Assessing the social dimension in strategic network optimization for a sustainable development: The case of bioethanol production in the EU

Abstract

The complexity of social indicators and their subjective and often qualitative nature render their inclusion into quantitative optimization models for network design and strategic decision-making challenging. The social dimension is thus often implemented only rudimentarily, thwarting a holistic sustainability assessment and neglecting many of the social issues addressed in the sustainable development goals (SDGs). This work presents a structured process for including a comprehensive set of social aspects by selecting applicable quantitative and regionalized social indicators. This approach is applied to the case of second-generation bioethanol production in the EU. Based on inter alia the Guidelines for Social Life Cycle Assessment of Products and Organizations, the Social Hotspots Database, state-of-the-art literature, as well as previous work, we compile 9 social objective functions and 25 functions for social hotspot identification. They are evaluated alongside 1 economic and 21 environmental LCA-based objective functions in a mixed-integer linear programming (MILP) model. Key results show that social optimization either leads to large, labor-intensive or regionally focused, indicator-driven networks. Injuries and fatalities in the feedstock sectors of Central and Eastern European countries is the primary social hotspot. On the level of the overarching SDGs, SDG13 is most congruent with other goals, while SDG7 is hindered by pursuing other goals. This study's approach is novel in strategic network design and the European bioeconomy, and, by operationalizing the social dimension, enables a more holistic life cycle sustainability assessment and the consideration of the SDGs. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges.