This book clarifies the direction of business innovation using new ICT such as the Internet of things (IoT), artificial intelligence (AI), smartphones, and cloud computing through a series of case studies on successful trials and advanced businesses in the Asia-Pacific where many industry sectors have been growing successfully in the 21st century. ICT has been playing an important role in value creation for customers and in profit generation for providers, contributing to various service innovation and business innovation. Now, digitalization using IoT and AI provides solutions to address various issues in the human society, which is transforming services and businesses in the 21st century. "What is the direction of the business innovation using new ICT?" is a highly concerned question for business researchers and practitioners. Aiming to answer the question, this book conducts a number of cases studies in the Asia-Pacific region, including the Mainland China, Taiwan, Japan, Malaysia, Vietnam, as well as Australia. Among the studies, there are 4 cases from ICT providers, 4 cases from traditional and services, and 6 cases from new ICT applications and businesses. Each case analyzes social needs and human desires, new value created, roles of new technologies, processes and difficulties in developing new businesses, the relationship among customers, providers, and stakeholders, value chain co-creation and optimization, factors of success, and business models. Finally, the direction of business innovation with new ICT in the Asia-Pacific is suggested by summarizing the findings from the case studies through the lens of the theoretical analysis in service science.

This book delves into the concept of data as a critical enterprise asset needed for informed decision making, compliance, regulatory reporting and insights into trends, behaviors, performance and patterns. With good data being key to staying ahead in a competitive market, enterprises capture and store exponential volumes of data. Considering the business impact of data, there needs to be adequate management around it to derive the best value. Data governance is one of the core data management related functions. However, it is often overlooked, misunderstood or confused with other terminologies and data management functions. Given the pervasiveness of data and the importance of data, this book provides comprehensive understanding of the business drivers for data governance and benefits of data governance, the interactions of data governance function with other data management functions and various components and aspects of data governance that can be facilitated by technology and tools, the distinction between data management tools and data governance tools, the readiness checks to perform before exploring the market to purchase a data governance tool, the different aspects that must be considered when comparing and selecting the appropriate data governance technologies and tools from large number of options available in the marketplace and the different market players that provide tools for supporting data governance. This book combines the data and data governance knowledge that the author has gained over years of working in different industrial and research programs and projects associated with data, processes and technologies with unique perspectives gained through interviews with thought leaders and data experts. This book is highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge and get guidance on implementing data governance in their own data initiatives.

A Standard for Auditing Computer Applications is a dynamic new resource for evaluating all aspects of automated business systems and systems environments. At the heart of A Standard for Auditing Computer Applications system is a set of customizable workpapers that provide blow-by-blow coverage of all phases of the IT audit process for traditional mainframe, distributed processing, and client/server environments.A Standard for Auditing Computer Applications was developed by Marty Krist, an acknowledged and respected expert in IT auditing. Drawing upon his more than twenty years of auditing experience with leading enterprise organizations, worldwide, Marty walks you step-by-step through the audit process for system environments and specific applications and utilities. He clearly spells out what you need to look for and where to look for it, and he provides expert advice and guidance on how to successfully address a problem when you find one.When you order A Standard for Auditing Computer Applications, you receive a powerful package containing all the forms, checklists, and templates you'll ever need to conduct successful audits on downloadable resources. Designed to function as a handy, on-the-job resource, the book follows a concise, quick-access format. It begins with an overview of the general issues inherent in any IT review. This is followed by a comprehensive review of the audit planning process. The remainder of the book provides you with detailed, point-by-point breakdowns along with proven tools for:evaluating systems environments-covers all the bases, including IT administration, security, backup and recovery planning, systems development, and moreEvaluating existing controls for determining hardware and software reliabilityAssessing the new system development processEvaluating all aspects of individual applications, from I/O, processing and logical and physical security to documentation, training, and programmed proceduresAssessing specific applications and utilities, including e-mail, groupware, finance and accounting applications, CAD, R&D, production applications, and more

This book gathers the best papers presented at the second conference held by the Russian chapter of the Association for Information Systems (AIS), which took place in Yekaterinburg, Russian Federation, in December 2019. It shares the latest insights into various aspects of the digitalization of the economy and the consequences of transformation in public administration, business and public life. Integrating a broad range of analytical perspectives, including economic, social and technological, this interdisciplinary book is particularly relevant for scientists, digital technology users, companies and public institutions.

This open access book explores the concept of Industry 4.0, which presents a considerable challenge for the production and service sectors. While digitization initiatives are usually integrated into the central corporate strategy of larger companies, smaller firms often have problems putting Industry 4.0 paradigms into practice. Small and medium-sized enterprises (SMEs) possess neither the human nor financial resources to systematically investigate the potential and risks of introducing Industry 4.0. Addressing this obstacle, the international team of authors focuses on the development of smart manufacturing concepts, logistics solutions and managerial models specifically for SMEs. Aiming to provide methodological frameworks and pilot solutions for SMEs during their digital transformation, this innovative and timely book will be of great use to scholars researching technology management, digitization and small business, as well as practitioners within manufacturing companies.

This book presents contemporary empirical methods in software engineering related to the plurality of research methodologies, human factors, data collection and processing, aggregation and synthesis of evidence, and impact of software engineering research. The individual chapters discuss methods that impact the current evolution of empirical software engineering and form the backbone of future research. Following an introductory chapter that outlines the background of and developments in empirical software engineering over the last 50 years and provides an overview of the subsequent contributions, the remainder of the book is divided into four parts: Study Strategies (including e.g. guidelines for surveys or design science); Data Collection, Production, and Analysis (highlighting approaches from e.g. data science, biometric measurement, and simulation-based studies); Knowledge Acquisition and Aggregation (highlighting literature research, threats to validity, and evidence aggregation); and Knowledge Transfer (discussing open science and knowledge transfer with industry). Empirical methods like experimentation have become a powerful means of advancing the field of software engineering by providing scientific evidence on software development, operation, and maintenance, but also by supporting practitioners in their decision-making and learning processes. Thus the book is equally suitable for academics aiming to expand the field and for industrial researchers and practitioners looking for novel ways to check the validity of their assumptions and experiences. Chapter 17 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book provides several inventory models for making the right decision in inventory management under different environments. Basically, the optimal ordering policies are determined for situations with and without shortages in production-inventory systems. The chapters in the book include various features of inventory modeling i.e., inflation, deterioration, supply chain, learning, credit financing, carbon emission policy, stock-dependent demand, among others. The book is a useful resource for academicians, researchers, students, practitioners, and managers who can be benefited with the policies provided in the chapters of the book.

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.

This book presents a collection of mathematical models that deals with the real scenario in the industries. The primary objective of this book is to explore various effective methods for inventory control and management using soft computing techniques. Inventory control and management is a very tedious task faced by all the organizations in any sector of the economy. It makes decisions for policies, activities, and procedures in order to make sure that the right amount of each item is held in stock at any time. Many industries suffer from indiscipline while ordering and production mismatch. It is essential to provide best ordering policy to control such kind of mismatch in the industries. All the mathematical model solutions are provided with the help of various soft computing optimization techniques to determine optimal ordering policy. This book is beneficial for practitioners, educators, and researchers. It is also helpful for retailers/managers for improving business functions and making more accurate and realistic decisions.

This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA). This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDA in IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy.

This book explores nonparametric statistical process control. It provides an up-to-date overview of nonparametric Shewhart-type univariate control charts, and reviews the recent literature on nonparametric charts, particularly multivariate schemes. Further, it discusses observations tied to the monitored population quantile, focusing on the Shewhart Sign chart. The book also addresses the issue of practically assuming the normality and the independence when a process is statistically monitored, and examines in detail change-point analysis-based distribution-free control charts designed for Phase I applications. Moreover, it introduces six distribution-free EWMA schemes for simultaneously monitoring the location and scale parameters of a univariate continuous process, and establishes two nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules. Lastly, the book proposes novel and effective method for early disease detection.

This edited book presents scientific and practical recommendations for the successful state and corporate management of regional development under the conditions of the digital economy. These conditions have produced a number of changes. On the one hand, new aspects of regional economies, which require management, are emerging, above all, digital technologies that have to be understood by the population, employees in the labor market, and regional companies. On the other hand, new opportunities for improving practices in the state and corporate management of regional development on the basis of digital technologies are also emerging: e-government systems, digital marketing, online trade, "smart" regions, etc. This book provides an overview of the leading digital technologies and demonstrates how they can be used to improve modern practices in the state and corporate management of regional development in the digital economy. The authors develop the conceptual foundations and put forward practical recommendations. In closing, the authors' conclusions and recommendations are applied to the example of modern Russia, ensuring the practical relevance of the research.

Customer experience engineering applied to the engineering department is rare, but needed. Most companies keep support, UX, engineering, product, and CX separate. To address this gap, this book highlights roles and techniques that are proven to accelerate issue detection and prevention by 30% or more. With the author's vast experience in tech support, he has developed techniques and skills that allow engineers to gain customer insights faster and through new and insightful sources that are within their reach. You will develop a deep understanding of the impact of issues; understand and optimize the speed of the engineering feedback loop (issue resolution time); and develop the ability to calculate the cost of the issues or customer friction to the business (in aggregate and on a case-by-case basis). Organizations can save significant money and add additional revenue by addressing customer friction proactively in collaboration with product, engineering, and site reliability engineering (SRE) functions and reduce the average time of an issue resolution by 80%. The cross-functional leadership, mentoring, and engineering techniques you'll learn from this proactive stance are very valuable and teachable, and this book will show you the path forward. What You Will Learn Gain the techniques and tools necessary to validate customer journey success in production Contribute to customer-centric key performance indicators (KPIs) on executive dashboards Create meaningful insights and data points that allowed the feedback loop to be optimized and efficient Who This Book is For Professionals participating in the value stream of digital software engineering for the benefit of customer experiences, directly or indirectly. You may be an engineer practicing DevOps or site reliability, or you might be a product owner, UX designer, or researcher. You might be working in support and seeking for new ways to engage with your engineering teams.

CHANGE! A Student Guide to Social Action guides students, faculty, and staff with the goal of helping students bring about the change they believe will improve their community. What distinguishes an experiential social action class from other social change courses is that students are actively involved in enacting a policy change of their choice, providing first-hand experience of democracy and power. Students can choose to start a new campaign, keep a campaign going from a previous semester, or join a community campaign. This valuable new edition includes updates to the Student Victories section, reordering and updating of chapters for better student learning, and updates to all of the portfolio assignments.

This monograph discusses software reuse and how it can be applied at different stages of the software development process, on different types of data and at different levels of granularity. Several challenging hypotheses are analyzed and confronted using novel data-driven methodologies, in order to solve problems in requirements elicitation and specification extraction, software design and implementation, as well as software quality assurance. The book is accompanied by a number of tools, libraries and working prototypes in order to practically illustrate how the phases of the software engineering life cycle can benefit from unlocking the potential of data. Software engineering researchers, experts, and practitioners can benefit from the various methodologies presented and can better understand how knowledge extracted from software data residing in various repositories can be combined and used to enable effective decision making and save considerable time and effort through software reuse. Mining Software Engineering Data for Software Reuse can also prove handy for graduate-level students in software engineering.

In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes. Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia and industry. Computational and Methodological Statistics and Biostatistics is composed of three main themes: * Recent developments in theory and applications of statistical distributions;* Recent developments in supervised and unsupervised modelling;* Recent developments in biostatistics; and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others.

Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results. Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included. Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website. This practical and systematic textbook/reference is a "need-to-have" tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a "need to use, need to keep" resource following one's exploration of the subject.

This book recapitulates the major developments in Decision Support Systems (DSS) over the last 30 years in order to evaluate the research areas of decision making and in which direction the field should proceed. As it attempts to find a consensus about the next steps for the future of DSS research, the book also enforces the trends and new technologies currently in use. The book examines topics such as decision analysis for enterprise systems and non-hierarchical networks, integrated solutions for decision support and knowledge management in distributed environments, decision support system evaluation and analysis through social networks, and e-learning and its application to real environments. It clearly presents the evidence to support their cases and attempts to promote an extensive and objective discussion. In addition, the book also reflects on approaches to dead-end ideas and failures in DSS to better understand the lessons learned. The contributions for this book have been written by thought leaders and influential researchers from the EURO Working Group of Decision Support Systems (EWG-DSS).

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.

Work with Db2 to write SQL and access databases using optimized code for the fastest response. This book will give you complete documentation on DB2 via Python for the IBM_db module and provide a number of examples for the usage of each module API. Begin by getting your free version of Db2 for Linux and Windows. While the book concentrates more on the Linux version of Db2, it also covers enough of the Windows version so that you're comfortable with obtaining and installing Db2 on your version of Windows. Next, you'll see how to install the sample database that comes with Db2, and take some data from the web to design a database around it, including tables and indexes. For Db2 to be really useful you need to use strong SQL expressions. This book provides specific examples of how to avoid using poor ones that can cause extra processing time for the query. Lastly, you'll look at each API in the ibm_db and ibm_db_dbi module. This module is not sponsored by IBM and must be installed separately from the Db2 database. After reading Foundation Db2 and Python you'll be able to install Db2 on Windows or Linux, and perform backups and restore data. What You'll Learn Obtain and install Db2 properly on Linux and Windows Create databases and load them on Db2 Work with ibm_db and ibm_db_dbi API modules for Python Write SQL for Db2 Review the future of the ibm_db Python module Who This Book Is For Python programmers and DB2 administrators interested in building application with Python and DB2

This book focuses on Fintech regulation in Asian, situating local developments in broader economic, regulatory and technological contexts. Over the last decade, Fintech - broadly defined as the use of new information technologies to help financial institutions and intermediaries compete in the marketplace - has disrupted the financial services sector. Like other 21st century technological developments, Fintech is a global phenomenon that plays out in local economic, political and regulatory contexts, and this dynamic interplay between global trends and local circumstances has created a complex and fast-changing landscape. Diverse stakeholders (most obviously incumbent financial service providers, tech start-ups and regulators) all pursue a competitive edge against a background of profound uncertainty about the future direction and possible effects of multiple emerging technologies. Compounding these difficulties are uncertainties surrounding regulatory responses. Policymakers often struggle to identify appropriate regulatory responses and increasingly turn to policy experimentation. Such issues add to the challenges for the various actors operating in the Fintech space. This situation is particularly fluid in Asia, since many jurisdictions are seeking to establish themselves as a regional hub for new financial services.

* A comprehensively updated revision of a book regarded by many as one the leading and authoritative titles for practitioners, academics and students in the domain of information systems and technology (IS/IT) strategy. * Presents a structured framework with tools, techniques and ways of thinking which provide a practical approach to building a digital strategy, expressed primarily in the language of business and management. * Brings together the implications of the significant advances in IT and the most useful current thinking, research, and experiences concerning the business impact and strategic opportunities created by IS/IT. *Peppard and Ward discuss the key questions that managers have to grapple with of where, when and how to invest in IS/IT, which is why a IS/IT (or digital) strategy is required.

Digital technologies are currently dramatically changing healthcare. This book introduces the reader to the latest digital innovations in healthcare in fields such as artificial intelligence, points out new ways in patient care and describes the limits of its application. It also offers essential guidance in the form of structured and authoritative contributions by domain experts spanning from artificial intelligence to hospital management to radiology to dentistry to preventive medicine. Furthermore, it shares ideas and experiences of industry veterans, in particular on how IT-driven solutions could solve long-standing issues in the fields of healthcare and hospitalization. It also gives advice on what new digital technologies to consider for becoming a healthcare market leader in the future. Taken together, these contributions provide a "road map" to guide decision makers, physicians, academics, industry representatives and other interested readers to understand the large impact of digital technology on healthcare today and its enormous potential for future development.

This book highlights the importance of talent management practices in recruiting, developing and retaining talented professionals in the digital and IT&C industry. It unpacks the distinctive characteristics of 'digital talent' represented by a wide spectrum of professionals and managers with digital abilities, competencies and skills who add considerable value to organizations and industries worldwide. It shows that despite digital talent's increased variety and significant contribution to digital transformation processes, much of the existing human resource and talent management research and practice fail to account for their distinctiveness. This book calls for the need for a new kind of talent management, referred to as 'digital talent management' (DTM) that is applicable to digital talent and decidedly integrates digital talent's distinctive characteristics into talent management strategies and practices in a human-centered manner. Drawing upon existing, yet disconnected, streams of literature and empirical evidence derived from the information technology and communication (IT&C) industry, this book defines digital talent and delineates strategies to attract, develop and retain them for an uncertain and renewed future.

This book highlights the opportunities and risks of digitalization and digital transformation for our global economy at both the micro and macro level. Experts from various fields, presenting both scientific and practice-oriented perspectives, identify and critically analyse areas of tension and development potential in connection with new business models and sustainability efforts in our society. It is divided into four parts, the first of which highlights new technological advances in areas such as blockchain, cryptocurrencies and fintechs, and discusses the challenges they pose for public regulation. The second part illustrates digitalization's effects on and potential advantages for public welfare, focusing on key areas such as education, health and smart cities. The third part focuses on challenges for corporate and public management, particularly for leadership and Corporate Social Responsibility, while the fourth part discusses new dimensions for analysis based on big data. The contributions gathered here are partly an outcome of the International Conference on Digitalization, Digital Transformation and Sustainability held in Budapest in October 2020 and generously supported by the Hanns Seidel Foundation.