A Dynamic View of Marketing Capabilities for SMEs’ Export Performance
Bibliographic record
Abstract
The aim of this paper is to analyse marketing capabilities, through the dynamic capabilities framework, in order to increase understanding of how gradual global SMEs operating in traditional sectors can improve their export performance.The work is based on the exploratory, descriptive, qualitative method of a case study. An Italian SME has been selected on the basis of its export performance and marketing activities. The study has been conducted through secondary data analysis and a semi-structured in-depth interview with the CEO, with the aim of highlighting the relevance of emerging dynamic marketing capabilities connected with international performance.The results show that a SME, which lacks resources for international expansion, can improve its export performance by adapting, integrating, building, and reconfiguring its existing internal and external marketing capabilities for international markets.The principal limitation of this work is that, by analysing a company belonging to the alcoholic beverage sector, where price decisions are often left to importers, it was not possible to analyse dynamic pricing capabilities. This paper offers a contribution to the discussion of the internationalization of gradual global SMEs from the perspective of marketing and dynamic capabilities, missing from the literature, which is mainly focused on the study of multinational and born global enterprises.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".