Understanding How Resources and Capabilities Affect Performance: Actively Applying the Resource-Based View in the Classroom
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 resource-based view is a strategic framework for understanding why some firms outperform others. Its importance is reflected in its wide inclusion in strategy texts as a tool for assessing a firm’s internal strengths and weaknesses. This article outlines an experiential exercise that demonstrates how different bundles of resources and capabilities may explain differences in value created across firms. The primary benefit of this in-class exercise is that students actively apply Barney’s VRIO ( v aluable, r are, i nimitable, and o rganized) framework to understand why their team won or lost. The debrief can also focus on issues such as the impact of imitability on sustainability, why strategies emerge, and elements of a good strategy. Preliminary data from 18 undergraduate and graduate sections indicates that learning objectives have been consistently met.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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