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<p>Source separation is essential for effective waste management, yet research on its efficiency remains limited. This study explores the effects of visual prompt design and bin combinations on waste separation behavior through a two-cycle experimental framework aimed at systematic improvement. In Cycle 1, a survey identified that environmental gain framing combined with numerical data was the most preferred design among all designed visual prompts. Implementation of this design significantly improved recyclable waste separation, with the effective capture rate (effCR) reaching 63.36%. In Cycle 2, while users preferred having more bin categories, the effCR for recyclables peaked at 79.76% in a 3-bin setup and declined to 40.74% in a 5-bin setup. This trend highlights how cognitive overload and choice paralysis negatively impact sorting accuracy as system complexity increases. Additionally, bin transparency proved critical, as the effCR for PET bottles dropped significantly from 85.65% to 35.05% when using untransparent bins. The findings indicate that while numerical environmental prompts drive initial engagement, bin transparency is essential for maintaining material-specific accuracy. However, the success of these interventions depends on keeping bin categories manageable to prevent cognitive overload. Ultimately, this integrated approach provides practical guidance for optimizing separation systems and advancing sustainable waste management practices.</p>

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Systematic improvement of source separation designs: the effects of visual prompts and trash bin combinations in enhancing waste separation behavior

  • 期刊论文

  • 发表日期：

    2026年6月18日

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  • Cheema Soralump,
  • Nine Yawai Phyo Ei,
  • Methawee Nukunudompanich,
  • Supawan Nakaroengrit,
  • Jarudej Asingsamanunt,
  • Nattapon Leeabai

摘要

Source separation is essential for effective waste management, yet research on its efficiency remains limited. This study explores the effects of visual prompt design and bin combinations on waste separation behavior through a two-cycle experimental framework aimed at systematic improvement. In Cycle 1, a survey identified that environmental gain framing combined with numerical data was the most preferred design among all designed visual prompts. Implementation of this design significantly improved recyclable waste separation, with the effective capture rate (effCR) reaching 63.36%. In Cycle 2, while users preferred having more bin categories, the effCR for recyclables peaked at 79.76% in a 3-bin setup and declined to 40.74% in a 5-bin setup. This trend highlights how cognitive overload and choice paralysis negatively impact sorting accuracy as system complexity increases. Additionally, bin transparency proved critical, as the effCR for PET bottles dropped significantly from 85.65% to 35.05% when using untransparent bins. The findings indicate that while numerical environmental prompts drive initial engagement, bin transparency is essential for maintaining material-specific accuracy. However, the success of these interventions depends on keeping bin categories manageable to prevent cognitive overload. Ultimately, this integrated approach provides practical guidance for optimizing separation systems and advancing sustainable waste management practices.