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Record W3161890395 · doi:10.4236/ti.2021.122006

Role of Technology Transfer, Innovation Strategy and Network: A Conceptual Model of Innovation Network to Facilitate the Internationalization Process of SMEs

2021· article· en· W3161890395 on OpenAlexvenueno aff
Serena Mancini, José Luís Calvo González

Bibliographic record

VenueTechnology and Investment · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsnot available
FundersUniversidad Nacional de Educación a DistanciaUniverzita Karlova v Praze
KeywordsInternationalizationBusinessCompetence (human resources)Context (archaeology)Knowledge managementConceptual modelIndustrial organizationKnowledge transferProcess (computing)Empirical researchConceptual frameworkEmpirical evidenceMarketingComputer scienceEconomicsManagement

Abstract

fetched live from OpenAlex

The purpose of this research paper is to increase the understanding on how the combination of technology transfer and innovation strategy has become key elements for ensuring the development and growth of SMEs since has enhanced their ability to be part of networks and has facilitated their access to international markets. We see that SMEs can balance their limited resources with careful participation in networks. Indeed most SMEs need to be part of networks to get their innovations and develop special competence on technology transfer and to rapidly access to international markets. Although there exists a well-developed tradition of industrial network research there is a lack of analysis of systematic and empirical models of network relating to the technology transfer and innovation strategy in the context of SMEs’ internationalization. Based on our research framework on theoretical insights from technology transfer’s topic and its extensive concepts of innovation, network and internationalization, we examine how the internationalization process is facilitated by SMEs’ networking capacity. Our findings allowed us to address an empirical study created to develop a systematic conceptual model of an innovation network and propositions regarding the access of SMEs to international markets. This model can be an easy-to-follow innovation model for SMEs when adopting a knowledge-transfer, innovation strategy, and networking approach. This helps to make certain that the important drivers and approaches for the innovative network capacity and internationalization performance of SMEs. These findings have critical implications for entrepreneurs in enhancing their firms in international performance. More specifically, we analyze how SMEs’ membership in networks or clusters stimulates the concrete collaboration with High Education Institutions (HEIs) or Public Research Institutions (PRIs), Governments, and other businesses and contribute to acquire and absorb innovation via different channels of external knowledge influencing SMEs’ behaviours at the international level.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.006
Scholarly communication0.0050.011
Open science0.0010.003
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.034
GPT teacher head0.244
Teacher spread0.210 · 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 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

Citations24
Published2021
Admission routes1
Has abstractyes

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