Assessing possible energy potential in a food and beverage industry: Application of IDA-ANN-DEA approach

Abstract

In the food and beverage industry, where growing, processing, packaging, distribution, storage, preparation, serving and disposing of food is the order of the day; energy consumption becomes an important input. Various energy models have been developed since the early 1970s, the period when energy caught the attention of policymakers due to the sudden price increase. Among the models are the index decomposition analysis (IDA), artificial neural network (ANN) and data envelopment analysis (DEA). The purpose of this study is to combine the strengths of these models, i.e., IDA, ANN and DEA, to allow biases in one model to offset biases in the other, so as to examine the effectiveness of energy management policies in a particular food and beverage industry. The integrated model applied to the food and beverage revealed that approximately 11% of energy consumed could be saved.