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Record W3124859352

Institutional Regime Shift in Intellectual Property Rights and Innovation Strategies of Firms in China

2017· article· en· W3124859352 on OpenAlexaff
Kenneth Guang-Lih Huang, Xuesong Geng, Heli Wang

Bibliographic record

VenueSingapore Management University Institutional Knowledge (InK) (Singapore Management University) · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInnovation Policy and R&D
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEmbeddednessChinaIntellectual propertyBusinessProperty rightsDifferential (mechanical device)Differential effectsEconomic systemMarket economyEconomicsPolitical scienceLawSociologyMicroeconomics
DOInot available

Abstract

fetched live from OpenAlex

Duplicate record, see https://ink.library.smu.edu.sg/lkcsb_research/5139/. This study develops a novel conceptual framework to understand the differential impact of formal institutional regime shift in intellectual property rights on the innovation and patenting strategies of Chinese and Western firms operating in China. We argue that to the extent that Chinese firms have been deeply embedded in China’s informal institutions, they are less responsive to formal institutional changes than Western firms operating in China. Using the major China patent law reform of 2001 as an exogenous event, we find results consistent with our key arguments: With the strengthening of the previously weak (utility model) patent protection, Chinese firms are less likely to apply for such patents to safeguard their innovations than Western firms. However, this difference becomes less pronounced in regions with higher quality intellectual property rights and legal institutions that foster research and development and innovation, and when Western firms gain longer operational experience in China. This study advances our understanding of the intricate interaction between formal and informal institutions and specifically how “stickiness” may arise in their substitutive relationship because of the embeddedness of firms in informal institutional environments. It also provides important implications for policy and innovation strategies for policy makers and firms in emerging economies.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.032
GPT teacher head0.221
Teacher spread0.189 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations1
Published2017
Admission routes1
Has abstractyes

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