Diversification Dynamics and Core Business Performance: The Roles of Synergy & Resource Redeployment
Bibliographic record
Abstract
Contemporary research delves into the dynamics of diversification and resource allocation in multi-business firms. This paper examines the interdependent effects of synergy and resource redeployment on two measures of core business performance – competitive standing and financial performance. Empirically, we look at the U.S. commercial and investment banking convergence context, which involves a significant degree of demand and supply side relatedness between these markets, and a relative shift in demand towards investment banking, which creates opportunity costs of staying in commercial banking (these opportunity costs motivate resource redeployment into investment banking). Using a unique twenty-year panel dataset on the largest 95 bank holding companies in 1987-2006, we show that, initially, increased investment banking market share allows a bank to grow its commercial bank share and performance, through a mechanism of reverse synergy. Beyond a certain point, higher investment banking share results in performance declines in commercial banking, due to the dominance of resource redeployment over synergy.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".