This book provides a set of integrated frameworks-capital, systems, and objects-that transcend managerial or technology hype by focusing on the long-term fundamentals that sustain organizational success, and it contains cases from South East Asia to elaborate this concept. Many organizations are currently addressing two important transformational issues: ecological sustainability and digitization. Sustainability is a goal, an end, and digitization is a process, a means to achieve a goal. This book introduces a flexible model that can be applied to current and future organizational challenges, including sustainability and digitization, because the fundamentals are constant. This book is designed to serve two purposes for the readers: first, to present three conceptual foundations for designing and operating organizations (capital, systems, and objects (section 1)); and second, to provide a reference source for implementing these ideas in your organization (sections 2 and 3). The first section of the book, chapters 1 through 7, sets forth the conceptual foundations. The chapters mix concepts and practical examples to give a new way of thinking about the setting in which one may work many days each year. The second section provides details and associated examples of every one of the thirty-six forms of capital conversion. It also illustrates how the five foundational systems support capital conversion in a variety of ways. Finally, the third section is about measuring capital and systems. The book covers measurement of all types of capital and systems performance and has been written for current and future organizational leaders to change the game and play it more effectively. The book will thus resonate with students of organizational behaviour and leadership strategy, organizational leaders, industry experts, and general readers.

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 provides a comprehensive overview of the field of software processes, covering in particular the following essential topics: software process modelling, software process and lifecycle models, software process management, deployment and governance, and software process improvement (including assessment and measurement). It does not propose any new processes or methods; rather, it introduces students and software engineers to software processes and life cycle models, covering the different types ranging from "classical", plan-driven via hybrid to agile approaches. The book is structured as follows: In chapter 1, the fundamentals of the topic are introduced: the basic concepts, a historical overview, and the terminology used. Next, chapter 2 covers the various approaches to modelling software processes and lifecycle models, before chapter 3 discusses the contents of these models, addressing plan-driven, agile and hybrid approaches. The following three chapters address various aspects of using software processes and lifecycle models within organisations, and consider the management of these processes, their assessment and improvement, and the measurement of both software and software processes. Working with software processes normally involves various tools, which are the focus of chapter 7, before a look at current trends in software processes in chapter 8 rounds out the book. This book is mainly intended for graduate students and practicing professionals. It can be used as a textbook for courses and lectures, for self-study, and as a reference guide. When used as a textbook, it may support courses and lectures on software processes, or be used as complementary literature for more basic courses, such as introductory courses on software engineering or project management. To this end, it includes a wealth of examples and case studies, and each chapter is complemented by exercises that help readers gain a better command of the concepts discussed.

Succeed in the course with this Study Guide for BUSINESS MATH, filled with vocabulary, fill-in-the-blank, true/false, multiple choice, and problem solving questions for each chapter.

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.

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 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.

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.

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.

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 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.

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.

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.

Technological advances in the last five years have allowed organizations to use Business Analytics to provide insights, increase understanding and it is hoped, gain the elusive 'competitive edge'. The rapid development of Business Analytics is impacting all enterprise competences profoundly and classical business professions are being redefined by a much deeper interplay between business and information systems.As computing capabilities for analysis has moved outside the IT glass-house and into the sphere of individual workers, they are no longer the exclusive domain of IT professionals but rather accessible to all employees. Complex open-source data analytics packages and client-level visualization tools deployed in desktops and laptops equip virtually any end-user with the instruments to carry out significant analytical tasks. All the while, the drive to improve 'customer experience' has heightened the demand for data involving customers, providers and entire ecosystems.In response to the proliferation of Business Analytics, a new Center and Masters of Science Program was introduced at the National University of Singapore (NUS). The Center collaborates with over 40 different external partner organizations in Asia-Pacific with which all MSBA students undertake individual projects. Business Analytics: Progress on Applications in Asia Pacific provides a useful picture of the maturity of the Business Analytics domain in Asia Pacific. For more information about the Business Analytics Center at NUS, visit the website at: msba.nus.edu/

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 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.

Creative problem solving (CPS) is a six-step process designed to help people systematically resolve nonroutine, ambiguous types of problems. Because most organizational problems tend to be nonroutine, skill in using CPS process can confer a significant competitive advantage. "Creative Problem Solving" gives training managers the information they need to develop and teach a course on CPS. VanGundy provides an overview of the process, elements of the creative climate needed to foster CPS and innovative thinking, creative thinking exercises designed to illustrate specific CPS principles, and easy-to-follow descriptions of proven idea-generated methods.

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.

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.

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 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.

Information, Organization and Management is a comprehensive treatment of the economic and technical foundations for new organizational forms, relations and processes. It provides a wide range of underlying concepts and frameworks that help the reader understand the major forces driving organizational and marketplace change, rather than presenting these changes as simple outcomes of technological or management fads. "The book has a heavier than usual economic bent, yet also considers the human cognitive aspects. The emphasis throughout is on the total concepts, with subsections at the end of each chapter describing the role of information and the implications for management. The content is well worth reading." Paul Gray, Claremont Graduate School and University of California at Irvine.

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.

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.

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.