Engineering Applications of Artificial Intelligence 87 (2020) 103338 Contents lists available at ScienceDirect Engineering Applications of Artificial Intelligence journal homepage: www.elsevier.com/locate/engappai A grey-layered ANP based decision support model for analyzing strategies of resilience in electronic supply chains ✩ R. Rajesh Management Division, ABV-Indian Institute of Information Technology & Management, Gwalior 474015, India ARTICLE INFO Keywords: Supply chain resilience Supply chain risk Resilient strategies Grey theory Analytic network process ABSTRACT Augmented globalization and vertical integration have made contemporary supply chains an intricate network subject to a number of vulnerabilities. Preemptive measures are needed for dealing with mutable risks and vulnerabilities to safeguard robust supply chain systems. Supply chain risk management (SCRM) connotes a set of risk management responses essentially instigated to confront supply chain risks. As supply chain risks are intertwined, one resilient strategy for risk mitigation can moderate several supply chain risks. A complex decision making problem involving twelve major supply chain risks and twenty one resilient strategies for risk mitigation have been acknowledged in this research with archetypal focus on electronics manufacturing supply chains. A combination of Multi criteria decision aid (MCDA) and artificial intelligence (AI) is increasingly used in decision making of complex real world problems. A decision support model incorporating an amalgamation of grey theory and layered analytic network process (ANP) has been employed for quantifying various resilient strategies for risk mitigation. The proposed model was also applied in a practical setting taking a case study of an electronics manufacturing company. Sensitivity analysis was also conducted to ensure the robustness of obtained results. The combined methodology proposed in this research could be effectively used by top management, to pigeonhole the resilient supply chain strategies for better managing their supply chains. 1. Introduction Supply chain systems are becoming more lengthy and complex, as a result of increased globalization and vertical integrations. In this scenario, proactive practices need to be adopted for securing supply chain systems by tackling core vulnerabilities. Vulnerabilities along with associated supply chain risks increases with increasing interactive complexities of the supply networks (Christopher and Peck, 2004). Hence, complex decision making situations involving evaluation of multiple criteria using several decision aids is becoming typical in modern supply chains. Multi criteria decision aid (MCDA) and artificial intelligence (AI) have been applied for increasing the success of deci- sion making considering complex real world problems. Supply chain risk management (SCRM) characterizes tools and practices of com- plex real world problems to better manage various supply chain risks (Christopher and Lee, 2004). SCRM extends its principles and practices over three major areas namely, supply chain management, enterprise risk management and crises management. As most of the companies develop plans to protect their supply chains against recurrent low impact risks and usually avoid high impact low likelihood risks, it is essential that SCRM should be integrated with supply chain planning (Chopra and Sodhi, 2012). ✩ No author associated with this paper has disclosed any potential or pertinent conflicts which may be perceived to have impending conflict with this work. For full disclosure statements refer to https://doi.org/10.1016/j.engappai.2019.103338. E-mail addresses: rajesh@iiitm.ac.in, rajeshambzha@gmail.com. The resilience capabilities and the sustainable competitive advan- tage of the firm increases when the level of risk sharing and the top management support increases (Ponomarov and Holcomb, 2009). The level of risk sharing is dependent on continual risk assessment, risk analysis and risk mitigation practices. Natural disasters, war, terrorism or any other external factors could lead to sudden unexpected break downs of supply chain, known as disruptions. Apart from that, security related issues are more frequently atop the minds of end consumers making it necessary for the members in the supply chain to take a new look at vulnerability measures. As observed from a complexity perspective of SCRM, managers are advised to reduce the interactive complexity of the supply chain by reducing the level of buffers at different stages. If the network is having a reasonably high interac- tive complexity, improved buffer levels are recommended to manage potential vulnerabilities (Yang and Yang, 2010). Managers will be able to tailor balanced and effective risk mitiga- tion strategies for their firms, by properly understanding the supply chain risks, its variety and inter connectedness. Also, managers should take into consideration of the frequency of occurrence of similar risks, as a measure of supply chain vulnerability (Manuj and Mentzer, 2008). In general, in order to meet the challenges of a turbulent business envi- ronment and to tackle vulnerabilities, structural flexibility of the supply https://doi.org/10.1016/j.engappai.2019.103338 Received 30 June 2016; Received in revised form 12 March 2018; Accepted 28 October 2019 Available online xxxx 0952-1976/© 2019 Elsevier Ltd. All rights reserved.