Towards a successful learning process of companies from developing countries involved in offshore outsourcing: proposal for an integrative analytical framework
Bibliographic record
Abstract
Purpose This paper aims to contribute to international business research by providing an integrative framework of the factors determining the learning process of outsourcing companies in developing countries. Design/methodology/approach A systematic review of the literature was performed with an analysis of 84 articles published in peer-reviewed academic journals, published between 2000 and 2020. Findings The results show that the different factors should be seen as complementary and not mutually exclusive. It is the interaction between macro and micro factors that jointly shape the learning of developing country subcontractors. Moreover, the results of the analysis show that many existing studies have not been based on specific theoretical frameworks. Research limitations/implications This study develops a roadmap of the current state of research on the determinants of learning among developing country subcontractors and offers suggestions to guide future research. The authors conclude with a call for methodological advancement and theory development on the topic. Originality/value To the best of the authors’ knowledge, this study proposes the first comprehensive review of the literature on the factors determining the learning of subcontractors in developing countries. The authors have tried to provide an integrative analytical framework to discuss what has been known and what needs to be known in this regard.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".