Design Thinking for Competitive Intelligence in a Digital Business Transformation Context
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 paper examines how Design Thinking (DTh) can enhance Competitive Intelligence (CI) practices in the context of businesses and organizations engaged in a Digital Transformation (DTr) journey. The objective of the paper is to summarize the key insights based on an extensive literature review and engage in a critical reflection that could open the possibility for future research focusing on the development of actionable frameworks that could help executive managers integrate DTh and CI practices in pursuing the DTr of their organization. One of its key contributions is the identification of the value proposition concept as an integrative construct that could help in bringing together the DTh and CI perspectives in designing and managing the DTr strategies of new or established firms. The insights formulated in this paper will be valuable to both scholars and practitioners.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| 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