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 provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge. The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are needed for real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.

This book intends to provide a reference manual to assist professionals and academics on further insights regarding: the impact of digital technologies in business, how to implement digital technologies, solutions for specific digital technologies barriers, and much more. Digital transformation marks a rethinking of how an organization uses technology, people, and processes in pursuit of new business models and new revenue streams, driven by changes in customer expectations around products and services. For many enterprises that build traditional goods, this means building digital products, such as a mobile applications or an ecommerce platform. To do so, they must use and integrate digital technologies. The pace of change is increasing. Organizations need to adapt or risk to disappear under innovators entrance in the market. With new digital technologies growing in an exponential rate in the last few decades, organizations are facing even more complex contexts. Managers are now pressed to take efficient decisions. The editors encourage the use of research methods such as Systematic Literature Review (SLR) or Multivocal Literature Review (MLR) (since many new technologies are usually evolved first by practitioners). However, other research methods can also be appreciated as case studies or experiments.

This book is designed to help MIS and information center managers and their staffs to efficiently and cost effectively meet the needs of end-users in their organizations. Focusing on managerial aspects of information centers, Robert J. Thierauf explores the ways in which new information technology--spreadsheets, query languages, report writers, word processing, etc.--can be placed in the hands of end-users without the interdepartmental conflict and loss of systems control often associated with such transitions.

The International Conference on Informatics and Management Science (IMS) 2012 will be held on November 16-19, 2012, in Chongqing, China, which is organized by Chongqing Normal University, Chongqing University, Shanghai Jiao Tong University, Nanyang Technological University, University of Michigan, Chongqing University of Arts and Sciences, and sponsored by National Natural Science Foundation of China (NSFC). The objective of IMS 2012 is to facilitate an exchange of information on best practices for the latest research advances in a range of areas. Informatics and Management Science contains over 600 contributions to suggest and inspire solutions and methods drawing from multiple disciplines including: Computer Science Communications and Electrical Engineering Management Science Service Science Business Intelligence

This book provides a theoretical and application-oriented analysis of deterministic scheduling problems in advanced planning and computer systems. The text examines scheduling problems across a range of parameters: job priority, release times, due dates, processing times, precedence constraints, resource usage and more, focusing on such topics as computer systems and supply chain management. Discussion includes single and parallel processors, flexible shops and manufacturing systems, and resource-constrained project scheduling. Many applications from industry and service operations management and case studies are described. The handbook will be useful to a broad audience, from researchers to practitioners, graduate and advanced undergraduate students.

This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.

Uses practical business cases in regional Australia to illustrate opportunities and challenges confronting businesses in non metropolitan regions

There are many books written for the accounting and finance community. However, there are very few books written to help the non-financial career professionals who still need to understand the conceptual fundamentals of accounting and finance. In 20 years of teaching this material to non-financial professionals, Dr. Bonner has perfected a teaching approach that works to help the non-financial professional engage with the material to use financial information in leveraging their career without becoming overloaded with information that is not helpful to them. Learning this material takes repetition, application, and building the thinking processes necessary for effectiveness. Many think the challenge with finance is the math, but as this book will demonstrate, it is a conceptual problem. If you understand the conceptual framework, you will understand the math. Dr. Julie Bonner is currently a tenured professor at Central Washington University in the information technology and administrative management department. Her career has spanned business and education for over 30 years. Initially, she received a Bachelor of Science degree in accounting, whereafter she earned an MBA and then a doctorate in organizational leadership.

This book presents the characteristics and benefits industrial organizations can reap from the Industrial Internet of Things (IIoT). These characteristics and benefits include enhanced competitiveness, increased proactive decision-making, improved creativity and innovation, augmented job creation, heightened agility to respond to continuously changing challenges, and intensified data-driven decision making. In a straightforward fashion, the book also helps readers understand complex concepts that are core to IIoT enterprises, such as Big Data, analytic architecture platforms, machine learning (ML) and data science algorithms, and the power of visualization to enrich the domains experts' decision making. The book also guides the reader on how to think about ways to define new business paradigms that the IIoT facilitates, as well how to increase the probability of success in managing analytic projects that are the core engine of decision-making in the IIoT enterprise. The book starts by defining an IIoT enterprise and the framework used to efficiently operate. A description of the concepts of industrial analytics, which is a major engine for decision making in the IIoT enterprise, is provided. It then discusses how data and machine learning (ML) play an important role in increasing the competitiveness of industrial enterprises that operate using the IIoT technology and business concepts. Real world examples of data driven IIoT enterprises and various business models are presented and a discussion on how the use of ML and data science help address complex decision-making problems and generate new job opportunities. The book presents in an easy-to-understand manner how ML algorithms work and operate on data generated in the IIoT enterprise. Useful for any industry professional interested in advanced industrial software applications, including business managers and professionals interested in how data analytics can help industries and to develop innovative business solutions, as well as data and computer scientists who wish to bridge the analytics and computer science fields with the industrial world, and project managers interested in managing advanced analytic projects.

In this volume recent advances in the use of modern quantitative models for the analysis of various problems related to the dynamics of social and economic systems are presented. The majority chapters describe tools and techniques of broadly perceived computational intelligence, notably fuzzy logic, evolutionary computation, neural networks and some non-standard probabilistic and statistical analyses. Due to the high complexity of the systems and problems considered, in many situations it is necessary to consider at the same time analytic, topological and statistical aspects and apply appropriate procedures and algorithms. This volume is a direct result of vivid discussions held during the Fifth International Workshop on Dynamics of Social and Economical Systems (DYSES) which was held at Benevento, Italy September 20-25, 2010, as well as a couple of post-workshop meetings and consultations.

This book is based on the review of literature on different themes related to business and management in the Asia Pacific context. All seven chapters included in this book explore the past, present and future of business and research. They cover diverse topics in the Asia Pacific context ranging from different ways of thinking to innovation implementation and efficiency, responsible tourism, internal marketing to leadership. This book will be useful for researchers, practitioners and policy makers. The chapters in this book were originally published as a special issue of the Asia Pacific Business Review.

Within entrepreneurship education, Team Academy is seen by some as an innovative pedagogical model that enhances social connectivity, as well as experiential, student-centred, and team-based learning. It also creates spaces for transformative learning to occur. This second book of the Routledge Focus on Team Academy book series includes chapters from contributors working with the TA methodology in academic institutions around the world that discuss the challenges, benefits, and approaches to embedding the TA methodology in practice (around coaching, assessment, transformative learning, partnerships, programme evolution, etc.). This book is aimed at academics, practitioners, and learners engaged in the Team Academy methodology, pedagogy, and model, as well as those interested in the area of entrepreneurial team learning. Readers will be inspired to innovate in their delivery methodologies and to explore learning-by-doing approaches to creating value. The book also aims to challenge the discourse around entrepreneurship and entrepreneurial activities, offering insights, research, stories, and experiences from those learning and working in the Team Academy approach.

Systemic Entrepreneurship focuses on creating an awareness of systemic entrepreneurship and illustrates the fact that one needs to approach entrepreneurial support activities from many different angles.

This edited three volume edition brings together significant papers previously published in the Journal of information Technology (JIT) over its 30 year publication history. The three volumes of Enacting Research Methods in Information Systems celebrate the methodological pluralism used to advance our understanding of information technology's role in the world today. In addition to quantitative methods from the positivist tradition, JIT also values methodological articles from critical research perspectives, interpretive traditions, historical perspectives, grounded theory, and action research and design science approaches. Volume 1 covers Critical Research, Grounded Theory, and Historical Approaches. Volume 2 deals with Interpretive Approaches and also explores Action Research. Volume 3 focuses on Design Science Approaches and discusses Alternative Approaches including Semiotics Research, Complexity Theory and Gender in IS Research. The Journal of Information Technology (JIT) was started in 1986 by Professors Frank Land and Igor Aleksander with the aim of bringing technology and management together and bridging the 'great divide' between the two disciplines. The Journal was created with the vision of making the impact of complex interactions and developments in technology more accessible to a wider audience. Retaining this initial focus, the JIT has gone on to extend into new and innovative areas of research such as the launch of JITTC in 2010. A high impact journal, JIT shall continue to publish leading trends based on significant research in the field.

Technological innovation is a core aspect of corporate and national competitiveness and it is not only complex-requiring cooperation and coordination among many stakeholders-but it also involves high risk due to uncertainty. Financial markets are a key to successful technological innovation. This book looks at how traditional financing and non-traditional ones transform corporate innovation strategy. This book reviews Korean companies to illustrate the impact of financialization on technological innovation through the relationships among financialization, managerial myopia and short-termism of innovation strategy. It does so by conducting an empirical study using Korean firm and USPTO data from the period of 1980 to 2017. By analyzing the innovation capabilities of Korean companies and presenting indicators of technological competitiveness, it offers insights into how financialization has influenced organizational behaviour, causing them to shift strategy formulation, decision making for production, investment and technological innovation away from a long-term perspective to short-term one. This concise book will be of interest to those interested in strategy and entrepreneurship innovation, especially policy makers focusing on financialization or national level innovation strategies.

Correctly functioning evaluation systems directly influence the efficient and effective planning and implementation of projects and the achievement of organisational objectives. This book critically analyses the results of research dedicated to mixed intelligent systems for project evaluation, taking into account the current state of knowledge in the field of project management. It argues for the need to move away from classical concepts and deploy interdisciplinary research methods in the development of comprehensive project evaluation systems. Considering contemporary issues relating to project evaluation, the author deals with both quantitative and qualitative evaluation methods and the problems surrounding systems that integrate them, before discussing the process of modelling mixed intelligent systems. Mixed Intelligent Systems makes a thought-provoking case for harnessing interdisciplinary methods and new ideas in project management research when developing evaluation systems.

The book investigates the entrepreneurial marketing (EM) concept within the broader discipline of international entrepreneurship. The analysis of this concept, and designing a model of EM antecedents, elements, and outcomes that was tested on the basis of empirical studies covering companies from three European countries, explores and develops the field of international marketing and entrepreneurship. The book examines the role of entrepreneurial marketing in the internationalization processes of new ventures and adopts both qualitative and quantitative methods for analyzing the antecedents and characteristics of entrepreneurial marketing, as well as their relationships with internationalization activities and firms' performances. It goes on to show how the application of entrepreneurial marketing may lead to an accelerated internationalization of companies originating from a transition market, as well as the Western-European markets. It addresses these topics with regards to entrepreneurial marketing and management and will be of interest to researchers, academics, managers, entrepreneurs, and students in the fields of international business, international marketing, and entrepreneurship.

This book provides a comprehensive approach to the study of policy analytics, modelling and informatics. It includes theories and concepts for understanding tools and techniques used by governments seeking to improve decision making through the use of technology, data, modelling, and other analytics, and provides relevant case studies and practical recommendations. Governments around the world face policy issues that require strategies and solutions using new technologies, new access to data and new analytical tools and techniques such as computer simulation, geographic information systems, and social network analysis for the successful implementation of public policy and government programs. Chapters include cases, concepts, methodologies, theories, experiences, and practical recommendations on data analytics and modelling for public policy and practice, and addresses a diversity of data tools, applied to different policy stages in several contexts, and levels and branches of government. This book will be of interest of researchers, students, and practitioners in e-government, public policy, public administration, policy analytics and policy informatics.

Over the last few years, we have witnessed an upsurge of enthusiasm about cryptocurrencies and, more generally, the so-called blockchain technology. In this new and updated edition, the authors explore what exactly these new technologies entail and promise. They argue that to understand the potential challenges and further developments in the market, one needs to develop an understanding of what needs these innovations fulfill and what business models are consistent with their use. For that, we need to sufficiently understand both the technology and how it affects the economic forces at play. This book goes beyond the headlines that say "blockchain will decentralize everything" and provides in-depth, rigorous analysis of what can be effectively decentralized and how this decentralization will work. The book draws not only on the general knowledge of digital currencies and blockchain technologies, but also on recent academic research on the topic. Featuring a fully updated chapter on cryptocurrencies and new chapters on smart contracts and enterprise blockchains, this book is critical reading for those interested in how technology developments impact business and society.

* Unlike other books on differentiation strategy, goes into detailed, clear explanations of the underlying concepts and principles * Goes beyond general guidelines to provide actionable, 'how to' details to create a differentiation strategy * Based on a process with proven results for large clients in such industries as hospitality management

This book introduces, explains, and illustrates the theories, concepts, and methods needed for sound enterprise engineering. These are based on foundational insights, specifically those concerning the employee-centric theory of organization, which are put into practice by coherently and consistently applying them to enterprise design and change. The book consists of five main chapters, the first of which emphasizes the importance of linking foundational insights with the enterprise engineering design science for practicing them in enterprise design within the scope of enterprise governance concerned with enterprise change. Chapter 2 summarizes the necessary philosophical, ontological and ideological foundations of enterprise design and change. Subsequently, chapter 3 outlines essential aspects of enterprise change and describes the relation between enterprise governance and the process of enterprise design, while chapter 4 details the enterprise engineering design science and the actual enterprise design process, its various perspectives and both its intermediate and final results. Lastly, chapter 5 illustrates in detail the application of all the process steps in a single, extensive example. In this way, the book shows how all the cornerstones of enterprise design and change, as well as the employee-centric theory of organization can be applied. The book is mainly intended for students in areas such as business administration, management and organization science, governance, and enterprise and information systems design. However, professionals working in these areas will also benefit from the book, as it provides them with all the elements needed for engineering enterprise design, and details their application.

This book integrates the concepts of big data analytics into mental health practice and research. Mental disorders represent a public health challenge of staggering proportions. According to the most recent Global Burden of Disease study, psychiatric disorders constitute the leading cause of years lost to disability. The high morbidity and mortality related to these conditions are proportional to the potential for overall health gains if mental disorders can be more effectively diagnosed and treated. In order to fill these gaps, analysis in science, industry, and government seeks to use big data for a variety of problems, including clinical outcomes and diagnosis in psychiatry. Multiple mental healthcare providers and research laboratories are increasingly using large data sets to fulfill their mission. Briefly, big data is characterized by high volume, high velocity, variety and veracity of information, and to be useful it must be analyzed, interpreted, and acted upon. As such, focus has to shift to new analytical tools from the field of machine learning that will be critical for anyone practicing medicine, psychiatry and behavioral sciences in the 21st century. Big data analytics is gaining traction in psychiatric research, being used to provide predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. Personalized Psychiatry - Big Data Analytics in Mental Health provides a unique opportunity to showcase innovative solutions tackling complex problems in mental health using big data and machine learning. It represents an interesting platform to work with key opinion leaders to document current achievements, introduce new concepts as well as project the future role of big data and machine learning in mental health.

This book presents the latest findings and ongoing research in the field of environmental informatics. It addresses a wide range of cross-cutting activities, such as efficient computing, virtual reality, disruption management, big data, open science and the internet of things, and showcases how these green information & communication technologies (ICT) can be used to effectively address environmental and societal challenges. Presenting a selection of extended contributions to the 32nd edition of the International Conference EnviroInfo 2018, at the Leibniz Supercomputing Centre in Garching near Munich, it is essential reading for anyone looking to expand their expertise in the area.

This book is open access under a CC BY-NC 4.0 license. This volume presents several case studies highlighting the latest findings in Industry 4.0 projects utilizing S-BPM features. Their potential is explored in detail, while the limits of engineering a company from a communication-centred perspective are also discussed. After a general introduction and an overview of the book in chapter 1, chapter 2 starts by condensing the industrial challenges driven by the German "Industry 4.0" trend to form a concrete vision for future production industries. Subsequently, chapter 3 introduces the basic concepts of S-BPM and its capabilities, in particular for supporting the restructuring of processes. The next three chapters then present various case studies, e.g. at an SME offering the production of atypical, unique and special purpose machinery, equipment and technologically complex units particularly useful in the automotive and electronic industries; and at a further SME producing highly-customized floor cleaning machines. Rounding out the coverage, the last two chapters summarize the achievements and lessons learned with regard to the road ahead. Overall, the book provides a realistic portrait of the status quo based on current findings, and outlines the future activities to be pursued in order to establish stakeholder-centred digital production systems. As such, developers, educators, and practitioners will find both the conceptual background and results from the field reflecting the state-of-the-art in vertical and horizontal process integration.