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Record W2020568965 · doi:10.1057/palgrave.jit.2000020

Performance Outcomes of Strategic and IT Competencies Alignment <sup>1</sup>

2004· article· en· W2020568965 on OpenAlexaff
Anne‐Marie Croteau, Louis Raymond

Bibliographic record

VenueJournal of Information Technology · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInformation Technology Governance and Strategy
Canadian institutionsUniversité du Québec à Trois-RivièresConcordia University
Fundersnot available
KeywordsStrategic alignmentStrategic information systemKnowledge managementStructural equation modelingInformation technologyFlexibility (engineering)Soft systems methodologyStrategic managementBusinessInformation systemProcess managementStrategic financial managementStrategic planningManagement information systemsComputer scienceManagementEngineeringMarketingEconomics

Abstract

fetched live from OpenAlex

This study empirically evaluates the business performance outcomes of aligning an organization's information technology (IT) competencies with its strategic competencies. Strategic competencies include components such as shared vision, cooperation, empowerment, and innovation, whereas IT competencies comprise connectivity, flexibility, and technological scanning. Top managers from 104 organizations completed a questionnaire analyzed with EQS, a structural equation modeling tool. Based on a covariation approach to alignment, results confirm that strategic and IT competencies alignment significantly enhances perceived business performance.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.210
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations114
Published2004
Admission routes1
Has abstractyes

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