This book covers recent research advances, methods and techniques, applications and projects in financial analytics, with a focus on the effects of the health crisis on banking activities and financial engineering. It explores the latest developments in banking regulation, banking and financial systems, financial engineering, and corporate finance in order to provide financial analytics that assess financial stability and sustainability. Written for researchers and practitioners alike, the book is intended to promote stimulating scientific exchanges, ideas and experiences in the field of financial analytics for economics and management.

This book gathers selected high-quality papers presented at the 31st European Conference on Operational Research, which was held in Athens, Greece on June 11-14, 2021. It highlights the latest advances in the application of operations research (OR) to technology-driven areas in business, finance, and economics, covering both theoretical and methodological developments, as well as real-world case studies. It also explores the connections between OR and other analytical disciplines, such as soft computing and computer science, which can promote the development of new decision support technologies.  

This book presents a collection of essays written by leading researchers to honor Roman Słowiński’s major scholarly interests and contributions. He is well-known for conducting extensive research on methodologies and techniques for intelligent decision support, where he combines operational research and artificial intelligence. The book reconstructs his main contributions, presents cutting-edge research and provides an outlook on the most promising and advanced domains of computer science and multiple criteria decision aiding.  The respective chapters cover a wide range of related research areas, including decision sciences, ordinal data mining, preference learning and multiple criteria decision aiding, modeling of uncertainty and imprecision in decision problems, rough set theory, fuzzy set theory, multi-objective optimization, project scheduling and decision support applications. As such, the book will appeal to researchers and scholars in related fields.

This book presents a rich collection of studies on the analysis of sustainable development from a multiple criteria decision-making (MCDM) perspective, written by some of the most prominent authors in the field of MCDM/A. The book constitutes a unique international reference guide to the analysis, measurement, and management of sustainability in a multidimensional decision analysis context. Chiefly intended for academics and policymakers, it reflects some of the latest methodological advances in decision-making, which are illustrated in real-life applications to sustainability-related topics in both the private and public sector.

Risk is the main source of uncertainty for investors, debtholders, corporate managers and other stakeholders. For all these actors, it is vital to focus on identifying and managing risk before making decisions. The success of their businesses depends on the relevance of their decisions and consequently, on their ability to manage and deal with the different types of risk. Accordingly, the main objective of this book is to promote scientific research in the different areas of risk management, aiming at being transversal and dealing with different aspects of risk management related to corporate finance as well as market finance. Thus, this book should provide useful insights for academics as well as professionals to better understand and assess the different types of risk.

This book presents a diverse range of recent operational research techniques that have been applied to agriculture and tourism management. It covers both the primary sector of agriculture and agricultural economics, and the tertiary sector of the tourism industry. Findings and lessons learned from these innovations can be readily applied to various other contexts. The book chiefly focuses on cooperative management issues, and on developing solutions to provide decision support in multi-criteria scenarios.

Unarguably, preserving the ecosystem, securing sustainability and understanding the dynamics of agro-food chains have all become vital policy objectives with several interlinked dimensions. The main objectives of this book are to draw the attention of researchers, policymakers and businesspeople to the relation between agro-food chains and the ecosystem, and to demonstrate the importance of building resilient agro-food chains that take into account climate change and environmental challenges. Agro-food chains as they function today can serve as powerful tools for promoting sustainable forms of agriculture, consumption and production that are embedded in a viable ecosystem. The book addresses a range of environmental, methodological and societal issues from a transaction perspective, while also providing extensive background information on the topic, and outlining future applications and research directions.

This book presents a diverse range of recent operational research techniques that have been applied to agriculture and tourism management. It covers both the primary sector of agriculture and agricultural economics, and the tertiary sector of the tourism industry. Findings and lessons learned from these innovations can be readily applied to various other contexts. The book chiefly focuses on cooperative management issues, and on developing solutions to provide decision support in multi-criteria scenarios.

Unarguably, preserving the ecosystem, securing sustainability and understanding the dynamics of agro-food chains have all become vital policy objectives with several interlinked dimensions. The main objectives of this book are to draw the attention of researchers, policymakers and businesspeople to the relation between agro-food chains and the ecosystem, and to demonstrate the importance of building resilient agro-food chains that take into account climate change and environmental challenges. Agro-food chains as they function today can serve as powerful tools for promoting sustainable forms of agriculture, consumption and production that are embedded in a viable ecosystem. The book addresses a range of environmental, methodological and societal issues from a transaction perspective, while also providing extensive background information on the topic, and outlining future applications and research directions.

This volume highlights recent applications of multiple-criteria decision-making (MCDM) models in the field of finance. Covering a wide range of MCDM approaches, including multiobjective optimization, goal programming, value-based models, outranking techniques, and fuzzy models, it provides researchers and practitioners with a set of MCDM methodologies and empirical results in areas such as portfolio management, investment appraisal, banking, and corporate finance, among others. The book addresses issues related to problem structuring and modeling, solution techniques, comparative analyses, as well as combinations of MCDM models with other analytical methodologies.

This book brings together research on cooperative management from the agriculture and food sector. By examining issues from food-policy, trade and environmental perspectives and presenting both methodological and empirical work, it allows readers to develop a deeper understanding of collective management processes and cooperative initiatives, and provides a theoretical background for promoting research in the various sectors in which market communities operate. On a more global level the offers insights into how to building powerful tools for decision making, particularly at a time when agriculture and the economy alike are affected by a volatile political, social and economical environment and are forced to undergo major structural changes.

This book provides an introduction to operational research methods and their application in the agrifood and environmental sectors. It explains the need for multicriteria decision analysis and teaches users how to use recent advances in multicriteria and clustering classification techniques in practice. Further, it presents some of the most common methodologies for statistical analysis and mathematical modeling, and discusses in detail ten examples that explain and show "hands-on" how operational research can be used in key decision-making processes at enterprises in the agricultural food and environmental industries. As such, the book offers a valuable resource especially well suited as a textbook for postgraduate courses.

This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies. Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a "big-data'" era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.

This volume highlights recent applications of multiple-criteria decision-making (MCDM) models in the field of finance. Covering a wide range of MCDM approaches, including multiobjective optimization, goal programming, value-based models, outranking techniques, and fuzzy models, it provides researchers and practitioners with a set of MCDM methodologies and empirical results in areas such as portfolio management, investment appraisal, banking, and corporate finance, among others. The book addresses issues related to problem structuring and modeling, solution techniques, comparative analyses, as well as combinations of MCDM models with other analytical methodologies.

This book provides an introduction to operational research methods and their application in the agrifood and environmental sectors. It explains the need for multicriteria decision analysis and teaches users how to use recent advances in multicriteria and clustering classification techniques in practice. Further, it presents some of the most common methodologies for statistical analysis and mathematical modeling, and discusses in detail ten examples that explain and show “hands-on� how operational research can be used in key decision-making processes at enterprises in the agricultural food and environmental industries. As such, the book offers a valuable resource especially well suited as a textbook for postgraduate courses.

This book focuses on the use of farm level, micro- and macro-data of cooperative systems and networks in developing new robust, reliable and coherent modeling tools for agricultural and environmental policy analysis. The efficacy of public intervention on agriculture is largely determined by the existence of reliable information on the effects of policy options and market developments on farmers' production decisions and in particular, on key issues such as levels of agricultural and non-agricultural output, land use and incomes, use of natural resources, sustainable-centric management, structural change and the viability of family farms. Over the last years, several methods and analytical tools have been developed for policy analysis using various sets of data. Such methods have been based on integrated approaches in an effort to investigate the above key issues and have thus attempted to offer a powerful environment for decision making, particularly in an era of radical change for both agriculture and the wider economy.

This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies. Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a "big-data'" era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.

This book presents recent advancements of research, new methods and techniques, applications and projects in decision making and decision support systems. It explores expert systems and neural networks, knowledge engineering and management, fuzzy sets and systems and computational methods for optimization, data analysis and decision making. It presents applications in Economics, Finance, Management and Engineering. The book undertakes to stimulate scientific exchange, ideas and experiences in the field of decision making in Economy and Management. Researchers and practitioners alike will benefit from this book, when they are dealing with imprecision, vagueness and uncertainty in the context of decision making.

The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.

This book focuses on the use of farm level, micro- and macro-data of cooperative systems and networks in developing new robust, reliable and coherent modeling tools for agricultural and environmental policy analysis. The efficacy of public intervention on agriculture is largely determined by the existence of reliable information on the effects of policy options and market developments on farmers' production decisions and in particular, on key issues such as levels of agricultural and non-agricultural output, land use and incomes, use of natural resources, sustainable-centric management, structural change and the viability of family farms. Over the last years, several methods and analytical tools have been developed for policy analysis using various sets of data. Such methods have been based on integrated approaches in an effort to investigate the above key issues and have thus attempted to offer a powerful environment for decision making, particularly in an era of radical change for both agriculture and the wider economy.

The primary purpose in this book is to present an integrated and innovative methodological approach for the construction and selection of equity portfolios. The approach takes into account the inherent multidimensional nature of the problem, while allowing the decision makers to incorporate specified preferences in the decision processes. A fundamental principle of modern portfolio theory is that comparisons between portfolios are generally made using two criteria; the expected return and portfolio variance. According to most of the portfolio models derived from the stochastic dominance approach, the group of portfolios open to comparisons is divided into two parts: the efficient portfolios, and the dominated. This work integrates the two approaches providing a unified model for decision making in portfolio management with multiple criteria.

This book provides a concise introduction into the fundamentals and applied techniques of multiple criteria decision making in the finance sector. Based on an analysis of the nature of financial decisions and the general methods of financial modelling, risk management and financial engineering, the book introduces into portfolio management, banking management and credit scoring. Finally the book presents an overview of further applications of multi criteria analysis in finance and gives an outlook on future perspectives for the application of MCDA in finance.

This book provides a new point of view on the field of financial engineering, through the application of multicriteria intelligent decision aiding systems. The aim of the book is to provide a review of the research in the area and to explore the adequacy of the tools and systems developed according to this innovative approach in addressing complex financial decision problems, encountered within the field of financial engineering. Audience: Researchers and professionals such as financial managers, financial engineers, investors, operations research specialists, computer scientists, management scientists and economists.

This book presents a set of new, innovative mathematical modeling tools for analyzing financial risk. Operational Tools in the Management of Financial Risks presents an array of new tools drawn from a variety of research areas, including chaos theory, expert systems, fuzzy sets, neural nets, risk analysis, stochastic programming, and multicriteria decision making. Applications cover, but are not limited to, bankruptcy, credit granting, capital budgeting, corporate performance and viability, portfolio selection/management, and country risk. The book is organized into five sections. The first section applies multivariate data and multicriteria analyses to the problem of portfolio selection. Articles in this section combine classical approaches with newer methods. The second section expands the analysis in the first section to a variety of financial problems: business failure, corporate performance and viability, bankruptcy, etc. The third section examines the mathematical programming techniques including linear, dynamic, and stochastic programming to portfolio managements. The fourth section introduces fuzzy set and artificial intelligence techniques to selected types of financial decisions. The final section explores the contribution of several multicriteria methodologies in the assessment of country financial risk. In total, this book is a systematic examination of an emerging methodology for managing financial risk in business.

Multicriteria analysis is a rapidly growing aspect of operations research and management science, with numerous practical applications in a wide range of fields. This book presents all the recent advances in multicriteria analysis, including multicriteria optimization, goal programming, outranking methods, and disaggregation techniques. The latest developments on robustness analysis, preference elicitation, and decision making when faced with incomplete information, are also discussed, together with applications in business performance evaluation, finance, and marketing. Finally, the interactions of multicriteria analysis with other disciplines are also explored, including among others data mining, artificial intelligence, and evolutionary methods.