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<p>Improper solid waste management (SWM) remains a critical challenge in coastal communities, where high policy awareness often fails to translate into sustainable practices. This study addresses the behavioral–implementation gap by examining households’ willingness to pay (WTP) for improved SWM services in the Lagonoy Gulf, Philippines, using a hybrid framework that integrates contingent valuation, econometric modeling, non-parametric estimation, and machine learning. A total of 692 households were surveyed using stratified random sampling. Despite high awareness of SWM policies (92.2%), improper practices persist, with 60.12% of households engaging in open burning. Results show that 57.51% of households are willing to pay, with a mean WTP of ₱79.60 and a median of ₱50, while the Turnbull estimator provides a conservative mean of ₱54.08. Econometric findings reveal that income (β = 0.0001, p &lt; 0.001) and community perception (β = 0.4566, p = 0.002) are positively associated with WTP, whereas household size (β =  −&#xa0; 0.1545, p = 0.029), occupation constraints, and dissatisfaction with waste services significantly reduce participation. Binary estimates reveal education as a key driver (β = 0.1941, p = 0.003). Machine learning models demonstrate strong predictive performance (R<sup>2</sup> = 0.71; accuracy = 0.80; AUC = 0.85), capturing nonlinear relationships. The study fills a methodological and policy gap by combining inference-based and predictive models to better explain environmental payment behavior in coastal settings. Policy implications emphasize strengthening institutional trust, improving service reliability, and designing equitable, community-based financing mechanisms. This work supports the development of sustainable, participatory SWM systems aligned with coastal resilience and blue economy goals.</p>

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Economic valuation and machine learning analysis of willingness to pay for improved solid waste management in coastal communities

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月14日

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  • Emmanuel A. Onsay,
  • Mary Matthew N. Jamer

摘要

Improper solid waste management (SWM) remains a critical challenge in coastal communities, where high policy awareness often fails to translate into sustainable practices. This study addresses the behavioral–implementation gap by examining households’ willingness to pay (WTP) for improved SWM services in the Lagonoy Gulf, Philippines, using a hybrid framework that integrates contingent valuation, econometric modeling, non-parametric estimation, and machine learning. A total of 692 households were surveyed using stratified random sampling. Despite high awareness of SWM policies (92.2%), improper practices persist, with 60.12% of households engaging in open burning. Results show that 57.51% of households are willing to pay, with a mean WTP of ₱79.60 and a median of ₱50, while the Turnbull estimator provides a conservative mean of ₱54.08. Econometric findings reveal that income (β = 0.0001, p < 0.001) and community perception (β = 0.4566, p = 0.002) are positively associated with WTP, whereas household size (β =  −  0.1545, p = 0.029), occupation constraints, and dissatisfaction with waste services significantly reduce participation. Binary estimates reveal education as a key driver (β = 0.1941, p = 0.003). Machine learning models demonstrate strong predictive performance (R2 = 0.71; accuracy = 0.80; AUC = 0.85), capturing nonlinear relationships. The study fills a methodological and policy gap by combining inference-based and predictive models to better explain environmental payment behavior in coastal settings. Policy implications emphasize strengthening institutional trust, improving service reliability, and designing equitable, community-based financing mechanisms. This work supports the development of sustainable, participatory SWM systems aligned with coastal resilience and blue economy goals.