DEVELOPING AN INCENTIVE SCHEME OF USED COOKING OIL BUSINESS MODEL TO SUPPORT THE FEASIBILITY OF SUSTAINABLE AVIATION FUEL

Abstract

The urgency to reduce aviation-related carbon emissions has intensified, driving a shift toward sustainable fuel innovations such as SAF. Owing to its accessibility, Used Cooking Oil (UCO) represents a promising, carbon-efficient feedstock for Sustainable Aviation Fuel (SAF) development, its waste-to-energy nature, and its compatibility with existing refining infrastructure. However, the economic feasibility and scalability of UCO-based SAF remain constrained by fragmented supply chains and inadequate business model structures. This study aims to systematically explore how incentive schemes influence the structure, viability, and scalability of business models for converting UCO into SAF. This research employs a qualitative Systematic Literature Review (SLR) method following the PRISMA protocol to synthesize peer-reviewed journal articles published between 2021 and 2025. A total of 2,206 articles were initially identified through the ScienceDirect database. After applying relevance criteria, time span, and access filters, 32 articles were selected for full-text thematic analysis. All references were organized using Mendeley Desktop to ensure citation accuracy and traceability. Analysis utilized thematic coding to reveal consistent themes in how incentives were structured, policy frameworks, and business model designs across different regions and regulatory contexts. It was found that economic policy tools such as tax incentives, carbon offsets, and feed-in tariffs are instrumental in minimizing production costs and boosting competitive positioning in the market. Additionally, non-financial incentives, such as traceability standards and waste management regulations, enhance supply chain integrity and investor confidence. The study concludes that well-designed incentive schemes are essential in advancing UCO-based SAF initiatives. Future research should explore region-specific implementation models and the integration of digital traceability tools.

DOI: https://doi.org/10.56238/sevened2026.008-068