Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations
Bibliographic record
Abstract
The authors content analyzed self-reported limitations and directions for future research in 1,276 articles published between 1982 and 2007 in the Academy of Management Journal, Administrative Science Quarterly, the Journal of Applied Psychology, the Journal of Management, and the Strategic Management Journal. In order of frequency, the majority of self-reported limitations, as well as directions for future research, pertains to threats to internal, external, and construct validity issues, and there is a significant increase in the reporting of these elements over time. Longitudinal analyses revealed that some of these increases varied across management subfields (i.e., business policy and strategy, organizational behavior, organizational theory, and human resource management), indicating unique research contexts within some research domains. Based on the analyses of self-reported limitations and future research directions, the authors offer eight guidelines for authors, reviewers, and editors. These guidelines refer to the need for authors to report limitations and to use a separate section for them and the need for reviewers to list limitations in their evaluations of manuscripts; authors and reviewers should prioritize limitations, and authors should report them in a way that describes their consequences for the interpretation of results. The guidelines for directions for future research focus on positioning them as a starting point for future research endeavors and for the advancement of theoretical issues. The authors also offer recommendations on how to use limitations and future research directions for the training of researchers. It is hoped that the adoption of these proposed guidelines and recommendations will maximize their value so that they can serve as true catalysts for further scientific progress in the field of management.
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 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 | 0.597 | 0.821 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.035 | 0.039 |
| Science and technology studies | 0.010 | 0.021 |
| Scholarly communication | 0.034 | 0.052 |
| Open science | 0.012 | 0.014 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".