This book focuses on the implementation of digital strategies in the public sectors in the US, Mexico, Brazil, India and Germany. The case studies presented examine different digital projects by looking at their impact as well as their alignment with their national governments' digital strategies. The contributors assess the current state of digital government, analyze the contribution of digital technologies in achieving outcomes for citizens, discuss ways to measure digitalization and address the question of how governments oversee the legal and regulatory obligations of information technology. The book argues that most countries formulate good strategies for digital government, but do not effectively prescribe and implement corresponding policies and programs. Showing specific programs that deliver results can help policy makers, knowledge specialists and public-sector researchers to develop best practices for future national strategies.

Technology in the world today impacts every aspect of society and has infiltrated every industry, affecting communication, management, security, etc. With the emergence of such technologies as IoT, big data, cloud computing, AI, and virtual reality, organizations have had to adjust the way they conduct business to account for changing consumer behaviors and increasing data protection awareness. The Handbook of Research on Social and Organizational Dynamics in the Digital Era provides relevant theoretical frameworks and the latest empirical research findings on all aspects of social issues impacted by information technology in organizations and inter-organizational structures and presents the conceptualization of specific social issues and their associated constructs. Featuring coverage on a broad range of topics such as business management, knowledge management, and consumer behavior, this publication seeks to advance the practice and understanding of technology and the impacts of technology on social behaviors and norms in the workplace and society. It is intended for business professionals, executives, IT practitioners, policymakers, students, and researchers.

This book addresses major challenges faced by farmers and the technological solutions based on Internet of Things (IoT). A major challenge in agriculture is cultivating and supplying high-quality produce at the best. Currently, around 50% of global farm produce never reaches the end consumer due to wastage and suboptimal prices. The book presents solutions that reduce the transport costs, improve the predictability of prices based on data analytics and the current market conditions, and reduce the number of middle steps and agents between the farmer and the end consumer. It discusses the design of an IoT-based monitoring system to analyze crop environments and a method to improve the efficiency of decision-making by analyzing harvest statistics. Further, it explores climate-smart methods, known as smart agriculture, that have been adopted by a number of Indian farmers.

This volume is the latest addition to the ""Cases on Information Technology Series"", a series which provides a collection of case studies focusing on IT implementation in organizations. The cases included in ""Cases on Information Technology: Lessons Learned, Volume 7"" cover a variety of IT initiatives, including enterprise systems, wireless technologies, rebuilding operating systems after destruction, and implementation within non-profit organizations. Each case includes integral information regarding organizations working with IT, including key individuals involved, intelligent steps taken or perhaps overlooked, and the final project outcomes. This volume is useful to IT managers and researchers, as it describes various scenarios of IT implementation and also unfortunate downfalls. Using the real-life situations as facilitators for classroom discussion, professors and students will benefit as well from this collection of cases.

This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics and urban environments. The book gathers selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic. The workshop was originally to be held on June 24-26, 2020, but had to be postponed as a consequence of the COVID-19 pandemic. Initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, the IWFOS workshops provide a forum to discuss the latest trends and advances in functional statistics and related fields, and foster the exchange of ideas and international collaboration in the field.

This book provides an overview of predictive methods demonstrated by open source software modeling with Rattle (R') and WEKA. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on prescriptive analytics. The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis. Chapter 1 gives an overview in the context of knowledge management. Chapter 2 discusses some basic data types. Chapter 3 covers fundamentals time series modeling tools, and Chapter 4 provides demonstration of multiple regression modeling. Chapter 5 demonstrates regression tree modeling. Chapter 6 presents autoregressive/integrated/moving average models, as well as GARCH models. Chapter 7 covers the set of data mining tools used in classification, to include special variants support vector machines, random forests, and boosting. Models are demonstrated using business related data. The style of the book is intended to be descriptive, seeking to explain how methods work, with some citations, but without deep scholarly reference. The data sets and software are all selected for widespread availability and access by any reader with computer links.

This book is an outcome of the 33rd International Conference EnviroInfo 2019, held at the University of Kassel, Germany. It presents a selection of papers that describe innovative scientific approaches and ongoing research in environmental informatics and the emerging field of computational sustainability. The respective articles cover a broad range of scientific aspects including advances in core technologies such as earth observation, environmental modelling, big data and machine learning, as well as applications of ICT solutions intended to support societal transformation processes toward the more sustainable management of resource use, transportation and the energy supply. Given its scope, the book is essential reading for scientists, experts and students in these fields of research.

This work highlights the coming age of management information systems for all types of executives by focusing on executive information systems, or EIS. Serving as a data-intensive system, an EIS offers a snapshot of a company's past and present operations as a way of predicting the future. In this book, Robert Thierauf provides a complete picture of executive information systems, from an introduction of what these systems are all about, to the hardware, software, and applications that form the basis of an EIS environment.

The work is divided into four basic sections. The first provides an overview of executive information systems, discussing the real need for an EIS, the essential characteristics underlying it, and its relationship to prior management information systems. The types of executive decision making typically found in an EIS environment, illustrated with specific examples, are also examined. The second section focuses on the computer hardware and software that is useful within an EIS operating mode, along with on-line databases that assist executives in decision making. The development of executive information systems is covered in section three, which features current approaches for executives and their staffs as well as methods to be followed by the Management Information Systems department. Finally, section four addresses various aspects of working in an EIS environment, including strategic planning, marketing, manufacturing, finance, and personnel. A master case study is presented, and each topic is explored in relation to it. Typical EIS applications are also described for each of the topic areas. With its combination of both EIS theory and practical applications, this work will be a valuable resource for senior executives and MIS professionals as well as for students of management and information systems. Public, academic, and business libraries will also find it to be a useful addition to their collections.

This book is based on the work of the YEEES Research Centre, an international network of scientists from partner universities in Germany, Mozambique, Namibia and South Africa. It presents inter- and transdisciplinary research that explores different ways of understanding resilience, an essential characteristic for systems, organizations and people - providing them with strength in the face of attacks and challenges, and both enabling and fostering constant adaptation and improvement. Building resilience to face today's ever-changing societal and environmental realities requires unbiased research activities that transcend the borders of countries and academic disciplines alike. The research addressed in this book, thus, is multidisciplinary and includes contributions to areas such as sustainable agriculture, entrepreneurial ecosystems, and smart communities, as well as groundbreaking work on skills development and ICT education. Highlighting the variety of research activities and their outcomes, this book offers a valuable resource for researchers and practitioners in the fields of sustainable resilience development.

The most thrilling and challenging intellectual issues of humanity - whether and how a consistent account of reality can be obtained, which field of knowledge is capable to deal with the whole of reality and its formal representation, and how powerful intelligent machines can be brought into existence - are research areas demanding innovative and comprehensive study.""Reality, Universal Ontology and Knowledge Systems: Toward the Intelligent World"" provides cutting-edge research on reality, its nature and fundamental structure, and how it may be effectively represented both by human minds and intelligent machines. Striving to describe a standard world model and universal formal ontology, it offers a uniformly organized human knowledge. It includes powerful reasoning systems, and secure communication interoperability between two species of intelligences, as well as existing human beings and nascent computing reasoning systems promising the profound revolution in human values and ways of life.

In this book, the authors analyze big data on global interdependence caused by the flows of commodities, money, and people, using a network science approach to obtain differing views of globalization and to clarify the facts on isolation of communities. Globalization reduces international economic inequality, i.e., it allows emerging countries to catch up while it increases relative poverty in some advanced countries. How should this trade-off between international and domestic inequalities be resolved? At the same time, the reduction of biocultural diversity caused by globalization needs to be avoided. What kind of change is required in local communities to conserve biocultural diversity? On the issue of commodity flow, research results of the supply-chain network, isolation in industry, and resource flows and stocks are presented in this book. For monetary flow, ownership networks, value-added networks, and profit shifting were studied; and regarding the flow of people, linkage of ethnic groups, immigrant assimilation, and refugees were examined. Based on the resulting view of globalization and isolation, the development of the isolation index using machine learning is discussed. Finally, recommendations for evidence-based policymaking in the United Nations are considered.

This edited book presents the state-of-the-art of applying fuzzy logic to managerial decision-making processes in areas such as fuzzy-based portfolio management, recommender systems, performance assessment and risk analysis, among others. Presenting the latest research, with a strong focus on applications and case studies, it is a valuable resource for researchers, practitioners, project leaders and managers wanting to apply or improve their fuzzy-based skills.

This uniquely accessible book helps readers use CABology to solve real-world business problems and drive real competitive advantage. It provides reliable, concise information on the real benefits, usage and operationalization aspects of utilizing the "Trio Wave" of cloud, analytic and big data. Anyone who thinks that the game changing technology is slow paced needs to think again. This book opens readers' eyes to the fact that the dynamics of global technology and business are changing. Moreover, it argues that businesses must transform themselves in alignment with the Trio Wave if they want to survive and excel in the future. CABology focuses on the art and science of optimizing the business goals to deliver true value and benefits to the customer through cloud, analytic and big data. It offers business of all sizes a structured and comprehensive way of discovering the real benefits, usage and operationalization aspects of utilizing the Trio Wave.

Public Information Technology: Policy and Management Issues constitutes a survey of many of the most important dimensions of managing information technology in the public sector. Written by noted academics and public administration practitioners, this book addresses general policy and administrative issues in this arena as well as the information technology skills needed by public managers.

The main objective of knowledge management is to support the creation, transfer, and application of knowledge. Researchers and practitioners have emphasized the important role of knowledge management in electronic business and IT outsourcing relationships. ""Knowledge Management Systems: Value Shop Creation"" is based on the premise that it is difficult, if not impossible, to manage an organization without at least some understanding of knowledge management and knowledge management systems. ""Knowledge Management Systems: Value Shop Creation"" combines knowledge management with other subject areas within the management information systems field. The scholarly value of this book can be found in insights generated from the contingent approach to linking knowledge management to other IT management topics and its uses.

This book presents a proposal for designing business process management (BPM) systems that comprise much more than just process modelling. Based on a purified Business Process Model and Notation (BPMN) variant, the authors present proposals for several important issues in BPM that have not been adequately considered in the BPMN 2.0 standard. It focusses on modality as well as actor and user interaction modelling and offers an enhanced communication concept. In order to render models executable, the semantics of the modelling language needs to be described rigorously enough to prevent deviating interpretations by different tools. For this reason, the semantics of the necessary concepts introduced in this book are defined using the Abstract State Machine (ASM) method. Finally, the authors show how the different parts of the model fit together using a simple example process, and introduce the enhanced Process Platform (eP2) architecture, which binds all the different components together. The resulting method is named Hagenberg Business Process Modelling (H-BPM) after the Austrian village where it was designed. The motivation for the development of the H-BPM method stems from several industrial projects in which business analysts and software developers struggled with redundancies and inconsistencies in system documentation due to missing integration. The book is aimed at researchers in business process management and industry 4.0 as well as advanced professionals in these areas.

This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership - while others concern more specific business situations (e.g., initial public offering, growth strategies, etc.). The important matter of selecting the right skills and people for an effective team will be extensively explained, and practical ways to recognize them and understanding their personalities will be provided. Finally, few relevant technological future trends will be acknowledged (i.e., IoT, Artificial intelligence, blockchain, etc.), especially for their close relation with the increasing amount of data and our ability to analyse them faster and more effectively.

This is the first book to explore how Semantic Web technologies (SWTs) can be used to create intelligent engineering applications (IEAs). Technology-specific chapters reflect the state of the art in relevant SWTs and offer guidelines on how they can be applied in multi-disciplinary engineering settings characteristic of engineering production systems. In addition, a selection of case studies from various engineering domains demonstrate how SWTs can be used to create IEAs that enable, for example, defect detection or constraint checking. Part I "Background and Requirements of Industrie 4.0 for Semantic Web Solutions" provides the background information needed to understand the book and addresses questions concerning the semantic challenges and requirements of Industrie 4.0, and which key SWT capabilities may be suitable for implementing engineering applications. In turn, Part II "Semantic Web-Enabled Data Integration in Multi-Disciplinary Engineering" focuses on how SWTs can be used for data integration in heterogeneous, multi-disciplinary engineering settings typically encountered in the creation of flexible production systems. Part III "Creating Intelligent Applications for Multi-Disciplinary Engineering" demonstrates how the integrated engineering data can be used to support the creation of IEAs, while Part IV "Related and Emerging Trends in the Use of Semantic Web in Engineering" presents an overview of the broader spectrum of approaches that make use of SWTs to support engineering settings. A final chapter then rounds out the book with an assessment of the strengths, weaknesses and compatibilities of SWTs and an outlook on future opportunities for applying SWTs to create IEAs in flexible industrial production systems. This book seeks to build a bridge between two communities: industrial production on one hand and Semantic Web on the other. Accordingly, stakeholders from both communities should find this book useful in their work. Semantic Web researchers will gain a better understanding of the challenges and requirements of the industrial production domain, offering them guidance in the development of new technologies and solutions for this important application area. In turn, engineers and managers from engineering domains will arrive at a firmer grasp of the benefits and limitations of using SWTs, helping them to select and adopt appropriate SWTs more effectively. In addition, researchers and students interested in industrial production-related issues will gain valuable insights into how and to what extent SWTs can help to address those issues.

This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics and supply chain management, such as the use of big data analytics in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed in the book are co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality constrained portfolio problem; and determining initial, basic and feasible solutions for transportation problems by means of the "supply demand reparation method" and "continuous allocation method." In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed deteriorating items varying with ramp type demand rate and shortages; an inventory model with shortages and deterioration for three different demand rates; outlier labeling methods for medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and the design of a "least cost ration formulation application for cattle"; a preservation technology model for deteriorating items with advertisement dependent demand and trade credit; a time series model for stock price forecasting in India; and asset pricing using capital market curves. The book offers a valuable asset for all researchers and industry practitioners working in these areas, giving them a feel for the latest developments and encouraging them to pursue further research in this direction.

Hands-on tools for implementing, designing, and managing a successful architectural process within a corporation

Enterprise architecture holds the key to an organization's success. Yet for many companies, the promised benefits of IT architecture still elude them. Dynamic Enterprise Architecture provides readers with a better understanding of the processes involved in successfully employing architectural thinking and empowers them with the instruments to analyze their own situations and identify points of improvement.

Based on the authors' decades of practical experience in the field, Dynamic Enterprise Architecture: Provides step-by-step guidance to help organizations successfully introduce an enterprise architecture system Focuses on the processes to make enterprise architecture work Discusses ways to avoid bottlenecking in enterprise architecture Provides tips and best practices for implementing the processes involved Shows readers the most effective ways to use IT in their organizations

Make the most out of enterprise architecture and achieve your business goals with the step-by-step guidelines found in Dynamic Enterprise Architecture.

This book offers readers a deeper understanding of the Cyberspace, of how institutions and industries are reinventing themselves, helping them excel in the transition to a fully digitally connected global economy. Though technology plays a key part in this regard, societal acceptance is the most important underlying condition, as it poses pressing challenges that cut across companies, developers, governments and workers. The book explores the challenges and opportunities involved, current and potential future concepts, critical reflections and best practices. It addresses connected societies, new opportunities for governments, the role of trust in digital networks, and future education networks. In turn, a number of representative case studies demonstrate the current state of development in practice.

How do we define the nature of our business, gather everything that we know about it, and then centralize our information in one, easily accessed place within the organization? Breslin and McGann call such knowledge our ways of working and the place where it will be found a business knowledge repository. All of a company's accumulated operations data, its manuals and procedures, its records of compliance with myriad regulations, its audits, disaster recovery plans--are essential information that today's management needs at its fingertips, and information that tomorroW's management must be sure can easily be found. Breslin and McGann show clearly and comprehensively how business knowledge repositories can be established and maintained, what should go into them and how to get it out, who should have access, and all of the other details that management needs to make the most of this valuable resource and means of doing business. An essential study and guide for management at upper levels in all types of organizations, both public and private.

Breslin and McGann show that once an organization's knowledge of itself is formulated into its ways of working, its so-called object orientation makes it easily maintained. The repository approach to organizing and consolidating knowledge makes it possible for all of its potential users to access it easily, without having to go to one source for one thing they need and to another for another thing, a tedious and costly procedure in many organizations that have allowed their information and knowledge resources to not only grow but become duplicated as well. The repository approach also makes it possible for management to organize and access information by job functions, and to make it available to employees more easily in training situations. Regulators and auditors are also more easily served. As a result, CFOs will find their annual audit and various compliance fees considerably reduced. Breslin and McGann's book is thus a blueprint for the creation of knowledge repositories and a discussion of how graphical communication between information systems creators and their client end users can be made to flow smoothly and efficiently.

This book presents SAP Next-Gen, an innovation community for SAP Leonardo. It is intended for next generation business leaders, Chief Digital Officers, Chief Innovation Officers, Chief Information Officers and IT professionals who are defining the vision, strategy, technologies and organizational changes needed to drive their exponential enterprise and to innovate with purpose. The book opens with an introduction to turning bold ideas into reality with a purpose-driven mindset supporting the 17 United Nations Global Goals. Part 1 focuses on what's at stake including Digital - The New Normal, Exponential Growth, and Innovation in the 21st century. Part 2 introduces readers to the SAP Next-Gen matchmaking model, and readers are invited to join SAP Next-Gen clubs for industries, technologies, and methodologies. Readers also learn about the Silicon Valleys of the world, make vs. buy vs. join, and where to learn more and get engaged with SAP Next-Gen. SAP Next-Gen is an innovation community for SAP Leonardo supporting SAP's 355,000+ customers across 25 industries in 180+ countries. SAP Next-Gen enables customers and partners to connect with academic thought leaders, researchers, and students in the SAP Next-Gen network of 3,200+ educational institutions across 111 countries worldwide, as well as with startups, tech community partners, venture firms, purpose driven partners, and SAP experts.

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. Offering readers a closer look at design thinking, and its innovation processes and methods, this volume addresses the new and growing field of neurodesign, which applies insights from the neurosciences in order to improve design team performance. Thinking and devising innovations are inherently human activities - and so is design thinking. Accordingly, design thinking is not merely the result of special courses or of being gifted or trained: it is a way of dealing with our environment and improving techniques, technologies and life in general. As such, 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.

This is the second of a two-part guide to quantitative analysis using the IBM SPSS Statistics software package; this volume focuses on multivariate statistical methods and advanced forecasting techniques. More often than not, regression models involve more than one independent variable. For example, forecasting methods are commonly applied to aggregates such as inflation rates, unemployment, exchange rates, etc., that have complex relationships with determining variables. This book introduces multivariate regression models and provides examples to help understand theory underpinning the model. The book presents the fundamentals of multivariate regression and then moves on to examine several related techniques that have application in business-orientated fields such as logistic and multinomial regression. Forecasting tools such as the Box-Jenkins approach to time series modeling are introduced, as well as exponential smoothing and naive techniques. This part also covers hot topics such as Factor Analysis, Discriminant Analysis and Multidimensional Scaling (MDS).