Modeling sustainable production indicators with linguistic preferences

Measuring sustainable production indicators (SPIs) is becoming an important environmental activity due to government directives and increasing awareness among the populous to protect the environment and reduce waste. For printed circuit board manufacturers, measuring SPIs that are dedicated to sustainable activities usually require a multi-criteria structure with driving and dependence power for tracking. Hence, the measures of SPIs are always based on subjective perceptions and interactive relations in nature. A hybrid method for composing a hierarchical structure based on linguistic preferences and that concurrently applies perception judgment is lacking. This study proposes a novel approach in which fuzzy set theory and interpretive structural modeling are adopted to address the analytical objective. The proposed criteria are categorized into a hierarchical structure and arranged into visual quadrants on a graph according to their driving and dependence powers. The insights graph and hierarchical structure could assist mangers in strategic planning related to improving their firms’ environmental activities. Managerial implications and concluding remarks are addressed.