The transition to a circular bioeconomy in developing economies is frequently hindered by the operational failure of biogas facilities due to feedstock supply discontinuity. Whilst biochemical potential is traditionally the primary selection criterion, this study postulates that logistic reliability serves as the governing constraint for sustainable implementation. To validate this paradigm shift, a spatially explicit decision-making framework integrating Shannon Entropy and TOPSIS was developed and applied to a representative tropical agro-industrial region. By evaluating conflicting criteria covering logistic availability, technical efficiency, and biochemical stability, the model identified Annual Residue Production as the dominant weighting factor. Results established Cattle Manure as the universal baseload substrate essential for mitigating seasonality risks, outweighing higher-yielding but intermittent agricultural residues. Spatial analysis further revealed distinct bioenergy clusters dictating tailored technological strategies: a high-potential Rice-Livestock cluster suitable for centralised industrial plants overseeing recalcitrant biomass, and a Cassava-Livestock cluster favourable for decentralised, low-tech digestion. This data-driven approach demonstrates that successful substrate selection must transcend theoretical yield maximisation to prioritise supply chain reliability, providing a robust roadmap for de-risking bioenergy investments in tropical regions.

The transition towards a circular bioeconomy in developing regions is frequently hindered by operational failures caused by feedstock discontinuity. Whilst biochemical potential is traditionally the primary selection criterion, this study postulates that logistic reliability serves as the governing constraint. To validate this strategic reorientation, a decision-making framework was developed and applied to a representative tropical agro-industrial region. A sensitivity analysis comparing objective, subjective and neutral weighting scenarios identified annual residue production as the dominant factor. Results established cattle manure as the universal baseload substrate essential for mitigating seasonality, outweighing higher-yielding but intermittent agricultural residues. Spatial analysis revealed distinct territorial vocations, identifying a high-availability rice–livestock cluster in the south suitable for centralised industrial plants and dispersed cassava–livestock nodes in the centre favourable for decentralised digestion. Furthermore, the assessment of energy autonomy demonstrated that the prioritised co-digestion scenarios could cover local residential electricity demand between 1.5 times and 81 times. Crucially, residues favoured by expert judgement proved logistically unfeasible despite superior theoretical yields. This data-driven approach demonstrates that successful substrate selection must transcend theoretical yield maximisation to prioritise supply chain reliability, providing a robust roadmap for de-risking bioenergy investments and ensuring regional energy autonomy.