The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Acquiring New Technologies and Capabilities: A Grounded Model of Acquisition Implementation
Abstract
In this study, we explore seven in-depth cases of high-technology acquisitions and develop an empirically grounded model of technology and capability transfer during acquisition implementation. We assess how the nature of the acquired firms' knowledge-based resources, as well as multiple dimensions of acquisition implementation, have both independent and interactive effects on the successful appropriation of technologies and capabilities by the acquirer. Our inquiry contributes to the growing body of research examining the transfer of knowledge both between and within organizations. Propositions are developed to help guide further inquiry into the dynamics of acquisition implementation processes in general and, more specifically, the process of acquiring new technologies and capabilities from other firms.
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Cites
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Cited by
Graebner, M. E., & Eisenhardt, K. M. (2004) · Administrative Science Quarterly · doi:10.2307/4131440 · Cited by 566
Bauer, F., & Matzler, K. (2014) · Strategic Management Journal · doi:10.1002/smj.2091 · Cited by 498
Crane, A. (2013) · Academy of Management Review · doi:10.5465/amr.2011.0145 · Cited by 478
How Do Firms Learn to Make Acquisitions? A Review of Past Research and an Agenda for the Future
Barkema, H. G., & Schijven, M. (2008) · Journal of Management · doi:10.1177/0149206308316968 · Cited by 473
The Process of Postmerger Integration: A Review and Agenda for Future Research
Graebner, M. E., Heimeriks, K. H., Huy, Q. N., & Vaara, E. (2017) · Academy of Management Annals · doi:10.5465/annals.2014.0078 · Cited by 466
Metadata
- Authors
- Ranft, A. L., & Lord, M. D.
- Venue
- Organization Science
- Published
- 2002-08
- Volume
- 13
- Issue
- 4
- Pages
- 420-441
- ISSN
- 1047-7039 (ISSN-L)
- 1526-5455
- OpenAlex
- W2158885365
- Cited by
- 787
- References
- 59
- FWCI
- 25.73
- Type
- journal article
- Language
- en
- Open access
- closed
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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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