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Cited by 220

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

New Ways to Promote Proenvironmental Behavior: The Application of Persuasion Theory to the Development Of Effective Proenvironmental Public Service Announcements

Bator, Renee J., Cialdini, Robert B.·2000·Journal of Social Issues

Abstract

The goal of this article is to provide specific guidelines to help create effective proenvironmental public service announcements (PSAs). Campaigndesigners are encouraged to initially identify and investigate the optimal target audience and then draft and test reactions by samples of that audience using pilot messages. Designers are also advised to consider research on attitude persistence, memory, and social norms and apply this research to the message content and presentation style. The article concludes with an application of research from social psychology to a series of overallguidelines for effective PSAs. If environmental campaign developers follow these specifications, the chance of PSA success should be enhanced.

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Crossref · 10.1111/0022-4537.00182

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Metadata

Authors
Bator, R. J., & Cialdini, R. B.
Venue
Journal of Social Issues
Publisher
Wiley
Published
2000-01
Volume
56
Issue
3
Pages
527-541
ISSN
  • 0022-4537 (ISSN-L)
  • 1540-4560
OpenAlex
W2052111859
Cited by
220
References
2
FWCI
8.84
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: New Ways to Promote Proenvironmental Behavior: The Application of Persuasion Theory to the Development Of Effective Proenvironmental Public Service Announcements. https://app.cochat.ai/papers/10.1111/0022-4537.00182
The paper
Bator, R. J., & Cialdini, R. B. (2000). New Ways to Promote Proenvironmental Behavior: The Application of Persuasion Theory to the Development Of Effective Proenvironmental Public Service Announcements. Journal of Social Issues. https://doi.org/10.1111/0022-4537.00182

Data sources

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.