Combining Quality of Service and Quality of Experience to Visualize and Analyze City Services

Research is rich in analyzing performance and quality of city services (e.g., the frequency and timeliness of the), while the quality of experience is usually overlooked. This research combines the quality of service and the quality of experience into a single multi-faceted framework. The proposed framework incorporates visualizations and implements urban analytics to compare QoS and QoE. Discrete event simulations and Markov Chain Models are created to model city services’ behavior and simulate events. At the same time, resilience metrics are used to evaluate the quality of the service. Data mining of social media, natural language processing, and emotion analysis techniques are employed to measure the QoE. The framework is implemented to analyze how services react to different types of service disruptions (e.g., weather, maintenance, attacks) through time and their effect on customers. This research’s main findings are related to the differences in resilience of the services during disruptions, while QoE reveals additional issues associated with their use. The proposed framework is illustrated through transportation services, providing insights on their performability and customer’s perception of the service. Future work involves collecting data on other services to test the framework further, as well as improving the layers of superimposed data for explorations and visualizations, thereby creating a decision-making tool for stakeholders.