IT outsourcing success: A dynamic capability-based model
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
This study proposes and tests a model of information technology outsourcing (ITO) capabilities as antecedents of ITO success. Building on the dynamic capabilities perspective (DCP), the model posits that ITO sensing, ITO seizing, and ITO orchestrating capabilities will influence ITO success by way of both successful reconfiguration of IT solutions and successful delivery of IT services. Building on extant ITO research, the model also hypothesizes that contract management capabilities and relationship management capabilities will influence ITO success via the successful delivery of IT services. Data from a cross-sectional survey of 152 large U.S.-based organizations in various industries were analyzed with PLS. The results support the hypothesis that successful reconfiguration mediates the effect of dynamic capabilities on ITO success. They partially support the hypothesis of successful delivery as mediator of the effect of dynamic capabilities on ITO success. The hypothesis of successful delivery as a mediator of the effect of relationship management capabilities and contract management capabilities on ITO success is supported only for relationship management capabilities. The study offers a theoretical anchoring for the conceptualization of ITO capabilities, which complements the rich and context-specific case-based literature of ITO capabilities and extends current research by adding to existing explanations of how ITO success is achieved.
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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 | 0.002 | 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 | 0.001 | 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