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entrepreneurship & innovation --- knowledge management & innovation --- management of innovation --- managing open innovation --- corporate innovation system --- economics of Innovation --- economics of innovation

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This book presents a rich selection of 36 real-world cases on how organizations in China explore the new growth pattern, business model innovation, and digital transformation in digital era. The topic of cases varies from digital marketing and Internet brands, the growth of digital platforms, digital transformation and the industrial Internet of things, strategies for cross-border e-commerce companies, and business model innovation in digital era, etc. These cases stem from a diverse set of industry sectors, reporting on best practices and lessons learned. The book shows how organizations strive to find new ways to develop and create new paths to grow in a digital world and shares essential practical insights into digital economy. All cases are presented in a standardized structure in order to provide valuable insights and essential guidance for practitioners, scholars as well as general readers.

Electronic commerce. --- Technological innovations. --- E-Business. --- e-Commerce and e-Business. --- Economics of Innovation. --- Economics --- Business & Economics

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“The author provides the reader with an innovative study of blockchain from an economics perspective. The author’s personal experience and credentials adds substantially to the body of literature that aids in our understanding of the blockchain phenomenon. It differs from other comparable studies with his perspective of examining the methodology of constructing mechanisms to accomplish blockchain consensus.” — Rosario Girasa, Distinguished Professor, Pace University, Pleasantville, New York, USA "Joshua Gans makes blockchain and consensus accessible to economists by applying his signature approach -- delving into a topic so deeply that he can extract its economic essence." - W. Scott Stornetta, Yugen Partners, Co-inventor of the Blockchain Blockchain technologies have been rapidly adopted for the creation of cryptocurrencies and have been explored for a myriad of applications. While this is of important economic interest, the computer science behind how blockchains operate to provide security and provenance has been largely inaccessible to economists. This book is a bridge between the computer science and the economics of blockchains. The focus is on the value and the achievement of blockchain consensus; that is, how distributed and independent nodes are able to reach an agreement on what the current state of digital ledgers, that are the product of blockchains, are. The book shows that the goals of computer scientists in designing blockchains place very high weight on security beyond what an economist trained in game theory and mechanism design would require. It shows how blockchains can be redesigned to account for key economic trade-offs, and will be of interest to researchers and students of economics, financial technology and computer science, alongside policymakers. Joshua Gans is a Professor of Strategic Management and holder of the Jeffrey S. Skoll Chair in Technical Innovation and Entrepreneurship at the Rotman School of Management, University of Toronto. He is also chief economist of its Creative Destruction Lab and oversees its blockchain program for startups.

Technological innovations. --- Economic development. --- Financial engineering. --- Computer science. --- Economics of Innovation. --- Economic Development, Innovation and Growth. --- Financial Technology and Innovation. --- Computer Science.

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This book is the third publication out of the Arts, Entrepreneurship, and Innovation (AEI) Lab that focuses exclusively on research that empirically investigates crossovers between arts, entrepreneurship and innovation. This volume does so specifically by using the lens of cultural economics. The chapters in this volume have been chosen not only because they have clear implications for policy and practice, but also because they contribute to theories of value creation in the cultural and creative industries. As a whole, this book addresses relationships between arts, entrepreneurship and innovation for workers, firms, and industry to bring clarity to how value is created in the arts. Previously published in Journal of Cultural Economics Volume 45, issue 4, December 2021 Chapters “Direct Memberships in Foreign Copyright Collecting Societies as an Entrepreneurial Opportunity for Music Publishers – Needs, Challenges, Opportunities and Solutions” and “Do Museums Foster Innovation Through Engagement with the Cultural and Creative Industries?” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Philosophy and psychology of culture --- Professional ethics. Deontology --- Sociology of culture --- cultuur --- deontologie --- bedrijfsethiek --- Art --- Culture --- Business ethics. --- Technological innovations. --- Theory of Arts. --- Cultural Studies. --- Business Ethics. --- Economics of Innovation. --- Philosophy. --- Study and teaching.

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Advances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI. It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted. It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions. Contributors: Daron Acemoglu, Massachusetts Institute of Technology Philippe Aghion, Collège de France Ajay Agrawal, University of Toronto Susan Athey, Stanford University James Bessen, Boston University School of Law Erik Brynjolfsson, MIT Sloan School of Management Colin F. Camerer, California Institute of Technology Judith Chevalier, Yale School of Management Iain M. Cockburn, Boston University Tyler Cowen, George Mason University Jason Furman, Harvard Kennedy School Patrick Francois, University of British Columbia Alberto Galasso, University of Toronto Joshua Gans, University of Toronto Avi Goldfarb, University of Toronto Austan Goolsbee, University of Chicago Booth School of Business Rebecca Henderson, Harvard Business School Ginger Zhe Jin, University of Maryland Benjamin F. Jones, Northwestern University Charles I. Jones, Stanford University Daniel Kahneman, Princeton University Anton Korinek, Johns Hopkins University Mara Lederman, University of Toronto Hong Luo, Harvard Business School John McHale, National University of Ireland Paul R. Milgrom, Stanford University Matthew Mitchell, University of Toronto Alexander Oettl, Georgia Institute of Technology Andrea Prat, Columbia Business School Manav Raj, New York University Pascual Restrepo, Boston University Daniel Rock, MIT Sloan School of Management Jeffrey D. Sachs, Columbia University Robert Seamans, New York University Scott Stern, MIT Sloan School of Management Betsey Stevenson, University of Michigan Joseph E. Stiglitz. Columbia University Chad Syverson, University of Chicago Booth School of Business Matt Taddy, University of Chicago Booth School of Business Steven Tadelis, University of California, Berkeley Manuel Trajtenberg, Tel Aviv University Daniel Trefler, University of Toronto Catherine Tucker, MIT Sloan School of Management Hal Varian, University of California, Berkeley

Artificial intelligence --- Economic aspects --- Artificial intelligence - Economic aspects --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Economic aspects. --- artificial intelligence. --- economics of innovation. --- general purpose technologies. --- inequality. --- machine learning. --- productivity. --- regulation.