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Cited by 426

The DOI matches its Crossref record; 93 of the 93 references it cites were found in a registry or an index.

Knowledge sources and impacts on subsequent inventions: Do green technologies differ from non-green ones?

Open access
Barbieri, Nicolò, Marzucchi, Alberto, Rizzo, Ugo·2020·Research Policy

Abstract

The paper investigates the nature and impact of green technological change. We focus on the search and impact spaces of green inventions: we explore the knowledge recombination processes leading to the generation of inventions and their impact on subsequent technological developments. Using a large sample of patents, filed during the period 1980-2012, we employ established patent indicators to capture the complexity, novelty and impact of the invention process. Technological heterogeneity is controlled for by comparing green and non-green technologies within narrow technological domains. We find that green technologies are more complex and appear to be more novel than non-green technologies. In addition, they have a larger and more pervasive impact on subsequent inventions. The larger spillovers of green technologies are explained only partially by novelty and complexity.

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Metadata

Authors
Barbieri, N., Marzucchi, A., & Rizzo, U.
Venue
Research Policy
Publisher
Elsevier BV
Published
2020-03
Volume
49
Issue
2
Pages
103901
ISSN
0048-7333 (ISSN-L)
OpenAlex
W2802264600
Cited by
426
References
93
FWCI
35.27
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Knowledge sources and impacts on subsequent inventions: Do green technologies differ from non-green ones? https://app.cochat.ai/papers/10.1016/j.respol.2019.103901
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Barbieri, N., Marzucchi, A., & Rizzo, U. (2020). Knowledge sources and impacts on subsequent inventions: Do green technologies differ from non-green ones? Research Policy. https://doi.org/10.1016/j.respol.2019.103901

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.