The Past and Future of Absorptive Capacity
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
“Absorptive capacity,” a widely studied construct in management research, remains underexplored in terms of its theoretical roots and development. In this curated collection, we present and analyze articles from the Academy of Management’s family of journals, shedding light on organizations’ abilities to recognize, assimilate, and apply external knowledge. We enhance our collective understanding of absorptive capacity by delineating four schools of thought that have been advanced through the articles in our collection. In addition to opportunities for further developing and integrating the ideas of the four schools of thought, we identify three themes for future research that span the schools and that also have the potential to leverage progress in this area of research. Building on the curated work, we explain opportunities for future research to tackle unresolved issues to offer insights regarding the roles of individuals and the microfoundations in the process and multidimensionality of absorptive capacity. We further explain the need to examine how advanced artificial intelligence may affect absorptive capacity, and call for future work to add to our understanding in this domain.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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