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Record W2143849718 · doi:10.1002/smj.550

Niche width revisited: organizational scope, behavior and performance

2006· article· en· W2143849718 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 · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsUniversity of Toronto
FundersNational Science Foundation
KeywordsScope (computer science)Diversification (marketing strategy)NicheGeneralist and specialist speciesIndustrial organizationNiche marketBusinessMarketingCompetitive advantagePhenomenonComputer scienceEconomicsEcologyBiology

Abstract

fetched live from OpenAlex

Abstract Although strategy research typically regards firm scope as a positional characteristic associated with performance differences, we propose that broad contemporary scope also provides insight into the routines that govern firm behavior. To attain broad scope, firms must repeatedly explore outside the boundaries of their current niche. Firms with broad niches therefore operate under a set of routines that repeatedly propel them into new market segments, expanding their niche. These niche expansions, however, involve risky organizational changes, behavior that disadvantages generalists relative to specialists, despite the positional value of broad scope. Empirical analyses of machine tool manufacturers and computer workstation manufacturers support this conjecture: (i) generalists introduce new products at a higher than optimal rate, thereby increasing their exit rates; and (ii) generalists also more frequently launch new models with novel features or targeted at new consumer segments rather than improving only incrementally on existing products, further accelerating their odds of failure. After adjusting for these behavioral differences, broad niche widths reduce exit rates, suggesting that they provide positional advantages. The paper discusses how this phenomenon may help to explain the diversification and multi‐nationality discounts. Copyright © 2006 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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.613
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.209
Teacher spread0.185 · 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