The central purpose of this book is to explore, from diverse theoretical and practical perspectives, how organizations can create meaningful user experiences and transform management practices through a deeper understanding of customer well-being.

As artificial intelligence, data analytics, and digital technologies continue to reshape markets and society, the relationship between firms and customers is undergoing a profound transformation. Success can no longer be achieved merely by improving customer satisfaction or optimizing transactions. Instead, leading organizations are embracing the emerging paradigms of Marketing 4.0, 5.0, and beyond, in which value is co-created through richer customer experiences, human-centered innovation, and digitally empowered relationships.

In this evolving environment, user experience (UX) has become a critical source of competitive advantage, while digital transformation (DX) has expanded beyond technological modernization to encompass the re-creation of value from the customer’s perspective. Yet despite growing investment in DX initiatives, many organizations continue to rely on a Marketing 2.0 mindset, using digital technologies primarily for customer segmentation, targeting, and recommendation systems based on past purchasing behavior.

This book argues that the future of marketing requires a more ambitious vision. Rather than viewing customers as recipients of algorithmic recommendations, it positions them as active participants in value co-creation. The focus shifts from predicting purchases to understanding how products, services, and experiences contribute to people's lives, personal development, and overall well-being.

The volume’s distinctive academic contribution lies in advancing a well-being-centered perspective on marketing and management. Drawing on the concepts and methodologies of service informatics, customer experience research, data science, and artificial intelligence, the chapters illuminate how organizations can design experiences that not only create economic value but also enhance the quality of life of customers and society.

Bringing together insights from leading scholars and practitioners, this book offers a forward-looking framework for understanding the next generation of marketing. It demonstrates how customer experiences accumulate over time to shape consumer well-being and how organizations can leverage digital technologies, human insight, and explainable artificial intelligence to create sustainable value in an increasingly complex world.

This volume will be of interest to researchers, graduate students, and professionals in marketing, management, information systems, service science, artificial intelligence, and consumer behavior who seek to understand the evolving relationship between technology, customer experience, and human well-being.

Michiko Tsubaki is Professor of Management Informatics at Tokyo University of Science and a leading scholar in the integration of management science, data science, and consumer well-being research.

Her international academic career began with study and research appointments at the University of Oxford, where she was a visiting graduate student in the Department of Biomathematics in 1988 and later a visiting fellow in the Department of Statistics in 1992. She joined the University of Electro-Communications, where she served as lecturer, associate professor, and later professor at the Graduate School of Informatics. In 2014, she was appointed vice president of the university. Since joining Tokyo University of Science in 2021, she has served as Professor and Dean of the Department of Management, advancing interdisciplinary education and research at the intersection of business administration and data science. Since 2025, she has also served as a director of Tokyo University of Science.

Throughout her academic career, Professor Tsubaki has pursued a consistent research agenda centered on understanding individual heterogeneity among stakeholders and developing analytical methodologies that support evidence-based management. Her work has contributed to the advancement of customer analytics, employee support systems, recommendation methodologies, and matching mechanisms between customers and service employees.

She received the prestigious Nikkei Quality Control Literature Award for her book Quality System Engineering Data Analysis for Qualitative Improvement of Education: Focusing on the Analysis of Individual Differences, which exemplifies her pioneering contributions to data-driven approaches for understanding human diversity and decision-making.

Professor Tsubaki has published extensively on methods for analyzing heterogeneity among customers and employees, providing practical frameworks for personalized recommendations, organizational support, and service optimization. Her research has increasingly focused on the role of well-being in marketing and management, moving beyond traditional measures of customer satisfaction toward a deeper understanding of the factors that enable individuals to lead better lives.

In recent years, she has developed innovative approaches that utilize explainable machine learning techniques, including Individual Conditional Expectation (ICE) and SHAP, to identify and predict the drivers of consumer well-being from large-scale behavioral data. Her research findings have been published in leading international outlets, including the Journal of Retailing and Consumer Services and the Springer Communications in Computer and Information Science (CCIS) series.

Professor Tsubaki also served as the supervising translator of the Japanese edition of Recommendation Engines by Michael Schrage, further contributing to the dissemination of cutting-edge knowledge on artificial intelligence and data-driven decision-making.

Among her recent international publications, the chapter “Analyzing Heterogeneous Consumer Well-being Using Explainable Machine Learning ICE” (Tsubaki & Zhao, 2026) was published in Springer’s Encyclopedia of Artificial Intelligence in Marketing. This work represents her continuing commitment to advancing explainable artificial intelligence and its application to understanding consumer well-being, customer experience, and value co-creation in the digital age.