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Record W3118741601 · doi:10.1111/radm.12450

The performance implications of patenting – the moderating effect of informal institutions in emerging economies

2021· article· en· W3118741601 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

VenueR and D Management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsYork University
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsLeverage (statistics)Transaction costBusinessContingencyIndustrial organizationValue (mathematics)Panel dataContext (archaeology)Institutional theoryResource dependence theoryEnterprise valueContingency theoryEconomicsAccountingMicroeconomicsFinanceManagement

Abstract

fetched live from OpenAlex

Research has highlighted the role of patenting on firms’ performance without elaborating on how patents can be leveraged to capture value. Drawing on the resource‐based view and institutional theory, this research attempts to extend patenting‐performance debate by examining the moderating effects of informal institutions – or specifically, political ties – on the patenting‐performance relationship. We argue that the leverage of political ties could eliminate uncertainty in patent rights by accessing information, reducing transaction costs, and facilitating bureaucratic arbitration, and therefore leads to better performance. Moreover, considering resource limitations and jurisdictional variations, the benefits of such a moderating approach may be more pronounced in a context characterized by high financial slack or low formal institutional development. Our analysis of panel data from 761 Chinese‐listed companies in the chemical, electronics, and pharmaceutical industries provides supports for both the moderating role of informal institutions on the patenting‐performance relationship and the contingency effects of financial slack and formal institutional development. This paper contributes to patent management literature by elaborating upon the mechanisms of how informal institutions can be leveraged to capture value from firms’ patent portfolios.

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 score0.192
Threshold uncertainty score0.307

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)0.0000.000

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 head0.016
GPT teacher head0.236
Teacher spread0.220 · 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