Prioritizing solutions to mitigate the risks due to adoption of intermodal railroad freight transportation for achieving sustainable development goals

Multiple cleaner strategies are being devised by governments worldwide to incorporate approaches aligning with sustainable development goals (SDGs), placing particular emphasis on the modal shift from unimodal road to intermodal railroad (IRR) freight transportation. This shift is gaining traction due to its documented positive impact on environmental, economic, and social sustainability. However, adopting IRR freight transportation in emerging economies faces hurdles, primarily attributable to inherent modal shift risks (MSRs). Addressing these MSRs requires the implementation of modal shift solutions (MSSs). This study aims to prioritize the MSSs to mitigate the impact of MSRs in IRR adoption, focusing on achieving SDGs with a case study conducted in the Indian logistics sector. The study is structured into four phases. The first phase identifies 37 sub-MSRs, categorized into seven main MSRs, accompanied by the 39 MSSs for IRR freight transportation adoption. The second phase employs the spherical fuzzy Bayesian best-worst method (SF-BBWM) to assess the relative weights of main and sub-MSRs. The third phase uses the spherical fuzzy C-means clustering (SF-CMC) algorithm to identify crucial MSSs. Finally, the fourth phase utilizes the spherical fuzzy combinative distance-based assessment (SF-CODAS) to prioritize these crucial MSSs. From the identified MSSs, pivotal solutions include developing an integrated physical IRR network across the freight transport chain and fostering relationships between stakeholders through long-term contracts and strategic partnerships. The available results are discussed to facilitate logistics stakeholders’ understanding of the implementation of MSSs aligning with SDGs to mitigate the impact of MSRs. [Display omitted] •Solutions to mitigate risks relevant to intermodal railroad are prioritized.•The proposed novel research framework is applied to the Indian logistics sector.•The framework integrates SF-BBWM, SF-CMC and SF-CODAS.•Sensitivity analysis is performed to check the consistency.