Bibliographic record
Abstract
This paper focuses on the concept of fit as a topic of research. The concept of fit has been viewed as an internal consistency among key strategic decisions or the alignment between strategic choices and critical contingencies with the environment (external), organization (internal), or both (external and internal). A number of research perspectives or approaches related to fit are presented.Research design problems are discussed: definition of terms, theoretical issues, and empirical issues. Emphasis is on how key variables or dimensions of fit are defined and measured in research. A six-celled matrix is proposed as a conceptual scheme to distinguish different perspectives of fit and to portray congruence relationships more accurately. The matrix includes three common dimensions: strategy, organization, and environment. The matrix also suggests two levels of strategy—corporate or business—and three domains of fit—external, internal, or integrated. These suggest different research perspectives for the study of fit. Examples from the literature are provided to illustrate and support this conceptual scheme. Finally, implications for management and further study are outlined.
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 | 0.026 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.005 | 0.029 |
| Scholarly communication | 0.011 | 0.023 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".