Country Environments and the Adoption of IT Outsourcing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research on information technology (IT) outsourcing adoption has been confined to a single-country perspective. The understanding of how country-specific variables influence the adoption of IT outsourcing is limited. This study uses new institutional economics to build a framework that links country-level factors to the adoption of IT domestic outsourcing. The authors suggest that country-level factors, such as the maturity of the IT-related legal system, social trust, uncertainty avoidance, Internet penetration, and the maturity of the IT outsourcing market, affect the opportunism costs and coordination costs involved in domestic IT outsourcing and influence its adoption among firms. The results show that the maturity of the IT-related legal system, social trust, and the maturity of the IT outsourcing market are positively associated with IT outsourcing adoption. The authors conclude the paper with a discussion of the study’s implications for practice and future research.
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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 | 0.000 |
| 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 | 0.002 |
| 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 it