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Cited by 258

The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.

Green lies and their effect on intention to invest

Open access
Gatti, Lucia, Pizzetti, Marta, Seele, Peter·2021·Journal of Business Research

Abstract

Abstract The article explores the consequences of greenwashing deceptions on intention to invest. It analyses whether the presence of a greenwashing lie to stakeholders is detrimental to intention to invest. When a company greenwashes, it deliberately deceives stakeholders about its environmental commitment. Our results suggest that greenwashing has a greater negative impact on intention to invest than a corporate misbehaviour unrelated to a deceptive communication. In order to understand how different forms of greenwashing may affect intention to invest, we develop a typology of greenwashing deceptions, based on the variety of greenwashing cases that have emerged recently. The results show that individuals are less inclined to invest in a company that falsifies its claims (falsification) and which engages in manipulative business practices (deceptive manipulation), as compared to a company that instrumentally selects which information to disclose (information selection) or tries to obscure misbehaviours through publicizing its good business practices (attention diversion).

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Metadata

Authors
Gatti, L., Pizzetti, M., & Seele, P.
Venue
Journal of Business Research
Publisher
Elsevier BV
Published
2021-04
Volume
127
Pages
228-240
ISSN
0148-2963 (ISSN-L)
OpenAlex
W3127302906
Cited by
258
References
83
FWCI
25.45
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Green lies and their effect on intention to invest. https://app.cochat.ai/papers/10.1016/j.jbusres.2021.01.028
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Gatti, L., Pizzetti, M., & Seele, P. (2021). Green lies and their effect on intention to invest. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2021.01.028

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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.