Advanced service offshore outsourcing: Exploring the determinants of capability development in emerging market firms
Bibliographic record
Abstract
Research Summary: We analyze the effect of offshored service task types on the development of capabilities in emerging market service provider firms. Using multiple case studies, we find that, dependent on task interdependent service types, implying different client interactions (firm‐external determinants), organizational capabilities are developed. More specifically, reciprocal task interdependent services generate human capital and management capabilities, while sequential task interdependent services generate organizational capital and management capabilities. Moreover, we find a relationship between the capabilities, where the deficient development of one capability can be mitigated by the development of another capability (firm‐internal determinants). Grounded in organization and service production theory, the article contributes to the thematic literature on service offshoring and the literature on organizational capabilities, with a particular focus on emerging market firms. Managerial Summary: Offshore outsourcing of advanced services is contributing to the development of capabilities for client firms, but is also expected to benefit service provider firms from emerging markets. Thus, we study how offshore outsourcing of services contributes to the development of these capabilities for service provider firms. We find that the characteristics of the services, which are causing different interactions with the client, help the firm develop a variety of capabilities. These capabilities affect the management, employees, and organization of service provider firms. Although the developed competencies are not a solution for all business development challenges of emerging market firms, the implications of this study could lead to competitive advantages for the firms if fully explored and exploited.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".