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Record W1591868722

Waves of IT Innovation in Industries: Extending Diffusion Through the Integration of Punctuated Equilibrium and Fit

2006· article· en· W1591868722 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

VenueJournal of the Association for Information Systems · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicInnovation Diffusion and Forecasting
Canadian institutionsQueen's University
Fundersnot available
KeywordsPunctuated equilibriumDiffusionPropositionConceptualizationMacroIndustrial organizationInnovation diffusionDisruptive innovationEconomic geographyEconometricsEconomicsComputer scienceKnowledge managementIndustrial engineeringBusinessMarketingEngineeringGeologyArtificial intelligencePhysicsThermodynamicsEpistemology
DOInot available

Abstract

fetched live from OpenAlex

At the industry level, Information Technology (IT) driven transformation can be characterized by the rapid diffusion of IT innovation across firms. This paper suggests that IT innovation has occurred over the past fifty years in four major waves, but that not all industries have been equally affected by each wave’s passage. It is proposed that the depth and rate of diffusion of an IT innovation wave within an industry is contingent on the congruence between the characteristics of the wave and those of the industry. The theoretical basis for this proposition is found in the integration of Punctuated Equilibrium Theory and Venkatraman’s conceptualization of perspectives on fit, providing a macro view of diffusion of IT innovation at the industry level of analysis.

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)0.009
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.102
GPT teacher head0.344
Teacher spread0.242 · 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