The research, published in Clean Technologies and Environmental Policy, responds to a problem that has frustrated policymakers across the developing world. Biofuel supply chains in emerging economies are constrained by fragmented governance, technological gaps, and competing sustainability priorities, and interventions aimed at one part of the chain often fail because deeper, upstream factors remain untouched. The team, led by Ilyas Masudin together with Rangga Primadasa and Dian Palupi Restuputri, set out to bring analytical order to this complexity by combining three established modeling techniques into a single, evidence-based pipeline for decision-makers.

The first technique, Interpretive Structural Modeling, or ISM, is a method for converting expert judgment about how factors influence each other into a hierarchical map. The researchers assembled a six-member multidisciplinary panel of domain experts who worked through structured questionnaires and Delphi-style consultations, assessing whether each of the seventeen decarbonization factors shaped, or was shaped by, every other factor. From these pairwise judgments, the team constructed a reachability matrix and distilled it into a layered structural model showing which factors sit at the base of the system, exerting influence from below, and which sit at the top, shaped by everything beneath them.

Complementing the structural model, the team applied MICMAC analysis, whose French name translates as cross-impact matrix multiplication applied to classification. This technique computes two scores for every factor: driving power, which measures how strongly a factor influences the rest of the system, and dependence power, which measures how strongly the factor is itself influenced. Plotting these scores sorts the seventeen factors into four families. Autonomous factors are relatively isolated; dependent factors are passive consequences of the system; linkage factors are both influential and unstable, amplifying whatever happens around them; and independent factors are the true engines of change, shaping the system while remaining largely beyond its control.

The structural analysis produced an unambiguous verdict about where the system’s leverage lies. Regulatory and policy support, designated CF7 in the study, and carbon pricing, designated CF8, each exhibited the maximum possible driving power of 17, meaning they influence every other factor in the framework while depending on none. In structural terms, these governance instruments are the roots of the entire decarbonization effort: strengthen them, and the effects cascade upward through technology adoption, financing, feedstock logistics, and stakeholder engagement. This finding aligns with a substantial body of literature showing that biofuel industries flourish or wither largely according to the policy environment that surrounds them.

Yet the study’s most consequential result emerged from its third component, Fuzzy VIKOR, a multi-criteria optimization technique that ranks alternatives by their closeness to an ideal compromise solution while explicitly handling the uncertainty inherent in human expert judgment. By encoding expert assessments as fuzzy numbers rather than crisp values, the method acknowledges that real-world evaluations are rarely precise. When the seventeen factors were ranked through this compromise-based lens, the ordering diverged sharply from the structural hierarchy. Technological maturity, CF13, emerged as the top-ranked priority with a VIKOR index Q of 0.000, the best possible compromise score, followed jointly by production process energy efficiency, CF4, and regulatory and policy support, CF7, each at Q equal to 0.274.

This divergence between the two lenses is the study’s central originality claim, and the authors argue it is a perspective absent from prior biofuel supply chain research. The structural analysis says that policy and carbon pricing are the systemic drivers whose improvement unlocks everything else. The compromise ranking says that technological maturity is the urgent binding constraint, the factor whose current inadequacy most severely holds back overall decarbonization performance relative to an ideal state. Both statements are true at once, and neither alone is sufficient. A government that pours resources into carbon pricing while the underlying conversion technologies remain immature may find its policies have nothing to grip; conversely, perfecting technologies without driving policy change leaves the system’s root causes untouched.

For emerging economies, the practical implications are considerable. The framework offers what the authors describe as a transparent, actionable tool to sequence interventions, optimize resource allocation under uncertainty, and foster stakeholder consensus on decarbonization roadmaps. Because the ISM layer reveals interdependencies, planners can identify which investments will propagate benefits through the chain; because the MICMAC layer classifies factors by driving and dependence power, planners can distinguish levers from symptoms; and because the Fuzzy VIKOR layer produces a compromise ranking robust to judgment uncertainty, planners can defend their sequencing choices to ministries, investors, and communities. The synthesis also demonstrates that effective decarbonization must concurrently address technological, governance, and socio-economic linkages to align emission reductions with broader circular economy and sustainability goals.

The study arrives amid intensifying global scrutiny of biofuels’ climate credentials. Life cycle assessments have shown that the carbon arithmetic of liquid biofuels depends heavily on feedstock choices, land use change, and production energy, while food-feed-fuel competition remains a persistent concern in biomass-constrained regions. In this context, a framework that helps emerging economies prioritize the factors that genuinely determine supply chain emissions, rather than spreading scarce resources across every plausible intervention, addresses a real and growing need. The authors report that the expert panel’s judgments were anonymized and obtained with verbal informed consent, and that no funding was received for the work.

The researchers acknowledge the inherent limits of expert-based modeling, and the framework is designed to be rerun as conditions evolve: as technologies mature, as carbon markets deepen, and as governance capacity strengthens, the interdependency structure and the compromise rankings can be recomputed to reflect the new reality. Data from the study will be made available on request. For now, the message for decision-makers in biofuel-producing developing nations is twofold: respect the structural roots of the system in policy and carbon pricing, but recognize that the most urgent bottleneck today is the maturity of the technologies themselves, and plan accordingly.

Subject of Research: A hybrid multi-criteria decision-making framework for prioritizing decarbonization factors in biofuel supply chains in emerging economies

Article Title: A hybrid ISM-MICMAC-Fuzzy VIKOR framework for decarbonizing biofuel supply chains in emerging economies

Article References: Masudin, I., Primadasa, R., & Restuputri, D. P. (2026). A hybrid ISM-MICMAC-Fuzzy VIKOR framework for decarbonizing biofuel supply chains in emerging economies. Clean Technologies and Environmental Policy, 28(10), Article 250. https://doi.org/10.1007/s10098-026-03601-w

Image Credits: AI Generated

DOI: 10.1007/s10098-026-03601-w

Keywords: biofuel supply chain, decarbonization, ISM, MICMAC, Fuzzy VIKOR, multi-criteria decision-making, emerging economies, technological maturity, carbon pricing, policy support, circular economy, sustainable energy