This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem. Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented. In addition, the book provides an overview of approaches to handling large collections of objects in a reasonable time. In particular, it addresses grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches, especially those used for community detection.

This book provides a comprehensive overview of various aspects of the development of smart cities from a secure, trusted, and reliable data transmission perspective. It presents theoretical concepts and empirical studies, as well as examples of smart city programs and their capacity to create value for citizens. The contributions offer a panorama of the most important aspects of smart city evolution and implementation within various frameworks, such as healthcare, education, and transportation. Comparing current advanced applications and best practices, the book subsequently explores how smart environments and programs could help improve the quality of life in urban spaces and promote cultural and economic development.

This book systematically and integrally introduces the new security management theories and methods in the e-commerce environment. Based on the perspective of dynamic governance of the whole process, starting from the theoretical framework, this book analyzes the gap between the current situation and requirements of security management, defines its nature, function, object and system, and designs and constructs the whole process security management organization and operation system of e-commerce. It focuses on the core and most prominent risk control links (i.e. security impact factors) in e-commerce security, including e-commerce information and network security risk, e-commerce transaction risk, e-commerce credit risk, e-commerce personnel risk, etc. Then, the tools and methods for identifying and controlling various risks are described in detail, at the same time, management decision-making and coordination are integrated into the risk management. Finally, a closed loop of self-optimization is established by a continuous optimization evolution path of e-commerce security management.

In this volume, noted experts in a variety of information, business, and management fields offer a comprehensive overview of the role information plays in global business and its impact on competition and competitiveness. At the core of the collection is a common belief in the essential value of information to the modern business and a recognition that the corporate intelligence function must today cope with changing realities produced by both new technology and the globalization of markets. Taking these as their points of departure, the contributors discuss a broad spectrum of corporate intelligence issues ranging from the uses of artificial intelligence and the structure of the corporate intelligence system to the nature of security threats, financial warfare, and corporate risk assessment.

The chapters are divided into five sections and begin with two essays on the emerging interrelated global world order. George Roukis discusses the corporate intelligence process as it embodies the global view, while Hugh Conway shows how modern technology has changed the corporate intelligence function. Three chapters explore the information applications of new technologies, including the use of the computer to further all aspects of corporate intelligence gathering and the emergence of an information industry to serve the needs of intelligence gatherers. The following section contains chapters that address, in turn, the use of intelligence in strategic decisionmaking, coping with bad news, the process of intelligence gathering, and field-marketing intelligence. Turning to a discussion of outside threats to corporate intelligence data security, the contributors examine computer security in general, defense related computer security, and the terrorist threat to corporations. In the final section, the contributors look at a number of strategic challenges. A particularly interesting chapter examines corporate intelligence in Japan; others look at geography and corporate risk assessment, the Soviet foreign intelligence service, and corporate responses to financial warfare. Competitive intelligence and marketing executives, as well as students in international business programs, will find this volume enlightening and provocative reading.

A revised and expanded advanced-undergraduate/graduate text (first ed., 1978) about optimization algorithms for problems that can be formulated on graphs and networks. This edition provides many new applications and algorithms while maintaining the classic foundations on which contemporary algorithm

This book examines the field of parallel database management systems and illustrates the great variety of solutions based on a shared-storage or a shared-nothing architecture. Constantly dropping memory prices and the desire to operate with low-latency responses on large sets of data paved the way for main memory-based parallel database management systems. However, this area is currently dominated by the shared-nothing approach in order to preserve the in-memory performance advantage by processing data locally on each server. The main argument this book makes is that such an unilateral development will cease due to the combination of the following three trends: a) Today's network technology features remote direct memory access (RDMA) and narrows the performance gap between accessing main memory on a server and of a remote server to and even below a single order of magnitude. b) Modern storage systems scale gracefully, are elastic and provide high-availability. c) A modern storage system such as Stanford's RAM Cloud even keeps all data resident in the main memory. Exploiting these characteristics in the context of a main memory-based parallel database management system is desirable. The book demonstrates that the advent of RDMA-enabled network technology makes the creation of a parallel main memory DBMS based on a shared-storage approach feasible.

This handbook collects the most up-to-date scholarship, knowledge, and new developments of big data and data analytics by bringing together many strands of contextual and disciplinary research. In recent times, while there has been considerable research in exploring the role of big data, data analytics, and textual analytics in accounting, and auditing, we still lack evidence on what kinds of best practices academics, practitioners, and organizations can implement and use. To achieve this aim, the handbook focuses on both conventional and contemporary issues facing by academics, practitioners, and organizations particularly when technology and business environments are changing faster than ever. All the chapters in this handbook provide both retrospective and contemporary views and commentaries by leading and knowledgeable scholars in the field, who offer unique insights on the changing role of accounting and auditing in today's data and analytics driven environment. Aimed at academics, practitioners, students, and consultants in the areas of accounting, auditing, and other business disciplines, the handbook provides high-level insight into the design, implementation, and working of big data and data analytics practices for all types of organizations worldwide. The leading scholars in the field provide critical evaluations and guidance on big data and data analytics by illustrating issues related to various sectors such as public, private, not-for-profit, and social enterprises. The handbook's content will be highly desirable and accessible to accounting and non-accounting audiences across the globe.

It is now well established that innovation is the main engine of competitiveness and economic growth. However, in this modern fast-paced world, the inherent nature of the innovation process has changed. On the one hand, the rapid technological revolution or the emergence of new countries on the international economic stage has underlined a shift towards a globalization of the economy. On the other hand, another trend towards a spatial concentration of economic and innovative activity has been identified. Despite the widening of the geographical options offered by globalization, production and innovation still appear particularly concentrated in specific locations and clusters are the ultimate representation of this regionalization stream. The New Geography of Innovation assesses both the theoretically and empirically intertwined - but surprisingly still relatively unexplored - relationship between innovation, clusters and multinational enterprises in today's economy. Based on a unique database of patent applications at the European Patent Office, this book not only emphasizes the marked discrepancies in terms of inventive performance between Swiss regions but also identifies the country's main inventive clusters, offers new insights on the internationalization of the innovation process and provides exclusive evidence of the importance of foreign clusters as a source of new knowledge.

This proceedings volume highlights the state-of-the-art knowledge related to optimization, decisions science and problem solving methods, as well as their application in industrial and territorial systems. It includes contributions tackling these themes using models and methods based on continuous and discrete optimization, network optimization, simulation and system dynamics, heuristics, metaheuristics, artificial intelligence, analytics, and also multiple-criteria decision making. The number and the increasing size of the problems arising in real life require mathematical models and solution methods adequate to their complexity. There has also been increasing research interest in Big Data and related challenges. These challenges can be recognized in many fields and systems which have a significant impact on our way of living: design, management and control of industrial production of goods and services; transportation planning and traffic management in urban and regional areas; energy production and exploitation; natural resources and environment protection; homeland security and critical infrastructure protection; development of advanced information and communication technologies. The chapters in this book examine how to deal with new and emerging practical problems arising in these different fields through the presented methodologies and their applications. The chapter topics are applicable for researchers and practitioners working in these areas, but also for the operations research community. The contributions were presented during the international conference "Optimization and Decision Science" (ODS2017), held at Hilton Sorrento Palace Conference Center, Sorrento, Italy, September 4 - 7, 2017. ODS 2017, was organized by AIRO, Italian Operations Research Society, in cooperation with DIETI (Department of Electrical Engineering and Information Technology) of University "Federico II" of Naples.

Advances in information technology (IT) have influenced how organizations do business. With IT playing such a pivotal role in the operations and success of an organization, it is imperative that it be used strategically. As a repository of cases, Cases on E-Readiness and Information Systems Management in Organizations: Tools for Maximizing Strategic Alignment contains research that readers can use to assess the e-readiness of their own organizations. This book presents principles, tools, and techniques about e-readiness, while also offering in-depth perspectives on applying the e-readiness model for the purpose of aligning IT with organizational strategies.

Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include: query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand on their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment.

This book highlights the economic and social science perspectives in light of COVID-19. During 2020, leaders found themselves at historic crossroads, taking decisions under remarkable pressures and uncertainties. However, windows of opportunity are being created to shape the economic recovery, restore the health of the environment, develop sustainable business models, strengthen regional development, revitalize global cooperation, harness Industry 4.0, and redesign the social contracts, skills, and jobs. This book is an excellent resource for all those interested in economics and social sciences perspectives on digitalization and big data, especially in the light of the recent crisis determined by COVID-19. The chapters cover topics related to new models in entrepreneurship and innovation, sustainability and education, data science and digitalization, marketing and finance, etc., that will develop innovative instruments for countries, businesses, and education to revive after the crisis.

This open access book presents a number of case studies on digital transformation in Norway, one of the fore-runners in the digital progress index established by the European Commission in 2020. They explore the process of adoption, diffusion and value generation from digital technologies, and how the use of different digital solutions has enabled Norwegian enterprises to digitally transform their operations and business models. The book starts with an introductory chapter summarizing a vast body of literature in order to synthesize what is already known about digital transformation before exploring the Norwegian context in more detail. Then a series of case studies from the private and public sector in Norway is presented. They document a process perspective which describes the sequence of events during and after adoption of digital solutions, as well as the types of business value that were realized. Through these single studies, the process of digital transformation is illustrated, a number of key findings highlighted, and eventually theoretical and practical recommendations based on these cases emphasized. The book closes with a brief overview of some emerging technologies, and comments on how they are likely to change different sectors. Digital transformation has been one of the priority areas for the Norwegian government over the past years and puts Norwegian enterprises upfront in adopting novel technologies and utilizing them for achieving organizational goals. This experience accumulated over the years makes the Norwegian context a particularly interesting one in understanding how private and public organizations make use of new digital solutions, what lessons can be learnt during the process, and what are some of the key success and failure factors. This way the book is written for practitioners who are currently involved in digital transformation projects in their organizations, researchers of information systems and management, as well as master students in degrees of informatics and technology management.

This textbook provides guidance to both students and practitioners of enterprise architecture (EA) on how to develop and maintain enterprise models. Rather than providing yet another list of EA notations and frameworks from A to Z, it focuses on methods to perform such tasks. The problem of EA maintenance, named Enterprise Cartography, is an important aspect addressed in this book because EA is a never ending challenge that increases as the organization transformations pace also increases. The long time perspective also entails the evolution of architectural frameworks and notations, something that does not occur when developing new models. Thus, a catalogue of patterns, principles and methods is presented to develop and maintain EA models and views. After a general introduction to the book in chapter 1, chapter 2 presents basic concepts for EA modeling. Chapter 3 further details the set of EA concepts needed to present the patterns, and principles, which are subsequently introduced in chapter 4. Next, chapter 5 describes enterprise cartography concepts and principles. The remaining book then turns to techniques and methodologies. In chapter 6 an EA development method is summarized. In chapter 7 an enterprise strategy design approach is proposed, while in chapter 8 a business process design methodology is described. Chapters 9 and 10 focus on information architecture and information systems architecture design approaches, including information systems architecture planning and application portfolio management. Eventually, chapter 11 describes a method for enterprise cartography (EC) design. Last not least, several case studies on EA and EC are proposed in the last chapter.

This book offers a comprehensive overview of Japan's media policies. In light of the attention Japanese media content has attracted in recent years, not only in Japan but also overseas, the book examines the media industry that supports such content. Beginning with the traditional terrestrial broadcasting industry, it also covers cable TV, satellite broadcasting, and over-the-top media services (OTT), as well as media policies for film, animation, games and music. The Ministry of Internal Affairs and Communications (MIC), a key media industry regulator in Japan, has been developing broadcasting policies for more than 70 years, and while their traditional policies have not changed in principle, the scope of their business sphere has expanded. For instance, major broadcasting stations in Tokyo, known as key stations, have played an important role in filmmaking with the big four film companies, and have started joint ventures with major OTT, such as Hulu. This book allows readers to gain a comprehensive understanding of the changes in the Japanese media industry in general and the related policies in Japan, while also offering insights into developments in the individual sectors.

This book adopts the managerial perspective to the study of smart cities. As such, this book is a necessary addition to the existing body of literature on smart cities. The chapters included in this book prove the case that transformation of cities to smart cities is a function of effective and efficient management practices implemented at diverse levels of smart cities. While advances in information and communication technology (ICT) are crucial, it is the ability to apply ICT consciously and efficiently that drives the transformation of cities to smart cities in a manner conducive to cities' sustainability and resilience. The book covers three sets of interconnected topics: Management and decision-making for urban design and infrastructure development Management and decision-making in context of smart cities development Ways of promoting and ensuring participation, representation and co-creation in smart cities These three groups of topics offer a great opportunity to acquire a clear, direct, and practice-driven knowledge and understanding of how effective management allows ICT-enhanced tools and applications to change smart cities, possibly making them smarter.

"Service Level Agreements for Cloud Computing" provides a unique combination of business-driven application scenarios and advanced research in the area of service-level agreements for Clouds and service-oriented infrastructures. Current state-of-the-art research findings are presented in this book, as well as business-ready solutions applicable to Cloud infrastructures or ERP (Enterprise Resource Planning) environments. "Service Level Agreements for Cloud Computing" contributes to the various levels of service-level management from the infrastructure over the software to the business layer, including horizontal aspects like service monitoring. This book provides readers with essential information on how to deploy and manage Cloud infrastructures. Case studies are presented at the end of most chapters. "Service Level Agreements for Cloud Computing" is designed as a reference book for high-end practitioners working in cloud computing, distributed systems and IT services. Advanced-level students focused on computer science will also find this book valuable as a secondary text book or reference.

This book addresses the concept of organizing which is centered around collective learning and on the organization paradigm. It presents a theory of organizational learning based on a model of memory, explaining processes and dynamics through which memory is built and updated.

This book provides an overview of the topics of data, sovereignty, and governance with respect to data and online activities through a legal lens and from a cybersecurity perspective. This first chapter explores the concepts of data, ownerships, and privacy with respect to digital media and content, before defining the intersection of sovereignty in law with application to data and digital media content. The authors delve into the issue of digital governance, as well as theories and systems of governance on a state level, national level, and corporate/organizational level. Chapter three jumps into the complex area of jurisdictional conflict of laws and the related issues regarding digital activities in international law, both public and private. Additionally, the book discusses the many technical complexities which underlay the evolution and creation of new law and governance strategies and structures. This includes socio-political, legal, and industrial technical complexities which can apply in these areas. The fifth chapter is a comparative examination of the legal strategies currently being explored by a variety of nations. The book concludes with a discussion about emerging topics which either influence, or are influenced by, data sovereignty and digital governance, such as indigenous data sovereignty, digital human rights and self-determination, artificial intelligence, and global digital social responsibility. Cumulatively, this book provides the full spectrum of information, from foundational principles underlining the described topics, through to the larger, more complex, evolving issues which we can foresee ahead of us.

Benchmarking is considered a must for modern management. This book presents an approach to benchmarking that has a solid mathematical basis and is easy to understand and apply. The book focuses on three main topics. It shows how to formalize the representation of benchmarking objects. Furthermore, it presents different methods from decision making and voting and their application to benchmarking. Finally, it discusses suitable features for different benchmarking objects. The objects considered are taken from IT management, but can be easily transferred to other business areas, which makes the book interesting for all practitioners in the management field.

There is little doubt that cyber-space has become the battle space for confrontations. However, to conduct cyber operations, a new armory of weapons needs to be employed. No matter how many, or how sophisticated an aggressor's kinetic weapons are, they are useless in cyber-space. This book looks at the milieu of the cyber weapons industry, as well as the belligerents who use cyber weapons. It discusses what distinguishes these hardware devices and software programs from computer science in general. It does this by focusing on specific aspects of the topic-contextual issues of why cyber-space is the new battleground, defensive cyber weapons, offensive cyber weapons, dual-use weapons, and the implications these weapons systems have for practice. Contrary to popular opinion, the use of cyber weapons is not limited to nation states; though this is where the bulk of news reporting focuses. The reality is that there isn't a sector of the political-economy that is immune to cyber skirmishes. So, this book looks at cyber weapons not only by national security agencies and the military, but also by law enforcement, and the business sector-the latter includes administrations termed non-government organisations (NGOs). This book offers study material suitable for a wide-ranging audience-students, professionals, researchers, policy officers, and ICT specialists.

As the most comprehensive reference work dealing with decision support systems (DSS), this book is essential for the library of every DSS practitioner, researcher, and educator. Written by an international array of DSS luminaries, its more than 70 chapters approach decision support systems from a wide variety of perspectives ranging from classic foundations to cutting-edge thought, informative to provocative, theoretical to practical, historical to futuristic, human to technological, and operational to strategic. The chapters are conveniently organized into 10 major sections: foundations of decision support systems, DSS fundamentals, multiparticipant DSSs, intelligent DSSs, effects of decision support, time and space issues, scopes of decision support, developing and managing decision support systems, cases and applications, and decision support horizons. Novices and experts alike will refer to the authoritative and stimulating content again and again for years to come.

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). Theobjective 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:

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Communications and Electrical Engineering

Management Science

Service Science

Business Intelligence

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Management Science

Service Science

Business Intelligence

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Service Science

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Communications and Electrical Engineering

Management Science

Service Science

Business Intelligence

Management Science

Service Science

Business Intelligence

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Management Science

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This book presents a framework for developing as well as a comprehensive collection of state-of-the-art process querying methods. Process querying combines concepts from Big Data and Process Modeling and Analysis with Business Process Intelligence and Process Analytics to study techniques for retrieving and manipulating models of real-world and envisioned processes to organize and extract process-related information for subsequent systematic use. The book comprises sixteen contributed chapters distributed over four parts and two auxiliary chapters. The auxiliary chapters by the editor provide an introduction to the area of process querying and a summary of the presented methods, techniques, and applications for process querying. The introductory chapter also examines a process querying framework. The contributed chapters present various process querying methods, including discussions on how they instantiate the framework components, thus supporting the comparison of the methods. The four parts are due to the distinctive features of the methods they include. The first three are devoted to querying event logs generated by IT-systems that support business processes at organizations, querying process designs captured in process models, and methods that address querying both event logs and process models. The methods in these three parts usually define a language for specifying process queries. The fourth part discusses methods that operate over inputs other than event logs and process models, e.g., streams of process events, or do not develop dedicated languages for specifying queries, e.g., methods for assessing process model similarity. This book is mainly intended for researchers. All the chapters in this book are contributed by active researchers in the research disciplines of business process management, process mining, and process querying. They describe state-of-the-art methods for process querying, discuss use cases of process querying, and suggest directions for future work for advancing the field. Yet, also other groups like business or data scientists and other professionals, lecturers, graduate students, and tool vendors will find relevant information for their distinctive needs. Chapter "Celonis PQL: A Query Language for Process Mining" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.