This book thoroughly prepares intermediate-level readers for research in social science, organization studies, economics, finance, marketing science, and business science as complex adaptive systems. It presents the advantages of social simulation studies and business intelligence to those who are not familiar with the computational research approach, and offers experienced modelers various instructive examples of using agent-based modeling and business intelligence approaches to inspire their own work. In addition, the book discusses cutting-edge techniques for complex adaptive systems using their applications.
To date, business science studies have focused only on data science and analyses of business problems. However, using these studies to enhance the capabilities of conventional techniques in the fields has not been investigated adequately. This book addresses managing the issues of societies, firms, and organizations to profit from interaction with agent-based modeling, human- and computer- mixed systems, and business intelligence approaches, an area that is fundamental for complex but bounded rational business environments.
With detailed research by leading authors in the field, Innovative Approaches in Agent-Based Modelling and Business Intelligence inspires readers to join with other disciplines and extend the scope of the book with their own unique contributions. It also includes the common challenges encountered in computational social science and business science to enable researchers, students, and professionals to resolve their own problems.
Содержание
1. Gallery for Evolutionary Computation and Artificial Intelligence Researches — Where Do We Come from and Where Shall We Go.- 2. Mathematical Technologies and Artificial Intelligence Toward Human Centric Innovation.- 3.Study on the Social Perspectives of Traffic Congestion in Sri Lanka through Agent-based Modeling and Simulation: Lessons Learned and Future Prospects.- 4. Information Technology and Finance.- 5. Two Phase Transitions in the Adaptive Voter Model based on the Homophily Principle.- 6. Use of Sensibility Analysis in Bayesian Network for Modeling an Agent.- 7. Analyzing the Influence of Headline News on Credit Markets in Japan.- 8. Consideration on an Integrated Approach to Solving Industrial Issues through Surveys, Statistics, and Simulations.- 9. U-Mart, 20 Year Experience of an Artificial Market Study.- 10. What Do Agents Recognize? — From Social Dynamics to Educational Experiments.- 11. Model prediction and inverse simulation.- 12. Identification of High-Frequency Herding Behavior in the Chinese Stock Market: An Agent-Based Approach.- 13. A Data Analysis Study on Factors of the Pedestrian Flows in Two Different Underground Malls Using Space Syntax Measures — Case Comparisons in Nagoya, Japan.- 14. A Study on Agent Modeling of Tourist Evacuation Behaviors in an Earthquake: A Case Study of an Evacuation Simulation of Himeji Castle.- 15. Virtual Grounding for Agent-Based Modeling in Incomplete Data Situation.- 16. Analysis of Problem Solving Processes.- 17. The Energy Transition Game: experiences and ways forward.- 18. A Co-evolutionary Opinion Model based on Bounded Confidence, Reference Range and Interactive Influence in Social Network.- 19. Prof. Dr Takao Terano as a brilliant educator.
Об авторе
Setsuya Kurahashi
Graduate School of Business Sciences
University of Tsukuba
Tokyo
Japan
Hiroshi Takahashi
Graduate School of Business Administration
Keio University
Yokohama-city
Japan
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