Hard and Soft Ways to Create Value from Information Flows: Lessons from the Canadian Financial Services Industry
Bibliographic record
Abstract
Abstract Over an extended period during the 1990s, using long interviews with the top management of five banks and secondary data, we studied the transformation of Canadian banks. We observed how the Canadian banks have changed to take full advantage of the increased technological potential for developing and exchanging information. The failure of the “pure players” has shown that the information advantages of the Internet are not sufficient to lead to sustainable competitive advantage. Existing financial institutions can make better use of that same information flow by combining it with organizational changes that make the new information more strategically valuable. By aligning information technology and the hard elements of their organizational architecture with soft elements like reputation, cooperation, and information sharing, traditional banks have developed powerful advantages in the 1990s. Résumé Dans les années 90, nous avons utilisé des données secondaires et les longues entrevues que nous avons eues avec les hauts responsables de cinq banques pour étudier les mutations du paysage bancaire canadien. Nous nous sommes intéressé à la façon dont les banques canadiennes se sont restructurées pour pouvoir tirer le maximum d'avantages des potentialités croissantes des technologies de l'information. L'échec relatif des banques virtuelles a démontré que les avantages informationnels basés sur le réseau Internet ne suffisent pas pour donner lieu à des avantages concurrentiels durables. Las banques traditionnelles peuvent parvenir à faire un meilleur usage des mêmes flux informationnels en les combinant à des changements organisationnels qui rendent la nouvelle information plus stratégiquenient valable. En accommodant les technologies de l'information et les composantes permanentes (hard elements) de leur architecture organisationnelle avec les composantes fluctuantes (soft elements) telles que la réputation, la coopération, et la diffusion des informations, les banques traditionnelles se sont créé de puissants avantages stratégiques au cours des années 90.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".