Scholarlink

<p>Accurate quantification method is critical for designing effective urban mine valorization strategies. However, traditional estimation methods such as product ownership models and disposal reports overlook behavioral complexities in low-income contexts, where informality and diverse user decisions dominate. This gap limits accurate estimates of accessible e-waste and the real urban mine potential. The study proposes a behaviorally-informed model that integrates a sentiment-based behavioral coefficient into stock estimation, grounded in the Theory of Planned Behavior. Using household data from Ouagadougou, the model corrects reported obsolete device stocks by combining perceived behaviors with attitudinal sentiment, then links accessible quantities to recoverable metal content. The model estimates that only 19–26% of household e-waste stock may be accessible under current behavioral conditions, yet behavioral weighting significantly reshapes estimates and scenario projections, with ambitious shifts increasing urban mine potential by over 60% by 2030. By bridging behavioral drivers and material recovery, the study pioneers a replicable model for estimating the mobilizable urban mine in low-income contexts. Findings offer actionable insights for informal recycling actors, emphasize the critical role of behavior-focused policies, and contribute to the advancement of socially informed urban mining frameworks.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrating a behavioral coefficient for locally adapted estimates of urban mine potential in low-income countries

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月5日

查看全文
  • Mahugnon Samuel Ahossouhe,
  • Djim Doumbe Damba,
  • Kouassi Dongo,
  • Alassane Sanou,
  • Satyanarayana Narra,
  • Qahtan Thabit,
  • Harinaivo Anderson Andrianisa

摘要

Accurate quantification method is critical for designing effective urban mine valorization strategies. However, traditional estimation methods such as product ownership models and disposal reports overlook behavioral complexities in low-income contexts, where informality and diverse user decisions dominate. This gap limits accurate estimates of accessible e-waste and the real urban mine potential. The study proposes a behaviorally-informed model that integrates a sentiment-based behavioral coefficient into stock estimation, grounded in the Theory of Planned Behavior. Using household data from Ouagadougou, the model corrects reported obsolete device stocks by combining perceived behaviors with attitudinal sentiment, then links accessible quantities to recoverable metal content. The model estimates that only 19–26% of household e-waste stock may be accessible under current behavioral conditions, yet behavioral weighting significantly reshapes estimates and scenario projections, with ambitious shifts increasing urban mine potential by over 60% by 2030. By bridging behavioral drivers and material recovery, the study pioneers a replicable model for estimating the mobilizable urban mine in low-income contexts. Findings offer actionable insights for informal recycling actors, emphasize the critical role of behavior-focused policies, and contribute to the advancement of socially informed urban mining frameworks.