Incumbent Firm Adaptation: New Perspectives on Organizational Change
Bibliographic record
Abstract
The ability of organizations to innovate and adapt to changes in the external environment is a critical component of competitive success. Research on incumbent firm adaptation has historically focused on the importance of developing new capabilities; increasingly, scholars are highlighting that adaptation also requires shifts in organizational characteristics and processes. The purpose of this symposium is to showcase current research that offers a range of perspectives on how incumbent firms engage in organizational change as their environments shift. Some of the papers draw attention to the implications of elements of organizations that have been given relatively little attention in the literature on incumbent adaptation—for example, the role of intra-organizational power struggles, routines, and organizational identity. Others consider the unique ways in which incumbents, versus new entrants, react to environmental change. The papers take a range of different theoretical and methodological approaches to the topic. Our symposium is intended to integrate these approaches to broaden our general understanding of organizational change. Truce Breaking and Remaking: The CEO's Role in Changing Organizational Routines Presenter: Sarah Kaplan; U. of Toronto
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| 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".