Resilience modeling of mobile service for quality assurance

Resilience modeling has gained significant interest from academia and business because it offers a fresh perspective on preparing for hurdles and overcoming them. Even though scholars across many fields have explored the idea of resilience, very few have concentrated on quantifying resilience. Bayesian networks (BNs) have developed from an emerging subject to one that is integral in the developing field of supply chain resilience and risk assessment. This paper uses BN modeling to ensure the resilience of a mobile service for quality assurance purposes. It employs BNs in a delay-time risk analysis case study to identify and model the numerous parameters responsible for a system’s failure rate. BN modeling enables system changing events to modify, update, and affect the failure rate or probability of failure. In order to illustrate the resilience evaluation process, a case study is examined. By including the BN models in a quality control system for mobile services, service providers can proactively identify and address any resilience problems. Developing a more comprehensive BN model in future research will involve multiple factors impacting the resilience of mobile services, such as network infrastructure, user behavior, and service provider strategies.