Unpacking the relationship between export coopetition activities and export sales performance
Bibliographic record
Abstract
Purpose While coopetition (cooperation among competitors) has been widely researched in domestic settings, relatively less work has evaluated how small exporters engage in these business-to-business (B2B) marketing strategies. Therefore, export coopetition activities could have different performance outcomes (and boundary conditions) to these B2B marketing practices in domestic arenas. Consequently, underpinned by resource-based theory (and focusing on smaller-sized and internationalised, businesses), the purpose of this paper is to unpack the relationship between export coopetition activities and export sales performance by accounting for key quadratic and moderating effects. Design/methodology/approach Survey responses were obtained from 107 small, and export-oriented, wine producers in South Africa. After refining the measurement scales, the quantitative data passed all major assessments of reliability, validity and common method variance. Subsequently, the elements of the conceptual model were tested through a hierarchical regression analysis. Moreover, a post-hoc test was undertaken to delve deeper into the nuances of the statistical results – and offer additional insights concerning how these B2B marketing strategies operate (and manifest) in export markets. Findings A significant non-linear (inverted U-shaped) relationship was found between export coopetition activities and export sales performance. No support was found for the moderators, namely, export geographical scope, export intensity or the interaction between these forms of internationalisation. An interesting issue to emerge from the post-hoc test was that export geographical scope yielded a quadratic link with export sales performance, for which the export coopetition activities construct did not moderate this connection (a non-significant interaction effect). These findings offer new insights that help inform the concentration versus spreading debate related to target market strategies. Originality/value New evidence emerges on the internationalisation of the coopetition construct, regarding how smaller-sized companies collaborate with their competitors within their export markets. Likewise, stronger insights arise concerning the dark sides of export coopetition activities via circumstances where they are harmful to internationalised firms. Moreover, improved claims are made about how resource-based theory serves as a useful tool to conceptualise the nuances of export coopetition activities and how they impact export sales performance. Collectively, this investigation not only responds to calls for research to evaluate coopetition in export markets but also embraces the complexities of these B2B marketing strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".