An integrated rough-fuzzy WINGS-ISM method with an application in ASSCM.

• We propose a new rough fuzzy Weighted Influence Non-linear Gauge System (WINGS). • We integrate the WINGS with the Interpretative Structural Modeling Method (ISM). • Rough and fuzzy judgments are used to deal with uncertainties in untested ASSCM. • We reveal interrelationship by direction, intensity and strength of dependencies. • We present a case study to evaluate the elements impacting ASSCM. Environmental deterioration, the COVID-19 pandemic and the Russian-Ukrainian conflict had brought chronic and dramatic impacts on agricultural supply chain around the world, resulting in high inflation rates and unavoidable costs. In order to reduce the adverse impacts and achieve sustainability in agricultural supply chain, it's necessary to scientifically explore composite indicators interlinked with agricultural sustainable supply chain management (ASSCM). The current study developed an integrated rough-fuzzy WINGS-ISM method to reveal the hierarchal and causal structure of indicators. It is found that environmental legislation, regulation, licensing, and government subsidies are the main drivers of ASSCM. Specifically, the government can guide the sustainable development of ASSCM by regulating the business environment. The financial support needs to be enlarged to optimize the structure in science and technology of ASSCM. Moreover, corporates and organizations are highly motivated by the increasing awareness of social responsibility and sustainability consciousness to improve the economic performance and achieve the ASSCM goals. A comparative analysis is proposed to illustrate the practicality and reliability of the results obtained from the proposed method, which can be utilized as a reference in ASSCM. [ABSTRACT FROM AUTHOR]