument for data collection following by Partial Least Squares (PLS) method using Smart PLS 3.0 for data analysis. The survey instrument will be created with items extracted from extant literature and the scenarios will be chosen from unauthorized access to computerized data. \\ \\ This study has a number of theoretical and practical implications. It contributes to ISP compliance body of knowledge by its novel theoretical approach such that individuals utilize a cognitive process to justify the inconsistency between their prior thought and the subsequent action (inertia). To the authors’ knowledge, cognitive dissonance theory has never been used in ISP compliance literature. Moreover, examining the moderating effect of inertia can shed light on the long standing debate regarding the effectiveness of deterrence on compliance. From a practical standpoint, the result of our study can help in designing training and information intervention programs for employees who are in inertia state and driving them toward attitude and behavior change. \\

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.823
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.310
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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