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Cited by 184

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Green process innovation: Where we are and where we are going

Open access
Khan, Sher Jahan, Kaur, Puneet, Jabeen, Fauzia, Dhir, Amandeep·2021·Business Strategy and the Environment

Abstract

Environmental pollution has worsened in the past few decades, and increasing pressure is being put on firms by different regulatory bodies, customer groups, NGOs and other media outlets to adopt green process innovations (GPcIs), which include clean technologies and end‐of‐pipe solutions. Although considerable studies have been published on GPcI, the literature is disjointed, and as such, a comprehensive understanding of the issues, challenges and gaps is lacking. A systematic literature review (SLR) involving 80 relevant studies was conducted to extract seven themes: strategic response, organisational learning, institutional pressures, structural issues, outcomes, barriers and methodological choices. The review thus highlights the various gaps in the GPcI literature and illuminates the pathways for future research by proposing a series of potential research questions. This study is of vital importance to business strategy as it provides a comprehensive framework to help firms understand the various contours of GPcI. Likewise, policymakers can use the findings of this study to fill in the loopholes in the existing regulations that firms are exploiting to circumvent taxes and other penalties by locating their operations to emerging economies with less stringent environmental regulations.

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Crossref · 10.1002/bse.2802

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Metadata

Authors
Khan, S. J., Kaur, P., Jabeen, F., & Dhir, A.
Venue
Business Strategy and the Environment
Publisher
Wiley
Published
2021-05-16
Volume
30
Issue
7
Pages
3273-3296
ISSN
  • 0964-4733 (ISSN-L)
  • 1099-0836
OpenAlex
W3163509316
Cited by
184
References
7
FWCI
25.04
Type
journal article
Language
en
Open access
hybrid

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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.