Within the IT-related business domain, it is important to advance theory building and practices regarding management and governance issues. Business Strategy and Applications in Enterprise IT Governance emphasizes how organizations enable both businesses and IT people to execute their responsibilities in support of business/IT alignment and the creation of business value from IT enabled corporation investments. This publication distributes leading research that is both academically executed and relevant for practice in the professional IT and business community.

Technology is constantly changing the way enterprises conduct business by optimizing current practices. As information technology continues to evolve and become a prevalent feature in day-to-day activities within organizations, it has become necessary to manage these technologies in order to meet the strategic objectives of an organization. Strategic IT Governance and Alignment in Business Settings investigates emergent research methodologies involving the application of information technology in organizations. Focusing on best practices, implementation issues, and empirical research within the field, this book is ideally suited for researchers, academics, students, and practitioners interested in the governance, strategy, architecture, and management of information systems.

The range of topics covered in ""Emerging E-Collaboration Concepts and Applications"" are broad and representative of the state-of-the-art discussion of conceptual and applied ecollaboration issues. Business organizations in the last 10 years have increasingly relied on distributed collaborative processes to maintain their competitiveness. E-collaboration technologies are at the source of something that underlies most business, political, and even societal developments - intense human collaboration. ""Emerging E-Collaboration Concepts and Applications"" is organized in three main parts: conceptual and methodological issues, applied research and challenges, and research syntheses and debate.

Metaheuristic algorithms are present in various applications for different domains. Recently, researchers have conducted studies on the effectiveness of these algorithms in providing optimal solutions to complicated problems. Advancements in Applied Metaheuristic Computing is a crucial reference source for the latest empirical research on methods and approaches that include metaheuristics for further system improvements, and it offers outcomes of employing optimization algorithms. Featuring coverage on a broad range of topics such as manufacturing, genetic programming, and medical imaging, this publication is ideal for researchers, academicians, advanced-level students, and technology developers seeking current research on the use of optimization algorithms in several applications.

This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples. As such, it quickly introduces readers to the peculiarities of each subject from both theoretical and the practical points of view. It also includes numerous examples and real-world applications that demonstrate how to handle different types of time series data. The associated software package, SSMMATLAB, is written in MATLAB and also runs on the free OCTAVE platform. The book focuses on linear time series models using a state space approach, with the Kalman filter and smoother as the main tools for model estimation, prediction and signal extraction. A chapter on state space models describes these tools and provides examples of their use with general state space models. Other topics discussed in the book include ARIMA; and transfer function and structural models; as well as signal extraction using the canonical decomposition in the univariate case, and VAR, VARMA, cointegrated VARMA, VARX, VARMAX, and multivariate structural models in the multivariate case. It also addresses spectral analysis, the use of fixed filters in a model-based approach, and automatic model identification procedures for ARIMA and transfer function models in the presence of outliers, interventions, complex seasonal patterns and other effects like Easter, trading day, etc. This book is intended for both students and researchers in various fields dealing with time series. The software provides numerous automatic procedures to handle common practical situations, but at the same time, readers with programming skills can write their own programs to deal with specific problems. Although the theoretical introduction to each topic is kept to a minimum, readers can consult the companion book 'Multivariate Time Series With Linear State Space Structure', by the same author, if they require more details.

This thesis presents a revolutionary technique for modelling the dynamics of a quantum system that is strongly coupled to its immediate environment. This is a challenging but timely problem. In particular it is relevant for modelling decoherence in devices such as quantum information processors, and how quantum information moves between spatially separated parts of a quantum system. The key feature of this work is a novel way to represent the dynamics of general open quantum systems as tensor networks, a result which has connections with the Feynman operator calculus and process tensor approaches to quantum mechanics. The tensor network methodology developed here has proven to be extremely powerful: For many situations it may be the most efficient way of calculating open quantum dynamics. This work is abounds with new ideas and invention, and is likely to have a very significant impact on future generations of physicists.

It is important for those in charge of implementing an enterprise resource planning (ERP) system to identify and understand the issues they face. ""Implementation Strategies for SAP R/3 in a Multinational Organization: Lessons from a Real-World Case Study"" provides readers with an instructive insight in the very complex process of ERP implementation in a global company. This book describes the issues, problems, and challenges of ERP execution as well as the strategies companies use to react to and resolve them successfully. The reader can focus on different types of issues - organizational as well as technical. It is a goldmine for instructors who can use the cases in different course settings and with different student audiences. Researchers and practioners will also find value in the detailed descriptions of challenges faced by companies such as Robert Bosch GmbH.

Computational Finance presents a modern computational approach to mathematical finance within the Windows environment, and contains financial algorithms, mathematical proofs and computer code in C/C++. The author illustrates how numeric components can be developed which allow financial routines to be easily called by the complete range of Windows applications, such as Excel, Borland Delphi, Visual Basic and Visual C++.
These components permit software developers to call mathematical finance functions more easily than in corresponding packages. Although these packages may offer the advantage of interactive interfaces, it is not easy or computationally efficient to call them programmatically as a component of a larger system. The components are therefore well suited to software developers who want to include finance routines into a new application.
Typical readers are expected to have a knowledge of calculus, differential equations, statistics, Microsoft Excel, Visual Basic, C++ and HTML.
A CD-ROM is included which contains: working computer code, demonstration applications and also pdf versions of several research articles.
* Enables reader to incorporate advanced financial modelling techniques in Windows compatible software
* Aids the development of bespoke software solutions covering GARCH volatility modelling, derivative pricing with Partial Differential Equations, VAR, bond and stock options
* Includes CD-ROM with adaptive software

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non- mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages. Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms. Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance-all of which are problems that occur frequently in practice. The text illustrates all parts of the modeling process through many hands-on, real-life examples. And every chapter contains extensive R code f

Computational finance deals with the mathematics of computer programs that realize financial models or systems. This book outlines the epistemic risks associated with the current valuations of different financial instruments and discusses the corresponding risk management strategies. It covers most of the research and practical areas in computational finance. Starting from traditional fundamental analysis and using algebraic and geometric tools, it is guided by the logic of science to explore information from financial data without prejudice. In fact, this book has the unique feature that it is structured around the simple requirement of objective science: the geometric structure of the data = the information contained in the data.

Computational finance deals with the mathematics of computer programs that realize financial models or systems. This book outlines the epistemic risks associated with the current valuations of different financial instruments and discusses the corresponding risk management strategies. It covers most of the research and practical areas in computational finance. Starting from traditional fundamental analysis and using algebraic and geometric tools, it is guided by the logic of science to explore information from financial data without prejudice. In fact, this book has the unique feature that it is structured around the simple requirement of objective science: the geometric structure of the data = the information contained in the data.

This book provides insights into important new developments in the area of statistical quality control and critically discusses methods used in on-line and off-line statistical quality control. The book is divided into three parts: Part I covers statistical process control, Part II deals with design of experiments, while Part III focuses on fields such as reliability theory and data quality. The 12th International Workshop on Intelligent Statistical Quality Control (Hamburg, Germany, August 16 - 19, 2016) was jointly organized by Professors Sven Knoth and Wolfgang Schmid. The contributions presented in this volume were carefully selected and reviewed by the conference's scientific program committee. Taken together, they bridge the gap between theory and practice, making the book of interest to both practitioners and researchers in the field of quality control.

This contributed book focuses on major aspects of statistical quality control, shares insights into important new developments in the field, and adapts established statistical quality control methods for use in e.g. big data, network analysis and medical applications. The content is divided into two parts, the first of which mainly addresses statistical process control, also known as statistical process monitoring. In turn, the second part explores selected topics in statistical quality control, including measurement uncertainty analysis and data quality. The peer-reviewed contributions gathered here were originally presented at the 13th International Workshop on Intelligent Statistical Quality Control, ISQC 2019, held in Hong Kong on August 12-14, 2019. Taken together, they bridge the gap between theory and practice, making the book of interest to both practitioners and researchers in the field of statistical quality control.

This book is published open access under a CC BY 4.0 license. This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.

Technology is continuously advancing and changing the way aspects of business are performed. The implementation of mobile business transactions to acquire various types of goods has changed the landscape of consumerism. Apps Management and E-Commerce Transactions in Real-Time is a timely research publication that features the latest scholarly trends, issues, and implications of the use of a new technological forum in electronic buying and selling. Including extensive coverage on a number of topics and perspectives such as social networks, customer satisfaction, and cloud computing, this book is ideally designed for researchers, academicians, and students seeking current research on mobile solutions in business deals.

Totally Awesome Stephen Monaco offers a comprehensive guide to social media marketing in Insightful Knowledge. He changes perceptions on social media marketing and tell readers how to develop their marketing strategies. Since social media needs to be part of your marketing efforts, read this book Monica Cornetti - Leading Authority on Entrepreneurial Thinking, and Author of Your Face Isn't Finished Until Your Lipstick is On YOU NEED THIS BOOK IF... you don't know where to start with your social media initiatives you've started your social media initiatives but aren't sure if you're on the right track your social media initiatives are in place and you believe you're on the right track none of your social media initiatives are directly tied to specific business objectives you fail to use social media monitoring / listening platforms in your social media you don't know what consumers are saying about your brand online you don't have a comprehensive Voice of Customer program in place you're not engaging consumers with relevant content across multiple platforms your company is driven by sales, rather than by marketing the breakneck tempo of today's business makes it difficult to adapt and keep up with change you no longer know how to reach potential customers

The topic of Enterprise Information Systems (EIS) is having an increasingly relevant strategic impact on global business and the world economy, and organizations are undergoing hard investments in search of the rewarding benefits of efficiency and effectiveness that these ranges of solutions promise. Organizational Integration of Enterprise Systems and Resources: Advancements and Applications show that EIS are at the same time responsible for tremendous gains in some companies and tremendous losses in others. Therefore, their adoption should be carefully planned and managed. This title highlights new ways to identify opportunities and overtake trends and challenges of EIS selection, adoption, and exploitation as it is filled with models, solutions, tools, and case studies. The book provides researchers, scholars, and professionals with some of the most advanced research, solutions, and discussions of Enterprise Information Systems design, implementation, and management.

This book is dedicated to the systematization and development of models, methods, and algorithms for queuing systems with correlated arrivals. After first setting up the basic tools needed for the study of queuing theory, the authors concentrate on complicated systems: multi-server systems with phase type distribution of service time or single-server queues with arbitrary distribution of service time or semi-Markovian service. They pay special attention to practically important retrial queues, tandem queues, and queues with unreliable servers. Mathematical models of networks and queuing systems are widely used for the study and optimization of various technical, physical, economic, industrial, and administrative systems, and this book will be valuable for researchers, graduate students, and practitioners in these domains.

Complexity of Seismic Time Series: Measurement and Application applies the tools of nonlinear dynamics to seismic analysis, allowing for the revelation of new details in micro-seismicity, new perspectives in seismic noise, and new tools for prediction of seismic events. The book summarizes both advances and applications in the field, thus meeting the needs of both fundamental and practical seismology. Merging the needs of the classical field and the very modern terms of complexity science, this book covers theory and its application to advanced nonlinear time series tools to investigate Earth's vibrations, making it a valuable tool for seismologists, hazard managers and engineers.

This book provides a tutorial in the use of Altair Compose and Altair Activate, software packages that provide system modeling and simulation facilities. Advanced system modeling software provide multiple ways of creating models: models can be programmed in specialized languages, graphically constructed as block-diagrams and state machines, or expressed mathematically in equation-based languages. Compose and Activate are introduced in this text in two parts. The first part introduces the multi-language environment of Compose and its use for modeling, simulation and optimization. The second describes the graphical system modeling and optimization with Activate, an open-system environment providing signal-based modeling as well as physical system component-based modeling. Throughout both parts are applied examples from mechanical, biological, and electrical systems, as well as control and signal processing systems. This book will be an invaluable addition with many examples both for those just interested in OML and those doing industrial scale modeling, simulation, and design. All examples are worked using the free basic editions of Activate and Compose that are available.