Strategy by Doing and Product-Market Performance: A Contingency View
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
The strategy-by-doing perspective argues that firms operating in highly dynamic environments can benefit from taking strategic actions in lieu of advance planning because such actions have learning effects that help the firm keep pace with changes in the environment. The implicit assumption is that strategy by doing is effective in dynamic environments but likely not in stable environments. This study challenges this notion and expands the purview of the strategy-by-doing perspective. We first argue that strategy by doing is generally an effective strategy due to the organizational learning it facilitates. We next discuss how environmental dynamism is multidimensional, encompassing both market and technological dynamism. The positive effects of strategy by doing on product-market performance are amplified in highly dynamic environments that feature high levels of both market and technological dynamism. We go on to argue that stable environments are also suitable for strategy by doing, where it can facilitate opportunity creation. However, strategy by doing may hinder performance in mixed environments where one form of dynamism is present and the other is not. Focusing on strategy by doing in the form of product changes, our analysis of 4,000 firms over a period of 20 years shows support for our arguments about environmental contingencies affecting the relationship between strategy by doing and performance. We discuss how these findings have implications for theory and practice.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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