This book discusses understand cybersecurity management in decentralized finance (DeFi). It commences with introducing fundamentals of DeFi and cybersecurity to readers. It emphasizes on the importance of cybersecurity for decentralized finance by illustrating recent cyber breaches, attacks, and financial losses. The book delves into understanding cyber threats and adversaries who can exploit those threats. It advances with cybersecurity threat, vulnerability, and risk management in DeFi. The book helps readers understand cyber threat landscape comprising different threat categories for that can exploit different types of vulnerabilities identified in DeFi. It puts forward prominent threat modelling strategies by focusing on attackers, assets, and software. The book includes the popular blockchains that support DeFi include Ethereum, Binance Smart Chain, Solana, Cardano, Avalanche, Polygon, among others. With so much monetary value associated with all these technologies, the perpetrators are always lured to breach security by exploiting the vulnerabilities that exist in these technologies. For simplicity and clarity, all vulnerabilities are classified into different categories: arithmetic bugs, re-Entrancy attack, race conditions, exception handling, using a weak random generator, timestamp dependency, transaction-ordering dependence and front running, vulnerable libraries, wrong initial assumptions, denial of service, flash loan attacks, and vampire Since decentralized finance infrastructures are the worst affected by cyber-attacks, it is imperative to understand various security issues in different components of DeFi infrastructures and proposes measures to secure all components of DeFi infrastructures. It brings the detailed cybersecurity policies and strategies that can be used to secure financial institutions. Finally, the book provides recommendations to secure DeFi infrastructures from cyber-attacks.

Inquiring Organizations: Moving from Knowledge Management to Wisdom' assembles into one volume a comprehensive collection of the key current thinking regarding the use of C. West Churchman's Design of Inquiring Systems as a basis for computer-based inquiring systems design and implementation. Inquiring systems are systems that go beyond knowledge management to actively inquire about their environment. While self-adaptive is an appropriate adjective for inquiring systems, they are critically different from self-adapting systems as they have evolved in the fields of computer science or artificial intelligence. Inquiring systems draw on epistemology to guide knowledge creation and organizational learning. As such, we can for the first time ever, begin to entertain the notion of support for wise"" decision-making. Readers of ""Inquiring Organizations: Moving from Knowledge Management to Wisdom"" will gain an appreciation for the role that epistemology can play in the design of the next generation of knowledge management systems, systems that focus on supporting wise decision-making processes.

The overall mission of this book is to provide a comprehensive understanding and coverage of the various theories and models used in IS research. Specifically, it aims to focus on the following key objectives: To describe the various theories and models applicable to studying IS/IT management issues. To outline and describe, for each of the various theories and models, independent and dependent constructs, reference discipline/originating area, originating author(s), seminal articles, level of analysis (i.e. firm, individual, industry) and links with other theories. To provide a critical review/meta-analysis of IS/IT management articles that have used a particular theory/model.To discuss how a theory can be used to better understand how information systems can be effectively deployed in today's digital world.

This book contributes to our understanding of a number of theories and models. The theoretical contribution of this book is that it analyzes and synthesizes the relevant literature in order to enhance knowledge of IS theories and models from various perspectives. To cater to the information needs of a diverse spectrum of readers, this book is structured into two volumes, with each volume further broken down into two sections.

The first section of Volume 1 presents detailed descriptions of a set of theories centered around the IS lifecycle, including the Success Model, Technology Acceptance Model, User Resistance Theories, and four others. The second section of Volume 1 contains strategic and economic theories, including a Resource-Based View, Theory of Slack Resources, Portfolio Theory, Discrepancy Theory Models, and eleven others.

The first section of Volume 2 concerns socio-psychological theories. These include Personal Construct Theory, Psychological Ownership, Transactive Memory, Language-Action Approach, and nine others. The second section of Volume 2 deals with methodological theories, including Critical Realism, Grounded Theory, Narrative Inquiry, Work System Method, and four others.

Together, these theories provide a rich tapestry of knowledge around the use of theory in IS research. Since most of these theories are from contributing disciplines, they provide a window into the world of external thought leadership."

This book presents high-quality papers from the Third International Conference on Smart Computing and Informatics (SCI 2018 19), organized by the School of Computer Engineering and School of Computer Application, Kalinga Institute of Industrial Technology Deemed to be University, Bhubaneswar, from 21 to 22 December 2018. It includes advanced and multi-disciplinary research on the design of smart computing and informatics, focusing on innovation paradigms in system knowledge, intelligence and sustainability that have the potential to provide realistic solutions to various problems in society, the environment and industry. The papers featured provide a valuable contribution to the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in varied disciplines of science, technology and health care.

Management of supply chains has been evolving rapidly over the last few years due to the inception of Industry 4.0, where businesses adopt automation technologies and data exchanges leading to dynamic and interconnected supply chain systems. Emphasizing on analytical approaches such as predictive and prescriptive modeling, this book presents state-of-the-art original research work dealing with advanced analytical models for the design, planning, and operation of the supply chain to provide faster and smarter decisions in the era of digitization. In particular, the book integrates machine learning and operations research models for faster and smarter decisions, presents prescriptive analytics models for strategic, tactical, and operational decision making in the supply chain, and addresses recent challenges such as sustainability in the supply chain, supply chain visibility, and supply chain digitalization. Key concepts are illustrated using real-life case studies, making the book a valuable reference for researchers, technical professionals, and students.

The overall mission of this book is to provide a comprehensive understanding and coverage of the various theories and models used in IS research. Specifically, it aims to focus on the following key objectives: To describe the various theories and models applicable to studying IS/IT management issues. To outline and describe, for each of the various theories and models, independent and dependent constructs, reference discipline/originating area, originating author(s), seminal articles, level of analysis (i.e. firm, individual, industry) and links with other theories. To provide a critical review/meta-analysis of IS/IT management articles that have used a particular theory/model.To discuss how a theory can be used to better understand how information systems can be effectively deployed in today's digital world.

This book contributes to our understanding of a number of theories and models. The theoretical contribution of this book is that it analyzes and synthesizes the relevant literature in order to enhance knowledge of IS theories and models from various perspectives. To cater to the information needs of a diverse spectrum of readers, this book is structured into two volumes, with each volume further broken down into two sections.

The first section of Volume 1 presents detailed descriptions of a set of theories centered around the IS lifecycle, including the Success Model, Technology Acceptance Model, User Resistance Theories, and four others. The second section of Volume 1 contains strategic and economic theories, including a Resource-Based View, Theory of Slack Resources, Portfolio Theory, Discrepancy Theory Models, and eleven others.

The first section of Volume 2 concerns socio-psychological theories. These include Personal Construct Theory, Psychological Ownership, Transactive Memory, Language-Action Approach, and nine others. The second section of Volume 2 deals with methodological theories, including Critical Realism, Grounded Theory, Narrative Inquiry, Work System Method, and four others.

Together, these theories provide a rich tapestry of knowledge around the use of theory in IS research. Since most of these theories are from contributing disciplines, they provide a window into the world of external thought leadership."

Foundations of Family Resource Management uses the lenses of consumer science, management, and economics, and beyond to help students make intelligent decisions about resources, time, and energies at the individual and family level. It has a strong interdisciplinary, global, and multicultural focus. This sixth edition brings in new material on millennials, delayed marriage, household composition, neuroscience, behavioral economics, sustainable consumption, technology, and handling crises. It has been updated in line with the latest census data and academic literature. The text contains lots of features to support student learning, including chapter summaries, "Did You Know?" questions, glossary of key terms, examples and cases, critical thinking activities, and review questions for discussion and reflection. Lecture slides and an instructor manual are available as digital supplements. This textbook meets the standards and criteria for the Certified Family Life Educator (CFLE) designation of the National Council on Family Relations (NCFR) and will be suitable for resource management courses in family and consumer science, human ecology, and human environmental science programs.

This book discusses the impact of advanced information technologies, such as data processing, machine learning, and artificial intelligence, on organizational decision-making processes and practices. One of the book's central themes is the interplay between human reasoning and machine logic in the context of organizational functioning, specifically, the fairly common situations in which subjective beliefs are pitted against objective evidence giving rise to conflict rather than enhancing the quality of organizational sensemaking. Aiming to not only raise the awareness of the potential challenges but also to offer solutions, the book delineates and discusses the core impediments to effective human-information technology interactions, and outlines strategies for overcoming those obstacles on the way to enhancing the efficacy of organizational decision-making.

This book focuses on several issues in the essence of information systems and their development as well as advanced utilization of new information technology. This book includes both theoretical foundations and practical approaches for each topic and should prove useful both to scientists in the field of information system science and to practitioners in information systems development and use. Many of the topics treated here have not appeared in the literature, although they are becoming increasingly important in the development of information systems. Topics covered include: contingencies in IT decision making; intelligent executive information systems; dynamic performance evaluation of information systems; exception handling in information systems, metamethodology of information system development and mobile computing. The outstanding feature of the book is its specific mixture of subjects under one framework of thinking about information systems. The book offers new perspectives on topics which are important today and in the future due to the rapidly changing nature of information systems and information technology. A useful book to researchers and systems developers, the book can also form the basis of an advanced course in information systems development.

Cognition-driven decision support system (DSS) has been recognized as a paradigm in the research and development of business intelligence (BI). Cognitive decision support aims to help managers in their decision making from human cognitive aspects, such as thinking, sensing, understanding and predicting, and fully reuse their experience. Among these cognitive aspects, decision makers situation awareness (SA) and mental models are considered to be two important prerequisites for decision making, particularly in ill-structured and dynamic decision situations with uncertainties, time pressure and high personal stake. In today s business domain, decision making is becoming increasingly complex. To make a successful decision, managers SA about their business environments becomes a critical factor.

This book presents theoretical models as well practical techniques of cognitiondriven DSS. It first introduces some important concepts of cognition orientation in decision making process and some techniques in related research areas including DSS, data warehouse and BI, offering readers a preliminary for moving forward in this book. It then proposes a cognition-driven decision process (CDDP) model which incorporates SA and experience (mental models) as its central components. The goal of the CDDP model is to facilitate cognitive decision support to managers on the basis of BI systems. It also presents relevant techniques developed to support the implementation of the CDDP model in a BI environment. Key issues addressed of a typical business decision cycle in the CDDP model include: natural language interface for a manager s SA input, extraction of SA semantics, construction of data warehouse queries based on the manger s SA and experience, situation information retrieval from data warehouse, how the manager perceives situation information and update SA, how the manager s SA leads to a final decision. Finally, a cognition-driven DSS, FACETS, and two illustrative applications of this system are discussed."

The ultimate textbook in Business Information Systems for future Managers Business Information Systems: Technology, Development and Management for the Modern Business, 6th Edition by Bocij, Greasley, and Hickie is a leading text that will help you understand the relevance and impact of information systems in today's business environment. Written in a language that is easy to follow, this text does not assume any prior knowledge of IS or ICT and is ideal for students attending courses related to Business Information Systems and Management Information Systems at an Undergraduate or Postgraduate level. Starting from basic concepts this book provides a comprehensive and accessible guide to: understanding the technology of Business Information Systems choosing the right Information System for an organisation developing and managing an efficient Business Information System employing information systems strategically to achieve organisational goals Taking a problem-solving approach, this thoroughly revised edition defines new concepts and studies the theory of information systems according to the most recent business and technological advances, covering contemporary key topics such as: Big Data Analytics Cloud Computing Industry 4.0 Internet of Things With new business examples, case studies, and web links fully integrated throughout, this must-have guide will provide you with all the tools you need to understand the opportunities and benefits Information Systems bring to an organisation and successfully run a business.

This volume discusses recent advances in Artificial Intelligence (AI) applications in smart, internet-connected societies, highlighting three key focus areas. The first focus is on intelligent sensing applications. This section details the integration of Wireless Sensing Networks (WSN) and the use of intelligent platforms for WSN applications in urban infrastructures, and discusses AI techniques on hardware and software systems such as machine learning, pattern recognition, expert systems, neural networks, genetic algorithms, and intelligent control in transportation and communications systems. The second focus is on AI-based Internet of Things (IoT) systems, which addresses applications in traffic management, medical health, smart homes and energy. Readers will also learn about how AI can extract useful information from Big Data in IoT systems. The third focus is on crowdsourcing (CS) and computing for smart cities. this section discusses how CS via GPS devices, GIS tools, traffic cameras, smart cards, smart phones and road deceleration devices enables citizens to collect and share data to make cities smart, and how these data can be applied to address urban issues including pollution, traffic congestion, public safety and increased energy consumption. This book will of interest to academics, researchers and students studying AI, cloud computing, IoT and crowdsourcing in urban applications.

This book explores nonparametric statistical process control. It provides an up-to-date overview of nonparametric Shewhart-type univariate control charts, and reviews the recent literature on nonparametric charts, particularly multivariate schemes. Further, it discusses observations tied to the monitored population quantile, focusing on the Shewhart Sign chart. The book also addresses the issue of practically assuming the normality and the independence when a process is statistically monitored, and examines in detail change-point analysis-based distribution-free control charts designed for Phase I applications. Moreover, it introduces six distribution-free EWMA schemes for simultaneously monitoring the location and scale parameters of a univariate continuous process, and establishes two nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules. Lastly, the book proposes novel and effective method for early disease detection.

This book provides a comprehensive and effective exchange of information on current developments in the management of manufacturing systems and Industry 4.0. The book aims to establish channels of communication and disseminate knowledge among professionals working in manufacturing and related institutions. In the book, researchers, academicians and practitioners in relevant fields share their knowledge from the sectors of management of manufacturing systems. The chapters were selected from several conferences in the field, with the topics including management of manufacturing systems with support for Industry 4.0, logistics and intelligent manufacturing systems and applications, cooperation management, and its effective applications. The book also includes case studies in logistics, RFID applications, and economic impacts in logistics, ICT support for industry 4.0, industrial and smart logistics, intelligent manufacturing systems and applications

This volume presents techniques and theories drawn from mathematics, statistics, computer science, and information science to analyze problems in business, economics, finance, insurance, and related fields. The authors present proposals for solutions to common problems in related fields. To this end, they are showing the use of mathematical, statistical, and actuarial modeling, and concepts from data science to construct and apply appropriate models with real-life data, and employ the design and implementation of computer algorithms to evaluate decision-making processes. This book is unique as it associates data science - data-scientists coming from different backgrounds - with some basic and advanced concepts and tools used in econometrics, operational research, and actuarial sciences. It, therefore, is a must-read for scholars, students, and practitioners interested in a better understanding of the techniques and theories of these fields.

This book develops insights of digitalization and the future of financial services to originate an innovative approach to financial field, in order to underpin research and practice in the wide area of digital finance. The aim of this book is to extend our understandings on how digitalization and the future of financial services can be helpful in different business circumstances in many cross-functional financial areas, such as financial markets, financial risk management, financial technologies, investment finance, etc. Thus, the book aims at addressing the relevance of digital finance for different players, highlighting differences in tools and processes as well as identifying innovative practices in financial digitalization. This can result in some novel theoretical and practical insights that can foster financial players, in order to proactively explore and exploit opportunities in financial digitalization and offset financial risks and increase efficiency.

There are many definitions of eHealth and no consensus around the underlying idea. Most contributions on eHealth focus on informatic, public health, legal, social and anthropological implications. This book investigates eHealth through community-based private practices such as pharmacies, hearing centres, opticians, and private medical centres from a management perspective. It first presents a systematic review of the theoretical research models that have been developed on eHealth. It then identifies the many innovative managerial implications of eHealth, and finally, it analyses reasons why some eHealth tools are or are not adopted.

We are living in the middle of a Fourth Industrial Revolution, with new technology leading to dramatic shifts in everything from manufacturing to supply chain logistics. In a lively, developing field of academic, procurement is often neglected. Despite this, procurement plays a vital role, connecting the organization with its ecosystem. At a time of change and economic crisis, a new business model is called for, which this book aims to define. Based on the applications of Industry 4.0 concepts to procurement, this book describes Procurement 4.0 as a method and a set of tools, helping businesses to improve the value of their products, reduce waste, become more flexible, and address the business needs of the future. It will appeal to academics in the area, as well as practitioners.

This book brings together valuable insights about the impact of the COVID-19 pandemic on the business environment from an Asian perspective. While some businesses in Asia have been swift to embrace the new normal, others have found the disruption to the traditional way of doing business challenging. Businesses are striving to respond, adapt, and thrive under the shadow of the unprecedented upheaval to the business environment that has forced them to rethink their strategies, processes, and operating models. There seems to be a consensus among business scholars and stakeholders that the continuous embrace of change and transformation of business models will assist businesses to sustain a long-term competitive advantage. The chapters in this book explore shifts in business innovation and strategies linked to the "new normal" of doing business during the pandemic, bringing to light issues, challenges, and opportunities that firms can expect to face in their need to ensure sustainability post-pandemic and beyond.

Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this "old" algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the "dangerous" uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the "2010 National Excellent Doctoral Dissertation Award", the highest honor for not more than 100 PhD theses per year in China.

This book is an outcome of the 34th International Conference EnviroInfo 2020, hosted virtually in Nicosia, Cyprus by the Research Centre on Interactive Media, Smart Systems and Emerging Technologies (RISE). It presents a selection of papers that describe innovative scientific approaches and ongoing research in environmental informatics and the emerging field of environmental sustainability, promoted and facilitated by the use of information and communication technologies (ICT). The respective articles cover a broad range of scientific aspects including advances in core environmental informatics-related technologies such as earth observation, environmental modelling, big data and machine learning, robotics, smart agriculture and food solutions, renewable energy-based solutions, optimization of infrastructures, sustainable industrial processes, and citizen science, as well as applications of ICT solutions intended to support societal transformation processes toward the more sustainable management of resource use, transportation and energy supplies. Given its scope, the book is essential reading for scientists, experts and students in these fields of research. Chapter "Developing a Configuration System for a Simulation Game in the Domain of Urban CO2 Emissions Reduction" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results. Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included. Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website. This practical and systematic textbook/reference is a "need-to-have" tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a "need to use, need to keep" resource following one's exploration of the subject.

Mortgage Backed Securities (MBS) are among the most complex of all financial instruments. Analysis of MBS requires blending empirical analysis of borrower behavior with mathematical modeling of interest rates and home prices. Over the past 25 years, Davidson and Levin have been at the leading edge of MBS valuation and risk analysis. Mortgage Valuation Models: Embedded Options, Risk and Uncertainty is a detailed description of the sophisticated theories and advanced methods that the authors employ in real-world analysis of mortgage backed securities. Issues such as complexity, borrower options, uncertainty, and model risk play a central role in their approach to valuation of MBS. The book describes methods for modeling prepayments and defaults of borrowers. It explores closed form, backward induction and Monte Carlo valuation using the Option-Adjusted-Spread (OAS) approach, explains the origin of OAS and its relationship to model uncertainty. With reference to the classical CAPM and APT, the book advocates extending the concept of risk-neutrality to modeling home prices and borrower options, well beyond interest rates. The coverage spans the range of mortgage products from loans, TBA (to be announced) pass-through securities to subordinate tranches of subprime-mortgage securitizations and describes valuation methods for both agency and non-agency MBS including pricing new loans; Davidson and Levin put forth new approaches to prudent risk measurement, ranking, and decomposition that can help guide traders and risk managers. It reveals quantitative causes of the 2007-09 financial crisis and provides insights into the future of the US housing finance system and mortgage modeling. Despite the advances in mortgage modeling and valuation, this remains an ever-evolving field. Mortgage Valuation Models will serve as a foundation for the future development of models for mortgage-backed securities.

This book covers a broad range of topics related to digitalization. Specifically, it views digitalization across different organizational levels, such as the level of individuals, teams, processes, firms, and ecosystems. It includes a collection of recent research and reflections on the topic that helps to understand the technological foundations of digitalization and its impacts. It also reflects on the process of digitalization and how it changes established ways of working, collaborating, and coordinating. With this book, the editors and authors honor Professor Dr. Armin Heinzl for his enormous and ongoing contributions to information systems research, education, and practice.

The authors offer a revolutionary solution to risk management. It's the unknown risks that keep leaders awake at night-wondering how to prepare for and steer their organization clear from that which they cannot predict. Businesses, governments and regulatory bodies dedicate endless amounts of time and resources to the task of risk management, but every leader knows that the biggest threats will come from some new chain of events or unexpected surprises-none of which will be predicted using conventional wisdom or current risk management technologies and so management will be caught completely off guard when the next crisis hits. By adopting a scientific approach to risk management, we can escape the limited and historical view of experience and statistical based risk management models to expose dynamic complexity risks and prepare for new and never experienced events.