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Exploring the Influence of Executive Management Diversity on IT Governance

2018· article· en· W2784039023 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 Information Systems and Technology Management · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInformation Technology Governance and Strategy
Canadian institutionsUniversité du Québec à Montréal
FundersAutorité des Marchés FinanciersCanadian Academic Accounting AssociationUniversité du Québec à Montréal
KeywordsDiversity (politics)Corporate governanceDiversity managementPolitical scienceProcess managementKnowledge managementBusinessPublic administrationManagementComputer scienceEconomicsLaw

Abstract

fetched live from OpenAlex

As all organizations are attaching more strategic importance to information technology (IT), IT governance has gained researchers’ interest. In fact, a large body of literature focuses on firm-specific or executive management attributes such as leadership as determinants of IT governance. However, it is still relevant to identify other factors influencing IT governance. Since executive management demographics and demographic diversity have an impact on strategic decisions, we explore the influence of executive management diversity on IT governance. Results suggest that IT governance for a high educational-high tenure diversity profile differs significantly from that for a low industry-moderate tenure diversity profile and a high industry-low tenure diversity profile. Furthermore, IT governance structures differ according to executive management diversity profile more than IT governance processes and relational mechanisms.

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)0.001
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: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0010.001
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 head0.019
GPT teacher head0.203
Teacher spread0.183 · 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