MétaCan
Menu
Back to cohort
Record W2099658122 · doi:10.1177/0149206312458704

Strategic Momentum

2012· article· en· W2099658122 on OpenAlex
Scott F. Turner, Will Mitchell, Richard A. Bettis

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 Management · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMomentum (technical analysis)Consistency (knowledge bases)IncentiveAmbiguityProductivityProduct innovationProduct (mathematics)MarketingInnovation managementBusinessNew product developmentEconomicsComputer scienceMicroeconomicsMathematics

Abstract

fetched live from OpenAlex

Research on strategic momentum considers how experience with innovation affects firms’ subsequent innovativeness. Traditionally the momentum literature has emphasized arguments for an accelerating effect of innovation experience, but recent critiques and contrasting empirical results suggest ambiguity regarding how experience with innovation affects subsequent innovative activity. In this study, we develop arguments for a more expanded view of strategic momentum, examining momentum in the form of temporal consistency of ongoing innovation. This expanded view argues that organizations have incentives for steady-state patterns of innovation in the form of temporal consistency of ongoing innovation. To explore this expanded view of momentum, we examine how experience with innovation facilitates these temporally consistent patterns of innovation, as well as how increasing organizational age may inhibit such consistency. Analyses of generational product innovation in business productivity software highlight the importance of temporal consistency for innovativeness and momentum.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.036
GPT teacher head0.242
Teacher spread0.206 · 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