The effects of the chief technology officer and firm and industry R&D intensity on organizational performance
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
Between 1993 and 2013 the number and power of CTOs increased; as indicated in the percentage of firms with CTOs, their increasing presence on boards, their compensation relative to their CEOs, and compensation relative to other highly compensated executives. Firms which pursue an aggressive technology strategy (powerful CTO, high R&D spending) in industries in which technology is a critical contingency have well above normal market adjusted returns while those which pursue that strategy in industries in which technology is not critical have well below normal returns. These results empirically confirm longstanding, untested assumptions in the field of technology management. Moreover, the effect of R&D expenditures on firm performance is contingent on the degree to which technology is a critical contingency in the industry and on the power of the firm's CTO. These findings may explain the mixed results of past studies of the effects of R&D expenditure on firm performance. A model which integrates its own insights with those of earlier work on CTOs, R&D expenditures, firm strategy, and firm power dynamics is presented and supported.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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