Multidisciplinary R&D project success in small firms: The role of multiproject status and project management experience
Bibliographic record
Abstract
R&D projects in small biotechnology firms frequently involve knowledge from multiple technical fields and research in different problem domains. An increase in project knowledge scope, defined as the number of technical fields an R&D project covers, can be challenging for resource‐constrained small firms. These firms often rely primarily on their principal investigators (PIs), who act as heavyweight project managers in guiding project ideas to successful R&D outcomes. PIs also work concurrently on multiple projects, a strategy to promote learning across projects. To better understand how small firms PIs manage projects with high knowledge scope, our research assembles and analyzes a data set of 1374 R&D projects conducted by 933 small firms in the context of U.S. Small Business Administration awards. Results, after accounting for endogeneity, suggest a negative association between project knowledge scope and project success, which we measured using patent forward citation counts. We also find that a PI's multiproject status negatively moderates (i.e., amplifies) this association, while project management experience positively moderates (i.e., weakens) it. A follow‐up post hoc analysis suggests that a shared problem domain is a key contingency for the moderation effects of both multiproject status and project management experience. Taken together, our research offers insights on how to effectively manage R&D projects in resource‐constrained small 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".