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Record W2808653066 · doi:10.1080/09537325.2018.1487551

Incubator interdependence and incubation performance in China’s transition economy: the moderating roles of incubator ownership and strategy

2018· article· en· W2808653066 on OpenAlexaff
Hong Jin, Yang Yang, Hongying Wang, Yu Zhou, Ping Deng

Bibliographic record

VenueTechnology Analysis and Strategic Management · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of Waterloo
FundersHefei UniversityNational Natural Science Foundation of China
KeywordsIncubatorBusinessChinaCompetition (biology)Industrial organizationGovernment (linguistics)Economic systemMarket economyBusiness administrationEconomicsPolitical scienceEcology

Abstract

fetched live from OpenAlex

Taking an ecological perspective, we examine how two types of interdependence among business incubators located in the same region – mutualism and competition – affect the performance of these incubators. Using a dataset on Chinese National Technology Business Incubators (NTBIs) from 2008 to 2012, we show that incubator interdependence, measured by regional incubator density, has an inverted U-shaped relationship with a focal NTBI’s performance. We further explore how incubator ownership (government-owned vs. non-government-owned) and strategy (specialised vs. diversified) moderate the above relationship in China’s transitional economy. The results indicate that the linkage between incubator interdependence and incubation performance is stronger for non-government-owned and diversified business incubators. Theoretical and managerial implications are discussed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
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 head0.012
GPT teacher head0.220
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2018
Admission routes1
Has abstractyes

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