Assessing Renewable Energy Investment in Africa: A Fuzzy TOPSIS Approach for Multi-criteria Decision Making

Ken Baumli

Student thesis: Master thesis


Energy poverty remains prevalent in many African countries, hindering economic development and increasing social inequality. Private investment is increasingly regarded as a necessary ingredient to remedy Africa’s energy challenges, although currently remains insuÿcient to address infrastructure requirements. The thesis seeks to delineate the financial and non-financial drivers of investment decisions, to understand better the barriers to private sector participation in renewable energy infrastructure projects. A fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach reinforces the relevance of Multi-Criteria Decision Making (MCDM) methodologies to uncover determinants of choice. Primary data collected from a sample of African energy sector professionals highlights that perceptions moderate selection outcomes through evaluation criteria. Behavioural finance theory and a risk identification framework, along with the conceptual model introduced by Masini and Menichetti (2013), are introduced to study the implications of investment behaviour. Problems related to investor confidence in policy e˙ectiveness and risk-sharing predominate as barriers to investment. Capacity building and policy instruments for renewable energy trade are proposed to address cognitive biases and political risk issues. Supplementing financial evaluation with MCDM, and risk-adjusted valuations, are identified as tools to address the immediate obstacles related to investment uncertainty. The implications of the thesis are profound, indicating that non-financial drivers are instrumental in addressing Africa’s investment gap.

EducationsMSc in International Business, (Graduate Programme) Final Thesis
Publication date2020
Number of pages169
SupervisorsTooraj Jamasb