The need for integrated methodological framework for sustainability assessment has been widely discussed and is urgent due to increasingly complex environmental system problems. These problems have impacts on ecosystems and human well-being which represent a threat to economic performance of countries and corporations. Integrated assessment crosses issues; spans spatial and temporal scales; looks forward and backward; and incorporates multi-stakeholder inputs. This study aims to develop an integrated methodology by capitalizing the complementary strengths of different methods used by industrial ecologists and biophysical economists. The computational methodology proposed here is systems perspective, integrative, and holistic approach for sustainability assessment which attempts to link basic science and technology to policy formulation. The framework adopts life cycle thinking methods—LCA, LCC, and SLCA; stakeholders analysis supported by multi-criteria decision analysis (MCDA); and dynamic system modelling. Following Pareto principle, the critical sustainability criteria, indicators and metrics (i.e., hotspots) can be identified and further modelled using system dynamics or agent based modelling and improved by data envelopment analysis (DEA) and sustainability network theory (SNT). The framework is being applied to development of biofuel supply chain networks. The framework can provide new ways of integrating knowledge across the divides between social and natural sciences as well as between critical and problem-solving research.

Tracking the environmental impacts of production, use, and disposal of products (e.g., goods, and services) have been an important issue in the global economy. Although Life Cycle Assessment (LCA) is a widely applied method to track these environmental impacts and support policies, it has certain limitations and an isolated way of evaluating the environmental impacts with no consideration of social and economic impacts and mechanisms. To overcome the limits of current LCA, three mechanisms have been proposed in the literature: (1) broadening the indicators by including social and economic indicators in addition to the environmental impacts; (2) broadening the scope of analysis from product-level assessment to national and global levels; (3) deepening the assessment by inclusion of more mechanisms to account for interrelations among the system elements, uncertainty analysis, stakeholder involvement, etc. With these developments, LCA has been evolving into a new framework called Life Cycle Sustainability Assessment (LCSA). Practical application of LCSA requires integration of various methods, tools, and disciplines. In this study, a comprehensive literature review is conducted to investigate recent developments, current challenges, and future perspectives in the LCSA literature. According to the review, a high number (40%) of LCSA studies are from the environmental science discipline, while contributions from other disciplines such as economics (3%) and social sciences (9%) are very low. On broadening the scope of analysis, 58% of the studies are product-level works, while 37% quantified the impacts at national level and achieved an economy-wide analysis, and only 5% of the studies were able to quantify the global impacts of products using LCSA framework. Furthermore, current applications of LCSA have not considered the rebound effects, feedback mechanisms, and interrelations of the system of interest sufficiently. To address these challenges, we present a complete discussion about the overarching role of systems thinking to bring tools, methods and disciplines together, and provide practical examples from the earlier studies that have employed various system-based methods. We discuss the importance of integrated system-based methods for advancement of LCSA framework in the following directions: (1) regional and global level LCSA models using multi-region input-output analysis that is capable of quantitatively capturing macro-level social, environmental, and economic impacts; (2) dealing with uncertainties in LCSA during multi-criteria decision-making process and expert judgments in weighting of LCSA indicators; and (3) integration of system dynamics modeling to reveal complex interconnections, dependencies, and causal relationships between sustainability indicators.