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Identifying interactions between determinants of intention for civic engagement against transportation noise exposure – a theory-driven classification tree analysis with cross-sectional data from the KORA study in Germany

Author

Listed:
  • Natalie Riedel
  • Emily Mena
  • Heike Köckler
  • Birgit Reineke
  • Annette Peters
  • Lars Schwettmann
  • Kathrin Wolf
  • Gabriele Bolte
  • Ute Kraus

Abstract

The European Environmental Noise Directive highlights public participation in the development and review of noise action plans. Considering unequal participation opportunities, determinants of public civic engagement are crucial. We conceptualised these determinants to arise from four components: (1) noise exposure, (2) environmental resources, (3) engagement-specific cognitions, and (4) general cognitions and emotions. We aimed to classify intention for civic engagement in a population-based sample from the German KORA study in the Augsburg region by using Conditional Inference Trees (CIT) with variables attributed to the four components (N = 3,743, 43–92 years). The “engagement-specific cognitions”-CIT showed the highest prevalence of civic engagement intention resulting from interactions between subjective norm (expecting positive feedback from significant others), self-efficacy (having confidence to engage), and knowledge of noise abatement planning (70.6% as compared to the sample average (11.2%)). To promote equitable decision-making, participation might benefit from focusing on residents’ cognitive-behavioural processes.

Suggested Citation

  • Natalie Riedel & Emily Mena & Heike Köckler & Birgit Reineke & Annette Peters & Lars Schwettmann & Kathrin Wolf & Gabriele Bolte & Ute Kraus, 2024. "Identifying interactions between determinants of intention for civic engagement against transportation noise exposure – a theory-driven classification tree analysis with cross-sectional data from the ," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 67(13), pages 3276-3309, November.
  • Handle: RePEc:taf:jenpmg:v:67:y:2024:i:13:p:3276-3309
    DOI: 10.1080/09640568.2023.2219829
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