Abstract
This paper presents an assessment of energy performance in South Africa from 1965 to 2014 using the technique for order of preference by similarity to ideal solution (TOPSIS). In this research, TOPSIS is used first in a two-stage approach to assess how energy in South Africa has performed using the most frequent indicators adopted by the literature. Afterwards, in the second stage, neural networks are combined with TOPSIS results as part of an attempt to produce a model for energy performance with good predictive ability. The results reveal different impacts of contextual variables such as the rise of China in foreign trade, the Apartheid Regime, and oil shocks on energy performance in South Africa.
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