The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
When Do (and Don't) Normative Appeals Influence Sustainable Consumer Behaviors?
Abstract
The authors explore how injunctive appeals (i.e., highlighting what others think one should do), descriptive appeals (i.e., highlighting what others are doing), and benefit appeals (i.e., highlighting the benefits of the action) can encourage consumers to engage in relatively unfamiliar sustainable behaviors such as “grasscycling” and composting. Across one field study and three laboratory studies, the authors demonstrate that the effectiveness of the appeal type depends on whether the individual or collective level of the self is activated. When the collective level of self is activated, injunctive and descriptive normative appeals are most effective, whereas benefit appeals are less effective in encouraging sustainable behaviors. When the individual level of self is activated, self-benefit and descriptive appeals are particularly effective. The positive effects of descriptive appeals for the individual self are related to the informational benefits that such appeals can provide. The authors propose a goal-compatibility mechanism for these results and find that a match of congruent goals leads to the most positive consumer responses. They conclude with a discussion of implications for consumers, marketers, and public policy makers.
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Cited by
How to SHIFT Consumer Behaviors to be More Sustainable: A Literature Review and Guiding Framework
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Schumann, J. H., von Wangenheim, F., & Groene, N. (2014) · Journal of Marketing · doi:10.1509/jm.11.0316 · Cited by 287
Metadata
- Authors
- White, K., & Simpson, B.
- Venue
- Journal of Marketing
- Publisher
- SAGE Publications
- Published
- 2013-03
- Volume
- 77
- Issue
- 2
- Pages
- 78-95
- ISSN
- 0022-2429 (ISSN-L)
- 1547-7185
- OpenAlex
- W1966027517
- Cited by
- 429
- References
- 12
- FWCI
- 36.33
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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