In the context of rapid ICT development, this book focuses on how gamification affects consumer engagement and can be used to create a shared value for customers and companies. Based on the constructs of shared value, consumer engagement and gamification, it creates a conceptual model and a research methodology to enable empirical testing and provide complex empirical research findings. The book demonstrates the use of game elements and the motivation to play games as a means of achieving a psychological effect, i.e., consumer engagement manifested through gamified activities and brand engagement. This joint empirical study, by an expert team, concludes that the analysis of consumer perceived value in the context of engagement in gamified activities should distinguish between not just the theoretically identified company/brand-related economic, emotional, functional and social values, but also between engagement-related social and functional values.

This book celebrates the 10-year anniversary of Software Center (a collaboration between 18 European companies and five Swedish universities) by presenting some of the most impactful and relevant journal or conference papers that researchers in the center have published over the last decade. The book is organized around the five themes around which research in Software Center is organized, i.e. Continuous Delivery, Continuous Architecture, Metrics, Customer Data and Ecosystems Driven Development, and AI Engineering. The focus of the Continuous Delivery theme is to help companies to continuously build high quality products with the right degree of automation. The Continuous Architecture theme addresses challenges that arise when balancing the need for architectural quality and more agile ways of working with shorter development cycles. The Metrics theme studies and provides insight to understand, monitor and improve software processes, products and organizations. The fourth theme, Customer Data and Ecosystem Driven Development, helps companies make sense of the vast amounts of data that are continuously collected from products in the field. Eventually, the theme of AI Engineering addresses the challenge that many companies struggle with in terms of deploying machine- and deep-learning models in industrial contexts with production quality. Each theme has its own part in the book and each part has an introduction chapter and then a carefully selected reprint of the most important papers from that theme. This book mainly aims at researchers and advanced professionals in the areas of software engineering who would like to get an overview about the achievement made in various topics relevant for industrial large-scale software development and management - and to see how research benefits from a close cooperation between industry and academia.

The three volumes of Interest Rate Modeling present a comprehensive and up-to-date treatment of techniques and models used in the pricing and risk management of fixed income securities. Written by two leading practitioners and seasoned industry veterans, this unique series combines finance theory, numerical methods, and approximation techniques to provide the reader with an integrated approach to the process of designing and implementing industrial-strength models for fixed income security valuation and hedging. Aiming to bridge the gap between advanced theoretical models and real-life trading applications, the pragmatic, yet rigorous, approach taken in this book will appeal to students, academics, and professionals working in quantitative finance. The first half of Volume III contains a detailed study of several classes of fixed income securities, ranging from simple vanilla options to highly exotic cancelable and path-dependent derivatives. The analysis is done in product-specific fashion covering, among other subjects, risk characterization, calibration strategies, and valuation methods. In its second half, Volume III studies the general topic of derivative portfolio risk management, with a particular emphasis on the challenging problem of computing smooth price sensitivities to market input perturbations.

Social entrepreneurs are change makers that aim to solve society's unsolved problems. Not surprisingly, social entrepreneurship has thus created high expectations. To better understand the potential as well as the limitations of social entrepreneurship, however, a more nuanced approach is needed in two ways. First, social entrepreneurship is a multi-level phenomenon. It spans macro-level questions as well as meso-level questions and, finally, micro-level questions. If we really want to understand social entrepreneurship, we need to bring together all three levels of analysis and see how they are connected. Second, while social entrepreneurship can certainly produce socially desirable outcomes, we also need a critical perspective to capture potential undesirable effects that social entrepreneurship can cause, often unintendedly, in society, in markets, in organizations, and for individuals. To this end, an ethical perspective can help complement the positive analysis of social entrepreneurship with a discussion of the normative implications of its potential "dark side". Looking at social entrepreneurship from both a multi-level analysis and an ethical perspective, Social Entrepreneurship and Business Ethics takes the reader on a journey through the "bright side" as well as the potential "dark side" of social entrepreneurship for societies, organizations, and individuals. Highlighting both, this book not only seeks to provoke researchers and students to advance their understanding of social entrepreneurship. It also hopes to help practitioners to better realize the positive contributions of social entrepreneurship for society.

The information systems field has contributed greatly to the rise of the information economy and the information society. Yet, after more than a quarter-century since its formation, it still is plagued by doubts about its identity and legitimacy. "Information Systems: The State of the Field" contains the reflections of leading IS scholars on the nature of the discipline, its core identity and the challenges of creating a strong and legitimate academic enterprise centred on information systems. It includes debates, reflections and commentaries from a group of leading information system scholars, and offers an overview of the state of the field at this time. This book is intended for all who are interested in the nature and direction of the information system field as it enters the 21st century.

"The sociologist Zygmund Bauman has defined a discipline which is constantly debating its credentials as a "flawed" discipline. This critique can certainly be applied to the IS discipline. The editors of this book must be congratulated on collecting together the principal writings reflecting the nature of the debate to provide a learned and fascinating account of where the field now stands and perhaps where it is going. It is essential reading for any student of IS."
--Frank Land, Emeritus Professor, Department of Information Systems, London School of Economics

"The struggle for identity, according to Alford North Whitehead entails a dialectic of "becoming." It evolves from coping with continuous change, a conflict of perspectives and always asking: "Who am I?," "Who are we?," "Who are we not?," "What do we inherit from our past?." In this imaginatively edited volume, King and Lyytinenrecount information systems' restless pursuit for identity. Anyone who is affected by the struggles, but more importantly everyone who wants to join it must read this book."
--Richard O. Mason, Carr P. Collins Distinguished Professor, Management Information Sciences, Edwin L. Cox School of Business, Southern Methodist University

Managing for IT skills is never easy at the firm level, due to the fact that technologies change constantly and rapidly. The supply and demand of IT skills fluctuate, and firms do not have commonly recognized frameworks to manage IT skills of their workforce. A consistent taxonomy of IT skills is underdeveloped and used infrequently in industry. This book provides the basic vocabulary and managerial framework for managing strategically the IT workforce at the firm level. It also informs managers what tools and services are available to assess the skill levels of their IT workforce and job candidates. Finally, it gives different perspectives on managing IT skills - how individuals, HR managers, educators, and governments approach IT skills management.

Among the many elementary expositions of psychoanalysis, "The Talking Cure" is unique in focusing on the actual analytic experience. Lichtenberg's approach is humanistic, demonstrating empathic understanding of the fears and hopes of the person seeking help. He provides a "feel" for what happens during the analytic voyage of self-discovery.

This book explores the possibility of integrating design thinking into today's technical contexts. Despite the popularity of design thinking in research and practice, this area is still too often treated in isolation without a clear, consistent connection to the world of software development. The book presents design thinking approaches and experiences that can facilitate the development of software-intensive products and services. It argues that design thinking and related software engineering practices, including requirements engineering and user-centric design (UX) approaches, are not mutually exclusive. Rather, they provide complementary methods and tools for designing software-intensive systems with a human-centric approach. Bringing together prominent experts and practitioners to share their insights, approaches and experiences, the book sheds new light on the specific interpretations and meanings of design thinking in various fields such as engineering, management, and information technology. As such, it provides a framework for professionals to demonstrate the potential of design thinking for software development, while offering academic researchers a roadmap for further research.

This book discusses the effect of global pandemic, Covid-19, on human resource and draws strategies with new job designing tools and techniques. It provides insights on how to develop new strategies for HR professionals in corporates and academicians. This book explores the implication of descriptive, predictive and prescriptive HR analytics practices for different functional domains and in different countries during COVID-19. It brings new dimensions of study in HR analytics which are sure to change after COVID-19 as it has affected the way people are going to work.

How might one determine if a financial institution is taking risk in a balanced and productive manner? A powerful tool to address this question is economic capital, which is a model-based measure of the amount of equity that an entity must hold to satisfactorily offset its risk-generating activities. This book, with a particular focus on the credit-risk dimension, pragmatically explores real-world economic-capital methodologies and applications. It begins with the thorny practical issues surrounding the construction of an (industrial-strength) credit-risk economic-capital model, defensibly determining its parameters, and ensuring its efficient implementation. It then broadens its gaze to examine various critical applications and extensions of economic capital; these include loan pricing, the computation of loan impairments, and stress testing. Along the way, typically working from first principles, various possible modelling choices and related concepts are examined. The end result is a useful reference for students and practitioners wishing to learn more about a centrally important financial-management device.

In recent years, digital business models have frequently been the subject of academic and practical discourse. The increasing interconnectivity across the entire supply chain, which is subsumed under the term Industry 4.0, can unlock even farther-reaching potentials for digital business models, affecting entire supply chains and ecosystems. This book examines the specific challenges and obstacles that supply chain and ecosystem management poses with regard to the development of digital business models. The top-quality contributions gathered here focus on the successful implementation of Industry 4.0 in digital business models for industrial organizations in a European context, making the book a valuable asset for researchers and practitioners alike.

* Covers the entire new venture management process, from ideas to finance to HRM * Now includes international cases in all chapters * Offers a complete and contemporary business plan for students to follow * Includes material on the latest issues in entrepreneurship, such as equity crowdfunding and 'blitzscaling'

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.

For courses in Graduate MIS, Decision Support Systems, and courses covering the principles of enterprise resource planning systems. This text takes a generic approach to enterprise resource planning systems and their interrelationships, covering all functional areas of this new type of management challenge. It discusses the re-design of business processes, changes in organizational structure, and effective management strategies that will help assure competitiveness, responsiveness, productivity, and global impact for many organizations in the years ahead.

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.