A RICH VISION OF FIRM SUSTAINABLE COMPETITIVE ADVANTAGE: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Sustainable competitive advantage (SCA) is a fundamental construct in strategic management.Relying on a systematic review of empirical studies, this article shows that SCA as a dependent variable is built upon three fundamental dyadic properties: 1) absolute vs. relative, 2) punctual vs. persistent, and 3) unistakeholder vs. multistakeholder.From these properties arise eight possible forms of advantage, of which only four were documented by our review.Above all, no academic attention has been given to the richest possible form of SCA (relative, persistent, and multistakeholder).Firm SCA should more often be conceptualized as the simultaneous persistence of superior performance for all firm stakeholders.Moreover, our review supports the structural role of the three pillars supporting SCA development in a firm: 1) the industry-, 2) resource-, and 3) institution-based views.Overall, this study reveals that differentiation strategies, intangibles assets, dynamic capabilities, governance, and networks are among the most direct and important levers to trigger a firm's SCA.Finally, this paper outlines the research and practical recommendations that may facilitate further initiatives in studying and fostering SCA development in firms.
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 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) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".