Gebundenes Buch

The Oxford Handbook of Agent-Based Computational Management Science

Beschreibung

Over the past few decades, agent-based modelling and agent-based computational technologies have spread into research on business and management. Agent-based modelling takes account of individual behavior alongside interactions within and across organizations and their competitive environment, seeking to explain complex, macro-level patterns emerging from micro-level behavior. These characteristics make an agent-based approach useful for studying a number of open issues in management, including adaptive behavior and dynamics in and across organizations, variable outcomes caused by management practices, and bridging micro-and macro-levels in organizational analysis. In The Oxford Handbook of Agent-based Computational Management Science, Friederike Wall, Shu-Heng Chen, and Stephan Leitner bring together a wide array of experts in the field to give a comprehensive overview of this novel approach in management science. In particular, the volume focuses on adaptive behavior and dynamics in and across organizations, non-linearities caused by management practices, and bridging micro-and macro-levels in organizational analysis. The Handbook addresses two purposes of agent-based approaches in management science. First, the volume shows how an agent-based approach advances theory-building in management. Second, it provides an overview of agent-based technologies employed for more practical issues in management. These comprise, for example, a normative understanding of systems design, such as determining which designs provide good results. An indispensable resource on agent-based modeling in management science, this Handbook introduces its current state from theoretical and operational perspectives and discusses its future opportunities.

Autor

Friederike Wall is a Full Professor of Management Control and Strategic Management at the University of Klagenfurt, Austria, since 2009. In 1996, she received the venia legendi (Habilitation) from the University of Hamburg, Germany, and she became a Full Professor of Management Control and Information Management at the University of Witten/Herdecke, Germany. She is an elected member of the Academia Europaea and was awarded the Austrian Cross of Honour for Science and Art First Class. Her scientific work focuses on agent-based modeling applied in management science, particularly for studying management control systems and the social dynamics associated with control mechanisms. Shu-Heng Chen is a Distinguished Professor in the Department of Economics, National Chengchi University (NCCU), Taipei, Taiwan. He serves as the editor-in-chief of Journal of New Mathematics and Natural Computation and Journal of Economic Interaction and Coordination. Chen holds a PhD. in Economics from University of California at Los Angeles. His research interests include computational intelligence, agent-based computational economics, and computational social sciences. He has more than 200 referred publications in international journals and edited book volumes, and authored Agent-based Computational Economics: How the Ideas Originated and Where It Is Going and co-authored Agent-based Modeling and Network Dynamics. Stephan Leitner is an Associate Professor at the University of Klagenfurt, Austria. His research is focused on simulations, especially those that use agents to simulate real-life behaviors in management science, organizational studies, and complex systems. He is particularly interested in updating traditional economic models with these simulations to see how management controls emerge and to understand the behaviors and control mechanisms in organizations and individuals. Leitner also looks into how self-organization and social dynamics can explain the dynamics within management science. His recent work aims at ensuring that social science research can be reliably replicated, emphasizing the importance of reproducibility in research.

Produktdetails

• Verlag: Oxford University Press
• Seitenzahl: 488
• Erscheinungstermin: 10. Februar 2026
• Englisch
• ISBN-13: 9780197668122
• ISBN-10: 0197668127
• Artikelnr.: 75491095