(How) does digital transformation promote boundary-spanning strategies Evidence from Chinese firms' unrelated diversification
Bibliographic record
Abstract
The emergence of new generations of digital technologies has presented firms with important strategic opportunities at the corporate level. This study investigates the digital transformation - unrelated diversification link and theorises the role of industry shakeout and the performance expectation gap in said relationship. Our analysis based on the data of China's A-share listed manufacturing firms from 2015 to 2020 shows that: 1) the degree of firms' digital transformation is positively correlated to the degree of their unrelated diversification; 2) industry shakeout positively moderates the above relationship, i.e., in industries with a higher degree of shakeout, the positive digital transformation-unrelated diversification link is more pronounced; 3) the performance expectation gap negatively moderates the digital transformation-unrelated diversification link, i.e., the greater the performance expectation gap, the weaker the positive correlation between firms' digital transformation and their unrelated diversification.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".