Measuring Environmental Strategy: Construct Development, Reliability, and Validity
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
Inconsistent results in prior work that link environmental strategy to competitive advantage may be due to the empirical difficulties of marrying the theoretical connection between a firm’s resource base and its environmental strategy. The authors contribute to the field by developing a measure that is congruent with the natural resource—based view, a dominant paradigm in this line of work. This article content analyses company reports and secondary data to develop a measure of environmental strategy grounded in the natural resource—based view. They identify six environmental capabilities that form components of a reliable, multidimensional construct of proactive environmental strategy. They also identify a measure of reactive compliance strategy. They verify reliability of their new measure through exploratory and confirmatory factor analyses, establish convergent and discriminant validity via a multitrait, multimethod matrix and demonstrate superior predictive validity of their measure compared to two others commonly used in the literature. In the conclusion, they discuss implications for research 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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