2020
DOI: 10.1016/j.tranpol.2020.04.018
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The evolution of dynamic interactions between the knowledge development of powertrain systems

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Cited by 12 publications
(7 citation statements)
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References 61 publications
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“…Our results relate to recent work on knowledge spillovers between the BEV, hybrid, and ICE powertrains [40]. In particular, using patent data from 2008 to 2016, the study reveals a symbiotic relationship between the ICE and hybrids, meaning that both powertrain technologies benefit from each other's knowledge development.…”
Section: Discussionsupporting
confidence: 78%
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“…Our results relate to recent work on knowledge spillovers between the BEV, hybrid, and ICE powertrains [40]. In particular, using patent data from 2008 to 2016, the study reveals a symbiotic relationship between the ICE and hybrids, meaning that both powertrain technologies benefit from each other's knowledge development.…”
Section: Discussionsupporting
confidence: 78%
“…Accordingly, our spatial perspective constitutes an additional dimension governing technological relations as illustrated by the diesel trajectory in the EU. The latter suggests that the knowledge spillover between hybrid and ICE are less pronounced in this territory because the environment is more favourable to ICE, which motivates manufacturers to pursue knowledge exploration in their own TIS instead of exploiting other technologies [40]. Moreover, the authors reveal a parasitic relationship, with BEVs benefitting from hybrids, and an amensalism in relation to ICE, again in favour of BEVs.…”
Section: Discussionmentioning
confidence: 93%
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“…A global patents database, used in [1] , documents the patents granted in the powertrain technological field of internal combustion engine vehicle (ICEV), hybrid electric vehicle (HEV) and battery electric vehicle (BEV) over 1985–2016. While these vehicle powertrains are satisfying the same transportation need of modern society, they are different in terms of comprising components.…”
Section: Datamentioning
confidence: 99%
“…Our database includes numerous descriptive features of each patent such as title, abstract, claim, priority, application and publication dates, IPCs, assignees/applicants, inventors, and cited references. These data are associated with the research article ‘The evolution of dynamic interactions between the knowledge development of powertrain systems’ [1] . The full dataset, which is attached to this article, may be useful to both researchers and practitioners interested in investigating, modelling or forecasting the complexity and evolution of the technical and knowledge domains of the vehicle powertrains, across a variety of instruments such as social network analysis and regression models.…”
mentioning
confidence: 99%