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Record W3124152171 · doi:10.2189/asqu.53.1.73

Can you have your Cake and Eat it too? Structural Holes' Influence on Status Accumulation and Market Performance in Collaborative Networks

2008· article· en· W3124152171 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

VenueAdministrative Science Quarterly · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsYork University
Fundersnot available
KeywordsCooperativenessBusinessIndustrial organizationInvestment (military)Structural equation modelingInformation sharingStylized factStructural holesMarketingMicroeconomicsEconomicsSocial capitalPersonality

Abstract

fetched live from OpenAlex

Analyses of investment banks acting as advisers for merger and acquisition transactions in the United Kingdom during 1992–2001 are used to examine the relationship between structural holes in a firm's network and its performance. We argue that the firms need two types of information—about new business opportunities and partners' cooperativeness—to pursue, respectively, two types of performance goals: status accumulation and market performance. Open networks facilitate access to information about new business opportunities, but at the same time, open ego networks limit access to information about partners' cooperativeness. We find that there is a positive and reciprocal relationship between status accumulation and market performance. We also find that structural holes increase firms' status accumulation but also dampen their market performance.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.004
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 head0.037
GPT teacher head0.293
Teacher spread0.256 · 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