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Record W2157272513 · doi:10.1287/orsc.1120.0811

The Persistent Effect of Geographic Distance in Acquisition Target Selection

2013· article· en· W2157272513 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

VenueOrganization Science · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsUniversity of TorontoMcGill University
Fundersnot available
KeywordsDimension (graph theory)Geographical distanceSelection (genetic algorithm)Economic geographyMarketingIndustrial organizationKnowledge managementBusinessComputer scienceData scienceEconomicsArtificial intelligenceSociology

Abstract

fetched live from OpenAlex

Valuable resources often exist at distant points from a firm’s current locations, with the result that strategic decisions such as growth have a spatial dimension in which firms seek information and choose between geographically distributed alternatives. Studies show that geographic proximity facilitates the flow of resources, but there is limited understanding of factors that exacerbate or ease the impact of geographic distance when firms seek new resources. This paper argues that the difficulty of search increases with distance, particularly when search involves greater information processing, but that firms can partially overcome the constraints of distance with direct, contextual, and vicarious learning. We study 2,070 domestic acquisition announcements by U.S. chemical manufacturers founded after 1979. The results demonstrate the persistent effect of spatial geography on organizational search processes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.006
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 head0.004
GPT teacher head0.192
Teacher spread0.187 · 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