Information Technology Outsourcing and Non-It Operating Costs: An Empirical Investigation1
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
Does information technology outsourcing reduce non-IT operating costs? This study examines this question and also asks whether internal IT investments moderate the relationship between IT outsourcing and non-IT operating costs. Using a panel data set of approximately 300 U.S. firms from 1999 to 2003, we find that IT outsourcing has a significant negative association with firms’ non-IT operating costs. However, this finding does not imply that firms should completely outsource their entire IT function. Our results suggest that firms benefit more in terms of reduction in non-IT operating costs when they also have higher levels of complementary investments in internal IT, especially IT labor. Investments in internal IT systems can make business processes more amenable to outsourcing, and complementary investments in internal IT staff can facilitate monitoring of vendor performance and coordination with vendors. We discuss the implications of these findings for further research and for practice.
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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 | 0.000 | 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 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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