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Record W4417507766 · doi:10.1108/imr-11-2024-0452

Implementing market-oriented behaviours and coopetition activities in export markets

2025· article· en· W4417507766 on OpenAlexaff
James M. Crick, Dave Crick

Bibliographic record

VenueInternational Marketing Review · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCoopetitionExport marketingExport performanceVariety (cybernetics)Survey data collectionRobustness (evolution)Core (optical fiber)

Abstract

fetched live from OpenAlex

Purpose Market-oriented behaviours (MOBs) have been widely studied in domestic and international settings. However, it is unclear how smaller-sized exporters can manage MOBs to enhance their sales performance. That is, under-resourced firms might be constrained by their size, meaning that they require other forms of assistance from key stakeholder groups (e.g. competitors) to boost their export sales performance when implementing export MOBs. Accordingly, guided by the wider aspects of resource-based theory, the purpose of this study is to delve deeper into the relationship between export MOBs and export sales performance under different degrees of export coopetition (collaboration with competitors). Design/methodology/approach The research team collected and analysed survey responses from 118 smaller-sized exporters within the New Zealand wine industry. Such statistical data passed all major robustness checks (i.e. for reliability, different forms of validity and common method variance). In addition to the core model-testing stage, several post-hoc tests were conducted to further examine the statistical findings. Findings As expected, export MOBs had a positive and significant relationship with export sales performance. Yet, a surprising result was that export coopetition activities negatively and significantly moderated this link (a two-way interaction effect). The subsequent post-hoc tests revealed a variety of interesting nuances pertaining to how export MOBs and export coopetition activities can positively and negatively influence export sales performance. Originality/value This study offers unique insights regarding the circumstances where export coopetition activities assist (and do not assist) under-resourced businesses to amplify the performance-enhancing benefits of export MOBs. New evidence demonstrates that while export MOBs can help smaller-sized exporters to thrive within their markets, coopetition (formally and/or informally) can negatively impact export sales performance when implemented in tandem with MOBs. Hence, this investigation identifies some of the dark sides of international forms of coopetition.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.600
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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)0.0010.000

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 head0.013
GPT teacher head0.274
Teacher spread0.260 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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