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Cited by 1,681

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Overcoming Local Search Through Alliances and Mobility

Rosenkopf, Lori, Almeida, Paul·2003·Management Science

Abstract

Recent research suggests that, due to organizational and relational constraints, firms are limited contextually—both geographically and technologically—in their search for new knowledge. But distant contexts may offer ideas and insights that can be extremely useful to innovation through knowledge recombination. So how can firms reach beyond their existing contexts in their search for new knowledge? In this paper, we suggest that two mechanisms—alliances and the mobility of inventors—can serve as bridges to distant contexts and, thus, enable firms to overcome the constraints of contextually localized search. Through the analysis of patent citation patterns in the semiconductor industry, we first demonstrate both the geographic and technological localization of knowledge. We then explore if the formation of alliances and mobility of active inventors facilitate interfirm knowledge flows across contexts. We find that mobility is associated with interfirm knowledge flows regardless of geographic proximity and, in fact, the usefulness of alliances and mobility increases with technological distance. These findings suggest that firms can employ knowledge acquisition mechanisms to fill in the holes of their existing technological and geographic context.

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Metadata

Authors
Rosenkopf, L., & Almeida, P.
Venue
Management Science
Published
2003-06
Volume
49
Issue
6
Pages
751-766
ISSN
  • 0025-1909 (ISSN-L)
  • 1526-5501
OpenAlex
W2170846062
Cited by
1,681
References
10
FWCI
114.25
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Overcoming Local Search Through Alliances and Mobility. https://app.cochat.ai/papers/10.1287/mnsc.49.6.751.16026
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Rosenkopf, L., & Almeida, P. (2003). Overcoming Local Search Through Alliances and Mobility. Management Science. https://doi.org/10.1287/mnsc.49.6.751.16026

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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.