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The influence of linear and cyclical temporal representations on risk perception of nuclear waste: an experimental study

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  • Corinne Moser
  • Michael Stauffacher
  • Pius Krütli
  • Roland W. Scholz

Abstract

Time is an important aspect of the issue of nuclear waste, both from a technical and from a perceptional perspective. Previous studies have investigated the relationship between time and risk perception of nuclear waste, applying the discounting paradigm and therefore limiting time to one very narrow aspect: its duration. However, time is a multifaceted concept and encompasses more than a linear property. The aim of our study is to test the influence of a different aspect of time, namely temporal representations (linear or cyclical) on risk perception of nuclear waste. In an experimental study we demonstrate that both linear and cyclical representations have a reducing effect on risk perception compared to the control condition, where no specific time representation was activated. Examining group differences, we also demonstrate that temporal representations have a differing influence depending on whether participants have a stable belief about nuclear waste or whether they belong to an ambivalent group that does not yet hold a stable belief. Furthermore, we replicate the well-documented gender gap in risk perception. Our results bear potentially interesting implications for risk communication by demonstrating a causal relationship between the graphic representation of time and risk perception of nuclear waste.

Suggested Citation

  • Corinne Moser & Michael Stauffacher & Pius Krütli & Roland W. Scholz, 2012. "The influence of linear and cyclical temporal representations on risk perception of nuclear waste: an experimental study," Journal of Risk Research, Taylor & Francis Journals, vol. 15(5), pages 459-476, May.
  • Handle: RePEc:taf:jriskr:v:15:y:2012:i:5:p:459-476
    DOI: 10.1080/13669877.2011.636836
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    Cited by:

    1. Qihui Xie & Yanan Xue, 2022. "The Prediction of Public Risk Perception by Internal Characteristics and External Environment: Machine Learning on Big Data," IJERPH, MDPI, vol. 19(15), pages 1-20, August.
    2. Roland W. Scholz & Gerald Steiner, 2022. "The role of transdisciplinarity for mineral economics and mineral resource management: coping with fallacies related to phosphorus in science and practice," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 35(3), pages 745-763, December.

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