Factors influencing the internationalization of small-sized textile firms in a Small Island Developing State: A Mauritian study
Bibliographic record
Abstract
Internationalization offers opportunities to small firms in small island developing states for market growth, sustainability, reduced dependency on local markets, and economies of scale. As small- and medium-sized enterprises (SMEs) are increasingly playing a significant role in many countries’ socioeconomic development, Mauritian-based textile manufacturers are seen as an engine of growth for the Mauritian economy by attracting foreign direct investment, subsequently creating jobs and strengthening the manufacturing base of the economy. In this regard, the contribution of the textile industry in transforming the Mauritian economy from a middle-income economy to a high-income economy is widely acknowledged. However, most of the small- and medium-sized Mauritian textile manufacturing firms are currently not internationalized and face several domestic survival and sustainability challenges resulting from the liberalized trading system adopted by the Mauritian government in 2005. In this article, we investigate firm size-related factors, which influence small textile manufacturers’ internationalization intentions. We argue that factors relating to financial and non-financial resources are the main causes discouraging small firms’ internationalization. These factors emerged from interviews with ten internationalized medium-sized textile manufacturers in Mauritius that overcame their size-related barriers. We further extended the research by surveying the whole population of internationalized medium-sized textile manufacturers in Mauritius for triangulation purposes.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".