Towards a Circular Bioeconomy: Structural Equation Modelling of Business Acceptance, Economic Viability and Emissions Reduction in Hybrid Biogas–Solar Microgrids

Lizarzaburu-Aguinaga D.; Farroñan E.V.R.; Carranza C.F.C.; Nakayo J.L.J.; Yrribari J.F.A. · Chemical Engineering Transactions (2026) · DOI: 10.3303/cet26125084

Resumen

The transition towards a circular bioeconomy requires integrated energy systems capable of simultaneously addressing environmental, economic, and organizational dimensions of sustainability. Decentralized hybrid biogas–solar microgrids offer a pathway to reduce greenhouse gas emissions while fostering rural development, yet their adoption depends on factors beyond techno-economic optimization. This study analyses causal relationships among business acceptance (BA), business economic viability (BEV), circular bioeconomy orientation (CBO) and contribution to emission reduction (CER) in hybrid biogas–solar microgrids. A quantitative, cross-sectional design was adopted, applying Partial Least Squares Structural Equation Modelling (PLS-SEM) to survey data from 70 agribusiness and waste-management companies with technical potential for microgrid adoption, using 5,000 bootstrap subsamples. Results confirmed that CBO significantly predicts BA (β = 0.585, p < 0.001, f2 = 0.520) and that BA is a strong antecedent of BEV (β = 0.763, p < 0.001, f2 = 1.391), with CBO also directly predicting CER (β = 0.662, p < 0.001, f2 = 1.002). However, neither BEV nor BA translated directly into perceived CER, and the indirect path BA → BEV → CER was non-significant, revealing a decoupling between economic and environmental dimensions at the pre-implementation stage. The findings suggest that emission reductions in hybrid microgrids behave as emergent, operation-dependent outcomes rather than as ex-ante organizational perceptions, and that policy interventions should sequentially strengthen circular orientation, technological acceptance, and economic demonstration. The study contributes an empirically validated model that supports planning and decision-making for decentralized energy systems in agro-industrial contexts. Copyright

Instituciones: Universidad Nacional Mayor de San Marcos; Universidad César Vallejo