Three years ago, the first Liquid Legal book compelled the legal profession to reassess its identity and to aspire to become a strategic partner for corporate executives as well as for clients. It also led to the foundation of the Liquid Legal Institute (LLI) - an association that sparks innovation and drives collaboration in the legal industry. This second Liquid Legal book builds on the LLI's progress and on the lessons learned by a legal community that has moved beyond focusing purely on LegalTech. It not only presents an outlook on how legal professionals will operate in the future, but also allows readers to develop a genuine understanding of the value of digitalization, standardization and new methodologies. Further, the book outlines a Common Legal Platform (CLP) and makes it the common point of departure for every author, offering inspiring insights from a wide range of forward-thinking experts who are all invested in driving new thinking within the legal ecosystem. The book also features "Liquid Legal Waves," which provide links between the various articles, connecting concrete ideas, practical solutions and specific topics and putting them into perspective, and so creating a true network of ideas for readers. A must read, this book is vibrant proof of the power of sharing, collaboration and coopetition, helping the legal profession to shape its digital future and revitalize its relevance while retaining a focus on the human lawyer.

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.

Electronic participation is an emerging and growing research area that makes use of internet solutions to enhance citizens' participation in government processes in order to provide a fair and efficient society. This book examines recommender-system technologies and voting advice applications as tools to enable electronic citizen participation during election campaigns. Further, making use of fuzzy classification, it provides an evaluation framework for eParticipation. A dynamic voting advice application developed for the 2017 Ecuador national election serves as a real-world case study to introduce readers to the practical implementation and evaluation issues. The book concludes with a comprehensive analysis of the 2017 election project based on altmetrics, Google Analytics and statistics from the case study.

Learn the fundamentals of Design Thinking and how to apply Design Thinking techniques in defining software development and AI solutions. Design Thinking is an approach to innovation which identifies problems and generates solution ideas that can be rapidly proven through prototyping. This book provides a brief history of Design Thinking and an overview of the process. It then drills down into more detail regarding methods and tools used in a Design Thinking workshops leading to useful prototypes. Guidance is provided on: Preparing for a Design Thinking Workshop Uncovering potential business problems that might be solved Prioritizing potential solutions Identifying and characterizing stakeholders Choosing the right prototypes for development Limiting scope and best practices in prototype building The book concludes with a discussion of best practices in operationalizing successful prototypes, and describes change management techniques critical for successful adoption. You can use the knowledge gained from reading this book to incorporate Design Thinking techniques in your software development and AI projects, and assure timely and successful delivery of solutions. What You Will Learn Gain foundational knowledge of what Design Thinking is and when to apply the technique Discover preparation and facilitation techniques used in workshops Know how ideas are generated and then validated through prototyping Understand implementation best practices, including change management considerations Who This Book Is For Business decision makers and project stakeholders as well as IT project owners who seek a method leading to fast development of successful software and AI prototypes demonstrating real business value. Also for data scientists, developers, and systems integrators who are interested in facilitating or utilizing Design Thinking workshops to drive momentum behind potential software development and AI projects.

Cryptography and encryption aren't just for geeks and spies-they're also part of our daily lives. This book enlightens you with the basics of digital cryptography and covers the must-do practices organizations need to implement when it comes to fending off data theft and eavesdroppers. You will uncover the concepts of digital encryption and examine key digital encryption algorithms and their various applications. Gauging cryptography from an enterprise perspective, you will get an in-depth look at common attacks that can occur in your systems and lean how to counter them Moving on to quantum computing, you will discover how it differs from the current computing paradigm and understand its potential for the future. After clearing the basics, you will take a close look at how quantum computers work in practice. Shifting focus to quantum cryptography, you will learn more about quantum key distribution (QKD) and how it differs from present-day encryption methodologies. You will also consider the current implementations of QKD, including distribution systems by SwissQuantum and QKD-distribution networks provided by the DARPA Quantum Network. Ultimately, you will learn the means of defending against cryptographic attacks in the up-and-coming quantum age, such as utilizing zero-knowledge proof (ZKP) systems. Deepen your knowledge of cryptographic concepts and be introduced to the new paradigm of quantum cryptography with this book. What You Will Learn Appreciate how digital encryption algorithms work Secure your infrastructure from cryptographic attacks Understand the basics of quantum information science Discover how cryptography relates to quantum computing Implement Quantum Key Distribution (QKD) Who This Book Is For This book is aimed at readers who have an interest in both well-established and up-and-coming types of cryptography, as well as members of organizations to whom privacy is a top priority.

This innovative book proposes new methodologies for the measurement of entrepreneurship by applying techniques of demography, engineering, mathematics and statistics. Using the data from the Global Entrepreneurship Monitor (GEM), statistical demographic techniques are used for the evaluation of data quality (EDQ), and a new methodology for the estimation of Specific Entrepreneurship Rates (SER) and the Global Entrepreneurship Rate (GER) is proposed. At the same time the authors present artificial intelligence techniques such as Fuzzy Time Series (FTS) to forecast data series of the entrepreneurial population. Finally, they present a case study of the implementation of Big Data in Entrepreneurship using GEM data that shows the latest technological trends for the management of data, in support of making more accurate decisions. Being a methodological book, the techniques presented can be applied to any dataset in different areas. Readers will learn new methodologies of analysis and measurement of entrepreneurship using data from the Global Entrepreneurship Monitor. They will be able to access the experience of the authors through each of the applied cases in which the reader is taken by the hand, both through the scientific method and through the methodology of construction of more accurate metrics in entrepreneurship, with less error. This book will be of value to students at an advanced level, academics and researchers in the fields of Entrepreneurship, Business Analytics and Research Methodology.

This proceedings volume presents recent theoretical and practical advances in operational research (OR). The papers focus on a number of key areas including combinatorial optimization, integer programming, heuristics, and mathematical programming. In addition, this volume highlights OR applications in different areas such as financial decision making, marketing, e-business, project management, scheduling, traffic and transportation. The chapters are based on papers presented at the 13th Balkan Conference on Operations Research (BALCOR). BALCOR is an established biennial conference. The selected papers promote international collaboration among researchers and practitioners, with a particular focus on the Balkan countries.

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.

Economies are changing - independent from their status, i.e. industrialized, threshold or developing. Technological advancement, e.g. in information or telecommunication, and environmental concerns make people rethink present and future activities. Many challenges can only be tackled internationally or interdisciplinary. The articles of WHZ conferences with DAAD-Alumni and partners from 20 nations take various problems and approaches to solutions into focus. The editors hope some of the ideas to give further thought to similar problems in other regions or areas of science or economy.About the Editors: H.-Ch. Brauweiler, Prof. Dr. Dr. h. c., Prof. of Accounting & Audit, WHZ Zwickau University. Research focus: University management, blended learning, regional development, risk management. V. Kurchenkov, Prof. Dr., Prof. of Public Administration & Management, VSU Volgograd. Research focus: Forecasting & planning, innovation management, municipal administration, economic policy. S. Abilov, Head of Intern. Dep., KAFU Ust Kamenogorsk. Research focus: University management, interdisciplinary & intercultural communication. B. Zirkler, Prof. Dr., Prof. of Accounting/Controlling, WHZ. Research focus: International accounting & controlling, effects of digitization and sustainability on controlling.

This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists' preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice

This book provides readers the "big picture" and a comprehensive survey of the domain of big data processing systems. For the past decade, the Hadoop framework has dominated the world of big data processing, yet recently academia and industry have started to recognize its limitations in several application domains and thus, it is now gradually being replaced by a collection of engines that are dedicated to specific verticals (e.g. structured data, graph data, and streaming data). The book explores this new wave of systems, which it refers to as Big Data 2.0 processing systems. After Chapter 1 presents the general background of the big data phenomena, Chapter 2 provides an overview of various general-purpose big data processing systems that allow their users to develop various big data processing jobs for different application domains. In turn, Chapter 3 examines various systems that have been introduced to support the SQL flavor on top of the Hadoop infrastructure and provide competing and scalable performance in the processing of large-scale structured data. Chapter 4 discusses several systems that have been designed to tackle the problem of large-scale graph processing, while the main focus of Chapter 5 is on several systems that have been designed to provide scalable solutions for processing big data streams, and on other sets of systems that have been introduced to support the development of data pipelines between various types of big data processing jobs and systems. Next, Chapter 6 focuses on covering the emerging frameworks and systems in the domain of scalable machine learning and deep learning processing. Lastly, Chapter 7 shares conclusions and an outlook on future research challenges. This new and considerably enlarged second edition not only contains the completely new chapter 6, but also offers a refreshed content for the state-of-the-art in all domains of big data processing over the last years. Overall, the book offers a valuable reference guide for professional, students, and researchers in the domain of big data processing systems. Further, its comprehensive content will hopefully encourage readers to pursue further research on the subject.

This book presents selected examples of digitalization in the age of digital change. It is divided into two sections: "Digital Innovation," which features new technologies that stimulate and enable new business opportunities; and "Digital Business Transformation," comprising business and management concepts that employ specific technological solutions for their practical implementation. Combining new insights from research, teaching and management, including digital transformation, e-business, knowledge representation, human-computer interaction, and business optimization, the book highlights the breadth of research as well as its meaningful and relevant transfer into practice. It is intended for academics seeking inspiration, as well as for leaders wanting to tap the potential of the latest trends to take society and their business to the next level.

This book provides a comprehensive and effective exchange of information on current developments in the management of manufacturing systems and Industry 4.0. The book aims to establish channels of communication and disseminate knowledge among professionals working in manufacturing and related institutions. In the book, researchers, academicians and practitioners in relevant fields share their knowledge from the sectors of management of manufacturing systems. The chapters were selected from several conferences in the field, with the topics including management of manufacturing systems with support for Industry 4.0, logistics and intelligent manufacturing systems and applications, cooperation management, and its effective applications. The book also includes case studies in logistics, RFID applications, and economic impacts in logistics, ICT support for industry 4.0, industrial and smart logistics, intelligent manufacturing systems and applications

This book highlights research and survey articles dedicated to big data techniques for cyber-physical system (CPS), which addresses the close interactions and feedback controls between cyber components and physical components. The book first discusses some fundamental big data problems and solutions in large scale distributed CPSs. The book then addresses the design and control challenges in multiple CPS domains such as vehicular system, smart city, smart building, and digital microfluidic biochips. This book also presents the recent advances and trends in the maritime simulation system and the flood defence system.

This volume presents selected papers from the International Conference on Urban Intelligence and Applications (ICUIA), which took place on May 10-12, 2019 in Wuhan, China. The goal of the conference was to bring together researchers, industry leaders, policy makers, and administrators to discuss emerging technologies and their applications to advance the design and implementation of intelligent utilization and management of urban assets, and thus contributing to the autonomous, reliable, and efficient operation of modern, smart cities. The papers are collated to address major themes of urban sustainability, urban infrastructure and management, smart city applications, image and signal processing, natural language processing, and machine learning for monitoring and communications applications. The book will be of interest to researchers and industrial practitioners working on geospatial theories and tools, smart city applications, urban mobility and transportation, and community well-being and management.

Features the use of Bayesian statistics to gain insights from empirical data

Featuring an accessible approach, "Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems" demonstrates how Bayesian statistics can help to provide insights into important issues facing business and management. The book draws on multidisciplinary applications and examples and utilizes the freely available software WinBUGS and R to illustrate the integration of Bayesian statistics within data-rich environments.

Computational issues are discussed and integrated with coverage of linear models, sensitivity analysis, Markov Chain Monte Carlo (MCMC), and model comparison. In addition, more advanced models including hierarchal models, generalized linear models, and latent variable models are presented to further bridge the theory and application in real-world usage.

"Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems "alsofeatures: Numerous real-world examples drawn from multiple management disciplines such as strategy, international business, accounting, and information systemsAn incremental skill-building presentation based on analyzing data sets with widely-applicable models of increasing complexityAn accessible treatment of Bayesian statistics that is integrated with a broad range of business and management issues and problemsA practical problem-solving approach to illustrate how Bayesian statistics can help provide insight into important issues facing business and managementThe use of WinBUGS and R to showcase the benefits of Bayesian statistics for the increasingly data-rich business environment

"Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems" is an important textbook for Bayesian statistics courses at the advanced MBA-level and also for business and management PhD candidates as a first course in methodology. In addition, the book is a useful resource for management scholars and practitioners as well as business academics and practitioners who need to broaden their methodological skill sets.

This book demonstrates the benefits and drawbacks of using digital technology in preparing online lessons and educational activities. The experience of the last year has shown that online education is becoming a priority. This gave impetus to the creation and development of a new generation of equipment for online education. The book presents latest innovative technologies and modern digital trends in the field of information and communication technology for online education, including personalized learning, neuro-information systems, mobile learning, development of software and hardware infrastructure, and the use of robotics technologies. Key technologies for managing risk and cybersecurity, such as cloud and data security, identity and trust convolution systems, computational intelligence and cryptography techniques, malware and attack analysis, are presented. The topic of cybersecurity is one of the most important issues in the modern digital world. The results of the research on recently developed software, decision support systems, and cloud technologies make a huge contribution to the development of information technology in the context of digitalization. This book is of interest for developers of applications and programs for online education, for software and hardware suppliers who want to keep up with the times and reorient existing IT systems for use in online education.

This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards. In the current dynamic environment, a viable tool known as multi-criteria decision analysis (MCDA) is increasingly being adopted to deal with complex business decisions. MCDA is an important decision support tool for analyzing goals and providing optimal solutions and alternatives. It comprises several distinct techniques, which are implemented by specialized decision-making packages. This book addresses a number of important MCDA methods, such as DEMATEL, TOPSIS, AHP, MAUT, and Intuitionistic Fuzzy MCDM, which make it possible to derive maximum utility in the area of analytics. As such, it is a valuable resource for researchers and academicians, as well as practitioners and business experts.

This book presents articles from the International Conference on Blockchain Technology (IC-BCT) 2019, held in Mumbai, India, and highlights recent advances in the field. It brings together researchers and industry practitioners to show case their ideas linked to business case studies, and provides an opportunity for engineers, researchers, startups and professionals in the field of Blockchain technology to further collaboration.

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 gathers the proceedings of the 14th International Conference on Management Science and Engineering Management (ICMSEM 2020). Held at the Academy of Studies of Moldova from July 30 to August 2, 2020, the conference provided a platform for researchers and practitioners in the field to share their ideas and experiences. Covering a wide range of topics, including hot management issues in engineering science, the book presents novel ideas and the latest research advances in the area of management science and engineering management. It includes both theoretical and practical studies of management science applied in computing methodology, highlighting advanced management concepts, and computing technologies for decision-making problems involving large, uncertain and unstructured data. The book also describes the changes and challenges relating to decision-making procedures at the dawn of the big data era, and discusses new technologies for analysis, capture, search, sharing, storage, transfer and visualization, and in the context of privacy violations, as well as advances in the integration of optimization, statistics and data mining. Given its scope, it will appeal to a wide readership, particularly those looking for new ideas and research directions.

Emerging technologies offer a plethora of unprecedented opportunities for entrepreneurs in the digital space. Understanding this evolution is essential for web-based business models to succeed. The Web 3.0 economy is here, and this book has arrived to serve as your guide. Technologies for Modern Digital Entrepreneurship is an in-depth look at the new developments of the digital economic system. Cryptocurrencies, Central Bank Digital Currencies, and Stable Coins are explained through timely case studies, as well as innovations in crowdfunding, educational marketplaces, and scalability in blockchain-based transactions. Author Dr. Abeba N. Turi expertly navigates the industry transition from platform-based centralized Web 2.0 economy to the distributed network economy. Turi additionally explores trust and reputation as currency in the digital economy and allays common fears in digital entrepreneurship such as mistrust by investors and intellectual property loss. Avoid falling behind your competitors in the Wild West that is modern digital entrepreneurship. Whether you are a business leader, a technology enthusiast, or a researcher in the field, Technologies for Modern Digital Entrepreneurship gives you the advantage of insightful knowledge using real data and meaningful examples. Amid global regulatory changes and the ever-shifting methods of digital entrepreneurship, our modern era demands this book. What You Will Learn Discover new trends in the digital economic system Comprehend the crowd-based digital business models Analyze the distributed information network economy Understand the workings of the currency system under the Web 3.0 economy, including Cryptocurrencies, Central Bank Digital Currencies, and Stable Coins Who This Book Is ForTechnology enthusiasts, tech and interdisciplinary students, digital business leaders, and researchers in the field

This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc. The book goes beyond standard application by placing a specific focus on the use of AI techniques to address the challenges related to the different applications and topics of energy transition. The contributions are classified according to the market and actor interactions (service providers, manufacturers, customers, integrators, utilities etc.), to the SG architecture model (physical layer, infrastructure layer, and business layer), to the digital twin of SG (business model, operational model, fault/transient model, and asset model), and to the application domain (demand side management, load monitoring, micro grids, energy consulting (residents, utilities), energy saving, dynamic pricing revenue management and smart meters, etc.).

The book discusses the opportunities and challenges of managing knowledge in the new reality of Industry 4.0. Addressing paradigmatic changes in value creation due to the development of digital technologies applied to manufacturing (additive manufacturing, IoT, robotics, etc.), it includes theoretical and empirical contributions on how Industry 4.0 technologies allow firms to create and exploit knowledge. The carefully selected expert contributions highlight the potential of these technologies in acquiring knowledge from a larger number of sources and examine approaches to innovation, organization of activities, and stakeholder development in the context of this next industrial revolution.

This book utilizes historical evidence to describe the development of the Toyota Production System (TPS). The development of TPS typifies the transformation of production control in interchangeable industries in the twentieth century. Much of the extensive literature available on TPS has been geared toward describing TPS from a number of different perspectives. Many researchers consider TPS distinct from American mass-production systems. Although TPS (and, more generally, the production control systems in the Japanese assembly industry) has differentiated itself from similar US production systems, the evolution of TPS is largely attributable to attempts to learn from, imitate, and modify pre-World War II US production methods. Through these efforts, TPS has achieved levels of efficiency in Japan comparable to those of US production systems. Additionally, a reliance on Information and Communication Technology (ICT) in relation to production control has facilitated the development of TPS. The literature on TPS, however, has largely ignored the vital relationship between ICT and production control due to an inordinate focus on "Kanban." Kanban translates to "signboard" in Japanese but is used to refer to an organic linkage between work in preceding and subsequent production processes. This book sheds light on the development of a fully digitalized Bill of Materials (BOM) at Toyota, behind its Kanban and production control.