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Capturing Value from Technological Innovation: Integration, Strategic Partnering, and Licensing Decisions
Abstract
The competitive potential embedded in new technology is not always captured by the innovator. Follower firms, customers, and suppliers are often the principal beneficiaries. When innovating firms lose to followers or imitators, the reason is often the failure of the innovator to build or access competitive capacity in activities, such as manufacturing, which are complementary to the innovation. This paper analyzes the make-or-buy decision with respect to these capacities in different competitive environments, including that of rapid technological change and easy imitation. Often it is pointless for firms to invest in R&D unless they are also willing to invest in the development of certain complementary capacities, at home or abroad.
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Citations
Cited by
The resource-based theory of competitive advantage: Implications for strategy formulation
Grant, R. M. (1991) · California Management Review · doi:10.2307/41166664 · Cited by 9,699
SOMETHING OLD, SOMETHING NEW: A LONGITUDINAL STUDY OF SEARCH BEHAVIOR AND NEW PRODUCT INTRODUCTION.
Katila, R., & Ahuja, G. (2002) · Academy of Management Journal · doi:10.2307/3069433 · Cited by 3,640
Unruh, G. C. (2000) · Energy Policy · doi:10.1016/s0301-4215(00)00070-7 · Cited by 3,304
Innovation, Openness, and Platform Control
Parker, G., & Van Alstyne, M. (2018) · Management Science · doi:10.1287/mnsc.2017.2757 · Cited by 549
Garrison, G., Wakefield, R. L., & Kim, S. (2015) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2015.03.001 · Cited by 250
Metadata
- Authors
- Teece, D. J.
- Venue
- Interfaces
- Published
- 1988-06
- Volume
- 18
- Issue
- 3
- Pages
- 46-61
- ISSN
- 0092-2102 (ISSN-L)
- 1526-551X
- OpenAlex
- W2163125255
- Cited by
- 430
- References
- 0
- FWCI
- 42.04
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
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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.
