MétaCan
Menu
Back to cohort
Record W2071528569 · doi:10.1002/smj.905

Erratic strategic decisions: when and why managers are inconsistent in strategic decision making

2010· article· en· W2071528569 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

VenueStrategic Management Journal · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsWestern University
Fundersnot available
KeywordsDynamismHostilityBusinessPerspective (graphical)Consistency (knowledge bases)Strategic thinkingPerceptionStrategic planningAffect (linguistics)Strategic controlStrategic managementMarketingPsychologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

Abstract While decision makers in organizations frequently make good decisions rooted in stable and consistent preferences, such consistency in outcomes is not always the case. In this study, we adopt a psychological perspective of judgment to investigate managers' erratic strategic decisions, which we define as a manager's inconsistent judgments that can shape the direction of the firm. In a study of 2,048 decisions made by 64 CEOs of technology firms, we examine how both metacognitive experience and perceptions of the external environment (hostility and dynamism) could affect the extent to which managers make erratic strategic decisions. The results indicate that managers with greater metacognitive experience make less erratic strategic decisions. The results also indicate that in hostile environments managers make more erratic strategic decisions. But contrary to our expectations, in dynamic environments managers make less erratic strategic decisions. Similarly, hostility and dynamism interact in their effect on erratic strategic decisions in that the positive relationship between environmental hostility and erratic strategic decisions will be less positive for managers experiencing high environmental dynamism than those experiencing low environmental dynamism. These results have important implications for strategic decision‐making research. Copyright © 2010 John Wiley & Sons, Ltd.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.693
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.272
Teacher spread0.221 · 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