The book features contributions that address both environmental economics and environmental management. It presents a novel dynamic modeling framework for environmental economics in which environmental absorption efficiency is considered as a time-dependent variable with its own dynamics. It also introduces several extensions and applications of the model, including the possibility of including self-regenerating environmental absorption efficiency, non-cooperative transboundary issues with two superimposed free-rider behaviors (i.e., emissions reduction and restoration efforts), and deforestation. In the environmental management context, it puts forward an entirely new dynamic modeling framework. Unlike static approaches, the model considers both flow and stock variables, reflecting the accumulation of pollution over time. In turn, the book assesses sustainable configurations for supply chain competition, providing mathematical insights and managerial recommendations that integrate accumulated pollution aspects and associated negative externalities. Overall, the book calls for combining environmental economics and environmental management in order to arrive at more realistic, empirically grounded models.

Given its focus, the book offers a valuable resource for researchers and graduate students with an interest in addressing pollution control challenges in the fields of economics and management science.

At the 15th Viennese Workshop on Optimal Control and Dynamic Games, held in July 2022, experts in economics and the management sciences identified a concerning trend: static decision-making models, while less effective than dynamic ones, are becoming increasingly prevalent. This book aims to address the economic and social costs associated with reliance on static models and to demonstrate the advantages of applying dynamic approaches.

Static models may be easier to formulate, but they often overlook the long-term consequences of decisions, promoting myopic practices that can lead to poor outcomes. In contrast, dynamic models foster a more comprehensive perspective, enabling foresight in decision-making – which is crucial for issues involving stock variables, such as pollution, reputation, and inventory. The book explores the limitations of static models, including their inability to capture long-term outcomes, history-dependent solutions, and the impact of abrupt contextual changes. It also highlights recent advances in dynamic modeling techniques that can enhance accuracy and help adapt to complex decision-making environments.

By promoting the shift from static to dynamic models, this book aspires to open new research opportunities and provide valuable insights for researchers, students, policymakers, and managers in the fields of economics and the management sciences.

With this book, distinguished and notable contributors wish to honor Professor Charles S. Tapiero’s scientific achievements. Although it covers only a few of the directions Professor Tapiero has taken in his work, it presents important modern developments in theory and in diverse applications, as studied by his colleagues and followers, further advancing the topics Tapiero has been investigating. The book is divided into three parts featuring original contributions covering the following areas: general modeling and analysis; applications to marketing, economy and finance; and applications to operations and manufacturing.

Professor Tapiero is among the most active researchers in control theory; in the late sixties, he started to enthusiastically promote optimal control theory along with differential games, successfully applying it to diverse problems ranging from classical operations research models to finance, risk and insurance, marketing, transportation and operations management, conflict management and game theory, engineering, regional and urban sciences, environmental economics, and organizational behavior. Over the years, Professor Tapiero has produced over 300 papers and communications and 14 books, which have had a major impact on modern theoretical and applied research. Notable among his numerous pioneering scientific contributions are the use of graph theory in the behavioral sciences, the modeling of advertising as a random walk, the resolution of stochastic zero-sum differential games, the modeling of quality control as a stochastic competitive game, and the development of impulsive control methods in management. Charles Tapiero’s creativity applies both in formulating original issues, modeling complex phenomena and solving complex mathematical problems.

The book features contributions that address both environmental economics and environmental management. It presents a novel dynamic modeling framework for environmental economics in which environmental absorption efficiency is considered as a time-dependent variable with its own dynamics. It also introduces several extensions and applications of the model, including the possibility of including self-regenerating environmental absorption efficiency, non-cooperative transboundary issues with two superimposed free-rider behaviors (i.e., emissions reduction and restoration efforts), and deforestation. In the environmental management context, it puts forward an entirely new dynamic modeling framework. Unlike static approaches, the model considers both flow and stock variables, reflecting the accumulation of pollution over time. In turn, the book assesses sustainable configurations for supply chain competition, providing mathematical insights and managerial recommendations that integrate accumulated pollution aspects and associated negative externalities. Overall, the book calls for combining environmental economics and environmental management in order to arrive at more realistic, empirically grounded models.

Given its focus, the book offers a valuable resource for researchers and graduate students with an interest in addressing pollution control challenges in the fields of economics and management science.

At the 15th Viennese Workshop on Optimal Control and Dynamic Games, held in July 2022, experts in economics and the management sciences identified a concerning trend: static decision-making models, while less effective than dynamic ones, are becoming increasingly prevalent. This book aims to address the economic and social costs associated with reliance on static models and to demonstrate the advantages of applying dynamic approaches.

Static models may be easier to formulate, but they often overlook the long-term consequences of decisions, promoting myopic practices that can lead to poor outcomes. In contrast, dynamic models foster a more comprehensive perspective, enabling foresight in decision-making – which is crucial for issues involving stock variables, such as pollution, reputation, and inventory. The book explores the limitations of static models, including their inability to capture long-term outcomes, history-dependent solutions, and the impact of abrupt contextual changes. It also highlights recent advances in dynamic modeling techniques that can enhance accuracy and help adapt to complex decision-making environments.

By promoting the shift from static to dynamic models, this book aspires to open new research opportunities and provide valuable insights for researchers, students, policymakers, and managers in the fields of economics and the management sciences.

With this book, distinguished and notable contributors wish to honor Professor Charles S. Tapiero’s scientific achievements. Although it covers only a few of the directions Professor Tapiero has taken in his work, it presents important modern developments in theory and in diverse applications, as studied by his colleagues and followers, further advancing the topics Tapiero has been investigating. The book is divided into three parts featuring original contributions covering the following areas: general modeling and analysis; applications to marketing, economy and finance; and applications to operations and manufacturing.

Professor Tapiero is among the most active researchers in control theory; in the late sixties, he started to enthusiastically promote optimal control theory along with differential games, successfully applying it to diverse problems ranging from classical operations research models to finance, risk and insurance, marketing, transportation and operations management, conflict management and game theory, engineering, regional and urban sciences, environmental economics, and organizational behavior. Over the years, Professor Tapiero has produced over 300 papers and communications and 14 books, which have had a major impact on modern theoretical and applied research. Notable among his numerous pioneering scientific contributions are the use of graph theory in the behavioral sciences, the modeling of advertising as a random walk, the resolution of stochastic zero-sum differential games, the modeling of quality control as a stochastic competitive game, and the development of impulsive control methods in management. Charles Tapiero’s creativity applies both in formulating original issues, modeling complex phenomena and solving complex mathematical problems.