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Record W4293660584 · doi:10.1287/stsc.2022.0174

See You in Your Backyard: Multipoint Contact, Firm’s Capacity and Capability, and Technological Expansion

2022· article· en· W4293660584 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

VenueStrategy Science · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsYork University
Fundersnot available
KeywordsIndustrial organizationCompetition (biology)Product (mathematics)BusinessTechnological changeCompetitive advantageEconomicsMarketing

Abstract

fetched live from OpenAlex

Past studies of multipoint competition have mainly focused on the effect of multipoint contact in product markets on firm competitive behaviors in those markets only. Our study advances this literature by examining how multipoint contact in product markets affects a firm’s expansion into a rival’s technological areas. We further investigate the factors that moderate the proposed effect. Our analyses suggest that the degree of multipoint contact between a firm and a rival in product markets has an inverted U-shaped relationship with the degree of the firm’s expansion into the rival’s technological areas (patent classes). Furthermore, the firm’s capacity (market share) and capability (status in terms of technological development) relative to the rival’s have different moderating effects on the relationship between multipoint contact in product markets and the firm’s expansion into the rival’s technological areas. Our findings contribute to the literatures on multipoint contact, competitive dynamics, and firm technology strategies.

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 score0.447
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
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 head0.043
GPT teacher head0.251
Teacher spread0.208 · 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