This book presents a comprehensive overview of enterprise architecture management with a specific focus on the business aspects. While recent approaches to enterprise architecture management have dealt mainly with aspects of information technology, this book covers all areas of business architecture from business motivation and models to business execution. The book provides examples of how architectural thinking can be applied in these areas, thus combining different perspectives into a consistent whole. In-depth experiences from end-user organizations help readers to understand the abstract concepts of business architecture management and to form blueprints for their own professional approach. Business architecture professionals, researchers, and others working in the field of strategic business management will benefit from this comprehensive volume and its hands-on examples of successful business architecture management practices.

This book presents intellectual, innovative, information technologies (I3-technologies) based on logical and probabilistic (LP) risk models. The technologies presented here consider such models for structurally complex systems and processes with logical links and with random events in economics and technology.
The volumedescribes the following components of risk management technologies: LP-calculus; classes of LP-models of risk and efficiency; procedures for different classes; special software for different classes; examples of applications; methods for the estimation of probabilities of events based on expert information.Also described area variety of training courses in these topics.
The classes of risk models treated here are: LP-modeling, LP-classification, LP-efficiency, and LP-forecasting. Particular attention is paid to LP-models of risk of failure to resolve difficult economic and technical problems. Amongst the discussed procedures of I3-technologies are the construction of LP-models, LP-identification of risk models; LP-risk analysis, LP-management and LP-forecasting of risk.
The book furtherconsiders LP-models of risk of invalidity of systems and processes in accordance with the requirements of ISO 9001-2008, LP-models of bank operational risks in accordance with the requirements of Basel-2, complex risk LP-models for preventing ammunition depot explosions, enterprise electric power supply systems, debugging tests of technical systems, etc. The book also considers LP-models of credit risks, securities portfolios, operational risks in banking, conteraction of bribes and corruption, etc.

A number of applications is given to show the effectiveness of risk management technologies. In addition, topics of lectures and practical computer exercises intended for a two-semester course Risk management technologies are suggested."

In a world moving towards services, driving service productivity is a central challenge for leaders and members of all types of organisations: for service businesses there is a clear need to be "productive", but it is far less clear what this exactly means. In this book, we invite you on a journey that explores the ways, tools and options for driving service productivity. We take an innovator's perspectives and look at the tricky challenge of service productivity as a landscape of options for designing the future of services. Case examples, from the airport, hotel, healthcare, and professional service industry, offer insights in the methods used and approaches taken in business practice. Research results provide food for thought and valuable advice on the path towards superior service productivity. Throughout the book we also listen to the views and advices of interviewed experts from academia as well as business practice on how to drive service productivity. A forecast on how service productivity and service innovation might evolve in the future provides us - and hopefully you as a reader - with the necessary food for thought to develop our own understanding of driving service productivity in different business settings. Overall, this book is not a traditional "academic product" that summarises the views of a few, but a co-created offering that profited enormously from the contributions of so many.

Economies around the globe have evolved into being largely service-oriented economies. Consumers no longer just want a printer or a car, they rather ask for a printing service or a mobility service. In addition, service-oriented organizations increasingly exploit new devices, technologies and infrastructures. Agility is the ability to deal with such changing requirements and environments. Agile ways of working embrace change as a positive force and harness it to the organization's competitive advantage. The approach described in this book focuses on the notion of a service as a piece of functionality that offers value to its customers. Instead of solely looking at agility in the context of system or software development, agility is approached in a broader context. The authors illustrate three kinds of agility that can be found in an agile enterprise: business, process and system agility. These three types of agility reinforce each other and establish the foundation for the agile enterprise. Architecture, patterns, models, and all of the best practices in system development contribute to agile service development and building agile applications. This book addresses two audiences. On the one hand, it aims at agile and architecture practitioners who are looking for more agile ways of working in designing and building business services or who are interested in extending and improving their agile methods by using models and model-based architectures. On the other hand, it addresses students of (enterprise) architecture and software development or service science courses, both in computer science and in business administration.

This book sheds new light on the current and future challenges faced by cities, and presents approaches, options and solutions enabled by Information and Communication Technologies (ICT) in the smart city context. By focusing on sustainability objectives within a rapidly changing social, economic, environmental and technological setting, it explores a variety of planning challenges faced by contemporary cities and the power of smart city developments in terms of providing innovative tools, approaches, methodologies and technologies to help cities cope with these challenges. Key issues addressed include smart city (e-) planning and (e-)participation; smart data management to facilitate decision-making processes in cities and insular communities on a variety of topics; smart and sustainable management aspects of climate change, water scarcity, mobility, energy, infrastructure, tourism, blue growth, risk assessment; etc. The book presents current and potential pathways and applications for the evolution of smart cities and communities, taking into consideration the unique problems and opportunities emanating from their specific geographical location. The case study examples mainly concern small and medium-sized cities and communities as well as insular areas in the Mediterranean region, while also incorporating lessons learned from other parts of the world. Their focus is on the specific opportunities and threats emerging in these urban and insular environments, which are characterized by their role as globally known tourist destinations, their coastal or port character, and unique cultural resources, as well as the high rated vulnerability in very many sustainability respects (social, economic, biodiversity, urbanization, migration, poverty, etc.) to be found in the Mediterranean region at large

The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data's immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.

This book grows from a conference on the state of the art and recent advances in Efficiency and Productivity. Papers were commissioned from leading researchers in the field, and include eight explorations into the analytical foundations of efficiency and productivity analysis. Chapters on modeling advances include reverse directional distance function, a new method for estimating technological production possibilities, a new distance function called a loss distance function, an analysis of productivity and price recovery indices, the relation of technical efficiency measures to productivity measures, the implications for benchmarking and target setting of imposing weight restrictions on DEA models, weight restrictions in a regulatory setting, and the Principle of Least Action. Chapters on empirical applications include a study of innovative firms that use innovation inputs to produce innovation outputs, a study of the impact of potential "coopetition" or cooperation among competitors on the financial performance of European automobile plants, using SFA to estimate the eco-efficiency of dairy farms in Spain, a DEA bankruptcy prediction model, a combined stochastic cost frontier analysis model/mixture hazard model, the evolution of energy intensity in nine Spanish manufacturing industries, and the productivity of US farmers as they age.

Blockchain and other trustless systems have gone from being relatively obscure technologies, which were only known to a small community of computer scientists and cryptologists, to mainstream phenomena that are now considered powerful game changers for many industries. This book explores and assesses real-world use cases and case studies on blockchain and related technologies. The studies describe the respective applications and address how these technologies have been deployed, the rationale behind their application, and finally, their outcomes. The book shares a wealth of experiences and lessons learned regarding financial markets, energy, SCM, healthcare, law and compliance. Given its scope, it is chiefly intended for academics and practitioners who want to learn more about blockchain applications.

With the quantity and quality of available works in Information Systems (IS) research, it would seem advantageous to possess a concise list of exemplary works on IS research, in order to enable instructors of IS research courses to better prepare students to publish in IS venues. To that end, The Handbook of Information Systems Research provides a collection of works on a variety of topics related to IS research. This book provides a fresh perspective on issues related to IS research by providing chapters from world-renowned leaders in IS research along with chapters from relative newcomers who bring some interesting and often new perspectives to IS research. This book should serve as an excellent text for a graduate course on IS research methods.

This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featuring chapters which discuss effective and efficient approaches in dealing with the inherent complexity and increasing demands in data science, a variety of application domains are covered. Various case studies by data management and analysis experts are presented in these chapters. Covered applications include banking, social networks, bioinformatics, healthcare, transportation and criminology. Highlighting the Importance of Big Data Management and Analysis for Various Applications will provide the reader with an understanding of how data management and analysis are adapted to these applications. This book will appeal to researchers and professionals in the field.

This book investigates the impact of production input factors on the market, consumer and producer energy demand characteristics in 30 industrial sectors for South Korea over the period 1980-2009, and for Japan over the period 1973-2006, with special emphasis placed on the effects of ICT investment on the demand for energy. A dynamic factor demand model is developed, accounting for the adjustment costs that are defined in terms of forgone output from current production. It addresses four key aspects of production and energy demand in manufacturing: first, it establishes the various relationships between different factors of production. Second, it investigates whether the energy demand in the industrial sectors in South Korea would be decreased or increased by substituting/complementing with other input factors such as ICT capital and labor. Third, it looks at sources of growth in the industrial sectors through decomposing the Divisia index based total factor productivity (TFP). Finally it provides appropriate policy recommendations based on these findings. The results of this study may provide industrial sectors' stakeholders and environmental and industrial policy makers with a flexible model that has the capacity to assess outcomes of various policies under certain scenarios. The factor demand methodology described in this book is very advanced and up-to-date. It can be used when teaching advanced graduate courses and in empirically advanced research. Therefore, it is highly relevant in both teaching as a main or supplementary text and in particular as a reference handbook in conducting empirical research. The focus on ICT effects on energy use makes this book an important addition to the existing literature on industrial development.

An ontology is a formal description of concepts and relationships that can exist for a community of human and/or machine agents. The notion of ontologies is crucial for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies considering ontology languages, ontology engineering methods, example ontologies, infrastructures and technologies for ontologies, and how to bring this all into ontology-based infrastructures and applications that are among the best of their kind. The field of ontologies has tremendously developed and grown in the five years since the first edition of the "Handbook on Ontologies." Therefore, its revision includes 21 completely new chapters as well as a major re-working of 15 chapters transferred to this second edition.

This book deals with the issues of modelling management processes of information technology and IT projects while its core is the model of information technology management and its component models (contextual, local) describing initial processing and the maturity capsule as well as a decision-making system represented by a multi-level sequential model of IT technology selection, which acquires a fuzzy rule-based implementation in this work.

In terms of applicability, this work may also be useful for diagnosing applicability of IT standards in evaluation of IT organizations. The results of this diagnosis might prove valid for those preparing new standards so that apart from their own visions they could, to an even greater extent, take into account the capabilities and needs of the leaders of project and manufacturing teams.

The book is intended for IT professionals using the ITIL, COBIT and TOGAF standards in their work. Students of computer science and management who are interested in the issue of IT project and technology management are also likely to benefit from this study. For young students of IT, it can serve as a source of knowledge in the field of information technology evaluation. This book is also designed for specialists in modelling socio-technical systems.

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This book contains the refereed proceedings of the 2nd Advances in Business Research International Conference (ABRIC2016). Chapters in the book address the theme of Advancing Knowledge, Connecting the World, reflecting on the emerging issues in various business management fields and the interconnections of multiple disciplines for creating knowledge advancement. Papers were carefully reviewed and selected and grouped into four main themes: economic and finance, marketing and communications, management, and information technology in business. The book serves as a helpful resource for students and researchers of business management, especially in understanding issues and cases of business in emerging economies and markets.

The Easy Introduction to Machine Learning (Ml) for Nontechnical People--In Business and Beyond Artificial Intelligence for Business is your plain-English guide to Artificial Intelligence (AI) and Machine Learning (ML): how they work, what they can and cannot do, and how to start profiting from them. Writing for nontechnical executives and professionals, Doug Rose demystifies AI/ML technology with intuitive analogies and explanations honed through years of teaching and consulting. Rose explains everything from early "expert systems" to advanced deep learning networks. First, Rose explains how AI and ML emerged, exploring pivotal early ideas that continue to influence the field. Next, he deepens your understanding of key ML concepts, showing how machines can create strategies and learn from mistakes. Then, Rose introduces current powerful neural networks: systems inspired by the structure and function of the human brain. He concludes by introducing leading AI applications, from automated customer interactions to event prediction. Throughout, Rose stays focused on business: applying these technologies to leverage new opportunities and solve real problems. Compare the ways a machine can learn, and explore current leading ML algorithms Start with the right problems, and avoid common AI/ML project mistakes Use neural networks to automate decision-making and identify unexpected patterns Help neural networks learn more quickly and effectively Harness AI chatbots, virtual assistants, virtual agents, and conversational AI applications

This book on Infectious Disease Informatics (IDI) and biosurveillance is intended to provide an integrated view of the current state of the art, identify technical and policy challenges and opportunities, and promote cross-disciplinary research that takes advantage of novel methodology and what we have learned from innovative applications. This book also fills a systemic gap in the literature by emphasizing informatics driven perspectives (e.g., information system design, data standards, computational aspects of biosurveillance algorithms, and system evaluation). Finally, this book attempts to reach policy makers and practitioners through the clear and effective communication of recent research findings in the context of case studies in IDI and biosurveillance, providing "hands-on" in-depth opportunities to practitioners to increase their understanding of value, applicability, and limitations of technical solutions. This book collects the state of the art research and modern perspectives of distinguished individuals and research groups on cutting-edge IDI technical and policy research and its application in biosurveillance. The contributed chapters are grouped into three units. Unit I provides an overview of recent biosurveillance research while highlighting the relevant legal and policy structures in the context of IDI and biosurveillance ongoing activities. It also identifies IDI data sources while addressing information collection, sharing, and dissemination issues as well as ethical considerations. Unit II contains survey chapters on the types of surveillance methods used to analyze IDI data in the context of public health and bioterrorism. Specific computational techniques covered include: text mining, time series analysis, multiple data streams methods, ensembles of surveillance methods, spatial analysis and visualization, social network analysis, and agent-based simulation. Unit III examines IT and decision support for public health event response and bio-defense. Practical lessons learned in developing public health and biosurveillance systems, technology adoption, and syndromic surveillance for large events are discussed. The goal of this book is to provide an understandable interdisciplinary IDI and biosurveillance reference either used as a standalone textbook or reference for students, researchers, and practitioners in public health, veterinary medicine, biostatistics, information systems, computer science, and public administration and policy.

"Socio-Technical Knowledge Management: Studies and Initiatives" connects knowledge management theory to knowledge management practice, allowing the empirical research presented to resolve challenges. It portrays knowledge management issues approached in a holistic and systematic manner which provides a better understanding of the benefits and limitations of various socio-technical knowledge management initiatives.

Healthcare Informatics: Improving Efficiency and Productivity examines the complexities involved in managing resources in our healthcare system and explains how management theory and informatics applications can increase efficiencies in various functional areas of healthcare services. Delving into data and project management and advanced analytics, this book details and provides supporting evidence for the strategic concepts that are critical to achieving successful healthcare information technology (HIT), information management, and electronic health record (EHR) applications. This includes the vital importance of involving nursing staff in rollouts, engaging physicians early in any process, and developing a more receptive organizational culture to digital information and systems adoption. We owe it to ourselves and future generations to do all we can to make our healthcare systems work smarter, be more effective, and reach more people. The power to know is at our fingertips; we need only embrace it. -From the foreword by James H. Goodnight, PhD, CEO, SAS Bridging the gap from theory to practice, it discusses actual informatics applications that have been incorporated by various healthcare organizations and the corresponding management strategies that led to their successful employment. Offering a wealth of detail, it details several working projects, including: A computer physician order entry (CPOE) system project at a North Carolina hospital E-commerce self-service patient check-in at a New Jersey hospital The informatics project that turned a healthcare system's paper-based resources into digital assets Projects at one hospital that helped reduce excesses in length of stay, improved patient safety; and improved efficiency with an ADE alert system A healthcare system's use of algorithms to identify patients at risk for hepatitis Offering the guidance that healthcare specialists need to make use of various informatics platforms, this book provides the motivation and the proven methods that can be adapted and applied to any number of staff, patient, or regulatory concerns.

This book examines current topics and trends in strategic auditing, accounting and finance in digital transformation both from a theoretical and practical perspective. It covers areas such as internal control, corporate governance, enterprise risk management, sustainability and competition. The contributors of this volume emphasize how strategic approaches in this area help companies in achieving targets. The contributions illustrate how by providing good governance, reliable financial reporting, and accountability, businesses can win a competitive advantage. It further discusses how new technological developments like artificial intelligence (AI), cybersystems, network technologies, financial mobility and smart applications, will shape the future of accounting and auditing for firms.

This book analyzes the effects of the latest technological advances in blockchain and artificial intelligence (AI) on business operations and strategies. Adopting an interdisciplinary approach, the contributions examine new developments that change the rules of traditional management. The chapters focus mainly on blockchain technologies and digital business in the "Industry 4.0" context, covering such topics as accounting, digitalization and use of AI in business operations and cybercrime. Intended for academics, blockchain experts, students and practitioners, the book helps business strategists design a path for future opportunities.

'New Technologies in Hospital Information Systems' is launched by the European Telematics Applications Project 'Healthcare Advanced Networked System Architecture' (HANSA) with support of the GMDS WG Hospital Information Systems and the GMDS FA Medical Informatics. It contains 28 high quality papers dealing with architectural concepts, models and developments for hospital information systems. The book has been organized in seven sections: Reference Architectures, Modelling and Applications, The Distributed Healthcare Environment, Intranet Solutions, Object Orientation, Networked Solutions and Standards and Applications. The HANSA project is based upon the European Pre-standard for Healthcare Information System Architecture which has been drawn up by CEN/TC 251 PT01-13. The editors felt that this standard will have a major impact on future developments for hospital information systems. Therefore the standard is completely included as an appendix.

Software and systems quality is playing an increasingly important role in the growth of almost all profit and non-profit organisations. Quality is vital to the success of enterprises in their markets. Most small trade and repair businesses use software systems in their administration and marketing processes. Every doctor's surgery is managing its patients using software. Banking is no longer conceivable without software. Aircraft, trucks and cars use more and more software to handle their increasingly complex technical systems. Innovation, competition and cost pressure are always present in on-going business decisions. The question facing all these organisations is how to achieve the right quality of their software-based systems and products; how to get the required level of quality, a level that the market will reward, a level that mitigates the organisation's risks and a level that the organisation is willing to pay for. Although a number of good practices are in place, there is still room for huge improvements. Thus, let us take a look into the two worlds of "Embedded systems" and "ICT systems" and let us learn from both worlds, from overlaps and individual solutions. The next step for industrialisation in the software industry is required now. Hence, three pillars will be focused in this book: (1) a fundamental notion of right software and systems quality (RiSSQ); (2) portfolio management, quality governance, quality management, and quality engineering as holistic approach over the three layers of an enterprise, i.e. strategic, tactical, and operational layer; and (3) an industrialisation framework for implementing our approach.

This book provides specialists and executives with a clear, yet practical set of recommendations to meet the challenges of digital transformation and ensure long-term success as a leader in a primarily digital business world. The authors describe the fundamental principles of digitization and its economic opportunities and risks, integrating them into a framework of classic and new management methods. The book also explores how increasing digitization - not only of communication, but of complete value chains - has led to a need to establish a digital business leadership. Digitization is changing people and markets: it causes the upheaval of entire industries, creates new digital-centric companies, and forces established companies to cope with the transformation activities associated with these digitization processes. New approaches and methods have to be learned, tried and tested patterns of thinking have to be explored, and last but not least, innovation activities have to be understood as continuous necessities. At the same time, digital business offers considerable opportunities for renewing competitive advantages, improving existing process structures and realigning products, services and business models.

This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of: 1. statistical, econometric, and machine learning techniques; 2. data handling capabilities; 3. at least one programming language. Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.

IT education, particularly at business colleges, is undergoing a transformation because of the emerging federated systems or enterprise-wide systems (ES). This follows a trend in industry, which uses complex software applications like SAP and others. This movement toward ES in industry has created major challenges for integrating ES into the classroom. ""Enterprise Systems Education in the 21st Century"" presents methods of reengineering business curricula in order to use ES solutions. It also helps ES vendors understand the higher education environment so they can support college and university programs. ""Enterprise Systems Education in the 21st Century"" acts as a platform for both educators and vendors to present solutions and experiences gained from the challenges of integrating ES into the business classroom.