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.

Extensive research conducted by the Hasso Plattner Design Thinking Research Program at Stanford University in Palo Alto, California, USA, and the Hasso Plattner Institute in Potsdam, Germany, has yielded valuable insights on why and how design thinking works. The participating researchers have identified metrics, developed models, and conducted studies, which are featured in this book, and in the previous volumes of this series. This volume provides readers with tools to bridge the gap between research and practice in design thinking with varied real world examples. Several different approaches to design thinking are presented in this volume. Acquired frameworks are leveraged to understand design thinking team dynamics. The contributing authors lead the reader through new approaches and application fields and show that design thinking can tap the potential of digital technologies in a human-centered way. In a final section, new ideas in neurodesign at Stanford University and at Hasso Plattner Institute in Potsdam are elaborated upon thereby challenging the reader to consider newly developed methodologies and provide discussion of how these insights can be applied to various sectors. Special emphasis is placed on understanding the mechanisms underlying design thinking at the individual and team levels. Design thinking can be learned. It has a methodology that can be observed across multiple settings and accordingly, the reader can adopt new frameworks to modify and update existing practice. The research outcomes compiled in this book are intended to inform and provide inspiration for all those seeking to drive innovation - be they experienced design thinkers or newcomers.

'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.

This book addresses the issue of smart and sustainable development in the Mediterranean (MED) region, a distinct part of the world, full of challenges and risks but also opportunities. Above all, the book focuses on smartening up small and medium-sized cities and insular communities, taking into account their geographical peculiarities, the pattern of MED urban settlements and the abundance of island complexes in the MED Basin. Taking for granted that sustainability in the MED is the overarching policy goal that needs to be served, the book explores different aspects of smartness in support of this goal's achievement. In this respect, evidence from concrete smart developments adopted by forerunners in the MED region is collected and analyzed; coupled with experiences gathered from successful, non-MED, examples of smart efforts in European countries. More specifically, current research and empirical results from MED urban environments are discussed, as well as findings from or concerning other parts of the world, which are of relevance to the MED region. The book's primary goal is to enable policymakers, planners and decision-making bodies to recognize the challenges and options available; and make to more informed policy decisions towards smart, sustainable, inclusive and resilient urban and regional futures in the MED.

This book presents selected examples of digitalization in the age of digital change. It is divided into two sections: "Digital Innovation," which features new technologies that stimulate and enable new business opportunities; and "Digital Business Transformation," comprising business and management concepts that employ specific technological solutions for their practical implementation. Combining new insights from research, teaching and management, including digital transformation, e-business, knowledge representation, human-computer interaction, and business optimization, the book highlights the breadth of research as well as its meaningful and relevant transfer into practice. It is intended for academics seeking inspiration, as well as for leaders wanting to tap the potential of the latest trends to take society and their business to the next level.

Bringing together theoretical and empirical studies from the Journal of Information Technology, this book provides a definitive guide to research discovered on the growing global sourcing phenomenon. Paying particular attention to Information Technology Outsourcing (ITO) and Business Process Outsourcing (BPO), theoretical chapters explore insightful ways of thinking about the different facets of outsourcing, and provide useful information to practitioners and researchers. Empirical chapters report the findings of 405 major research studies into the risks and successes of relationships between customer and vendor, the development of trust in these relationships, the factors affecting locations for offshoring, and specialized offshoring organizations such as captive centres. In this comprehensive study, the editors present an expert review of the historical development of this field, and offer analysis of emerging findings and practices for the future.

This book highlights the growing number of 'post-bureaucratic' firms that are abandoning hierarchical organizational forms in favor of self-managing teams. Addressing the need to outperform, these new organization types foresee the benefits of an organic structure with new and more indirect forms of control, and aim to coordinate the activities of highly-skilled workers without relying on a bureaucratic superstructure. The chapters explore the tensions that exist between external and internal institutional forces. As new forms of control strategies emerge, mostly value-based, this book accounts for the cognitive categories, conventions, rules and logic that should be integrated and combined with traditional forms of managerial controls in order to enable co-existence with established bureaucratic frameworks. This book will be of interest to academics in the fields of organizational behavior and innovation management, and also practitioners and managers aiming to shift from a traditional hierarchical structure to post-bureaucratic forms.

This book offers readers essential orientation on cybersecurity safeguards, and first and foremost helps them find the right balance between financial expenditures and risk mitigation. This is achieved by pursuing a multi-disciplinary approach that combines well-founded methods from economics and the computer sciences. Established decision making techniques are embedded into a walk-through for the complete lifecycle of cybersecurity investments. Insights into the economic aspect of the costs and benefits of cybersecurity are supplemented by established and innovative economic indicators. Readers will find practical tools and techniques to support reasonable decision making in cybersecurity investments. Further, they will be equipped to encourage a common understanding using economic aspects, and to provide cost transparency for the senior management.

This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox to improve understanding and exploit business opportunities related to Big Data and analytics.

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.

Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and much expanded edition emphasizes the implementation of these techniques through the use of R. This free but incredibly powerful software is rapidly developing into the de facto standard for statistical computation, not just in academic circles but also in practice. With R, one can do simulations, find maximum likelihood estimators, compute distributions by inverting transforms, and much more.

This book addresses the topic of exploiting enterprise-linked data with a particular focus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and "standard" data consuming technologies by analysing real-world use cases, and proposes the enterprise knowledge graph to fill such gaps. It provides concrete guidelines for effectively deploying linked-data graphs within and across business organizations. It is divided into three parts, focusing on the key technologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents a simple architecture to elucidate the main phases and tasks required during the lifecycle of knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-the art knowledge-graph construction approaches, and then discusses exploration and exploitation techniques as well as advanced question-answering topics concerning knowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledge graph applications in the media industry, healthcare and cultural heritage, and offers conclusions and future visions.

This book features both cutting-edge contributions on managing knowledge in transformational contexts and a selection of real-world case studies. It analyzes how the disruptive power of digitization is becoming a major challenge for knowledge-based value creation worldwide, and subsequently examines the changes in how we manage information and knowledge, communicate, collaborate, learn and decide within and across organizations. The book highlights the opportunities provided by disruptive renewal, while also stressing the need for knowledge workers and organizations to transform governance, leadership and work organization. Emerging new business models and digitally enabled co-creation are presented as drivers that can help establish new ways of managing knowledge. In turn, a number of carefully selected and interpreted case studies provide a link to practice in organizations.

This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes: The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I). The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests. Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets. Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of "Big Data" analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development. A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories of development to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP. Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.

Advanced Topics in Information Resources Management features the most current research findings in all aspects of information resources management. From successfully implementing technology change to understanding the human factors in IT utilization, this important volume addresses many of the managerial and organizational applications to and implications of information technology in organizations. Volume three will prove to be instrumental in the improvement and development of the theory and practice of information resources management while educating organizations on how they can benefit from and improve their information resources and all the tools utilized to gather, process, disseminate, and manage this valuable resource. *Note: This book is part of a new series entitled "Advanced Topics in "Information Resources Management." This book is Volume Three within this series (Vol. III, 2004).

This book presents a systematic literature review of 156 published papers on business model innovation (BMI). The aim is to identify and integrate the different theoretical perspectives, analytical levels, and empirical contexts in order to deepen understanding of this complex phenomenon. The authors conduct an inductive thematic analysis based on an informal ontological classification that identifies 56 key themes. Within each theme, discussion focuses on thematic patterns, potential inconsistencies and debates, and future directions and opportunities for research. The book makes a number of significant contributions to the field. First, it offers a deeper understanding of the evolution of research on BMI through an ontological map that identifies the key thematic areas in the literature. Second, a multilevel model is developed that clarifies the concept of BMI by identifying its drivers, contingencies, and outcomes. Third, the authors identify clear and specific directions for further research and offer suggestions on research design, creating an informative road map for the future. The book will be of value both to scholars and researchers and to practitioners.

This book describes analytical techniques for optimizing knowledge acquisition, processing, and propagation, especially in the contexts of cyber-infrastructure and big data. Further, it presents easy-to-use analytical models of knowledge-related processes and their applications. The need for such methods stems from the fact that, when we have to decide where to place sensors, or which algorithm to use for processing the data-we mostly rely on experts' opinions. As a result, the selected knowledge-related methods are often far from ideal. To make better selections, it is necessary to first create easy-to-use models of knowledge-related processes. This is especially important for big data, where traditional numerical methods are unsuitable. The book offers a valuable guide for everyone interested in big data applications: students looking for an overview of related analytical techniques, practitioners interested in applying optimization techniques, and researchers seeking to improve and expand on these techniques.

While the web itself is about twenty years old, businesses are still impleme- ing the technology into the fabric of the business model. The background section will focus on defining the building blocks for the framework including defining the basic components of Web 1. 0 which focused on the presence and business transaction. The Web 2. 0 section will focus on defining the basic building blocks of customer interactions, while the final section will focus on a review the wine industry. 2. 1 Web 1. 0: Presence and Electronic Commerce The term Web 1. 0 emerged from the research around the development of Web 2. 0. Prior to this, researchers commonly referred to Web 1. 0 as Electronic C- merce or E-Business. Where as, web 1. 0 focused on a read only web interface, Web 2. 0 focuses on a read-write interface where value emerges from the contri- tion of a large volume of users. The Internet initially focused on the command and control of the information itself. Information was controlled by a relative small number of resources but distributed to a large number which spawned the massive growth of the web itself. Like television before it, the web allowed for the broadcasting of information to a large number of users. Initial web sites were built simply to communicate presence or provide information on the business - self. This component includes information like marketing materials, investor re- tions, employment opportunities, and product information.

Reinhard Brandl proposes a method to derive estimates for the expected resource consumption of customer-oriented services during standard load tests. This facilitates the determination of usage-based cost allocation keys significantly. He implements the concept in a software tool kit, evaluates it in a set of experiments with multi-tier database applications, and analyzes how the method can be integrated into existing IT processes at the BMW Group.

This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.

This book examines agile approaches from a management perspective by focusing on matters of strategy, implementation, organization and people. It examines the turbulence of the marketplace and business environment in order to identify what role agile management has to play in coping with such change and uncertainty. Based on observations, personal experience and extensive research, it clearly identifies the fabric of the agile organization, helping managers to become agile leaders in an uncertain world. The book opens with a broad survey of agile strategies, comparing and contrasting some of the major methodologies selected on the basis of where they lie on a continuum of ceremony and formality, ranging from the minimalist technique-driven and software engineering focused XP, to the pragmatic product-project paradigm that is Scrum and its scaled counterpart SAFe (R), to the comparatively project-centric DSDM. Subsequently, the core of the book focuses on DSDM, owing to the method's comprehensive elaboration of program and project management practices. This work will chiefly be of interest to all those with decision-making authority within their organizations (e.g., senior managers, line managers, program, project and risk managers) and for whom topics such as strategy, finance, quality, governance and risk management constitute a daily aspect of their work. It will, however, also be of interest to those readers in advanced management or business administration courses (e.g., MBA, MSc), who wish to engage in the management of agile organizations and thus need to adapt their skills and knowledge accordingly.

Forecasting is a crucial function for companies in the fashion industry, but for many real-life forecasting applications in the, the data patterns are notorious for being highly volatile and it is very difficult, if not impossible, to analytically learn about the underlying patterns. As a result, many traditional methods (such as pure statistical models) will fail to make a sound prediction. Over the past decade, advances in artificial intelligence and computing technologies have provided an alternative way of generating precise and accurate forecasting results for fashion businesses. Despite being an important and timely topic, there is currently an absence of a comprehensive reference source that provides up-to-date theoretical and applied research findings on the subject of intelligent fashion forecasting systems. This three-part handbook fulfills this need and covers materials ranging from introductory studies and technical reviews, theoretical modeling research, to intelligent fashion forecasting applications and analysis. This book is suitable for academic researchers, graduate students, senior undergraduate students and practitioners who are interested in the latest research on fashion forecasting.

Readings in Virtual Research Ethics: Issues and Controversies provides an in-depth look at the emerging field of online research and the corresponding ethical dilemmas associated with it. Issues related to traditional research ethics such as autonomy or respect for persons, justice, and beneficence are extended into the virtual realm and such areas as subject selection and recruitment, informed consent, privacy, ownership of data, and research with minors, among many others are explored in the media and contexts of email surveys and interviews, synchronous chat, virtual ethnography, asynchronous discussion lists, and newsgroups.

Systems for Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) are currently separate. The potential of the latest technologies and changes in operational and analytical applications over the last decade have given rise to the unification of these systems, which can be of benefit for both workloads. Research and industry have reacted and prototypes of hybrid database systems are now appearing.

Benchmarks are the standard method for evaluating, comparing and supporting the development of new database systems. Because of the separation of OLTP and OLAP systems, existing benchmarks are only focused on one or the other. With the rise of hybrid database systems, benchmarks to assess these systems will be needed as well.

Based on the examination of existing benchmarks, a new benchmark for hybrid database systems is introduced in this book. It is furthermore used to determine the effect of adding OLAP to an OLTP workload and is applied to analyze the impact of typically used optimizations in the historically separate OLTP and OLAP domains in mixed-workload scenarios.

For businesses large and small, investment in digital technologies is now a priority essential for success. Digitizing Government provides practical advice for understanding and implementing digital transformation to increase business value and improve client engagement, and features case studies from the private and public sectors.