A systematic review of the application of multi-criteria decision-making in evaluating Nationally Determined Contribution projects


Year of Publication: 2022

Authors: F.H. Abanda a, E.L. Chia, K.E. Enongene, M.B. Manjia, K. Fobissie, U.J.M.N. Pettang,
C. Pettang


Analyses in the past decade and more recently, catastrophic events, including extreme temperatures, un predictable weather patterns, floods, and wildfires caused by climate change, have become too common
worldwide. There is overwhelming evidence that country commitments expressed in National Determined
Contributions (NDCs) can contribute to stabilising or reversing the course of impacts of climate change. With the multiplicity of NDC measures, compounded by their complexities and limited resources, multi-criteria decision-making tools can be used in making informed decisions about their development. Furthermore, while many countries are blessed with an abundance of sustainable resources and technologies to feed into NDCs, a major challenge is prioritising them as part of the national and global climate change mitigation and adaptation agenda. Many multi-criteria decision-making (MCDM) methods and tools have been developed over the years.
However, their implementation in practice for prioritising NDC measures is still not well-known despite their high acceptance in academic literature. This study adopts a systematic review of the peer-reviewed literature from the Web of Science and grey literature from the recently launched Technology Needs Assessment database to fully understand the MCDM tools used in evaluating NDC projects from academic versus practice perspectives. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method adopted, culminated in the identification of 464 peer-reviewed journal articles and 50 TNA reports used in the analysis. The results indicate amongst the many MCDM techniques in peer reviewed literature, Analytic Hierarchy Process (AHP) is the most widely used in research, while simplified MCDM methods are the most used in practice.