The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
R&D Networks
Abstract
We develop a model of strategic networks that captures two distinctive features of interfirm collaboration: bilateral agreements and nonexclusive relationships. Our analysis highlights the relationship between market competition, firms' incentives to invest in R&D, and the architecture of collaboration networks. In the absence of firm rivalry, the complete network, where each firm collaborates with all others, is uniquely stable, industry-profit maximizing, and efficient. By contrast, under strong market rivalry the complete network is stable, but intermediate levels of collaboration and asymmetric networks are more attractive from a collective viewpoint. This suggests that competing firms may have excessive incentives to form collaborative links.
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Cites
Learning to predict by the methods of temporal differences
Sutton, R. S. (1988) · Machine Learning · doi:10.1007/bf00115009 · Cited by 5,148
Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
Sutton, R. S., Precup, D., & Singh, S. (1999) · Artificial Intelligence · doi:10.1016/s0004-3702(99)00052-1 · Cited by 3,119
Cited by
ARZAGHI, M., & HENDERSON, J. V. (2008) · Review of Economic Studies · doi:10.1111/j.1467-937x.2008.00499.x · Cited by 508
Allen, F., & Babus, A. (2008) · SSRN Electronic Journal · doi:10.2139/ssrn.1094883 · Cited by 365
Metadata
- Authors
- Goyal, S., & Moraga-Gonzalez, J. L.
- Venue
- The RAND Journal of Economics
- Publisher
- Wiley
- Published
- 2001
- Volume
- 32
- Issue
- 4
- Pages
- 686
- ISSN
- 0741-6261 (ISSN-L)
- OpenAlex
- W2096773542
- Cited by
- 360
- References
- 2
- FWCI
- 17.00
- Type
- journal article
- Language
- en
- Open access
- closed
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- Goyal, S., & Moraga-Gonzalez, J. L. (2001). R&D Networks. The RAND Journal of Economics. https://doi.org/10.2307/2696388
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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.
