An integrated approach for modeling sustainability risks in freight transportation systems

Integrating sustainability into freight transportation systems (FTSs) is a complex and challenging task due to the sheer number of inherent sustainability risks. Sustainability risks disrupt the socio-economicenvironmental efficiency of freight operations and act as impediments in the development of sustainable freight transportation systems (SFTSs). The area of sustainability risk management is still unexplored and immature in the operational research domain. This study addresses these research gaps and contributes in a three-fold manner. Firstly, a rigorous approach is used to identify a total of 36 potential sustainability risks uniquely classified into 7 categories for the FTSs. Secondly, the research proposes two prominent perspectives namely, ontological and epistemological perspectives to understand risks and develops a novel framework for managing sustainability risks in FTSs. Thirdly, a novel approach by integrating fuzzy evidential reasoning algorithm (FERA) with expected utility theory is developed to quantitatively model and profile sustainability risk for different risk preferences namely, risk-averse; risk-neutral; and risk-taking scenarios. FERA is a flexible and robust approach, which transforms the experts’ inputs into belief structures and aggregates them using the evidence combination rule proposed in Dempster-Shafer Theory to overcome the problem of imprecise results caused by average scoring in existing models. A sensitivity analysis is conducted to demonstrate the robustness of the proposed model. Unlike conventional perception, our study suggests that most of the high priority sustainability risks are behaviorally and socially induced rather than financially driven. The results provide significant managerial implications including a focus on skills development, and on social and behavioral dimensions while managing risks in FTSs.