Leveraging ICT to Enhance Bioenergy Production from Agricultural Waste: A Systematic Review
DOI:
https://doi.org/10.15575/gdcs.v61i1.3269Keywords:
Agricultural Waste, Bioenergy, ICT (Information and Communication Technology), Supply Chain ManagementAbstract
The transition to a circular economy necessitates the valorisation of abundant resources like agricultural waste into bioenergy. However, the development of this sector is frequently hampered by inefficient, fragmented, and economically unviable supply chains. This study aims to systematically review how Information and Communication Technology (ICT) is leveraged to enhance the efficiency, profitability, and scalability of bioenergy production from agricultural waste. Employing a rigorous Systematic Literature Review (SLR) methodology based on the PRISMA guidelines, we synthesized evidence from the major international databases, ScienceDirect and Emerald Insight, focusing on publications from the last five years (2021–2025). The synthesis of results reveals that key ICT applications, such as GIS for route optimisation, IoT sensors for real-time feedstock monitoring, and mobile platforms for coordinating logistics between farmers and biorefineries are critical for overcoming supply chain barriers. These technologies demonstrably reduce logistical costs, improve feedstock quality control, and create transparent, viable business models for farmers. A key finding highlights that ICT creates a powerful synergy where economic efficiency and environmental sustainability are mutually reinforcing. Key challenges identified include the high initial investment for technology adoption and the digital literacy gap in rural communities. In conclusion, strategically leveraging ICT is fundamental to transforming the agricultural waste-to-energy ecosystem from a nascent concept into a robust and sustainable industry. This review’s primary contribution is a comprehensive conceptual framework of ICT interventions across the supply chain stages, and the identification of critical socio-institutional research gaps regarding farmer adoption models and supportive policy measures.
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