In light of the recent financial crisis in Europe and the increasing importance of sustainability in construction, insights and practical guidance for financial evaluation and risk management of infrastructure projects are extremely valuable for a well-planned future. According to the International Organization for Standardization (ISO 15686, 2009), the life cycle cost of infrastructure projects includes the cost of construction, operation, maintenance, and the end-of-life phases. Each stage includes hypotheses regarding the financial costs and costs considering several risks that might be encountered during the construction and service life of an infrastructure project. The correct and early estimation of these risks may guarantee the viability of the project. The Financial Evaluation and Risk Management of Infrastructure Projects delves into an intriguing issue and encompasses all the stages of a project from its concept that initially attempts to serve a need to the minimization of its service value. Cost-benefit analysis is indisputably considered an essential element among various evaluation methods for fostering optimal decision-making and ranking infrastructure projects over decades. Life cycle cost aspects became an important tool of knowledge about how to optimize an investment from the early stages of designing an infrastructure project. Financial Evaluation and Risk Management of Infrastructure Projects is a comprehensive guide for professionals and students in the fields of construction and investment, as well as financial and investment institutions. The book covers all stages of a project, from its concept to the minimization of its service value and highlights the importance of life cycle cost aspects in optimizing infrastructure project investments. The book also discusses the valuation of assets via the "future economic benefits" approach as a correct asset management accounting, which can prevent over and under estimation of investments and repair debt. The book emphasizes the need for cost-effective and sustainable infrastructure projects that incorporate "value for money" construction solutions, taking into account all risks involved. This book is ideal for professionals in the field of construction, investment institutions, students in construction and investments, and financial and investments institutions.

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 focuses on corporate governance and proposes a novel framework for combining the Corporate Governance Framework (CGF) with current corporate finance issues arising in the Contemporary Business Environment (CBE) and cointegrating them with today's business needs. It consists of a good collection of state-of-the-art approaches that will be useful for new researchers and practitioners working in this field, helping them to quickly grasp the current state of corporate governance and corporate financial performance.Good corporate governance is not only important for companies, but also for the society. To begin with, good corporate governance strengthens the public's faith and trust in corporate governance. Legislative processes were developed to protect the society from known threats and prevent problems from occurring or recurring. Recent corporate scandals shed light on the impact that corporations have on social responsibility. The new focus on the corporate governance framework increases the responsibility and accountability of companies to their stakeholders and provides a solid framework for enhancing corporate performance.

This book is a good collection of state-of-the-art approaches to financial engineering. It will be especially useful to new researchers and practitioners working in this field and will help them to quickly grasp the current state of financial engineering. The book equips the readers with comprehensive understanding of technological issues and financial innovations in environmental and social matters. It will allow the readers to use new econometric and operational methods to examine certain innovative products. Finally, it proposes new operational solutions based on a framework of analysis that has not yet been explored, so that the dialogue between financial engineering professionals and company managers may be more efficient, effective and impactful.

Optimization and evaluation are essential to the operations of several sectors such as the healthcare sector and the agriculture industry. Improvement of optimizations and evaluation are imperative for industry success and ensures that better services are provided to global consumers across sectors. Interdisciplinary Perspectives on Operations Management and Service Evaluation is a critical scholarly publication that focuses on operations management across several sectors and assessment strategies for the improvement of these industries. Featuring a range of topics such as fuzzy logic, ecosystem services, and metaheuristics, this book is ideal for managers, service evaluators, marketers, academicians, business professionals, researchers, practitioners, and students.

In recent years, there has been a swell of investment opportunities in contemporary asset classes that have gained considerable attention, including cryptocurrencies, hedge funds, and private equity. These alternative investments provide the opportunity to enhance the diversification of financial portfolios and harvest risk premiums that traditional assets like stocks and bonds fail to provide. The emergence of these new properties has created the need to further understand the mechanics, risks, and returns of alternative investments. Recent Advances and Applications in Alternative Investments is a pivotal reference source that provides vital research on the emergence and development of complementary asset classes in the field of finance and investment. While highlighting topics such as carbon emission markets, renewable energy, and digital currencies, this publication explores modern investment strategies as well as the latest products and new types of risk. This book is ideally designed for managers, strategists, accountants, financial professionals, economists, brokers, investors, business practitioners, policymakers, researchers, and academicians seeking current research on contemporary developments in investment strategies and alternative assets.

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.

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 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 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.

As its title implies, Advances in Multicriteria Analysis presents the most recent developments in multicriteria analysis and in some of its principal areas of application, including marketing, research and development evaluation, financial planning, and medicine. Special attention is paid to the interaction between multicriteria analysis, decision support systems and preference modeling. The five sections of the book cover: methodology; problem structuring; utility assessment; multi-objective optimisation; real world applications. Audience: Researchers and professionals who are operations researchers, management scientists, computer scientists, statisticians, decision analysts, marketing managers and financial analysts.

Advances in Stochastic Modelling and Data Analysis presents the most recent developments in the field, together with their applications, mainly in the areas of insurance, finance, forecasting and marketing. In addition, the possible interactions between data analysis, artificial intelligence, decision support systems and multicriteria analysis are examined by top researchers. Audience: A wide readership drawn from theoretical and applied mathematicians, such as operations researchers, management scientists, statisticians, computer scientists, bankers, marketing managers, forecasters, and scientific societies such as EURO and TIMS.

Financial analyses, investments, and accounting practices are continually developing and improving areas that have seen significant advancements in the past century. However, the recent bankruptcies by major banks, the debt crisis in the European Union, and the economic turmoil in several countries have caused severe downfalls in financial markets and financial systems worldwide. As the world works to recover, it is important to learn from these financial crises to ensure a more secure and sustainable outlook for organizations and the global future. Perspectives, Trends, and Applications in Corporate Finance and Accounting is a crucial resource providing coverage on the stock market, public deficits, investment firms' performances, banking systems, and global economic trends. This publication highlights areas including, but not limited to, the relationship between the stock market and macroeconomics, earnings management, and pricing models while also discussing previous financial crises. This book is a vital reference work for accountants, financial experts, investment firms, corporate leaders, researchers, and policy makers.

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.

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.

The prediction of the valuation of the "quality" of firm accounting disclosure is an emerging economic problem that has not been adequately analyzed in the relevant economic literature. While there are a plethora of machine learning methods and algorithms that have been implemented in recent years in the field of economics that aim at creating predictive models for detecting business failure, only a small amount of literature is provided towards the prediction of the "actual" financial performance of the business activity. Machine Learning Applications for Accounting Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment. The book applies machine learning models to identify "quality" characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. Covering topics that include data mining; fraud governance, detection, and prevention; and internal auditing, this book is essential for accountants, auditors, managers, fraud detection experts, forensic accountants, financial accountants, IT specialists, corporate finance experts, business analysts, academicians, researchers, and students.

This chapter describes a study conducted at the Swinburne University of Technology in Australia, in their School of Business. The study was to explore the applicability of a judgment-analytic decision support system to the assessment of the likelihood of an applicant being selected for admission to the School's Graduate Certificate in Business Administration (GCBA) program. The likelihood of a program administrator selecting a particular applicant is directly linked to the assessment of the likelihood of that applicant's success in the GCBA program. The purpose of this study, in effect, was to analyze the administrative judgment process in assessment of an applicant's likelihood of success in the program. THE PROCESS OF HUMAN JUDGMENT Human judgment is a process through which an individual uses social infonnation to make decisions. The social infonnation is obtained from an individual's environment and is interpreted through the individual's cognitive image of the environment. The. cognitive image provides a representation of the environment based on past experiences and training, and essentially predisposes the person to respond to social infonnation in predictable ways. An individual's policies or beliefs about the environment represent these patterns. Human judgments are based then upon one's interpretation of available infonnation. They are probability statements about one's environment and how one reacts to it. This condition leads to the human judgment process being inherently limited. It is fundamentally a covert process. It is seldom possible for an individual to accurately describe his or her judgment process accurately.

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 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.

This book provides comprehensive coverage of the latest research on multiple criteria research analysis (MCDA) and related areas, gathering a collection of high-quality chapters prepared by leading scholars in the field. By covering the established streams in MCDA research and simultaneously exploring new and emerging areas of application, it offers a unique reference resource for the future development of MCDA. The book approaches MCDA as one of the most active areas in operations research and management science (OR/MS). It presents not only the significant advances achieved to date, but also the new opportunities and challenges arising for both the theory and practice of MCDA. Among many others, the book addresses behavioral and conceptual aspects of decision aiding and decision making, problem structuring issues in the framework of new technological and socio-economic advances, methodological and algorithmic advances for analytical modeling and decision aiding, as well as a number of new application areas in engineering, business, and the social sciences.

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.

This book provides a new point of view on the subject of the management of uncertainty. It covers a wide variety of both theoretical and practical issues involving the analysis and management of uncertainty in the fields of finance, management and marketing. Audience: Researchers and professionals from operations research, management science and economics.

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.

The book discusses a new approach to the classification problem following the decision support orientation of multicriteria decision aid. The book reviews the existing research on the development of classification methods, investigating the corresponding model development procedures, and providing a thorough analysis of their performance both in experimental situations and real-world problems from the field of finance.
Audience: Researchers and professionals working in management science, decision analysis, operations research, financial/banking analysis, economics, statistics, computer science, as well as graduate students in management science and operations research.

Other publications that exist on this topic, are mainly focused on the general aspects and methodologies of the field and do not refer extensively to bank ALM. On the other hand the existing books on goal programming techniques do not involve the ALM problem and more specifically the bank ALM one. Therefore, there is a lack in the existing literature of a comprehensive text book that combines both the concepts of bank ALM and goal programming techniques and illustrates the contribution of goal programming techniques to bank ALM. This is the major contributing feature of this book and its distinguishing characteristic as opposed to the existing literature.

This volume would be suitable for academics and practitioners in operations research, management scientists, financial managers, bank managers, economists and risk analysts. The book can also be used as a textbook for graduate courses of asset liability management, financial risk management and banking risks.