This article presents an assessment of energy performance in South Africa from 1965 to 2014, using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In this research, TOPSIS is initially applied in a two-stage approach to evaluate energy performance in South Africa, using the most frequently adopted indicators in the literature. In the second stage, neural networks are combined with the TOPSIS results as part of an effort to produce an energy performance model with strong predictive capabilities.

The findings reveal different impacts of contextual variables - such as China’s rise in foreign trade, the apartheid regime, and oil shocks - on South Africa’s energy performance.

Researcher: Peter Wanke
Brazilian School of Public and Business Administration (FGV EBAPE)

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