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Record W2293403710 · doi:10.17705/1jais.00068

Theoretical Explanations for Firms' Information Privacy Behaviors

2005· article· en· W2293403710 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of the Association for Information Systems · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of CanadaQueen's University
KeywordsPrivacy policyInformation privacyBusinessPrivacy by DesignInformation systemKnowledge managementCompetitive advantageManagement information systemsResource-based viewPersonally identifiable informationInternet privacyComputer scienceMarketingComputer securityPolitical science

Abstract

fetched live from OpenAlex

Information privacy is an important information management issue that is increasingly challenging managers and policy makers. While many studies have investigated information privacy as an individual, sectoral, or national level phenomenon, there is a gap in our understanding of organizational approaches to developing and implementing policies and programs to manage customer information privacy. Information systems research lacks theory to explain firm level information privacy behaviors. This article argues for an expanded repertoire of theories to be applied to investigating information privacy, especially the role that the pursuit of competitive necessity versus competitive advantage plays in explaining organizational level behavior. The authors outline how the Institutional Approach (IA) and the Resource-Based View (RBV) of the firm offer compelling theoretical explanations for firms' behaviors and should be applied to privacy research within the information systems area.

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)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.007
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 head0.018
GPT teacher head0.300
Teacher spread0.282 · 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