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Record W2802849241 · doi:10.1108/ics-09-2017-0066

Escalation of commitment as an antecedent to noncompliance with information security policy

2018· article· en· W2802849241 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInformation and Computer Security · 2018
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAntecedent (behavioral psychology)Sunk costsTask (project management)PsychologyTest (biology)Value (mathematics)PerceptionSocial psychologyMarketingBusinessEconomicsMicroeconomicsComputer science

Abstract

fetched live from OpenAlex

Purpose This study aims to identify antecedents to noncompliance behavior influenced by decision contexts where investments in time, effort and resources are devoted to a task – referred to as a task unlikely to be completed without violating the organization’s information security policy (ISP). Design/methodology/approach An empirical test of the suggested relationships in the proposed model was conducted through a field study using the survey method for data collection. Pre-tests, pre-study, main study and a follow-up study compose the frame of our methodology where more than 500 respondents are involved across different organizations. Findings The results confirm that the antecedents that explain the escalation of commitment behavior in terms of the effect of lost assets, such as time, effort and other resources, give us a new lens to understand noncompliance behavior; employees seem to escalate their commitments to the completion of their tasks at the expense of becoming noncompliant with ISP. Research limitations/implications One of the key areas that requires further attention from this study is to better understand the role of risk perceptions on employee behavior when dealing with value conflicts. Depending on how risk-averse or risk seeking an employee is, the model showed no significant support in either case to influence their noncompliance behavior. The authors therefore argue that employees' noncompliance may be influenced by more powerful beliefs, such as self-justification and sunk costs. Practical implications The results show that when employees are caught in tasks undergoing difficulties, they are more likely to increase noncompliance behavior. By understanding better how project obstacles result in such tasks, security managers can define new mechanisms to counter employees’ shift from compliance to noncompliance. Social implications Apart from encouraging compliance with enforcement mechanisms (using direct behavioral controls like sanctions or rewards), indirect behavior controls may also encourage compliance. The authors suggest that the ISPs should state that the organization would take positive actions toward task completion and help their employees to resolve their problems quickly. Originality/value This study is the first to tackle escalation of commitment theories and use antecedents that explain the effect of lost assets, such as time, effort and other resources can also explain noncompliance with ISP in terms of the value conflicts, where employees would often choose to forego compliance at the expense of finishing their tasks.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.783
Threshold uncertainty score0.843

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.011
Open science0.0010.000
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 head0.007
GPT teacher head0.250
Teacher spread0.243 · 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