Deep Learning and Prediction of Survival Period for Breast Cancer Patients -- Should Managers Care About Intra-Household Heterogeneity? -- Penalizing Neural Network and Autoencoder for the Analysis of Marketing Measurement Scales in Service Marketing Applications -- Prediction of Gasoline Octane Loss Based on t-SNE and Random Forest -- Introducing AI General Practitioners to Improve Healthcare Services -- A U-Net Architecture Based Model for Precise Air Pollution Concentration Monitoring -- An Interpretable Ensemble Model of Acute Kidney Disease Risk -- Algorithm for Predicting Bitterness of Children's Medication -- Intelligent Identification of High Emission Road Segment Based on Large-Scale Traffic Datasets -- Construction Cost Prediction for Multi-family Housing Projects based on Support Vector Regression -- Evolution of Intellectual Structure of Data Mining Research Based on Keywords -- Development of a Cost Optimization Algorithm for Food and Flora Waste to Fleet Fuel (F4).

This book showcases state-of-the-art advances in service science and related fields of research, education, and practice. It presents emerging technologies and applications in contexts ranging from healthcare, energy, finance, and information technology to transportation, sports, logistics, and public services. Regardless of its size and service, every service organization is a service system. Due to the socio-technical nature of service systems, a systems approach must be adopted in order to design, develop and deliver services aimed at meeting end users' utilitarian and socio-psychological needs alike. Understanding services and service systems often requires combining multiple methods to consider how interactions between people, technologies, organizations and information create value under various conditions. The papers in this volume highlight a host of ways to approach these challenges in service science and are based on submissions to the 2021 INFORMS Conference on Service Science.