قابلیت های تکنولوژیکی و انعطاف پذیری زنجیره تامین شرکت ها: تجزیه و تحلیل رابطه ای با استفاده از مدل سازی کامل  تعریف شده (TISM)  Technological capabilities and supply chain resilience of firms: A relational analysis using Total Interpretive  Structural Modeling (TISM)

1. Introduction In this competitive world of globalization and vertical integration, supply chains (SC) needs to be smarter with efficient and responsive products. Along with that, the associated risks with supply networks have been exacerbated. Supply chain risk management represents proactive practices to manage risks and to effectively confront them (Colicchia and Strozzi, 2012; Manuj et al., 2014; Markmann et al., 2013; Sodhi et al., 2012). Supply chain resilience, the property by which supply chains are able to handle impending vulnerabilities and potential disruptions is becoming a success factor for all leading firms (Brandon-Jones et al., 2014; Hohenstein et al., 2015; Wieland and Marcus Wallenburg, 2013; Rajesh and Ravi, 2015; Rajesh, 2016). In this milieu, a major question arises whether the companies are technologically capable of bringing supply chain resilience. Before investing much on supply chain risk management practices, companies need to identity their technological capabilities and its influences on supply chain resilience. Companies that are too immature in their capabilities cannot implement several risk management practices altogether. Apart from that, many of the technological capabilities are interrelated and have the competences to influence the other (Huo, 2012; Lin, 2014; Meyr et al., 2015; Williams et al., 2013). A research in this direction could possibly make companies aware of their technological capabilities and the most influential capabilities for which managers can give primary attention. A total interpretive structural modeling is used in this research to identity, interpret and acknowledge the major technological capabilities of firms that influence the resilience capabilities of their supply chains. Since the model is developed on interpretive modeling logic, the reachability matrices are constructed on relational basis and are interpreted logically. Each relation represented in the final reachability matrix designates whether the causal/ influential relations are strong enough to justify the model. A case evaluation of the same was also carried out in an electronics manufacturing industry to identity the influence relations and the level of their technological capabilities. A relational digraph was also plotted to represent the prominent causal relations. The relational digraph is prepared on basis of the final reachability matrix and interpretive logic of the relations represented by it. Only conspicuous relations of either direct or transitive are represented in the digraph. The transitive relation logic is one of the equivalence properties for equalities and is a property common to equalities and inequalities. The model has been validated with a panel of experts and the relational digraph is updated. This research could find potential applications for operations managers to identify and relate their technological capabilities to supply chain and operational resilience.