Abstract
Due to the shortcoming of data envelopment analysis (DEA) not presenting any spatial meaning in regard to decision-making units (DMUs) and their peers, this research uses spatial agglomeration analysis to fill in this gap. It also establishes a closed-loop circular economy DEA model that replaces a conventional linear DEA approach to investigate whether low energy efficiency DMUs are adjacent to high energy efficiency peers by examining a spatial scatter diagram, because geographical analysis and spatial learning recommendations can help upgrade the energy efficiency of a low energy efficiency country. The observation data cover 27 European Union (EU) countries and the United Kingdom (UK) and span the period 2001 to 2014. The empirical results show that: (i) no matter whether the EU country is bordered by the sea, or is an island country, or is a landlocked country, this does not prevent the country from achieving energy efficiency; (ii) there are four energy efficiency centers in the EU, but they do not distinctly agglomerate; and (iii) there is a phenomenon of radical degradation in energy efficiency from high energy efficiency centers to low energy efficiency countries.
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