Global Enterprise Transitions: Managing the Process addresses the importance of information technology management and issues in operating information systems in the global dynamic business environment. This book embraces discussions of the global information technology theory, frameworks and IT architecture, discovery of global knowledge management, improvement of the global information systems development methodologies, and applications of the latest technologies such as mobile technology and web services in the global information systems development and operations.

Advanced Topics in Global Information Management is a series of books that examine global information management (GIM), and its research and implications. GIM research continues to progress, with some scholars pushing the boundaries of thinking and others challenging the status quo. ""Advanced Topics in Global Information Management, Volume 5"" is a part of this series. ""Advanced Topics in Global Information Management, Volume 5"" discusses how many businesses exist in a global environment. Whether they are large or small companies, they may have suppliers or customers that reside in different geographical locations. The ability to function in this global environment has been facilitated by the use of information technology. Through research projects, this book addresses the ability of both large and small business, and government, from the national level to local level, to function in altered environments by using information technology. In all of these situations, both businesses and governments must be able to function and respond to various stakeholders by adopting the appropriate, and necessary, cultural perspective.

Charged with ensuring the confidentiality, integrity, availability, and delivery of all forms of an entity's information, Information Assurance (IA) professionals require a fundamental understanding of a wide range of specializations, including digital forensics, fraud examination, systems engineering, security risk management, privacy, and compliance. Establishing this understanding and keeping it up to date requires a resource with coverage as diverse as the field it covers. Filling this need, the Encyclopedia of Information Assurance presents an up-to-date collection of peer-reviewed articles and references written by authorities in their fields. From risk management and privacy to auditing and compliance, the encyclopedia's four volumes provide comprehensive coverage of the key topics related to information assurance. This complete IA resource: Supplies the understanding needed to help prevent the misuse of sensitive information Explains how to maintain the integrity of critical systems Details effective tools, techniques, and methods for protecting personal and corporate data against the latest threats Provides valuable examples, case studies, and discussions on how to address common and emerging IA challenges Placing the wisdom of leading researchers and practitioners at your fingertips, this authoritative reference provides the knowledge and insight needed to avoid common pitfalls and stay one step ahead of evolving threats. Also Available OnlineThis Taylor & Francis encyclopedia is also available through online subscription, offering a variety of extra benefits for researchers, students, and librarians, including: Citation tracking and alerts Active reference linking Saved searches and marked lists HTML and PDF format options Contact Taylor and Francis for more information or to inquire about subscription options and print/online combination packages. US: (Tel) 1.888.318.2367; (E-mail) [email protected] International: (Tel) +44 (0) 20 7017 6062; (E-mail) [email protected]

Presented are innovative teaching and learning techniques for the teaching of knowledge-based paradigms. The main knowledge-based intelligent paradigms are expert systems, artificial neural networks, fuzzy systems and evolutionary computing. Expert systems are designed to mimic the performance of biological systems. Artificial neural networks can mimic the biological information processing mechanism in a very limited sense. Evolutionary computing algorithms are used for optimization applications, and fuzzy logic provides a basis for representing uncertain and imprecise knowledge.

This book provides a coherent overview of the most important modelling-related security techniques available today, and demonstrates how to combine them. Further, it describes an integrated set of systematic practices that can be used to achieve increased security for software from the outset, and combines practical ways of working with practical ways of distilling, managing, and making security knowledge operational. The book addresses three main topics: (1) security requirements engineering, including security risk management, major activities, asset identification, security risk analysis and defining security requirements; (2) secure software system modelling, including modelling of context and protected assets, security risks, and decisions regarding security risk treatment using various modelling languages; and (3) secure system development, including effective approaches, pattern-driven development, and model-driven security. The primary target audience of this book is graduate students studying cyber security, software engineering and system security engineering. The book will also benefit practitioners interested in learning about the need to consider the decisions behind secure software systems. Overall it offers the ideal basis for educating future generations of security experts.

The Remote Work Handbook: The Definitive Guide for Operationalizing Remote Work as a Competitive Business Strategy is for readers seeking to leverage the business benefits of a flexible, remote workforce. It is a practical guide for building and implementing remote work at any size organization. C-suite executives, operation leaders, business owners, or entrepreneurs who recognize the workplace is changing can use it to re-tool their operations for a strategic business advantage. Mari Anne Snow, the author, is a recognized remote work expert with over 20 years of experience leading remote teams and has re-written the rules of leadership to unlock the potential in remote and distributed teams. In this book, she shares all her secrets. The book explores the untapped potential of remote teams and lays out the business case for adopting a new, flexible workplace model to build organizational resilience and a competitive edge. It takes the reader through the step-by-step process of constructing a remote work operating model, staging an implementation, then institutionalizing and sustaining the change. It includes down-to-earth professional and personal stories that alert the reader to the top priorities and operational realities they will face as they craft their own implementation plan for operationalizing remote work at their company.

"[A] valuable addition[s] to the stock of material available for fledgling social scientists. Lewis-Bec?s book is best for early nurture. . . "

--Eric Tanenbaum in ESRC Data Archive Bulletin

"This book, I predict, will turn the statistics-shy into eager practitioners, and skillful ones to boot. . . . It?s a masterpiece of clarity and appliedness, written in a refreshing and engaging style. Not only is a lot of ground covered--as much as can be packed into a first-semester course in data analysis--but the author also grapples with issues of statistical theory (specification error, collinearity, least-squares estimation)."

--Helmet Norpoth, SUNY at Stony Brook

"This is a very fine book that will make an excellent addition to the Sage quantitative application series. It does a nice job of illustrating how data analysis is conducted by taking a simple, easy-to-motivate example and following it through the entire gamut of data analysis steps."

--Herbert Weisberg, The Ohio State University

Written at a level appropriate for the advanced undergraduate course on data analysis, this accessible volume introduces the reader to the "art" of data analysis from data-gathering to multiple regression in which a dependent variable is influenced by several independent variables. The book focuses on the interpretation of a statistical result, in particular those that come from nonexperimental social research. Using a consistent data set throughout the book in order to illustrate the various analytic techniques, the author covers such topics as univariate statistics, measures of association, the statistical significance of the relationship between two variables, and simple regression where the dependent variable is influenced by a single independent variable. The last chapter offers analysis recommendations. Data Analysis will provide social science researchers with the tools to select and evaluate statistical tests appropriate for their particular research question.

Traditional business practices have been left behind due to the increased use of data analytics and information technology in companies worldwide. This development has led to businesses implementing transformative projects that use these new technologies in their decision-making systems. Altering the entire architecture of a company is a daunting task; however, researchers are finding methods through applied mathematics that can make it easier on companies. Implementing analytical models into current business processes is vital for professionals across the globe. Using Applied Mathematical Models for Business Transformation is an essential reference source that discusses the advancement of decision-making systems in business environments with the use of applied mathematics, algorithms, and information technology. Featuring research on topics such as decision-making systems, critical success factors, and global enterprise architecture, this book is ideally designed for project managers, financial analysts, business strategists, software engineers, technical architects, students, researchers, and educators seeking coverage on the transformation of business practices using applied mathematics and information technology.

The only up-to-date introductory textbook on sport entrepreneurship and innovation. Entrepreneurial skills are essential for anybody working in sport management, particularly in the face of COVID-related challenges. Introduces key theory and focuses on best practice, based on real world scenarios. Includes practitioner voices throughout.

Data mining is the process of extracting hidden patterns from data, and it's commonly used in business, bioinformatics, counter-terrorism, and, increasingly, in professional sports. First popularized in Michael Lewis' best-selling Moneyball: The Art of Winning An Unfair Game, it is has become an intrinsic part of all professional sports the world over, from baseball to cricket to soccer. While an industry has developed based on statistical analysis services for any given sport, or even for betting behavior analysis on these sports, no research-level book has considered the subject in any detail until now. Sports Data Mining brings together in one place the state of the art as it concerns an international array of sports: baseball, football, basketball, soccer, greyhound racing are all covered, and the authors (including Hsinchun Chen, one of the most esteemed and well-known experts in data mining in the world) present the latest research, developments, software available, and applications for each sport. They even examine the hidden patterns in gaming and wagering, along with the most common systems for wager analysis.

Here's a broad, integrated view of existing communications technologies available world-wide -- including the Internet and Web, digital mobile telephony, ISDN, SMDS, frame relay, and ATM -- from a practical business perspective. Covering both private and public networks, the book offers a basic explanation of a wide range of technologies and describes their underlying principles and features, as well as the factors that differentiate them. The guide also showcases typical applications, exposes inherent limitations, explains pricing and methods of comparison, and discusses security pitfalls and protection systems.

This is a compilation of papers presented at the Information System Concepts conference in Marburg, Germany. The special focus is consolidation and harmonisation of the numerous and widely diverging views in the field of information systems. This issue has become a hot topic, as many leading information system researchers and practitioners come to realise the importance of better communication among the members of the information systems community, and of a better scientific foundation of this rapidly evolving field.

This book collects high-quality papers on the latest fundamental advances in the state of Econophysics and Management Science, providing insights that address problems concerning the international economy, social development and economic security. This book applies the multi-fractal detrended class method, and improves the method with different filters. The authors apply those methods to a variety of areas: financial markets, energy markets, gold market and so on. This book is arguably a systematic research and summary of various kinds of multi-fractal detrended methods. Furthermore, it puts forward some investment suggestions on a healthy development of financial markets.

This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the "Challenge of Big Data and Applications of Statistics," in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.

Current database technology and computer hardware allow us to gather, store, access, and manipulate massive volumes of raw data in an efficient and inexpensive manner. In addition, the amount of data collected and warehoused in all industries is growing every year at a phenomenal rate. Nevertheless, our ability to discover critical, non-obvious nuggets of useful information in data that could influence or help in the decision making process, is still limited. Knowledge discovery (KDD) and Data Mining (DM) is a new, multidisciplinary field that focuses on the overall process of information discovery from large volumes of data. The field combines database concepts and theory, machine learning, pattern recognition, statistics, artificial intelligence, uncertainty management, and high-performance computing. To remain competitive, businesses must apply data mining techniques such as classification, prediction, and clustering using tools such as neural networks, fuzzy logic, and decision trees to facilitate making strategic decisions on a daily basis. Knowledge Discovery for Business Information Systems contains a collection of 16 high quality articles written by experts in the KDD and DM field from the following countries: Austria, Australia, Bulgaria, Canada, China (Hong Kong), Estonia, Denmark, Germany, Italy, Poland, Singapore and USA.

This book examines the requirements, risks, and solutions to improve the security and quality of complex cyber-physical systems (C-CPS), such as production systems, power plants, and airplanes, in order to ascertain whether it is possible to protect engineering organizations against cyber threats and to ensure engineering project quality. The book consists of three parts that logically build upon each other. Part I "Product Engineering of Complex Cyber-Physical Systems" discusses the structure and behavior of engineering organizations producing complex cyber-physical systems, providing insights into processes and engineering activities, and highlighting the requirements and border conditions for secure and high-quality engineering. Part II "Engineering Quality Improvement" addresses quality improvements with a focus on engineering data generation, exchange, aggregation, and use within an engineering organization, and the need for proper data modeling and engineering-result validation. Lastly, Part III "Engineering Security Improvement" considers security aspects concerning C-CPS engineering, including engineering organizations' security assessments and engineering data management, security concepts and technologies that may be leveraged to mitigate the manipulation of engineering data, as well as design and run-time aspects of secure complex cyber-physical systems. The book is intended for several target groups: it enables computer scientists to identify research issues related to the development of new methods, architectures, and technologies for improving quality and security in multi-disciplinary engineering, pushing forward the current state of the art. It also allows researchers involved in the engineering of C-CPS to gain a better understanding of the challenges and requirements of multi-disciplinary engineering that will guide them in their future research and development activities. Lastly, it offers practicing engineers and managers with engineering backgrounds insights into the benefits and limitations of applicable methods, architectures, and technologies for selected use cases.

Innovation, agility, and coordination are paramount in the support of value in the global knowledge economy. Therefore, the long-term success of a company is increasingly dependent on its underlying resilience and agility. ""Knowledge Reuse and Agile Processes"" addresses flexibility of both business and information systems through component technology at the nexus of three seemingly unrelated disciplines: service-oriented architecture, knowledge management, and business process management. Providing practitioners and academicians with timely, compelling research on agile, adaptive processes and information systems, this premier reference source will enhance the collection of every reference library.

This book examines how fuzzy methods can be employed to manage service levels in business and IT alignment. It starts by mapping the dependencies of service level agreements, coming up with gradual and bi-polar concepts to eventually classify the level of coupling by intuitionistic fuzzy sets. The second part presents an approach to analyze the impact of service failures using intuitionistic fuzzy methods (IFSFIA). Lastly, the third part of the book extends the concept towards business and IT-aligned service-level engineering and provides two use cases.

As the global economy turns more and more service oriented, Information Technology-Enabled Services (ITeS) require greater understanding. Increasing numbers and varieties of services are provided through IT. Furthermore, IT enables the creation of new services in diverse fields previously untouched. Because of the catalyzing nature of internet technology, ITeS today has become more than "Outsourcing" of services. This book illustrates the enabling nature of ITeS with its entailment of IT, thus contributing to the betterment of humanity. The scope of this book is not only for academia but also for business persons, government practitioners and readers from daily lives. Authors from a variety of nations and regions with various backgrounds provide insightful theories, research, findings and practices in various fields such as commerce, finance, medical services, government and education. This book opens up a new horizon with the application of Internet-based practices in business, government and in daily lives. Information Technology-Enabled Services works as a navigator for those who sail to the new horizon of service oriented economies.

This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.

This book introduces readers to the field of conformance checking as a whole and outlines the fundamental relation between modelled and recorded behaviour. Conformance checking interrelates the modelled and recorded behaviour of a given process and provides techniques and methods for comparing and analysing observed instances of a process in the presence of a model, independent of the model's origin. Its goal is to provide an overview of the essential techniques and methods in this field at an intuitive level, together with precise formalisations of its underlying principles. The book is divided into three parts, that are meant to cover different perspectives of the field of conformance checking. Part I presents a comprehensive yet accessible overview of the essential concepts used to interrelate modelled and recorded behaviour. It also serves as a reference for assessing how conformance checking efforts could be applied in specific domains. Next, Part II provides readers with detailed insights into algorithms for conformance checking, including the most commonly used formal notions and their instantiation for specific analysis questions. Lastly, Part III highlights applications that help to make sense of conformance checking results, thereby providing a necessary next step to increase the value of a given process model. They help to interpret the outcomes of conformance checking and incorporate them by means of enhancement and repair techniques. Providing the core building blocks of conformance checking and describing its main applications, this book mainly addresses students specializing in business process management, researchers entering process mining and conformance checking for the first time, and advanced professionals whose work involves process evaluation, modelling and optimization.

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

Multicriteria analysis is a rapidly growing aspect of operations research and management science, with numerous practical applications in a wide range of fields. This book presents all the recent advances in multicriteria analysis, including multicriteria optimization, goal programming, outranking methods, and disaggregation techniques. The latest developments on robustness analysis, preference elicitation, and decision making when faced with incomplete information, are also discussed, together with applications in business performance evaluation, finance, and marketing. Finally, the interactions of multicriteria analysis with other disciplines are also explored, including among others data mining, artificial intelligence, and evolutionary methods.

There are two types of readers that will find this book useful: those who have an interest in the Metadatabase model as an integration technology, and those who also seek a general discussion on information system analysis and design. To this end, a general conceptual framework on enterprise integration and modeling is provided in the first chapter, and is used to tie together all of the remaining chapters of the book. The next two chapters present some basics and examples of systems analysis and design for enterprise modeling; which serve the purposes of general discussion on the subject as well as illustrating the modeling methods particular to the Metadatabase approach. The particular methods are discussed fully in Chapter 4. An overview of the Metadatabase Model is provided in Chapter 5 and illustrated with a paper demonstration' of a basic Metadatabase prototype in Chapter 6. The main technical elements of the model are presented in Chapters 7-9. The model is then applied to manufacturing in Chapter 10, where a core information model for implementing the Metadatabase approach to integration is also included. Chapter 11 extends the Metadatabase technology into the realm of information visualization. The new user interface model developed can be applied to integrate the traditional management of information in an enterprise with new cyberspace applications such as electronic commerce. The Metadatabase model of enterprise information integration (for multiple systems) has been developed at Rensselaer Polytechnic Institute under the sponsorships of Alcoa, Digital, GE, GM, and IBM (from 1986-1995 through the Computer-Integrated Manufacturing and the Adaptive Integrated ManufacturingEnterprises programs), the National Science Foundation (since 1991), Samsung (since 1995), and U.S. Army (since 1995). The technology is being developed into a product for Samsung and the Army. This is the first expository book on the topic.

This book analyses quantitative open source software (OSS) reliability assessment and its applications, focusing on three major topic areas: the Fundamentals of OSS Quality/Reliability Measurement and Assessment; the Practical Applications of OSS Reliability Modelling; and Recent Developments in OSS Reliability Modelling. Offering an ideal reference guide for graduate students and researchers in reliability for open source software (OSS) and modelling, the book introduces several methods of reliability assessment for OSS including component-oriented reliability analysis based on analytic hierarchy process (AHP), analytic network process (ANP), and non-homogeneous Poisson process (NHPP) models, the stochastic differential equation models and hazard rate models. These measurement and management technologies are essential to producing and maintaining quality/reliable systems using OSS.