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Record W4393443885 · doi:10.33423/jmpp.v25i1.6891

Protecting Intellectual Property in International Expansion: Preparing an Innovation-Based SME

2024· article· en· W4393443885 on OpenAlexaff
Majid Eghbali-Zarch, Mohamed Zain Patel

Bibliographic record

VenueJournal of Management Policy and Practice · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsIntellectual propertyBusinessTechnology innovationProperty (philosophy)Industrial organizationPolitical scienceLaw

Abstract

fetched live from OpenAlex

A key concern among innovation-based SMEs is to protect their intellectual property (IP) as they grow internationally. To explore the challenges such resource-constrained firms face, we conducted action research at a technology-based SME that aspired to expand internationally. Through collaborative and periodic interventions, we sought to help managers of the organization work around the issues that surfaced while preparing to internationalize further. Our collaboration led us to examine isolating mechanisms, such as rapid international expansion, that the SME could deploy to pre-empt competitive imitation of their innovative products and processes, especially as their IP is not protected legally (e.g., by patents). Results point to inevitable identified tensions and paradoxes, leading us to approaches and practices the firm can adopt.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.067
GPT teacher head0.309
Teacher spread0.242 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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