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Visual Prompts or Volunteer Models: An Experiment in Recycling

Author

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  • Zi Yin Lin

    (Sustainable Behaviour Research Group, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China)

  • Xiao Wang

    (Sustainable Behaviour Research Group, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China)

  • Chang Jun Li

    (Sustainable Behaviour Research Group, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China)

  • Micheil P. R. Gordon

    (Sustainable Behaviour Research Group, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
    Values and Sustainability Research Group, University of Brighton, Watts Building, Lewes Road, Brighton BN2 4GJ, UK)

  • Marie K. Harder

    (Sustainable Behaviour Research Group, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
    Values and Sustainability Research Group, University of Brighton, Watts Building, Lewes Road, Brighton BN2 4GJ, UK)

Abstract

Successful long-term programs for urban residential food waste sorting are very rare, despite the established urgent need for them in cities for waste reduction, pollution reduction and circular resource economy reasons. This study meets recent calls to bridge policy makers and academics, and calls for more thorough analysis of operational work in terms of behavioral determinants, to move the fields on. It takes a key operational element of a recently reported successful food waste sorting program—manning of the new bins by volunteers—and considers the behavioral determinants involved in order to design a more scalable and cheaper alternative—the use of brightly colored covers with flower designs on three sides of the bin. The two interventions were tested in a medium-scale, real-life experimental set-up that showed that they had statistically similar results: high effective capture rates of 32%–34%, with low contamination rates. The success, low cost and simple implementation of the latter suggests it should be considered for large-scale use. Candidate behavioral determinants are prompts, emotion and knowledge for the yellow bin intervention, and for the volunteer intervention they are additionally social influence, modeling, role clarification, and moderators of messenger type and interpersonal or tailored messaging.

Suggested Citation

  • Zi Yin Lin & Xiao Wang & Chang Jun Li & Micheil P. R. Gordon & Marie K. Harder, 2016. "Visual Prompts or Volunteer Models: An Experiment in Recycling," Sustainability, MDPI, vol. 8(5), pages 1-16, May.
  • Handle: RePEc:gam:jsusta:v:8:y:2016:i:5:p:458-:d:69665
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    References listed on IDEAS

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    1. Dai, Y.C. & Gordon, M.P.R. & Ye, J.Y. & Xu, D.Y. & Lin, Z.Y. & Robinson, N.K.L. & Woodard, R. & Harder, M.K., 2015. "Why doorstepping can increase household waste recycling," Resources, Conservation & Recycling, Elsevier, vol. 102(C), pages 9-19.
    2. Delmas, Magali A. & Fischlein, Miriam & Asensio, Omar I., 2013. "Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012," Energy Policy, Elsevier, vol. 61(C), pages 729-739.
    3. Secondi, Luca & Principato, Ludovica & Laureti, Tiziana, 2015. "Household food waste behaviour in EU-27 countries: A multilevel analysis," Food Policy, Elsevier, vol. 56(C), pages 25-40.
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    Cited by:

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    2. Yihan Zhao & Rong Chen & Mitsuyasu Yabe & Buxin Han & Pingping Liu, 2021. "I Am Better Than Others: Waste Management Policies and Self-Enhancement Bias," Sustainability, MDPI, vol. 13(23), pages 1-19, November.
    3. Kiriaki M. Keramitsoglou & Konstantinos P. Tsagarakis, 2018. "Public Participation in Designing the Recycling Bins to Encourage Recycling," Sustainability, MDPI, vol. 10(4), pages 1-17, April.
    4. Congiu, Luca & Botta, Enrico & Zoli, Mariangela, 2025. "Biases and nudges in the circular economy: A review," Ecological Economics, Elsevier, vol. 233(C).
    5. Ben Ma & Yixuan Jiang, 2022. "Domestic Waste Classification Behavior and Its Deviation from Willingness: Evidence from a Random Household Survey in Beijing," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    6. Lucas, Benjamin & Francu, R. Elena & Goulding, James & Harvey, John & Nica-Avram, Georgiana & Perrat, Bertrand, 2021. "A Note on Data-driven Actor-differentiation and SDGs 2 and 12: Insights from a Food-sharing App," Research Policy, Elsevier, vol. 50(6).
    7. Changjun Li & Firooz Firoozmand & Marie K. Harder, 2021. "The Impacts of Shanghai’s July 2019 Municipal Domestic Waste Management Regulations on Energy Production," Energies, MDPI, vol. 14(22), pages 1-13, November.

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