Corporate governance is not just about models of best practice organisation or prescriptions following laws or social conventions. Corporate governance is also about persons of power seeking performance, and they do so in ways that transcend structures and pre-conceived notions of the structural set-up of the business. This book emphasises the decision-making dimensions of corporate governance, placing it right in the messy middle of the ever-changing world of capitalism, focussing on the interplay between professional managers and shareholders. This book aims to bring together several fresh perspectives on the development of capitalism seen through the lens of corporate governance. It illustrates the role of intentionality and persons, both as a method with which to understand processes of change, but also as a principle with which to seek a deeper understanding of the corporate governance choices made. It will be of interest to researchers, academics and students in the fields of corporate governance and entrepreneurship, as well as practitioners and other audience interested in the evolution of capitalism and corporate culture.

This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the "curse of dimensionality", their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task. Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks; Describe implementation and evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality; Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. "This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge." M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas "In science the difficulty is not to have ideas, but it is to make them work" From Carlo Rovelli

Digital entrepreneurship refers to business activities in the digital media and information and information and communication technologies. It encompasses entrepreneurial pursuits in areas such as artificial intelligence, blockchain, internet of things, and augmented reality among many more. The digital economy is expected to bring about $60 Trillion in revenue by 2025. With the rise and proliferation of emerging technologies globally, entrepreneurs have pursued opportunities to leverage skills, abilities, and resources to find innovative revenue streams. Companies such as Facebook, Uber, and Twitter are examples of highly successful digital firms that have become giants in the industry. Entrepreneurs and executives from all over the world are looking to follow in their footsteps. The book will outline and discuss ideas and approaches for companies of all sizes to benefit from the digital economy. This edited book brings together chapter contributions from leading practice experts and academics from all over the world. It advances contemporary thinking on digital entrepreneurship and aims to become the ultimate reference guide on the subject, making it especially valuable to researchers, academics, students, and professionals in the fields of entrepreneurship, international business, and the management of technology and innovation.

This book analyses the historical context and progression of "significant innovations" beginning with the industrial revolution, starting around 1750 to the present. It explores the interrelationship, causes, and evolutionary process of contemporary "disruptive" inventions and the role played by global finance and international commerce to support these. First, the authors examine the environment and circumstances surrounding the inventors and explore their backgrounds to determine, why at a specific time, they identified a need that became the seed for invention and, what was their method of successfully commercializing their innovation. Secondly, they focus on the financing of the inventor, the innovation, and the commercialization of the invention(s). They analyze the changes in finance during the shift from a labor-based production process to a more capital-intensive production process, and what new financial products or financial markets were created to facilitate this transition. Third, they explore the impact of global commerce on the inventor country's innovation environment and international competition impacting the innovation's production, distribution, and sales, as well as, investigating any financial impact from the demand side and whether that impact was domestic or global in character. Furthermore, they consider if and how global finance and international commerce including the migration of people, together play a role in helping the disruptive invention satisfy a need in society, whether from a production or consumption perspective. Finally, they search for common elements that repeatedly inspired inventors and their disruptive innovations over time. This book will appeal to global government officials, business leadership, early career professionals, and students across a number of disciplines including finance, economics, business, engineering, and technology.

*Addresses a shift in thinking about entrepreneurial education, away from business and toward school education internationally. *Supports learning about and through entrepreneurial thinking within the context of school teaching. *Encourages teachers to develop their own entrepreneurial thinking skills.

*Addresses a shift in thinking about entrepreneurial education, away from business and toward school education internationally. *Supports learning about and through entrepreneurial thinking within the context of school teaching. *Encourages teachers to develop their own entrepreneurial thinking skills.

In this book the author aims to describe the path from Information Technology to Information Management and Information Governance. This path allows organizations to identify IT Business Value and take advantage of it. The book synthesizes the main approaches that have emerged in recent years, compares these approaches along multiple variables, and finally proposes an advanced and new approach to Information Governance, based on the concept of Organizational Absorptive Capacity. Furthermore, the book presents a new approach to Information Management: the SIGMA (Strategic Information Governance Modelling and Assessment) approach. The new approach is centered on information as a key factor allowing integration between IT applications, organizational capabilities and business strategy. In particular, the Absorptive Capacity concept is presented and discussed: this concept represents the ability of an organization to maintain and absorb the potential of information and IT investments. After having presented and discussed the model, we also provide the reader with a brief presentation of how the SIGMA approach should be applied in companies. The book adopts a scientific approach to ensure methodological rigour; however, it is also concrete and describes problems from the viewpoints of managers, adopting a clear and easy-to-understand language in order to capture the interest of top managers and graduate students.

This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA). This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDA in IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy.

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

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

IT solutions from the leading edge

Information technology promises much but, as many businesses are finding, it often fails to deliver. Representing the new wave of thinking about I.T., this thought-provoking collection assembles leading researchers from four continents, including Dan Robey, Robert Zmud, Claudio Ciborra and Robert Benjamin. Writing with deep knowledge of both I.T. and business, they persuasively argue for the integration of the core business unit and the I.T. function, advocate a new role for I.T. professionals, stress the importance of managing outcomes rather than process, and provide practical guidelines for turning new ideas into new management practices.

This book explores the impact of design science and design thinking on tourism planning, gathering contributions from leading authorities in the field of tourism research and providing a comprehensive and interconnected panorama of cutting-edge results that influence the current and future design of tourist destinations. The book builds on recent findings in psychology, geography and urban and regional planning, as well as from economics, marketing and communications, and explores the opportunities arising from recent advances in the Internet and related technologies like memory, storage, RFID, GIS, mobile and social media in the context of collecting and analyzing traveler-related data. It presents a broad range of insights and cases on how modern design approaches can be used to develop new and better touristic experiences, and how they enable the tourism industry to track and communicate with visitors in a more meaningful way and more effectively manage visitor experiences.

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

Social Entrepreneurship: A Practical Introduction equips aspiring entrepreneurs with the tools needed to design and launch businesses to create positive social change in their communities. This accessible textbook aims to educate and motivate people interested in social entrepreneurship, showing that such businesses are a valuable part of the community development toolbox. Each chapter focuses on a key aspect of social entrepreneurship, from value creation and business planning to impact measurement and scaling up. Different social business models are presented, with analysis of their strengths and weaknesses. Cases and examples are included throughout the book and showcase real-life social enterprises in North America, South America, Europe, Australia, Africa, and the Caribbean. Discussion questions also support reflection and learning. A downloadable workbook offers support with checklists, social impact measurement, and other areas. An instructor manual containing test questions and experiential exercises is also available as a digital supplement for adopters. This book is ideal for introductory courses in social entrepreneurship and community development. It will also be valuable for those involved in social enterprises on the ground.

Social Entrepreneurship: A Practical Introduction equips aspiring entrepreneurs with the tools needed to design and launch businesses to create positive social change in their communities. This accessible textbook aims to educate and motivate people interested in social entrepreneurship, showing that such businesses are a valuable part of the community development toolbox. Each chapter focuses on a key aspect of social entrepreneurship, from value creation and business planning to impact measurement and scaling up. Different social business models are presented, with analysis of their strengths and weaknesses. Cases and examples are included throughout the book and showcase real-life social enterprises in North America, South America, Europe, Australia, Africa, and the Caribbean. Discussion questions also support reflection and learning. A downloadable workbook offers support with checklists, social impact measurement, and other areas. An instructor manual containing test questions and experiential exercises is also available as a digital supplement for adopters. This book is ideal for introductory courses in social entrepreneurship and community development. It will also be valuable for those involved in social enterprises on the ground.

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

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

Includes global case studies of organizations in the cultural sector to facilitate translation of theory into practice Author team combines academic and practitioner expertise Unique combination of fundraising and creative/cultural industries

Israeli national neoliberalism has promoted innovation policies leading to an ostensible paradox: At the center is a startup nation with a vibrant and successful high-tech entrepreneurial ecosystem, accumulating resources and enabling constant growth. At the geographical and social periphery, there has emerged a parallel society with often-marginalized groups not able to keep up. In one of the most unequal countries with a high rate of poverty, entrepreneurial heroes are celebrated at the center, promoting a myth that all could be self-made successes. At the periphery, entrepreneurs are struggling to survive, often pushed into precarious working and living conditions. Applying critical theory discourse, this book illustrates how neoliberalism and entrepreneurship are intertwined and how the startup nation has evolved in Israel. It explores how national neoliberal state policies have targeted technological innovation as a tool to obtain a competitive advantage in the international arena rather than aiming at increasing economic achievements and well-being for all. It will demonstrate that the Israeli entrepreneurship scene exemplifies the existence of parallel entrepreneurial societal spaces, analyze the positionality of entrepreneurs belonging to a variety of groups that characterize Israeli society, and uncover structural disadvantages and related levels of precarity as well as existing links between entrepreneurial advantages and disadvantages, mobility and varying degrees of social marginality. Dark Sides of the Startup Nation sheds light onto the problematic and sometimes contradictory myth that entrepreneurship is meritocratic and that neoliberal capitalism provides everyone with equal opportunities to succeed. The book will be of interest to researchers, academics, policy makers and students in the fields of entrepreneurship and small business management, responsibility and business ethics, and technology and innovation.

Includes global case studies of organizations in the cultural sector to facilitate translation of theory into practice Author team combines academic and practitioner expertise Unique combination of fundraising and creative/cultural industries

The only up-to-date introductory textbook on sport entrepreneurship and innovation. Entrepreneurial skills are essential for anybody working in sport management, particularly in the face of COVID-related challenges. Introduces key theory and focuses on best practice, based on real world scenarios. Includes practitioner voices throughout.

For courses in decision support systems, computerised decision-making tools, and management support systems. Market-leading guide to modern analytics, for better business decisions Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus - analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT.

This book examines returns on experience and managerial practices to generate deeper collaboration, intensify co-creation, support start-ups and established companies to explore, develop, and accelerate their projects thanks to open labs (living labs, fab labs, coworking spaces, "third spaces", etc.). Open labs are the beatbox to create a rhythm in ecosystems and make all stakeholders move forward, faster, together. This book proposes a framework to understand how open labs, innovation hubs, and collaborative spaces contribute to ecosystems. The book looks beyond the short-term effects of open labs and identifies four main dimensions: communities, physical spaces, events, and portfolios of services offered to private businesses, entrepreneurs, and start-ups, established companies, or public institutions. Drawing on extensive field research lasting over five years, with more than 40 cases and more than 200 interviews plus direct observation within different environments, this edited book investigates how managers run these labs, and how "users" or "clients" evolve when benefitting from their services. All chapters analyse how an actual management impacts the dynamics of communities, how it shapes the co-evolution between open labs and their ecosystems, and how the management of the physical space impacts the mission of the lab and its role in the ecosystem. Open Labs and Innovation Research is written for scholars and researchers in the fields of innovation studies and management science. This book can also inform teaching, public policymaking, and professional practice.

This book focusses on various options of taking up ventures for starting entrepreneurship in small/large scale in the field of renewable energy technologies. The book covers the fundamentals of entrepreneurship, renewable energy resources, their technologies involved and applications along with financial evaluations. The book will cater to the needs of students, researchers, various stakeholders, entrepreneurs etc. by providing valuable information on renewable energy technologies and their applications in developing entrepreneurship and establishing enterprise at individual level, specifically focusing on low carbon technology for sustenance of environment which is becoming increasingly important.

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