The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Interfirm Collaboration Networks: The Impact of Large-Scale Network Structure on Firm Innovation
Open accessAbstract
The structure of alliance networks influences their potential for knowledge creation. Dense local clustering provides information transmission capacity in the network by fostering communication and cooperation. Nonredundant connections contract the distance between firms and give the network greater reach by tapping a wider range of knowledge resources. We propose that firms embedded in alliance networks that exhibit both high clustering and high reach (short average path lengths to a wide range of firms) will have greater innovative output than firms in networks that do not exhibit these characteristics. We find support for this proposition in a longitudinal study of the patent performance of 1,106 firms in 11 industry-level alliance networks.
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
Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557
Centrality in social networks conceptual clarification
Freeman, L. C. (1978) · Social Networks · doi:10.1016/0378-8733(78)90021-7 · Cited by 17,062
Burt, R. S. (1992) · doi:10.4159/9780674029095 · Cited by 9,093
Interorganizational Collaboration and the Locus of Innovation: Networks of Learning in Biotechnology
Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996) · Administrative Science Quarterly · doi:10.2307/2393988 · Cited by 8,499
Regression Analysis of Count Data
Cameron, A. C., & Trivedi, P. K. (2013) · doi:10.1017/cbo9781139013567 · Cited by 6,640
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×
“Different types of relationships may be better or worse for searching for, versus transferring, knowledge (Hansen 1999).”
BackgroundCollaboration and Creativity: The Small World Problem
Uzzi, B., & Spiro, J. (2005) · American Journal of Sociology · doi:10.1086/432782 · Cited by 1,885
Interaction Effects in Multiple Regression
Jaccard, J., & Turrisi, R. (2003) · doi:10.4135/9781412984522 · Cited by 1,797
Interfirm cooperation and startup innovation in the biotechnology industry
Shan, W., Walker, G., & Kogut, B. (1994) · Strategic Management Journal · doi:10.1002/smj.4250150505 · Cited by 1,166
Cited by
Carnabuci, G., & Operti, E. (2013) · Strategic Management Journal · doi:10.1002/smj.2084 · Cited by 596
Entrepreneurship in digital platforms: Anetwork‐centric view
Srinivasan, A., & Venkatraman, N. (2018) · Strategic Entrepreneurship Journal · doi:10.1002/sej.1272 · Cited by 331
Comparing alliance network structure across industries: observations and explanations
Rosenkopf, L., & Schilling, M. A. (2007) · Strategic Entrepreneurship Journal · doi:10.1002/sej.33 · Cited by 222
Self-citationOn the evolution of mobile platform ecosystem structure and strategy
Basole, R. C., & Karla, J. (2011) · Business & Information Systems Engineering · doi:10.1007/s12599-011-0174-4 · Cited by 192
Ego-Network Stability and Innovation in Alliances
Kumar, P., & Zaheer, A. (2019) · Academy of Management Journal · doi:10.5465/amj.2016.0819 · Cited by 171
Metadata
- Authors
- Schilling, M. A., & Phelps, C. C.
- Venue
- Management Science
- Published
- 2007-07
- Volume
- 53
- Issue
- 7
- Pages
- 1113-1126
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2052709366
- Cited by
- 1,551
- References
- 10
- FWCI
- 106.10
- Type
- journal article
- Language
- en
- Open access
- green
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Interfirm Collaboration Networks: The Impact of Large-Scale Network Structure on Firm Innovation. https://app.cochat.ai/papers/10.1287/mnsc.1060.0624
- The paper
- Schilling, M. A., & Phelps, C. C. (2007). Interfirm Collaboration Networks: The Impact of Large-Scale Network Structure on Firm Innovation. Management Science. https://doi.org/10.1287/mnsc.1060.0624
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.
