Architecture and evolvability of innovation ecosystems
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 132-144 |
Journal / Publication | Technological Forecasting and Social Change |
Volume | 136 |
Publication status | Published - 1 Nov 2018 |
Externally published | Yes |
Link(s)
Abstract
Prior studies have implied that the architecture of firms’ participation in an innovation ecosystem may affect the evolvability of their own ecosystems, thus conditioning firm strategies and performance. However, specific influences are unknown. In this paper, we abstract and model an innovation ecosystem as a network of firms connected by their technological dependences and assess its evolvability in the framework of the NK model. Network simulations suggest that although firms’ influence diversity promotes ecosystem evolvability, their influence density limits ecosystem evolvability. We also relate these findings to empirically observed differences in the architecture and evolvability of the automotive and electronics ecosystems. Implications from our findings may help firms either to better sense their ecosystems’ evolution prospects and adjust their strategies accordingly or to design and manage their technological dependences and the architecture of their ecosystem participation to influence the evolvability of their ecosystem in favor of their strategic intents and capability advantages. © 2017 Elsevier Inc.
Research Area(s)
- Evolvability, Industry architecture, Innovation ecosystem, Networks, Simulation
Bibliographic Note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
Citation Format(s)
Architecture and evolvability of innovation ecosystems. / Luo, Jianxi.
In: Technological Forecasting and Social Change, Vol. 136, 01.11.2018, p. 132-144.
In: Technological Forecasting and Social Change, Vol. 136, 01.11.2018, p. 132-144.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review