Understanding Pro-Environmental Behavior: Models and Messages

  • Myria Allen
Chapter
Part of the CSR, Sustainability, Ethics & Governance book series (CSEG)

Abstract

Certainly societal Discourses shape our individual worldviews, and our behaviors are influenced by our organizations’ quest for legitimacy during stakeholder interactions. However, when individuals communicate about sustainability-related initiatives, part of that exchange is influenced by each person’s environmental values, attitudes, and beliefs. What influences an individual’s pro-environmental values and behaviors? How can communication facilitate individual-level behavioral change? This chapter identifies factors influencing an individual’s pro-environmental values and behaviors; discusses the tentative link between values, attitudes, and behaviors; and identifies how communication can be used to influence individual-level behavioral change. Literature is reviewed which identifies and discusses pro-environmental values and beliefs and defines pro-environmental behaviors. Various persuasion and social influence theories are reviewed to help practitioners better understand how to stimulate pro-environmental behaviors. Key models of pro-environmental behavior are identified. Information is drawn from social marketing, health-related models, stages of change models, energy use reduction models, and communication campaign literatures. At the end of each block of theories, ways these theories can guide practice are highlighted. The chapter ends by focusing on concrete message strategies and the importance of interpersonal communication. Interview data is drawn from Sam’s Club; Bayern Brewing; the South Dakota Bureau of Administration; the State Farm Insurance processing facility in Lincoln, NE; the Neil Kelly Company; the City of Fayetteville; the University of Colorado, Boulder; and the University of Colorado, Denver.

Keywords

Behavioral Intention Social Marketing Descriptive Norm Injunctive Norm Sustainability Initiative 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Myria Allen
    • 1
  1. 1.Department of CommunicationUniversity of ArkansasFayettevilleUSA

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