The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Innovation and firm growth: Does firm age play a role?
Abstract
This paper explores the relationship between innovation and firm growth for firms of different ages. We hypothesize that young firms undertake riskier innovation activities which may have greater performance benefits (if successful), or greater losses (if unsuccessful). Using an extensive Spanish Community Innovation Survey sample for the period 2004–2012, we apply panel quantile regressions to study the effect of R&D activities on firm growth (i.e. sales growth, productivity growth and employment growth). Our results show that young firms face larger performance benefits from R&D at the upper quantiles of the growth rate distribution, but face larger decline at the lower quantiles. R&D investment by young firms therefore appears to significantly riskier than R&D investment by more mature firms, which suggests some policy implications.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Understanding Interaction Models: Improving Empirical Analyses
Brambor, T., Clark, W. R., & Golder, M. (2006) · Political Analysis · doi:10.1093/pan/mpi014 · Cited by 6,223
The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits
Hansen, M. T. (1999) · Administrative Science Quarterly · doi:10.2307/2667032 · Cited by 5,809 · cited 1×
“There is evidence on the positive effect of firm age on the likelihood of superior organizational (Argote, 1999), new product development (Hansen, 1999; Sivadas and Dwyer, 2000) and innovative outcomes (Tripsas and Gavetti, 2000).”
Understanding dynamic capabilities
Winter, S. G. (2003) · Strategic Management Journal · doi:10.1002/smj.318 · Cited by 5,315
The dynamic resource‐based view: capability lifecycles
Helfat, C. E., & Peteraf, M. A. (2003) · Strategic Management Journal · doi:10.1002/smj.332 · Cited by 4,553
Aging, Obsolescence, and Organizational Innovation
Sørensen, J. B., & Stuart, T. E. (2000) · Administrative Science Quarterly · doi:10.2307/2666980 · Cited by 1,862
Causal inference with observational data
Nichols, A. (2007) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0800700403 · Cited by 339
Cited by
Cost pressure or innovation-driven? Social insurance and firm exporting
Zhao, X., Jia, C., & Li, H. (2025) · International Review of Financial Analysis · doi:10.1016/j.irfa.2025.104086 · Cited by 9
Metadata
- Authors
- Coad, A., Segarra, A., & Teruel, M.
- Venue
- Research Policy
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 45
- Issue
- 2
- Pages
- 387-400
- ISSN
- 0048-7333 (ISSN-L)
- OpenAlex
- W1923243065
- Cited by
- 912
- References
- 6
- FWCI
- 86.49
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
