Tinglong Dai – författare

How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century?Editors Tinglong Dai and Sridhar Tayur, aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers a wide range of macro-, meso- and micro-level thrusts—such as market design, competing interests, global health, personalized medicine, residential care and concierge medicine, among others—and structures what has been a highly fragmented research area into a coherent scientific discipline.The handbook also provides an easy-to-comprehend introduction to five essential research tools—Markov decision process, game theory and information economics, queueing games, econometric methods, and data science—by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts.The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook: Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective—a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable—can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately.Facilitates collaboration between healthcare experts and analytics scholar to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose.The handbook is designed to be accessible to the independent reader, and it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course.

How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century?

Editors Tinglong Dai and Sridhar Tayur, aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers a wide range of macro-, meso- and micro-level thrusts—such as market design, competing interests, global health, personalized medicine, residential care and concierge medicine, among others—and structures what has been a highly fragmented research area into a coherent scientific discipline.

The handbook also provides an easy-to-comprehend introduction to five essential research tools—Markov decision process, game theory and information economics, queueing games, econometric methods, and data science—by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts.

The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook:

Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective—a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable—can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately. Facilitates collaboration between healthcare experts and analytics scholar to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose.

The handbook is designed to be accessible to the independent reader, and it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course.

How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century?

Editors Tinglong Dai and Sridhar Tayur, aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers a wide range of macro-, meso- and micro-level thrusts—such as market design, competing interests, global health, personalized medicine, residential care and concierge medicine, among others—and structures what has been a highly fragmented research area into a coherent scientific discipline.

The handbook also provides an easy-to-comprehend introduction to five essential research tools—Markov decision process, game theory and information economics, queueing games, econometric methods, and data science—by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts.

The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook:

Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective—a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable—can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately. Facilitates collaboration between healthcare experts and analytics scholar to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose.

The handbook is designed to be accessible to the independent reader, and it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course.

Bringing together some of the world’s foremost supply-chain thinkers, this book shows how artificial intelligence (AI) is rewriting the rules of global supply chain management. It explores machine learning, computer vision, large-language models, and generative AI in action – how they’re used to refine demand forecasts, optimize inventories, and drive down costs while service levels soar. The book examines AI-driven demand forecasting and inventory optimization, which enhances the accuracy of predicting customer demand and managing inventory levels to reduce costs and improve service. It covers intelligent logistics and transportation management, and utilizing AI to optimize routing, scheduling, and fleet management, which leads to increased efficiency and sustainability. The discussion extends to procurement and supplier relationship management, where procurement processes are streamlined and supplier partnerships are strengthened through AI-driven analytics and decision-making tools. In turn, the book confronts the hard questions of ethics, data privacy, and algorithmic bias, equipping readers to harness AI’s power responsibly and ethically across the entire supply chain. These topics are vital, as they address the pressing need for supply chains to become more agile, resilient, and responsive in today’s rapidly changing global market. By exploring these areas, the book aims to provide readers with a nuanced understanding of the current landscape and future directions of AI in supply chain management. The problem this book sets out to solve is the knowledge gap between the theoretical potential of AI and its practical application within supply chains around the globe. By presenting real-world examples, case studies, and expert analyses, it offers actionable insights that can be applied to enhance operational efficiency and strategic decision-making. The book is intended for supply chain professionals, business leaders, academics, policymakers, and students seeking a better grasp of the intersection of AI and supply chain management. It serves as both a reference guide and a source of inspiration for those looking to leverage AI technologies to drive innovation and competitiveness in their organizations.