Environmental Management
S. Sunarti; R.S.Y. Zebua; J.H. Tjakraatmadja; A. Ghazali; B. Rahardyan; K. Koeswinarno; S. Suradi; N. Nurhayu; R.H.A. Ansyah
Abstract
BACKGROUND AND OBJECTIVES: Community engagement is crucial to overcome environmental issues, including waste management. Several education-based initiatives have been employed to improve community engagement in waste management programs, but the effects were not satisfied in changing resident behavior ...
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BACKGROUND AND OBJECTIVES: Community engagement is crucial to overcome environmental issues, including waste management. Several education-based initiatives have been employed to improve community engagement in waste management programs, but the effects were not satisfied in changing resident behavior for sustainable engagement. Some studies suggested social learning as the solution to improve community engagement through practice-based and dialogue-based learning activities. Nevertheless, it needed more empirical evidence to show the effect. This study aimed to measure the effect of social learning on improving individual waste management behavior and how social learning influence it.METHODS: Using SmartPLS 3.2.9, this study measured the causal relationship of social learning activities to individual affective and behavioral factors. This study involved 504 residents exposed to social learning activities in Kawasan Bebas Sampah/ Zero Waste Area program in Bandung City, Indonesia as the respondents to gather the data using survey method.FINDINGS: The study found that social learning activities have significantly influenced waste management behavior indirectly through Affective factors. The data showed that Dialogue-based learning has no significant effect on Affective factors for all significance levels (β = -0.0862, P > 0.01). Instead, path model analysis indicated the mediating effect of Practice-based learning for Dialogue-based learning and Affective Factors, with the accuracy model at a moderate level (R2 = 42%; Q2 = 0.2258). Meanwhile, supporting facilities influenced both Practice-based learning (β = 0.3116, P < 0.001) and Affective factors (β = 0.4419, P < 0.001) significantly. Further path model analysis demonstrated that without “Affective Factors” being nurtured, learning activities and Facilities would not be able to improve behavior significantly, as all paths directing to Behavioral Domain (Intention and WMB) had an insignificant effect (P value > 0.05).CONCLUSION: This study offered empirical evidence, showing the mechanism of social learning to improve waste management behavior. The Learning activities should combine Dialogue and Practice-based learning to influence waste management behavior significantly, while Affective factors become the direct effect of Learning Activities. Supporting facilities were required to support the learning by providing routine waste collection systems and recycling facilities beneficial for the residents. In order to improve the learning activity effectiveness, the facilitators need to pay more attention to the learning contents to nurture the expected Affective Factors factors.
