MétaCan
Menu
Back to cohort
Record W4399798139 · doi:10.55482/jcim.2024.34138

Breaking Boundaries: A Study on the Innovative Network Strategies of Canadian SMEs Expanding into Unfamiliar Markets

2024· article· en· W4399798139 on OpenAlexaffvenueabout
Anas Qutob, Yu Wei Ye

Bibliographic record

VenueJournal of Comparative International Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCLARITYOutsourcingBusinessObjectivity (philosophy)EntrepreneurshipInstitutionIndustrial organizationMarketingEconomic geographyPublic relationsPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Small and medium-sized enterprises (SMEs) rely on network ties to facilitate overseas expansion. However, the expansion may be hindered when geographical and institutional distance is great, and boundaries of network connections are reached since the information from those networks may be distorted and lack objectivity. Nevertheless, Canadian SMEs with native-born owners have succeeded in expanding into geographically and institutionally distant markets despite possessing no pre-existing ties. Drawing on insights from institution- and network-based views, we investigate this understudied issue through a generic inductive interview of six Canadian SMEs that have either expanded into or plan expansion into the United Arab Emirates in which they had no pre-existing ties. Results reveal that all firms understood that institutional differences affect the business environment. They embarked on a distinct networking approach, focusing on broadening their existing network in the early stage and making full use of outsourcing networking activities. The research helps pave the way for further clarity and understanding of the dynamic nature of international entrepreneurship when relating to distant yet commercially attractive markets.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.000
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 head0.032
GPT teacher head0.297
Teacher spread0.265 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Comparative International ManagementSame topicOutsourcing and Supply Chain ManagementFrench-language works237,207