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 provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists' preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice

This book presents the first broad reflection on the challenges, opportunities, and implications of Artificial Intelligence (AI) in the Gulf Cooperation Council (GCC). Unique results and insights are derived through case studies from diverse disciplines, including engineering, economics, data science, policy-making, governance, and humanscience. Particularly related to these 'softer' disciplines, we make some unexplored yet topical contributions to the literature, with a focus on the GCC (but by no means limited to it), including AI and implications for women, Islamic schools of thought on AI, and the power of AI to help deliver wellbeing and happiness in cities and urban spaces. Finally, the readers are provided with a synthesis of ideas, lessons learned, and a path forward based on the diverse content of the chapters. The book caters to the educated non specialist with interest in AI, targeting a wide audience including professionals, academics, government officials, policymakers, entrepreneurs, and non-governmental organizations.

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."

Design Science Research is a powerful paradigm enabling researchers to make important contributions to society and industry. Simply stated, the goal of DSR is to generate knowledge on how to find innovative solutions to important problems in the form of models, methods, constructs and instantiations. Over the past 20 years, the design science research (DSR) paradigm has developed into an established paradigm in Information Systems Research and it is of strong uptake in many other disciplines, including Management Science and Computer Science. This book provides a collection of twelve DSR cases, presented by experienced researchers in the field. It offers readers access to real-world DSR studies, together with the authors' reflections on their research processes. These cases will support researchers who want to engage in DSR, and represent a valuable addition to existing introductions to DSR methods and processes. Readers will learn from the hands-on experiences of respected experts who have conducted extensive DSR in a range of application contexts.

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 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.

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.

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.

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

Accounting Information Systems (AISs) delivers unprecedented coverage of these types of financial systems. The text examines how developments in IT affect business processes and controls, the effect of recent regulatory developments on the design and operation of AISs, and how you can use AISs to add value to an organization.

The 16th Edition covers important new IT developments in AIS, such as robotic process automation, blockchain and data analytics. Not only will you see how AIS has changed the role of an accountant, but you'll also be prepared for a successful accounting career in public practice, industry or government.

Appropriate for one or two term courses in introductory Business Statistics. With Statistics for Management, Levin and Rubin have provided a non-intimidating business statistics textbook that students can easily read and understand. Like its predecessors, the Seventh Edition includes the absolute minimum of mathematical/statistical notation necessary to teach the material. Concepts are fully explained in simple, easy-to-understand language as they are presented, making the text an excellent source from which to learn and teach. After each discussion, readers are guided through real-world examples to show how textbook principles work in professional practice.

This open access book contributes to the creation of a cyber ecosystem supported by blockchain technology in which technology and people can coexist in harmony. Blockchains have shown that trusted records, or ledgers, of permanent data can be stored on the Internet in a decentralized manner. The decentralization of the recording process is expected to significantly economize the cost of transactions. Creating a ledger on data, a blockchain makes it possible to designate the owner of each piece of data, to trade data pieces, and to market them. This book examines the formation of markets for various types of data from the theory of market quality proposed and developed by M. Yano. Blockchains are expected to give data itself the status of a new production factor. Bringing ownership of data to the hands of data producers, blockchains can reduce the possibility of information leakage, enhance the sharing and use of IoT data, and prevent data monopoly and misuse. The industry will have a bright future as soon as better technology is developed and when a healthy infrastructure is created to support the blockchain market.

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.

Shedding new light on the human side of big data through the lenses of emotional and social intelligence competencies, this book advances the understanding of the requirements of the different professions that deal with big data. It also illustrates the empirical evidence collected through the application of the competency-based methodology to a sample of data scientists and data analysts, the two most in-demand big data jobs in the labor market. The book provides recommendations for the higher education system to offer better designed curricula for entry-level big data professions. It also offers managerial insights in describing how organizations and specifically HR practitioners can benefit from the competency-based approach to overcome the skill shortage that characterizes the demand for big data professional roles and to increase the effectiveness of the selection and recruiting processes.

For graduate and undergraduate courses in IT management and IT strategy. The authors utilize their years of working with companies on IT management / strategy to provide students with a practical look at the evolution of IT in business.

This book focusses on various options of taking up ventures for starting entrepreneurship in small/large scale in the field of renewable energy technologies. The book covers the fundamentals of entrepreneurship, renewable energy resources, their technologies involved and applications along with financial evaluations. The book will cater to the needs of students, researchers, various stakeholders, entrepreneurs etc. by providing valuable information on renewable energy technologies and their applications in developing entrepreneurship and establishing enterprise at individual level, specifically focusing on low carbon technology for sustenance of environment which is becoming increasingly important.

* International approach, with examples and cases from the US, Europe and Africa * Each chapter contains objectives, case studies, discussion questions and further reading suggestions. * PPT slides and data sets available as digital supplements

This open access book shows the breadth and various facets of e-Science, while also illustrating their shared core. Changes in scientific work are driven by the shift to grid-based worlds, the use of information and communication systems, and the existential infrastructure, which includes global collaboration. In this context, the book addresses emerging issues such as open access, collaboration and virtual communities and highlights the diverse range of developments associated with e-Science. As such, it will be of interest to researchers and scholars in the fields of information technology and knowledge management.