Economic indicators and bioenergy supply in developed economies: QROF-DEMATEL and random forest models

Abstract

Bioenergy is a renewable energy source that saves from fossil fuel dependence. Therefore, it is important to increase the efficiency of bioenergy investments to create an environmentally sustainable energy supply. This paper aims to identify economic indicators significant in forecasting the supply of bioenergy. Considering this goal, an integrated evaluation has been performed for 17 developed economies using the Random Forest method and the Fuzzy Decision-Making Trial and Evaluation Laboratory (QROF-DEMATEL) method. The main contribution of this study is conducting analysis by using both quantitative and qualitative data. Additionally, the coherence of the results made with the QROF-DEMATEL method is also verified by implementing a sensitivity analysis. The results of both approaches are quite similar and provide information about the reliability of the findings. This situation demonstrates that for the development of bioenergy investments, firstly, countries’ macroeconomic conditions should be improved. Consequently, economic growth and unemployment (weighting results - 0.159 and 0.155) should be primarily considered for the bioenergy supply forecast.