Waste crisis and potential implications of forest Fires: Perspective from psychosocial cognition

Context

Agroforestry projects in the Peat Hydrological Unit (PHU) area represent the largest peat forest management and support center for sustainable ecological growth. However, old habits such as littering and burning become complicated tasks for strategic forest management. Components of past behavior, social norms, and risk management interventions should be adapted as the psychosocial cognitive part of a complex mitigation behavior cycle prediction. The integration of psychosocial cognitive strategies into sustainable development not only increases collective awareness and responsibility locally and supports the future management of global environmental health.

Novelty

This study aims to provide a constructive understanding of the prediction of hybrid feedback loops cognitive maps in the behavioral cycle of burning and waste crisis mitigation using SCT, SME, CBSM, and social capital variable.

Methods

This study used survey data on psychosocial cognitive assessments collected from communities involved in agroforestry projects in PHU, West Kalimantan. The psychosocial cognitive components of SCT, SME, CBSM, and social capital were measured using the Planning Environmental Behavior Index (PEBI). Data were analyzed using hybrid feedback loops model combining Bayesian simulation and logistic hierarchy to obtain the statistical efficiency logFC (Fold Change).

Results

Logistic regression analysis of psychosocial cognitive items in the SCT, CBSM, and SME components revealed a significant influence of norms (β = 0.26, t(124) = 2.47, ρ < 0.05) and trust (β = 0.13, t(124) = 1.05, ρ < 0.05). However, the network component (β = 0.09, t(124) = 0.37, ρ > 0.20) did not significantly predict waste crisis and forest fire mitigation behavior. The SCT items showed hierarchical statistical significance: PPC (β = 0.39, t(124) = 3.27, ρ < 0.05), RP (β = 0.19, t(124) = 2.07, ρ < 0.05), and PEC (β = 0.44, t(124) = 2.24, ρ < 0.05). Similarly, SME items significantly contributed to PPC (β = 0.46, t(124) = 3.33, ρ < 0.05), RP (β = 0.24, t(124) = 2.51, ρ < 0.05), and PEC (β = 0.59, t(124) = 3.48, ρ < 0.05). CBSM predictions showed the significance of PEC control for the proportion stage of CR (β = 0.31, t(124) = 2.64, ρ < 0.05) and ME (β = 0.44, t(124) = 2.24, ρ < 0.05). Based on the hybrid feedback loop model, logistic regression of PEC items and social norms significantly predicted the mitigation behavior cycle, especially at the “action” and “outcome expectation” nodes.

Conclusion

The predictive findings suggest that PEC items and social norms influence the reinforcement of hybrid feedback loops at the “action” and “outcome expectancy” nodes in analyzing the cognitive map of the perceived mitigation behavior cycle.