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Cited by 204

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Achieving Sustainable Development by Collaborating in Green Product Innovation

Melander, Lisa·2017·Business Strategy and the Environment

Abstract

Collaboration in green product innovation (GPI) is becoming increasingly important, and research on such innovation has grown in recent years. This study reviews literature on external collaborations in GPI to investigate drivers, inter‐organizational factors and intra‐organizational factors for such collaborations. The review includes a total of 67 papers. Survey studies and case studies are the methodologies applied most in the reviewed papers. The most common collaborators are suppliers and customers. Drivers include economic factors, regulations, customer demand, competitiveness and firm performance. Numerous inter‐organizational collaboration factors are presented and summarized in terms of partner selection, relationship management, knowledge access and agreements. Intra‐organizational factors mainly concern cross‐functional collaboration, capabilities and internal practices. Implications for policy and practitioners are presented. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment

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Metadata

Authors
Melander, L.
Venue
Business Strategy and the Environment
Publisher
Wiley
Published
2017-05-30
Volume
26
Issue
8
Pages
1095-1109
ISSN
  • 0964-4733 (ISSN-L)
  • 1099-0836
OpenAlex
W2609060126
Cited by
204
References
3
FWCI
20.80
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Achieving Sustainable Development by Collaborating in Green Product Innovation. https://app.cochat.ai/papers/10.1002/bse.1970
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Melander, L. (2017). Achieving Sustainable Development by Collaborating in Green Product Innovation. Business Strategy and the Environment. https://doi.org/10.1002/bse.1970

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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.