Internationalization of transnational entrepreneurial firms from an advanced to emerging economy: the role of transnational mixed-embeddedness
Bibliographic record
Abstract
Purpose This study investigates the role of transnational mixed-embeddedness when transnational entrepreneurial firms (TEFs) become internationalized. First-generation immigrant entrepreneurs who maintain business arrangements in their home and host countries own TEFs. In many cases, they internationalize from emerging economies to advanced economies. Nevertheless, this study focuses on TEF cases that internationalize from an advanced to an emerging economy, which prior transnational entrepreneurship studies have largely overlooked. Design/methodology/approach This research uses a qualitative approach based on six TEF case studies from Canada and the UK venturing into China to explore TEFs' internationalization. Findings The case studies explore the elements that constitute TEFs' cognitive and relational embeddedness—two main types of embeddedness—in home and host countries and how TEFs exploit such embeddedness for their internationalization. The results suggest that high levels of transnational mixed-embeddedness help TEFs reduce resource and institutional distance barriers in home countries, thereby assisting their internationalization. A framework that visualizes the role of transnational mixed-embeddedness in TEFs' internationalization and novel categorizations of transnational mixed-embeddedness is proposed. Originality/value Although there has been a growing demand for research on the emergence of internationalized smaller firms, there have been few empirical efforts on TEFs' internationalization. It is still unclear how TEFs internationalize differently than homegrown entrepreneurial firms. This study fills this gap in transnational entrepreneurship literature by examining the influence of transnational mixed-embeddedness on TEFs' internationalization.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".