Multivariate Statistical Factor and Cluster Analyses for Selecting Food Waste Optimal Recycling Methods

Abstract

In Taiwan, four alternatives have been considered for final disposal of food wastes; they are pig feed, anaerobic digestion, feedstuff production, and composting. However, an optimal method has not been determined. This research applied multivariate factor analysis and cluster analysis to analyze the information collected using the Likert scale questionnaires so that reliable and effective quantitative results can be obtained for more robust decision making. Composting stands out as the most acceptable method through the analysis of the quantified degrees of preference and the grades of acceptability. Additionally, a quantified strength, weakness, opportunity, and threat (SWOT) analysis was compiled through the original questionnaires. Comparison of the results obtained using the multiple-variable statistical analysis and the SWOT analysis confirms that SWOT results are valuable references for general decision making. However, whether results are consistent or not depends on the conditions of individual cases studied.