## 2 Literature Review
### SC Network Resilience Management and Supplier Management Prioritization Approach  
One of the remaining critical issues faced by the OSCM managers is in effectively operationalizing and incorporating interconnected firm's capability and network structural attributes in the supplier management process [69]. To address this multidimensional nature of supply network evaluation process, analytical tool that can effectively integrate both internal and environmental measures into the decision process can prove useful from the supply network risk management perspective. Mainly, there are two major evaluation models for SC network resilience management, such as dynamic capability improvement model and network optimization model. The dynamic capability improvement model often focuses on identifying and acknowledging prominent influential factors to improve overall firm capabilities and performance. Such models require an effortful task for interpretation, thus, systematic analyses are often adopted to alleviate vagueness in its findings. [PERSON] [40] developed total interpretive structural modeling to identify and categorize major technological capabilities of firms that influence the overall supply chain resilience capabilities. They identified SC design modification and planning capabilities as the prominent relations among various factors based on a case evaluation of electronics manufacturing industry in India. [PERSON] and [PERSON] [39] examined a conceptual model between SC capabilities and resilience, contingent on the perception of supplier risk. Grounded in the resource-based view of firms, their research highlighted the importance of the perception of supplier in decision-making with respect to integration and deployment of capabilities for SC resilience. The network optimization model relies on the assumption that the interdependence structure significantly drives and moderates the overall network performance. Recent research streams follow that the supply chain exhibits the properties of a complex adaptive system (nonlinearity, adaptation, self-organization, emergence) [70], and that such system now should be thoroughly investigated based on a set of interdependent firms and their interactions. [PERSON] and [PERSON] [71] adopted grey theory and multiobjective programming to improve overall airline flexibility considering passenger's service level, operating cost, airline route length, concentration of traffic flow. [PERSON] and [PERSON] [24] adopted a Bayesian network to model the causal relationship of primary (cost, quality, lead time), green (CO2 emission, environmental practice) and resilience attributes of each connected firm in supplier evaluation context. Their application aided in quantifying the appropriateness of suppliers based on such criteria, empowering the ability select suppliers based on the expert evidence. [PERSON] and [PERSON] [72] operationalized the NK fitness landscape model to quantitatively demonstrate the effectiveness of degree of interdependence and interdependence patterns on the relationship between trust level and SC performance. However, in the context of resilience management, the optimal status of attributes such as resilience and network values are ambiguous and difficult to specify; thus, both positive and negative measures of the quantified relationship should be considered. Abovementioned approaches lack the integrative perspective of network structural relationship and network design. Consequently, practitioners can benefit from a revised approach that delineates vulnerable suppliers and provides a guideline to supply network management for a sustainable performance. From this aspect, the proposed approach in this study provides a value adding alternatives to a specific network management problem: (i) it can deal with both ordinal and cardinal attributes in decision making.