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Record W2165543564 · doi:10.1109/hicss.1991.184090

How does information technology affect business value-A reassessment and research propositions

2002· article· en· W2165543564 on OpenAlex
Heather A. Smith, James D. McKeen

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

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInformation Technology Governance and Strategy
Canadian institutionsQueen's University
Fundersnot available
KeywordsValuation (finance)Framing (construction)Information technologyValue (mathematics)Knowledge managementAffect (linguistics)Value of informationComputer scienceMarketingBusinessSociologyEngineeringArtificial intelligenceAccounting

Abstract

fetched live from OpenAlex

Because of the tremendous growth in the investment in information technology (IT), senior management has begun to demand that the value of this investment be assessed. This assessment is not possible without measurement. As a result, many feel that the measurement of IT value will be the critical management task for the next decade. The purpose of the article is threefold. First, it reviews the 'valuation of IT' research which has been done to date with the hope of understanding the reason for the equivocal results which have been obtained. It does this by examining the assumptions and measures which have been used in framing this research. Second, it looks at how organizational performance is measured and how performed is presumed to be affected by information technology. Finally, it explores a new set of assumptions, measures, and research propositions which may yield more fruitful results in assessing the value of information technology.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.006
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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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