Alireza Aliahmadi - Department of Management and Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
Hamed Nozari - Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
Javid Ghahremani-Nahr - Faculty Member of Academic Center for Education, Culture and Research (ACECR), Tehran, Iran.
Agnieszka Szmelter-Jarosz - Department of Logistics, Faculty of Economics, University of Gdańsk, Poland.

In recent years, the high complexity of the business environment, dynamism and environmental change, uncertainty and concepts such as globalization and increasing competition of organizations in the national and international arena have caused many changes in the equations governing the supply chain. In this case, supply chain organizations must always be prepared for a variety of challenges and dynamic environmental changes. One of the effective solutions to face these challenges is to create a resilient supply chain. Resilient supply chain is able to overcome uncertainties and disruptions in the business environment. The competitive advantage of this supply chain does not depend only on low costs, high quality, reduced latency and high level of service. Rather, it has the ability of the chain to avoid catastrophes and overcome critical situations, and this is the resilience of the supply chain. AI and IoT technologies and their combination, called AIoT, have played a key role in improving supply chain performance in recent years and can therefore increase supply chain resilience. For this reason, in this study, an attempt was made to better understand the impact of these technologies on equity by examining the dimensions and components of the Artificial Intelligence of Things (AIoT)-based supply chain. Finally, using nonlinear fuzzy decision making method, the most important components of the impact on the resilient smart supply chain are determined. Understanding this assessment can help empower the smart supply chain.

Smart Supply Chain, AIoT-based Supply Chain, Artificial intelligence, Fuzzy prioritization