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Product Innovations in Emerging Economies: The Role of Foreign Knowledge Access Channels and Internal Efforts in Chinese Firms

2009· article· en· W2113004604 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

VenueManagement and Organization Review · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEmerging marketsAbsorptive capacityBusinessIndustrial organizationChinaIndigenousForeign direct investmentProduct (mathematics)New product developmentProduct innovationMarketingInternational tradeEconomics

Abstract

fetched live from OpenAlex

In this paper, we theoretically and empirically investigate factors that contribute to product innovation by firms in emerging markets. Combining the innovation literature with the latecomer literature on ‘catch-up’ strategies of firms in newly industrialized economies, we posit that access to foreign knowledge is essential for fostering product innovation. In particular, we investigate how innovation clusters formed by inward foreign direct investments in an emerging market and export activities of a firm are effective channels for acquiring foreign knowledge. We also suggest firms that invest in research and development and marketing activities benefit further from access to foreign knowledge due to increased absorptive capacity. Empirically, we employ information on over 160,000 indigenous manufacturing firms in China in 2005–2006. We find strong empirical support for our theoretical framework and conclude by discussing the implications for both theory and managerial practice.

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 score0.230
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.248
Teacher spread0.239 · 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