Abstract
Biofuel supply chains (BSCs) face diverse uncertainties that pose serious challenges. This has led to an expanding body of research focused on studying these challenges. Hence, there is a growing need for a comprehensive review that summarizes the current studies, identifies their limitations, and provides essential advancements to support scholars in the field. To overcome these limitations, this research aims to provide insights into managing uncertainties in BSCs. The review utilizes the Systematic Reviews and Meta-Analyses (PRISMA) method, identifying 205 papers for analysis. This study encompasses three key tasks: first, it analyses the general information of the shortlisted papers. Second, it discusses existing methodologies and their limitations in addressing uncertainties. Lastly, it identifies critical research gaps and potential future directions. One notable gap involves the underutilization of machine learning techniques, which show potential for risk identification, resilient planning, demand prediction, and parameter estimations in BSCs but have received limited attention. Another area for investigation is the potential of agent-based simulation, which can contribute to analysing resilient policies, evaluating resilience, predicting parameters, and assessing the impact of emerging technologies on BSC resilience in the twenty-first century. Additionally, the study identifies the omission of various realistic assumptions, such as backward flow, lateral transshipments, and ripple effects in BSC. This study highlights the complexity of managing uncertainties in BSCs and emphasizes the need for further research and attention. It contributes to policymakers' understanding of uncertain sources and suitable approaches while inspiring researchers to address limitations and generate breakthrough ideas in managing BSC uncertainties.