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.

This two-volume set LNCS 12861 and LNCS 12862 constitutes the refereed proceedings of the 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, held virtually, in June 2021. The 85 full papers presented in this two-volume set were carefully reviewed and selected from 134 submissions. The papers are organized in topical sections on Deep Learning for Biomedicine, Intelligent Computing Solutions for SARS-CoV-2 Covid-19, Advanced Topics in Computational Intelligence, Biosignals Processing, Neuro-Engineering and much more.

This book highlights interdisciplinary insights, latest research results, and technological trends in Business Intelligence and Modelling in fields such as: Business Intelligence, Business Transformation, Knowledge Dissemination & Implementation, Modeling for Logistics, Business Informatics, Business Model Innovation, Simulation Modelling, E-Business, Enterprise & Conceptual Modelling, etc. The book is divided into eight sections, grouping emerging marketing technologies together in a close examination of practices, problems and trends. The chapters have been written by researchers and practitioners that demonstrate a special orientation in Strategic Marketing and Business Intelligence. This volume shares their recent contributions to the field and showcases their exchange of insights.

This Handbook shows the enormous impetus given to the scientific debate by linking planning as a science of purposeful interventions and complexity as a science of spontaneous change and non-linear development. Emphasising the importance of merging planning and complexity, this comprehensive Handbook also clarifies key concepts and theories, presents examples on planning and complexity and proposes new ideas and methods which emerge from synthesising the discipline of spatial planning with complexity sciences.

This Festschrift volume is published in honor of Takao Terano on the occasion of his retirement. Takao Terano is a leading expert in the areas of agent-based modelling, knowledge systems, evolutionary computation, and service science.The contributions in this volume reflect the breadth and impact of his work. The volume contains 12 full papers related to Takao Terano’s research. They deal with various aspects of artificial intelligence, multi-agent systems, collaborative and social computing, social networks, ubiquitous computing.

During the 21st century business environments have become more complex and dynamic than ever before. Companies operate in a world of change influenced by globalisation, volatile markets, legal changes and technical progress. As a result, they have to handle growing volumes of data and therefore require fast storage, reliable data access, intelligent retrieval of information and automated decision-making mechanisms, all provided at the highest level of service quality. Successful enterprises are aware of these challenges and efficiently respond to the dynamic environment in which their business operates. Business Intelligence (BI) and Performance Management (PM) offer solutions to these challenges and provide techniques to enable effective business change. The important aspects of both topics are discussed within this state-of-the-art volume. It covers the strategic support, business applications, methodologies and technologies from the field, and explores the benefits, issues and challenges of each. Issues are analysed from many different perspectives, ranging from strategic management to data technologies, and the different subjects are complimented and illustrated by numerous examples of industrial applications. Contributions are authored by leading academics and practitioners representing various universities, research centres and companies worldwide. Their experience covers multiple disciplines and industries, including finance, construction, logistics, and public services, amongst others. Business Intelligence and Performance Management is a valuable source of reference for graduates approaching MSc or PhD programs and for professionals in industry researching in the fields of BI and PM for industrial application.

This book examines reconstruction and resilience of historic cities and societies from multiple disciplinary and complementary perspectives and, by doing so, it helps researchers and practitioners alike, among them reconstruction managers, urban governance and professionals. The book builds on carefully selected and updated papers accepted for the 2019 Silk Cities international conference on ‘reconstruction, recovery and resilience of historic cities and societies’, the third Silk Cities conference held in L’Aquila, Italy, 10-12 July 2019, working with University of L’Aquila and UCL. This multi-scale, and multidisciplinary book offers cross-sectoral and complimentary voices from multiple stakeholders, including academia, urban governance, NGOs and local populations. It examines post-disaster reconstruction strategies and case studies from Europe, Asia and Latin America that provide a valuable collection for anyone who would like to get a global overview on the subject matter. It thereby enables a deeper understanding of challenges, opportunities and approaches in dealing with historic cities facing disasters at various geographical scales. Additionally, it brings together historical approaches to the reconstruction of historical cities and those of more recent times. Thus, it can be used as a reference book for global understanding of the subject matter.

The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their "immigration" to the world of Homo sapiens, or symbiogenesis.

Tobacco consumption continues to be the leading cause of preventable disease and death in the United States. The Food and Drug Administration (FDA) regulates the manufacture, distribution, and marketing of tobacco products - specifically cigarettes, cigarette tobacco, roll-your-own tobacco, and smokeless tobacco - to protect public health and reduce tobacco use in the United States. Given the strong social component inherent to tobacco use onset, cessation, and relapse, and given the heterogeneity of those social interactions, agent-based models have the potential to be an essential tool in assessing the effects of policies to control tobacco. Assessing the Use of Agent-Based Models for Tobacco Regulation describes the complex tobacco environment; discusses the usefulness of agent-based models to inform tobacco policy and regulation; presents an evaluation framework for policy-relevant agent-based models; examines the role and type of data needed to develop agent-based models for tobacco regulation; provides an assessment of the agent-based model developed for FDA; and offers strategies for using agent-based models to inform decision making in the future.

This is the era of Big Data and computational social science. It is an era that requires tools which can do more than visualise data but also model the complex relation between data and human action, and interaction. Agent-Based Models (ABM) - computational models which simulate human action and interaction – do just that. This textbook explains how to design and build ABM and how to link the models to Geographical Information Systems. It guides you from the basics through to constructing more complex models which work with data and human behaviour in a spatial context. All of the fundamental concepts are explained and related to practical examples to facilitate learning (with models developed in NetLogo with all code examples available on the accompanying website). You will be able to use these models to develop your own applications and link, where appropriate, to Geographical Information Systems. All of the key ideas and methods are explained in detail: geographical modelling; an introduction to ABM; the fundamentals of Geographical Information Science; why ABM and GIS; using QGIS; designing and building an ABM; calibration and validation; modelling human behavior. An applied primer, that provides fundamental knowledge and practical skills, it will provide you with the skills to build and run your own models, and to begin your own research projects.