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Cited by 485

The DOI matches its Crossref record; 99 of the 99 references it cites were found in a registry or an index.

Enhancing corporate sustainable development: Stakeholder pressures, organizational learning, and green innovation

Zhang, Feng, Zhu, Lei·2019·Business Strategy and the Environment
DOI 10.1002/bse.2298
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Abstract

Green innovation has become the main path toward achieving corporate sustainable development. Despite the centrality of organizational learning in firms pursuing green activities, little research has considered its role in the relationship between stakeholder pressures and green innovation. By combining stakeholder theory and organizational learning theory, this study explores whether environmental pressures from different stakeholders influence green innovation differently and how this is further mediated by organizational learning. From a sample of 259 Chinese manufacturing firms, we find that consumer pressure has a greater positive effect on green product innovation than regulation pressure, whereas regulation pressure is more positively related to green process innovation than consumer pressure. Moreover, these two relationships are partially mediated by exploration learning and exploitation learning, respectively. These findings advance the existing research on the stakeholder pressures–green innovation linkage by revealing that consumer and regulation pressures influence green product innovation and green process innovation differently and through different organizational learning approaches.

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Metadata

Authors
Zhang, F., & Zhu, L.
Venue
Business Strategy and the Environment
Publisher
Wiley
Published
2019-03-08
Volume
28
Issue
6
Pages
1012-1026
ISSN
  • 0964-4733 (ISSN-L)
  • 1099-0836
DOI
10.1002/bse.2298
OpenAlex
W2922383698
Cited by
485
References
99
FWCI
41.81
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.