Arbeitspapier
Knowing me, knowing you: inventor mobility and the formation of technology-oriented alliances
We link the hiring of R&D scientists from industry competitors to the subsequent formation of collaborative agreements, namely technology-oriented alliances. By transferring technological knowledge as well as cognitive elements to the hiring firm, mobile inventors foster the alignment of decision frames applied by potential alliance partners in the process of alliance formation thereby making collaboration more likely. Using data on inventor mobility and alliance formation amongst 42 global pharmaceutical firms over 16 years, we show that inventor mobility is positively associated with the likelihood of alliance formation in periods following inventor movements. This relationship becomes more pronounced if mobile employees bring additional knowledge about their prior firm's technological capabilities and for alliances aimed at technology development rather than for agreements related to technology transfer. It is weakened, however, if the focal firm is already familiar with the competitor's technological capabilities. By revealing these relationships, our study contributes to research on alliance formation, employee mobility, and organizational frames.
- Sprache
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Englisch
- Erschienen in
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Series: IRTG 1792 Discussion Paper ; No. 2018-007
- Klassifikation
-
Wirtschaft
Mathematical and Quantitative Methods: General
- Ereignis
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Geistige Schöpfung
- (wer)
-
Wagner, Stefan
Goossen, Martin C.
- Ereignis
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Veröffentlichung
- (wer)
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Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
- (wo)
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Berlin
- (wann)
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2018
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Wagner, Stefan
- Goossen, Martin C.
- Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
Entstanden
- 2018