A Theoretical Framework for Supply Chain Resilience: Integrating Complexity and Network Theories to Understand Adaptive Capabilities

Contemporary supply chains represent interconnected networks with interdependency, structural complexity, uncertainty, and open to disturbances that can be transmitted over organizational and geographical lines. supply-chain resilience has drawn attention in a considerable amount, but still research in the field tends to separate the analysis of structural resilience mechanisms and organizational adaptive capabilities. As a result, a rather small theoretical convergence still exists on the issue of the joint effects of network structure, adaptive capabilities, information visibility, organizational learning, and disruption characteristics producing a resilient performance collectively. This conceptual paper presents a unified setup through cross-disciplinary synthesis of work done in the area of resilience of supply chains, Complexity Theory and Complex Adaptive Systems, Network Theory, and Dynamic Capabilities Theory. Literature synthesis way through the four stages is applied: finding compatible concepts, formulating theoretical mechanisms, identifying overlaps among the concepts, formulating relations between features of the network and the consequences of the resilience. This concept presents supply chains as complex adaptive networks. Within these networks, such characteristics as centrality, the degree of connectivity, redundancy in structure, modularity, and variety form simultaneously the vulnerability and the variety of the options for response. The ability through information visibility of disturbance and its meaning is a key step, whereas through the utilization of the capacity to adapt it is possible to convert structural resources into collective actions by sensing decoding reacting, re-designing, continuing the process with learning, and sometimes by a complete change if circumstances allow. A set of different attributes of disruptions like magnitude, length of the effect speed breadth, and predictability are all factors that influence the relationship between various occurrences. Resilience is presented as a construct with multiple facets covering the aspects before the incident - resistance, after the incident - response effectiveness and recovery, and finally adaptation and transformation of the supply network. A number of theoretically sound and well-justified propositions are put forward in the paper which can be empirically proven. And, the model features a feedback mechanism through which a disruption, a disruption-induced change, and a new state will lead to a reinforcement of adaptive capacities. The study offers two contributions: Firstly, it brings structural and functional causes of supply chain resilience into the dynamic model. Secondly, it develops an operational model that offers a way to look at resilience from multiple perspectives and a method of combining structural and functional resilience. Future research is encouraged that will empirically support the relationships through structural equation modeling, longitudinal work, agent-based modeling, and simulation of disruption scenarios when talking about different industries, network configurations, and disruption types.