Community-Owned Circular Business Models for Livestock Waste: Participatory Value-Chain Design and Determinants of Adoption Readiness in Rural Indonesia
DOI:
https://doi.org/10.64268/josce.v2i2.114Keywords:
Business Model Canvas, circular economy, community enterprise, livestock waste, organic fertilizer, participatory value chainAbstract
Background: Livestock manure is simultaneously an environmental liability and a locally available nutrient resource, yet technical conversion into organic fertilizer does not automatically create a viable circular enterprise.
Aims: This study examined how participatory value-chain design and a community-owned business model can reduce operational uncertainty and strengthen household readiness to engage in livestock-waste valorization in Arjasa Village, East Java, Indonesia.
Methods: A Year-1 participatory mixed-methods case study combined a structured baseline survey of 60 livestock-keeping households, multi-actor discussions, process walkthroughs, value-chain mapping, and Business Model Canvas co-design. An exploratory logistic model assessed associations between adoption readiness and five designable mechanisms: access to an offtake memorandum of understanding, microfinance, perceived relative advantage, governance trust, and short training, with contextual controls.
Results: Forty-six percent of households met the operational definition of early adoption or firm participation commitment. Offtake access showed the largest association with readiness (OR = 3.40), followed by microfinance (OR = 2.60), perceived relative advantage (OR = 2.20 per 1 SD), governance trust (OR = 1.90 per 1 SD), and short training (OR = 1.80). The model showed useful exploratory discrimination (AUC = 0.81), while participatory mapping identified feedstock variability, inconsistent processing endpoints, weak quality records, and uncertain market absorption as the main value-chain frictions.
Conclusion: The findings support a risk-reduction architecture in which market assurance, light finance, credible governance, clear product value, and compact learning mechanisms are designed together rather than treated as separate interventions. Because the sample is small and cross-sectional, the regression estimates are interpreted as preliminary associations that require confirmation in subsequent implementation cycles.
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