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Cited by 354

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

Green consumption: Environmental knowledge, environmental consciousness, social norms, and purchasing behavior

Lin, Szu‐Tung, Niu, Han‐Jen·2018·Business Strategy and the Environment

Abstract

The 2015 Paris Agreement is the first historical global accord aiming to palliate global warming. Climate change has caused ecological, economic, and social disasters, among other things and has made not only nations review their environmental protection issues but also the consumers paying more attention to the environment and encouraging green oriented buying behaviors. This study targets Taiwan's consumers, and 649 valid questionnaires were recovered. Exploratory factor analysis was applied to extract the trait factors, whereas confirmatory factor analysis and structural equation modeling were used for the verification of the scale and structural model, respectively. The result shows that the consumers' environmental knowledge, environmental consciousness, and the social norms have had a positive effect on their environmental attitude, as do their environmental knowledge and the social norms to a sense of well‐being. Consumers purchasing intention and behavior are pointing towards green products. Therefore, companies need to respond to the consumers' demand and fulfill their social responsibility to release the green products so as to satisfy the consumers' needs.

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Crossref · 10.1002/bse.2233

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Metadata

Authors
Lin, S., & Niu, H.
Venue
Business Strategy and the Environment
Publisher
Wiley
Published
2018-10-04
Volume
27
Issue
8
Pages
1679-1688
ISSN
  • 0964-4733 (ISSN-L)
  • 1099-0836
OpenAlex
W2894690375
Cited by
354
References
7
FWCI
27.22
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.