An empirical assessment of transaction risks of IT outsourcing arrangements: an event study
Bibliographic record
Abstract
Our paper uses stock market reactions to assess various risks associated with IT outsourcing. Because much of the value and cost of IT outsourcing is intangible, hidden, and long-term oriented, most prior studies have articulated IT outsourcing risks conceptually and paid little attention to an empirical validation of such risks. We employ an event study methodology to assess how investors perceive and evaluate the risks related to IT outsourcing. More precisely, we empirically test the extent to which sources of IT outsourcing transaction risk (including asset-specificity, resource dependency, technological discontinuity, and performance monitoring) influence investors' reactions to IT outsourcing announcements. Our results indicate that investors exhibit two extreme responses: one perceives that benefits from IT outsourcing outweigh the risks associated with it; the other adopts the exact opposite view. Further analyses reveal that asset specificity of the IT resources to be outsourced and the size of the contract are negatively correlated with investors' reactions as measured by stocks' cumulative abnormal returns (CARs). Contrary to our predictions, contract duration and performance monitoring problems were not significantly associated with the market reaction. We discuss these findings and offer implications for both research and practice.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".