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Cited by 232

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Explaining Socially Responsible Consumer Behavior: A Meta-Analytic Review of Theory of Planned Behavior

Han, Tae-Im, Stoel, Leslie·2017·Journal of International Consumer Marketing

Abstract

This study reviews previous studies on socially responsible consumers and identifies major antecedents of behavioral intentions to contribute to the theoretical understanding of their purchase behaviors. Meta-analytic procedures were used to (1) quantify the relationship between theory of planned behavior (TPB) constructs, (2) examine the contribution of additional predictors to explain behavioral intention, and (3) identify moderators that influence the strength of the relationships between TPB constructs. The results reveal key factors underlying the consumer decision-making process and provide useful information for marketers in developing strategies that can increase acceptance and purchase of products/services that address consumers' ethical concerns.

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Crossref · 10.1080/08961530.2016.1251870

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Metadata

Authors
Han, T.-I., & Stoel, L.
Venue
Journal of International Consumer Marketing
Published
2016-12-02
Volume
29
Issue
2
Pages
91-103
ISSN
  • 0896-1530 (ISSN-L)
  • 1528-7068
OpenAlex
W2559723709
Cited by
232
References
13
FWCI
13.22
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Explaining Socially Responsible Consumer Behavior: A Meta-Analytic Review of Theory of Planned Behavior. https://app.cochat.ai/papers/10.1080/08961530.2016.1251870
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Han, T.-I., & Stoel, L. (2017). Explaining Socially Responsible Consumer Behavior: A Meta-Analytic Review of Theory of Planned Behavior. Journal of International Consumer Marketing. https://doi.org/10.1080/08961530.2016.1251870

Data sources

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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.