Do Market Leaders Lead in Business Process Innovation? The Case(s) of E-business Adoption
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
Are market leaders more likely to be early adopters of business process innovations? Although they tend to enjoy economies of scale in adoption, leaders may find that adjustment costs also increase with scale. Prior work has focused on how misalignment of incumbents’ internal capabilities may affect their technology strategy. However, technology-capability misalignment may exist outside the firm boundary as well. In this paper, I build on mainstream product innovation concepts to predict when market leaders will adopt certain business process innovations. I then test these predictions in a large data set on early e-business adoption, leveraging its novel insight into focal firms, their markets, and their customers. I find market leaders were significantly more likely to embrace new information technology-enabled practices—except when customer adjustment costs were a significant concern. These findings highlight the strategic significance of external capabilities in the face of technological change. This paper was accepted by Bruno Cassiman, business strategy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.007 |
| 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