The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
Knowledge Recombination Across Technological Boundaries: Scientists vs. Engineers
Open accessAbstract
Building on the seminal work of Thomas J. Allen, we contribute to the emerging microlevel theory of knowledge recombination by examining how individual-level characteristics of inventors affect the breadth of their technological recombinations. Our data set combines information from 30,550 European patents with matched survey data obtained from 1,880 inventors. The analysis supports the view that inventors with a scientific education are more likely to generate patents that span technological boundaries (in our case, 30 broad, top-level technological domains) than inventors with an engineering degree. A doctoral degree is associated with increased recombination breadth for all groups of inventors. The breadth of an inventor's technological recombinations diminishes with increasing temporal distance to his education, but the differences between scientists and engineers persist over time. Our findings provide several new insights for research on inventors, the literature on organizational learning and innovation, and strategy research. This paper was accepted by Lee Fleming, entrepreneurship and innovation.
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Cites
Absorptive Capacity: A New Perspective on Learning and Innovation
Cohen, W. M., & Levinthal, D. A. (1990) · Administrative Science Quarterly · doi:10.2307/2393553 · Cited by 35,728
The Structure of Scientific Revolutions
Kuhn, T. S., & Schlegel, R. (1963) · Physics Today · doi:10.1063/1.3050879 · Cited by 35,538
Exploration and Exploitation in Organizational Learning
March, J. G. (1991) · Organization Science · doi:10.1287/orsc.2.1.71 · Cited by 21,942
An Evolutionary Theory of Economic Change.
Loasby, B. J., Nelson, R. R., & Winter, S. G. (1983) · The Economic Journal · doi:10.2307/2232409 · Cited by 21,366
A Dynamic Theory of Organizational Knowledge Creation
Nonaka, I. (1994) · Organization Science · doi:10.1287/orsc.5.1.14 · Cited by 17,809 · cited 1×
“Because of the contextual embeddedness of distant technological knowledge (Nonaka 1994), an important part of this meta-learning ability is the skill to characterize phenomena in general forms and to abstract from the complexity of particular objects or systems (Nersessian 2002).”
BackgroundCapitalism, Socialism and Democracy
Fukuyama, F., & Schumpeter, J. A. (1997) · Foreign Affairs · doi:10.2307/20048211 · Cited by 15,264
Knowledge of the firm, combinative capabilities, and the replication of technology
Kogut, B., & Zander, U. (1992) · Organization Science · doi:10.1287/orsc.3.3.383 · Cited by 12,939
Upper Echelons: The Organization as a Reflection of Its Top Managers
Hambrick, D. C., & Mason, P. A. (1984) · The Academy of Management Review · doi:10.5465/amr.1984.4277628 · Cited by 10,220
THE STRUCTURE OF SCIENTIFIC REVOLUTIONS
MCGUIRE, J. E. (1963) · Philosophical Books · doi:10.1111/j.1468-0149.1963.tb00813.x · Cited by 8,424
Laursen, K., & Salter, A. (2006) · Strategic Management Journal · doi:10.1002/smj.507 · Cited by 6,324
Cited by
Renewing Research on Problemistic Search—A Review and Research Agenda
Posen, H. E., Keil, T., Kim, S., & Meissner, F. D. (2018) · Academy of Management Annals · doi:10.5465/annals.2016.0018 · Cited by 462
Copy, transform, combine: Exploring the remix as a form of innovation
Flath, C. M., Friesike, S., Wirth, M., & Thiesse, F. (2017) · Journal of Information Technology · doi:10.1057/s41265-017-0043-9 · Cited by 96
Metadata
- Authors
- Gruber, M., Harhoff, D., & Hoisl, K.
- Venue
- Management Science
- Published
- 2013-04
- Volume
- 59
- Issue
- 4
- Pages
- 837-851
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2132444505
- Cited by
- 305
- References
- 73
- FWCI
- 22.54
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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