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Cited by 419

The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.

Resource efficient eco-innovations for a circular economy: Evidence from EU firms

Cainelli, Giulio, D’Amato, Alessio, Mazzanti, Massimiliano·2020·Research Policy

Abstract

Abstract Innovation adoption and diffusion by firms are key pillars for the EU strategy on resource efficiency and the development of a circular economy. This paper presents new EU evidence regarding the role of environmental policy and green demand drivers to sustain the adoption of resource efficiency-oriented eco-innovations. Using a large cross-section dataset of EU firms and accounting for sample selection and endogeneity, the results strongly support the idea that environmental policy and demand-side factors are both significant in driving the adoption of innovations that promote recycling, reduce waste and decrease the use of materials. The paper provides a relevant piece of new, quantitative-based knowledge, which complements the large case study-based evidence on sound management and policy strategies for the circular economy.

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Metadata

Authors
Cainelli, G., D’Amato, A., & Mazzanti, M.
Venue
Research Policy
Publisher
Elsevier BV
Published
2020-02
Volume
49
Issue
1
Pages
103827
ISSN
0048-7333 (ISSN-L)
OpenAlex
W2977894039
Cited by
419
References
46
FWCI
42.47
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Resource efficient eco-innovations for a circular economy: Evidence from EU firms. https://app.cochat.ai/papers/10.1016/j.respol.2019.103827
The paper
Cainelli, G., D’Amato, A., & Mazzanti, M. (2020). Resource efficient eco-innovations for a circular economy: Evidence from EU firms. Research Policy. https://doi.org/10.1016/j.respol.2019.103827

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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.