This book describes five qualitative investment decision-making methods based on the hesitant fuzzy information. They are: (1) the investment decision-making method based on the asymmetric hesitant fuzzy sigmoid preference relations, (2) the investment decision-making method based on the hesitant fuzzy trade-off and portfolio selection, (3) the investment decision-making method based on the hesitant fuzzy preference envelopment analysis, (4) the investment decision-making method based on the hesitant fuzzy peer-evaluation and strategy fusion, and (5) the investment decision-making method based on the EHVaR measurement and tail analysis.

This book describes five qualitative investment decision-making methods based on the hesitant fuzzy information. They are: (1) the investment decision-making method based on the asymmetric hesitant fuzzy sigmoid preference relations, (2) the investment decision-making method based on the hesitant fuzzy trade-off and portfolio selection, (3) the investment decision-making method based on the hesitant fuzzy preference envelopment analysis, (4) the investment decision-making method based on the hesitant fuzzy peer-evaluation and strategy fusion, and (5) the investment decision-making method based on the EHVaR measurement and tail analysis.

This book aims to justify the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making context. It also discusses the development of the TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) with related examples and MATLAB codes. This is the first book devoted to TOPSIS and its fuzzy versions. It presents the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making content and discusses the development of the TOPSIS method in classical and fuzzy context. The book justifies the use of fuzzy logic as an uncertainty theory and provides illustrative examples for each fuzzy TOPSIS extension, along with related MATLAB codes and case studies. This book is for industrial engineers, operations research engineers, systems engineers, and production engineers working in the areas of decision analysis, multi-criteria decision making, and multiple objective optimization.

This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph.D. students in various disciplines, as well as practitioners and researchers.

FINTECH and CRYPTOCURRENCY Dive into the world of fintech and cryptocurrency through the engaging perspectives of this diverse group of authors and uncover the intricate connections between technology, finance, and cryptocurrency that make this a must-have for anyone intrigued by the future of digital society. Digital currencies, decentralization of money, and the growth of new technologies like blockchain, the Internet of Things, and machine learning have produced new opportunities and difficulties for banking and finance, as well as users of these services in electronic commerce. New banking and finance technologies may improve operational efficiency, risk management, compliance, and client pleasure, but they can decrease barriers and introduce new concerns, such as cybersecurity risk. Cryptocurrencies with smart contracts for payments and trading, as well as AI systems with adaptive algorithms that allow picture and speech recognition, expert judgement, group categorization, and forecasting in a variety of fields, are instances of increased automation. Simultaneously, the potentials pose risks and raise regulatory concerns. The rise of blockchain technology and its widespread use have had a significant impact on the operation and management of digital systems. At the same time, researchers and practitioners have paid close attention to digital finance. Blockchain’s first applications were limited to the production of digital currency, but it has now been expanded to include financial and commercial applications. Innovative digital finance has had a huge impact on business and society since it has been extensively adopted by businesses and consumers. As a result, the goal of this edited book is to expand and deepen our knowledge of the business possibilities of novel blockchain and digital financial applications.

Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business and engineering processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to business information management in various current real-world problems by proposing crisp or uncertain multiple-criteria decision-making (MCDM) models and techniques, mostly including multi-attribute decision-making (MADM) approaches, in addition to a single paper proposing an interactive multi-objective decision-making (MODM) approach. Particular attention is devoted to information aggregation operators—65% of papers dealt with this item. The topics of this Special Issue gained attention in Europe and Asia. A total of 48 authors from seven countries contributed to this Issue. The papers are mainly concentrated in three application areas: supplier selection and rational order allocation, the evaluation and selection of goods or facilities, and personnel selection/partner selection. A number of new approaches are proposed that are expected to attract great interest from the research community.

This work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more. Each of the 22 chapters includes practical applications along with new developments/results. This book may be used as a textbook in graduate operations research, industrial engineering, and economics courses. It will also be an excellent resource, providing new suggestions and directions for further research, for computer programmers, mathematicians, and scientists in a variety of disciplines where multicriteria decision making is needed.