Enterprise Information Systems Assurance and System Security: Managerial and Technical Issues brings together authoritative authors to address one of the most pressing challenges in the IT field - how to create secure environments for the application of technology to serve future needs. This book bridges the gap between theory and practice, academia and industry, computer science and MIS. The chapters provide an integrated, holistic perspective on this complex set of challenges, supported with practical experiences of leading figures from all realms. ""Enterprise Information Systems Assurance and System Security: Managerial and Technical Issues"" provides an excellent collection for corporate executives who are charged with securing their systems and data, students studying the topic of business information security, and those who simply have an interest in this exciting topic.

This book presents trends, developments, and examples of how digital disruption is currently reshaping the logistics industry. Logistics is the invisible force behind the global economy, influencing and providing a lens into all economic activities. Chapters written by respected experts in the field describe how new technologies such as autonomous vehicles, blockchain, Internet of things (IoT), and state-of-the-art freight management solutions are fundamentally changing supply chain solutions. Special emphasis is placed on promising start-ups and venture capital firms around the world that are now investing in the future of logistics. "Supply chains hold significant room for optimization to the benefit of customers, industry participants, authorities and the environment. This book provides a unique set of perspectives from industry leaders covering a wide range of topics. It is a 'must read' for anyone seeking to understand and contribute to a better tomorrow in supply chains logistics." - Thomas Bagge, Chief Executive Officer and Statutory Director DCSA "The need for standardisation and digitalisation in logistics is no longer an option. This book gives insights from industry experts, shows trends and innovations in platforms, underlines the need for transparency and how big data and analytics can make a world of difference. It's an incredible resource if you wish to better understand the new normal of logistics." - Global Chief Digital & Information Officer, MSC Mediterranean Shipping Company "This book presents readers with a straightforward and comprehensive assessment of supply chain innovation and trends and their impact on the industry. With contributions from several industry leaders, it provides critical knowledge and insight that supply chain and logistics managers need to implement disruptive technologies strategically." - Rene Jacquat, Founder / Advisor, LogiChain Solutions

With this textbook, Vaisman and Zimanyi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes "Fundamental Concepts" including conceptual and logical data warehouse design, as well as querying using MDX, DAX and SQL/OLAP. This part also covers data analytics using Power BI and Analysis Services. Part II details "Implementation and Deployment," including physical design, ETL and data warehouse design methodologies. Part III covers "Advanced Topics" and it is almost completely new in this second edition. This part includes chapters with an in-depth coverage of temporal, spatial, and mobility data warehousing. Graph data warehouses are also covered in detail using Neo4j. The last chapter extensively studies big data management and the usage of Hadoop, Spark, distributed, in-memory, columnar, NoSQL and NewSQL database systems, and data lakes in the context of analytical data processing. As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Power BI. All chapters have been revised and updated to the latest versions of the software tools used. KPIs and Dashboards are now also developed using DAX and Power BI, and the chapter on ETL has been expanded with the implementation of ETL processes in PostgreSQL. Review questions and exercises complement each chapter to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available online and includes electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter. Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style. "I can only invite you to dive into the contents of the book, feeling certain that once you have completed its reading (or maybe, targeted parts of it), you will join me in expressing our gratitude to Alejandro and Esteban, for providing such a comprehensive textbook for the field of data warehousing in the first place, and for keeping it up to date with the recent developments, in this current second edition." From the foreword by Panos Vassiliadis, University of Ioannina, Greece.

This book defines and develops the concept of data capital. Using an interdisciplinary perspective, this book focuses on the key features of the data economy, systematically presenting the economic aspects of data science. The book (1) introduces an alternative interpretation on economists' observation of which capital has changed radically since the twentieth century; (2) elaborates on the composition of data capital and it as a factor of production; (3) describes morphological changes in data capital that influence its accumulation and circulation; (4) explains the rise of data capital as an underappreciated cause of phenomena from data sovereign, economic inequality, to stagnating productivity; (5) discusses hopes and challenges for industrial circles, the government and academia when an intangible wealth brought by data (and information or knowledge as well); (6) proposes the development of criteria for measuring regulating data capital in the twenty-first century for regulatory purposes by looking at the prospects for data capital and possible impact on future society. Providing the first a thorough introduction to the theory of data as capital, this book will be useful for those studying economics, data science, and business, as well as those in the financial industry who own, control, or wish to work with data resources.

This open access book provides an in-depth description of the EU project European Language Grid (ELG). Its motivation lies in the fact that Europe is a multilingual society with 24 official European Union Member State languages and dozens of additional languages including regional and minority languages. The only meaningful way to enable multilingualism and to benefit from this rich linguistic heritage is through Language Technologies (LT) including Natural Language Processing (NLP), Natural Language Understanding (NLU), Speech Technologies and language-centric Artificial Intelligence (AI) applications. The European Language Grid provides a single umbrella platform for the European LT community, including research and industry, effectively functioning as a virtual home, marketplace, showroom, and deployment centre for all services, tools, resources, products and organisations active in the field. Today the ELG cloud platform already offers access to more than 13,000 language processing tools and language resources. It enables all stakeholders to deposit, upload and deploy their technologies and datasets. The platform also supports the long-term objective of establishing digital language equality in Europe by 2030 - to create a situation in which all European languages enjoy equal technological support. This is the very first book dedicated to Language Technology and NLP platforms. Cloud technology has only recently matured enough to make the development of a platform like ELG feasible on a larger scale. The book comprehensively describes the results of the ELG project. Following an introduction, the content is divided into four main parts: (I) ELG Cloud Platform; (II) ELG Inventory of Technologies and Resources; (III) ELG Community and Initiative; and (IV) ELG Open Calls and Pilot Projects.

This book provides an understanding of innovation models and why they are important in the business context, and considers sources of innovation and how to apply business frameworks using real-world examples of innovation-led businesses. After providing a solid background to the key concepts related to innovation models, the book looks at why innovation takes place and where the sources of innovation lie, from corporate research to crowd-sourced and government-funded initiatives. Innovation models across manufacturing, services and government are explored, as well as measuring innovation, and the impact of design thinking and lean enterprise principles on innovation and sustainability-driven imperatives. Offering a truly comprehensive and global approach, Business Innovation should be core or recommended reading for advanced undergraduate, postgraduate, MBA and Executive Education students studying Innovation Management, Strategic Management and Entrepreneurship.

Agile/virtual enterprise (A/VE) is seen as a new and most advanced organizational paradigm, and is expected to serve as a vehicle towards a seamless perfect alignment of the enterprise within the market. ""Agile Virtual Enterprises: Implementation and Management Support"" addresses A/VE as a highly dynamic, reconfigurable agile network of independent enterprises sharing all resources, including knowledge, market, and customers; using specific organizational architectures that introduce the enterprises' true virtual environments.

This book explores the diverse roles that marketing can, and should, play in modern, twenty-first century technology transfer in university-industry collaborations. Using various marketing lenses, it takes readers through the challenges of technology transfer and commercialization of science-based innovations. It presents research based, but practice-focused, conclusions relating to marketing implementation at different stages of the commercialization process. The author suggests that marketing's strategic role spans the whole process from idea generation, development, valuation, customer matching and marketization. Such approaches can improve the effectiveness of public money spent on research, university-industry cooperation, and research commercialization. The book will appeal to students, university teachers and researchers in a wide range of fields including: technology management, innovation, marketing, and science commercialization. It will also be of interest to those concerned directly with the practices of university technology transfer and commercialization, such as the employees, and leaders of technology transfer offices and researcher-entrepreneurs.

This book includes high-quality research papers presented at 20th International Conference on Informatics in Economy (IE 2021), which is held in Bucharest, Romania during May 2021. The book covers research results in business informatics and related computer science topics, such as IoT, mobile-embedded and multimedia solutions, e-society, enterprise and business solutions, databases and big data, artificial intelligence, data-mining and machine learning, quantitative economics.

This book establishes constructivist, interpretivist, and linguistic approaches based on conventions about the nature of qualitative and text data, the author's influence on text interpretation, and the validity checks used to justify text interpretations. Vast quantities of text and qualitative data in organizations often go unexplored. Text analytics outlined in this book allow readers to understand the process of converting unstructured text data into meaningful data for analysis in order to measure employee opinions, feedback, and reviews through sentiment analysis to support fact-based decision making. The methods involve using NVivo and RapidMiner software to perform lexical analysis, categorization, clustering, pattern recognition, tagging, annotation, memo creation, information extraction, association analysis, and visualization. The methodological approach in the book uses innovation theory as a sensitizing concept to lay the foundation for the analysis of research data, suggesting approaches for empirical exploration of organizational learning, knowledge management, and innovation practices amongst geographically dispersed individuals and team members. Based on data obtained from a private educational organization that has offices dispersed across Asia through focus group discussions and interviews on these topics, the author highlights the need for integrating organizational learning, knowledge management, and innovation to improve organizational performance, exploring perspectives on collective relationships and networks, organizational characteristics and structures, and tacit and overt values which influence such innovation initiatives. In the process, the author puts forward a new theory which is built on three themes: relationship and networks, knowledge sharing mechanisms, and the role of social cognitive schema that facilitate emergent learning, knowledge management, and innovation.

This book features the latest research in the area of immersive technologies, presented at the 6th International Augmented Reality and Virtual Reality Conference, held in online in 2020. Bridging the gap between academia and industry, it presents the state of the art in augmented reality (AR) and virtual reality (VR) technologies and their applications in various industries such as marketing, education, health care, tourism, events, fashion, entertainment, retail and the gaming industry. The book is a collection of research papers by prominent AR and VR scholars from around the globe. Covering the most significant topics in the field of augmented and virtual reality and providing the latest findings, it is of interest to academics and practitioners alike.

Students and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of investigation. The challenge is that the analytic tools required go far beyond the standard methods and models of basic statistics. This textbook aims to equip health care researchers with the most important elements of a modern health analytics toolkit, drawing from the fields of statistics, health econometrics, and data science. This textbook is designed to overcome students' anxiety about data and statistics and to help them to become confident users of appropriate analytic methods for health care research studies. Methods are presented organically, with new material building naturally on what has come before. Each technique is motivated by a topical research question, explained in non-technical terms, and accompanied by engaging explanations and examples. In this way, the authors cultivate a deep ("organic") understanding of a range of analytic techniques, their assumptions and data requirements, and their advantages and limitations. They illustrate all lessons via analyses of real data from a variety of publicly available databases, addressing relevant research questions and comparing findings to those of published studies. Ultimately, this textbook is designed to cultivate health services researchers that are thoughtful and well informed about health data science, rather than data analysts. This textbook differs from the competition in its unique blend of methods and its determination to ensure that readers gain an understanding of how, when, and why to apply them. It provides the public health researcher with a way to think analytically about scientific questions, and it offers well-founded guidance for pairing data with methods for valid analysis. Readers should feel emboldened to tackle analysis of real public datasets using traditional statistical models, health econometrics methods, and even predictive algorithms. Accompanying code and data sets are provided in an author site: https://roman-gulati.github.io/statistics-for-health-data-science/

Business Process Management (BPM) has been in existence for decades. It uses, complements, integrates and extends theories, methods and tools from other scientific disciplines like: strategic management, information technology, managerial accounting, operations management etc. During this period the main focus themes of researchers and professionals in BPM were: business process modeling, business process analysis, activity based costing, business process simulation, performance measurement, workflow management, the link between information technology and BPM for process automation etc. More recently the focus moved to subjects like Knowledge Management, Enterprise Resource Planning (ERP) Systems, Service Oriented Architectures (SOAs), Process Intelligence (PI) and even Social Networks. In this collection of papers we present a review of the work and the outcomes achieved in the classic BPM fields as well as a deeper insight on recent advances in BPM. We present a review of business process modeling and analysis and we elaborate on issues like business process quality and process performance measurement as weel as their link to all other organizational aspects like human resources management, strategy, information technology (being SOA, PI or ERP), other managerial systems, job descriptions etc. We also present recent advances to BPR tools with special focus on information technology, workflow, business process modeling and human resources management tools. Other chapters elaborate on the aspect of business process and organizational costing and their relationship to business process analysis, organizational change and reorganization. In the final chapters we present some new approaches that use fuzzy cognitive maps and a recently developed software tool for scenario creation and simulation in strategic management, business process management, performance measurement and social networking.

The audience of this book is quite wide. The first chapters can be read by professionals, academics and students who want to get some basic insight into the BPM field whereas the remaining present more elaborate and state of the art concepts methodologies and tools for an audience of a more advanced level."

This book acts as a valuable quick-access resource on the challenges and opportunities that the digital age presents to organizational leadership. Balanced, comprehensive, and thought-provoking, the book will be useful to professionals and practitioners. The book broadly follows a macro, meso, and micro approach to argumentation and is best read from beginning to end. The book synopsizes the historical context of technological revolutions and reflects on first-order results from enhanced use of information and communication technology in organizations; considers second-level impacts from information and communication technology on economy, society, work, and the very act of organizing; maps out core concepts of agility and principles that leaders should honor to exploit agility in newfound workforce ecosystems; showcases emerging leadership behaviors and mindsets; and specifies the good practice needed to plan and lead digital strategies. The book invites reference to the author's popular Knowledge Solutions: Tools, Methods, and Approaches to Drive Organizational Performance (2017) and the more recent Leading Solutions: Essays in Business Psychology (2021), which it both rests on and extends.

This book provides significant conceptual and empirical contributions to the understanding of service science and the practices of service sectors in the wake of the fourth industrial revolution bringing together a collection of articles written by keynote and invited speakers at the 2nd Service Science Symposium held on 24 November 2019. The symposium was organised by the Serviceology Society Malaysia (SESMA), which aims to bring service researchers and practitioners under one roof to redefine service concepts and ideas and explore their application in real industrial and community settings. In their contributions, authors present multiple real-world cases of service systems to demonstrate how organisations can incorporate service science to achieve sustainable development. By re-examining the existing service science models and the value creation process using valuable insights obtained from industries and communities in Malaysia, Japan and Taiwan, the authors present a new way forward for organisations.

Shipping is the world's oldest sharing economy and is conducted in a self-organizing manner. Shipping is capital, energy, and information intensive, and with the growing impact of digitalization and climate change, there is a need to rethink the management and operations of this critical global industry - assisted in no small way by maritime informatics. Building upon the recently published inaugural book Maritime Informatics by Springer, this book will address some of the most recent practical developments and experiences, particularly from a global perspective. The focus of the book is to address contemporary movements to tackle global concerns and to complement Maritime Informatics.

This book is about turning data into smart decisions, knowledge into wisdom and business into business intelligence and insight. It explores diverse paradigms, methodologies, models, tools and techniques of the emerging knowledge domain of digitalized business analytics applications. The book covers almost every crucial aspect of applied artificial intelligence in business, smart mobile and digital services in business administration, marketing, accounting, logistics, finance and IT management. This book aids researchers, practitioners and decisions makers to gain enough knowledge and insight on how to effectively leverage data into competitive intelligence.

The inspiration for this book came from the Industrial Session of the ISMIS 2017 Conference in Warsaw. It covers numerous applications of intelligent technologies in various branches of the industry. Intelligent computational methods and big data foster innovation and enable the industry to overcome technological limitations and explore the new frontiers. Therefore it is necessary for scientists and practitioners to cooperate and inspire each other, and use the latest research findings to create new designs and products. As such, the contributions cover solutions to the problems experienced by practitioners in the areas of artificial intelligence, complex systems, data mining, medical applications and bioinformatics, as well as multimedia- and text processing. Further, the book shows new directions for cooperation between science and industry and facilitates efficient transfer of knowledge in the area of intelligent information systems.

The information systems (IS) field represents a multidisciplinary area that links the rapidly changing technology of information (or communications and information technology, ICT) to the business and social environment. Despite the potential that the IS field has to develop its own native theories to address current issues involving ICT it has consistently borrowed theories from its "reference disciplines," often uncritically, to legitimize its research. This volume is the first of a series intended to advance IS research beyond this form of borrowed legitimization and derivative research towards fresh and original research that naturally comes from its own theories. It is inconceivable for a field so relevant to the era of the hyper-connected society, disruptive technologies, big data, social media, "fake news" and the weaponization of information to not be brimming with its own theories. The first step in reaching the goal of developing native IS theories is to reach an agreement on the need for theory (its rationale) and its role as the most distinctive product of human intellectual activity. This volume addresses what theories are, why bother with theories and the process of theorizing itself because the process of developing theories cannot be divorced from the product of that process. It will lay out a research agenda for decades to come and will be invaluable reading for any academic in the IS field and related disciplines concerned with information, systems, technology and their management.

This first book on Maritime Informatics describes the potential for Maritime Informatics to enhance the shipping industry. It examines how decision making in the industry can be improved by digital technology, and introduces the technology required to make Maritime Informatics a distinct and valuable discipline. Based on participating in EU funded research over the last six years to improve the shipping industry, the editors stipulate that there is a need for the new discipline of Maritime Informatics, which studies the application of information systems to increasing the efficiency, safety, and ecological sustainability of the world's shipping industry. This book examines competition and collaboration between shipping companies, and also companies who serve shipping needs, such as ports and terminals. Practical examples from leading experts give the reader real world examples for better understanding.

This book focuses on the implementation of Artificial Intelligence in Business, Education and Healthcare, It includes research articles and expository papers on the applications of Artificial Intelligence on Decision Making, Entrepreneurship, Social Media, Healthcare, Education, Public Sector, FinTech, and RegTech. It also discusses the role of Artificial Intelligence in the current COVID-19 pandemic, in the health sector, education, and others. It also discusses the impact of Artificial Intelligence on decision-making in vital sectors of the economy.

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).

This book goes beyond the hype, delving into real world technologies and applications that are driving our future and examines the possible impact these changes will have on industries, economies and society at large. It details the actions governments and regulators must take in order to ensure these changes bring about positive benefits to the public without stifling innovation that may well be the future source of value creation. It examines how organisations in a world of digital ecosystems, where industry boundaries are blurring, must undertake radical digital transformation to survive and thrive in this new digital world. The reader is taken through a framework that critically examines (i) Digital Connectivity including 5G and IoT; (ii) Data Capture and Distribution which includes smart connected verticals; (iii) Data Integrity, Control and Tokenisation that includes cyber security, digital signatures, blockchain, smart contracts, digital assets and cryptocurrencies; (iv) Data Processing and Artificial Intelligence; and (v) Disruptive Applications which include platforms, virtual and augmented reality, drones, autonomous vehicles, digital twins and digital assistants.

What do vehicle manufacturers like Rosenbauer, logistics companies like DB Schenker, a compressor manufacturer such as Bauer, an elevator manufacturer such as ThyssenKrupp, and a hygiene goods manufacturer like Hagleitner all have in common? They all use the potential of digitization to offer smarter and faster services to customers and to actively shape the digital transformation of their business models. This book provides valuable insights with concise and established guidelines for the successful digital transformation of business models. Professionals in management, strategic planning, business development, as well as researchers and students from the fields of innovation/technology management, strategic management, and entrepreneurship would particularly benefit from this book.

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.