An Assessment of Resource-Based Theorizing on Firm Growth and Suggestions for the Future
Bibliographic record
Abstract
Together, Penrosean and Barnean resource-based logic make up the dominant theoretical approach to understanding firm growth. While extant literature focuses on a common lineage between Penrosean theory and the resource-based view (RBV), we explicate divergence at these origins of resource-based theorizing and subject the growth implications of each to meta-analytic testing. RBV’s central tenets concern resources that meet valuable, rare, inimitable, and nonsubstitutable (VRIN) criteria, while Penrose’s theory discusses the versatility of resources. Theoretically, VRIN resources allow firms to exploit unique opportunities, while versatile resources allow firms to recombine resources in novel ways to create growth. Using meta-analytic techniques, we find that versatile resources are associated with higher levels of growth, whereas VRIN resources are not. We offer novel insights into alternative characteristics of resources derived from the same conceptualization of the firm, add greater specificity to the performance construct, and open up avenues for new theorizing on firm growth that is more closely aligned with Penrose’s theory.
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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 | 0.049 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.011 | 0.026 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".