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Inducing Pro-environmental Behavior

  • Srinivasan Sunderasan
Chapter

Abstract

The global commons are jointly owned and their inhabitants are severally obligated to ensure their preservation. The major challenge facing pro-environmental behavior is the inter-temporal spread of the costs incurred and the benefits slated to be derived (or injury likely to be avoided), and that this difference in timing could span several decades or even centuries. Scientists, statesmen, planners, or technocrats could serve as “choice architects” and design plans for others: ultimately, however, it is individuals who make consumption-related choices on ways of living, traveling, or in preferring products or services over others. Notwithstanding political grandstanding, long-drawn negotiations, convoluted documentation, and international discord, the median individual’s willingness to align with a cooperative group and to bear the costs that would hopefully accrue distant benefits, and having a sizable number of such willing individuals representing the median, would determine eventual environmental outcomes.

This chapter draws on the resources of environmental economics, game theory, behavioristic psychology, and oriental philosophy to present an informal social network approach to achieving pro-environmental outcomes. The model begins with a morally committed, altruistic opinion – leader, “the man in the middle,” acting as a social nudge to induce anonymous altruism among a group of marginal consumers. This group then works through conspicuous consumption of pro-environmental goods and moral suasion to induce reciprocal altruism among a larger group of price-conscious and possibly reticent consumers. Finally, it is envisaged that this group would achieve the desired tipping point by inducing conformity and pro-social behavior among sizable numbers of common people, who otherwise fear isolation or derision.

Keywords

Gross Domestic Product Marginal Abatement Cost Gross Domestic Product Growth Reciprocal Altruism Combat Climate Change 
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 India 2013

Authors and Affiliations

  1. 1.Verdurous Solutions Private LimitedMysoreIndia

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