A cognitive perspective of decision making in acquisition programs: insights from the high technology industry
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
Abstract: This paper explores the strategy formulation and the concepts related to decision making regarding acquisition formation in the information technology industry. Acquisitions, as part of the technical collaboration between firms in the information technology industry, have been intensive since 1990. The complexity of the related issues, critical success factors, conditions, triggers, motivations, causes, effects and their interlinked relationships, have not been fully covered in the literature of strategic management. In this paper, they are explored with a holistic approach to the study of strategic management, using a cause and effect mapping technique, known as cognitive mapping. The application of this research tool and the results help us to understand the importance of each concept (causes and consequences) used, the interrelationships between them, and the complexity of the decision making process. The paper is a contribution to the field of strategic management and to the cognitive approach in the management science.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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