This proceedings volume presents current research and innovative solutions into capital markets, particularly in Poland. Featuring contributions presented at the 10th Capital Market Effective Investments (CMEI 2018) conference held in Miedzyzdroje, Poland, this book explores the future of capital markets in Poland as well as comparing it with the capital markets of other developed regions around the world. Divided into four parts, the enclosed papers provide a background into the theoretical foundations of capital market investments, explores different approaches-both classical and contemporary-to investment decision making, analyzes the behaviors of investors using experimental economics and behavioral finance, and explores practical issues related to financial market investments, including real case studies. In addition, each part of the book begins with an introductory chapter written by thematic editors that provides an outline of the subject area and a summary of the papers presented.

The aim of this volume is to provide deep insights and the latest scientific developments and trends in experimental economics. Derived from the 2015 Computational Methods in Experimental Economics (CMEE) conference, this book features papers containing research and analysis of economic experiments concerning research in such areas as management science, decision theory, game theory, marketing and political science. The goal is to present possibilities for using various computer methods in the scope of experimental economics to further provide researchers with a wide variety of tools. The field of experimental economics is rapidly evolving. Modern use of experimental economics requires the integration of knowledge in the domains of economic sciences, computer science, psychology, and neuroscience. Recent research includes experiments conducted both in the laboratory and in the field, and the results are used for testing and a better understanding of economic theories. Researchers working in this field use mainly a set of well-established methods and computer tools that support the experiments. Methods such as artificial intelligence, computer simulation and computer graphics, however, are not represented enough in experimental economics studies and most experimenters do not consider their usage. The goal of the conference and the enclosed papers is to allow for an exchange of experiences and to promote joint initiatives to insight change in this trend.

These proceedings highlight research on the latest trends and methods in experimental and behavioral economics. Featuring contributions presented at the 2017 Computational Methods in Experimental Economics (CMEE) conference, which was held in Lublin, Poland, it merges findings from various domains to present deep insights into topics such as game theory, decision theory, cognitive neuroscience and artificial intelligence. The fields of experimental economics and behavioral economics are rapidly evolving. Modern applications of experimental economics require the integration of know-how from disciplines including economics, computer science, psychology and neuroscience. The use of computer technology enhances researchers' ability to generate and analyze large amounts of data, allowing them to use non-standard methods of data logging for experiments such as cognitive neuronal methods. Experiments are currently being conducted with software that, on the one hand, provides interaction with the people involved in experiments, and on the other helps to accurately record their responses. The goal of the CMEE conference and the papers presented here is to provide the scientific community with essential research on and applications of computer methods in experimental economics. Combining theories, methods and regional case studies, the book offers a valuable resource for all researchers, scholars and policymakers in the areas of experimental and behavioral economics.

Contemporary economists, when analyzing economic behavior of people, need to use the diversity of research methods and modern ways of discovering knowledge. The increasing popularity of using economic experiments requires the use of IT tools and quantitative methods that facilitate the analysis of the research material obtained as a result of the experiments and the formulation of correct conclusions. This proceedings volume presents problems in contemporary economics and provides innovative solutions using a range of quantitative and experimental tools. Featuring selected contributions presented at the 2018 Computational Methods in Experimental Economics Conference (CMEE 2018), this book provides a modern economic perspective on such important issues as: sustainable development, consumption, production, national wealth, the silver economy, behavioral finance, economic and non-economic factors determining the behavior of household members, consumer preferences, social campaigns, and neuromarketing. International case studies are also offered.

Making important business decisions is usually a difficult and complicated task. In the modern economy where businesses have to solve increasingly complex decision-making problems, it is important to learn and use methods and techniques including the analysis of behavioral data to support decision-making in practice. This book presents various methods and solutions to problems in modern data acquisition techniques and practical aspects of decision making. In particular, it addresses such important issues as: business decision making, multi-criteria decision analysis (MCDA), multidimensional comparative analysis (MCA), decision games and data acquisition techniques for decision making (declarative techniques and cognitive neuroscience techniques). Important topics such as consumers' rational behavior, environmental management accounting, operational research methods, neuroscience including epigenetics, DEA analysis etc., as well as case studies related to decision making in management are also included.

This proceedings volume presents the latest scientific research and trends in experimental economics, with particular focus on neuroeconomics. Derived from the 2016 Computational Methods in Experimental Economics (CMEE) conference held in Szczecin, Poland, this book features research and analysis of novel computational methods in neuroeconomics. Neuroeconomics is an interdisciplinary field that combines neuroscience, psychology and economics to build a comprehensive theory of decision making. At its core, neuroeconomics analyzes the decision-making process not only in terms of external conditions or psychological aspects, but also from the neuronal point of view by examining the cerebral conditions of decision making. The application of IT enhances the possibilities of conducting such analyses. Such studies are now performed by software that provides interaction among all the participants and possibilities to register their reactions more accurately. This book examines some of these applications and methods. Featuring contributions on both theory and application, this book is of interest to researchers, students, academics and professionals interested in experimental economics, neuroeconomics and behavioral economics.

Methods used for regional development analysis are employed mainly to make forecasts and comparisons. Forecasting models of various types (e.g. econometric models) are usually used for forecasting. Recently, vector-autoregressive models (VAR) have become popular. These models were proposed by Sims in 1980. On the contrary, taxonomic methods (that are in the center of attention as far as the present publication is concerned) are most often employed to make comparisons. Linear ordering methods, including standard methods, are the most popular among ta- nomic methods. They are based on different distance and similarity measures, which leads to the fact that they do not always provide reliable information. When, for example, one construes the standard for a base year and then compares it with data for other years, it may turn out that the measure determined will have worse values than the standard for a real object (region, micro region) although this object is better from the standard. Hence, one must look for new methods employed in regional development analysis or improve hitherto existing ones in such a way so that information obtained re?ects the reality to a larger extent. The main aim of the present publication is to work out methodological basis for regional development analysis based on vector calculus together with assumptions about computer system supporting the implementation of the method suggested.

Methods used for regional development analysis are employed mainly to make forecasts and comparisons. Forecasting models of various types (e.g. econometric models) are usually used for forecasting. Recently, vector-autoregressive models (VAR) have become popular. These models were proposed by Sims in 1980. On the contrary, taxonomic methods (that are in the center of attention as far as the present publication is concerned) are most often employed to make comparisons. Linear ordering methods, including standard methods, are the most popular among ta- nomic methods. They are based on different distance and similarity measures, which leads to the fact that they do not always provide reliable information. When, for example, one construes the standard for a base year and then compares it with data for other years, it may turn out that the measure determined will have worse values than the standard for a real object (region, micro region) although this object is better from the standard. Hence, one must look for new methods employed in regional development analysis or improve hitherto existing ones in such a way so that information obtained re?ects the reality to a larger extent. The main aim of the present publication is to work out methodological basis for regional development analysis based on vector calculus together with assumptions about computer system supporting the implementation of the method suggested.

A new era is emerging in which a group of quantitative methods featuring characteristics of multidimensional comparative analysis (MCA) and multi-criteria decision-making analysis (MCDA) can be used to automate objective decision-making processes. This book introduces the character of the criteria (desirable, non-desirable, motivating, demotivating, and neutral) to MCDA and MCA methods. It presents the author’s own developed methods, the preference vector method (PVM), for solving multi-criteria problems in decision making; and, vector measure construction method (VMCM), which is dedicated to solving typical problems in the field of multidimensional comparative analysis. All methods are explained step by step with relevant examples, primarily in the fields of economics and management.

Making important business decisions is usually a difficult and complicated task. In the modern economy where businesses have to solve increasingly complex decision-making problems, it is important to learn and use methods and techniques including the analysis of behavioral data to support decision-making in practice. This book presents various methods and solutions to problems in modern data acquisition techniques and practical aspects of decision making. In particular, it addresses such important issues as: business decision making, multi-criteria decision analysis (MCDA), multidimensional comparative analysis (MCA), decision games and data acquisition techniques for decision making (declarative techniques and cognitive neuroscience techniques). Important topics such as consumers' rational behavior, environmental management accounting, operational research methods, neuroscience including epigenetics, DEA analysis etc., as well as case studies related to decision making in management are also included.

Contemporary economists, when analyzing economic behavior of people, need to use the diversity of research methods and modern ways of discovering knowledge. The increasing popularity of using economic experiments requires the use of IT tools and quantitative methods that facilitate the analysis of the research material obtained as a result of the experiments and the formulation of correct conclusions. This proceedings volume presents problems in contemporary economics and provides innovative solutions using a range of quantitative and experimental tools. Featuring selected contributions presented at the 2018 Computational Methods in Experimental Economics Conference (CMEE 2018), this book provides a modern economic perspective on such important issues as: sustainable development, consumption, production, national wealth, the silver economy, behavioral finance, economic and non-economic factors determining the behavior of household members, consumer preferences, social campaigns, and neuromarketing. International case studies are also offered.

This proceedings volume presents current research and innovative solutions into capital markets, particularly in Poland. Featuring contributions presented at the 10th Capital Market Effective Investments (CMEI 2018) conference held in Miedzyzdroje, Poland, this book explores the future of capital markets in Poland as well as comparing it with the capital markets of other developed regions around the world. Divided into four parts, the enclosed papers provide a background into the theoretical foundations of capital market investments, explores different approaches-both classical and contemporary-to investment decision making, analyzes the behaviors of investors using experimental economics and behavioral finance, and explores practical issues related to financial market investments, including real case studies. In addition, each part of the book begins with an introductory chapter written by thematic editors that provides an outline of the subject area and a summary of the papers presented.

These proceedings highlight research on the latest trends and methods in experimental and behavioral economics. Featuring contributions presented at the 2017 Computational Methods in Experimental Economics (CMEE) conference, which was held in Lublin, Poland, it merges findings from various domains to present deep insights into topics such as game theory, decision theory, cognitive neuroscience and artificial intelligence. The fields of experimental economics and behavioral economics are rapidly evolving. Modern applications of experimental economics require the integration of know-how from disciplines including economics, computer science, psychology and neuroscience. The use of computer technology enhances researchers' ability to generate and analyze large amounts of data, allowing them to use non-standard methods of data logging for experiments such as cognitive neuronal methods. Experiments are currently being conducted with software that, on the one hand, provides interaction with the people involved in experiments, and on the other helps to accurately record their responses. The goal of the CMEE conference and the papers presented here is to provide the scientific community with essential research on and applications of computer methods in experimental economics. Combining theories, methods and regional case studies, the book offers a valuable resource for all researchers, scholars and policymakers in the areas of experimental and behavioral economics.

This proceedings volume presents the latest scientific research and trends in experimental economics, with particular focus on neuroeconomics. Derived from the 2016 Computational Methods in Experimental Economics (CMEE) conference held in Szczecin, Poland, this book features research and analysis of novel computational methods in neuroeconomics. Neuroeconomics is an interdisciplinary field that combines neuroscience, psychology and economics to build a comprehensive theory of decision making. At its core, neuroeconomics analyzes the decision-making process not only in terms of external conditions or psychological aspects, but also from the neuronal point of view by examining the cerebral conditions of decision making. The application of IT enhances the possibilities of conducting such analyses. Such studies are now performed by software that provides interaction among all the participants and possibilities to register their reactions more accurately. This book examines some of these applications and methods. Featuring contributions on both theory and application, this book is of interest to researchers, students, academics and professionals interested in experimental economics, neuroeconomics and behavioral economics.

The aim of this volume is to provide deep insights and the latest scientific developments and trends in experimental economics. Derived from the 2015 Computational Methods in Experimental Economics (CMEE) conference, this book features papers containing research and analysis of economic experiments concerning research in such areas as management science, decision theory, game theory, marketing and political science. The goal is to present possibilities for using various computer methods in the scope of experimental economics to further provide researchers with a wide variety of tools. The field of experimental economics is rapidly evolving. Modern use of experimental economics requires the integration of knowledge in the domains of economic sciences, computer science, psychology, and neuroscience. Recent research includes experiments conducted both in the laboratory and in the field, and the results are used for testing and a better understanding of economic theories. Researchers working in this field use mainly a set of well-established methods and computer tools that support the experiments. Methods such as artificial intelligence, computer simulation and computer graphics, however, are not represented enough in experimental economics studies and most experimenters do not consider their usage. The goal of the conference and the enclosed papers is to allow for an exchange of experiences and to promote joint initiatives to insight change in this trend.