Publications by Type: Book

2021
Tang C. 2/1/2021. Data Capital: How Data is Reinventing Capital for Globalization. 1st ed., Pp. 391. Cham, Switzerland: Springer International Publishing AG (Signed the Contract in 2016). Publisher's VersionAbstract

This book defines and develops the concept of data capital. Using an interdisciplinary perspective, this book focuses on the key features of the data economy, systematically presenting the economic aspects of data science. The book (1) introduces an alternative interpretation on economists’ observation of which capital has changed radically since the twentieth century; (2) elaborates on the composition of data capital and it as a factor of production; (3) describes morphological changes in data capital that influence its accumulation and circulation; (4) explains the rise of data capital as an underappreciated cause of phenomena from data sovereign, economic inequality, to stagnating productivity; (5) discusses hopes and challenges for industrial circles, the government and academia when an intangible wealth brought by data (and information or knowledge as well); (6) proposes the development of criteria for measuring regulating data capital in the twenty-first century for regulatory purposes by looking at the prospects for data capital and possible impact on future society.

Providing the first a thorough introduction to the theory of data as capital, this book will be useful for those studying economics, data science, and business, as well as those in the financial industry who own, control, or wish to work with data resources. 

 
Da ta Cap ital, n.
1. A human-created resource that is naturally one capital. 2. A digital, intangible capital form that claims to cover almost the digital part of all existing capital, from tangibles’ digital twin and intangibles’ measurable aspect, to financials. 3. The strategic economic resources for the data economy. 4. A parasitic economic logic to develop new forms of business that serve the industries within the first three categories of Fisher-Clark’s classification. 5. An intangible wealth marked by concentrations of information, knowledge, and wisdom unprecedented in human history. 6. A possible sovereign power that is subordinated to modern global architecture but has no physical boundaries. 7. The origin of a decentralized instrumentation power that asserts dominance over society and brings the opportunities for market democracy.
 
 
unnamed_2.jpg booksellerflyer bookcover.jpg Highlghts, Acknowledge, and Contents Part I Part II Part III Part IV List of tables, illustrations, case studies, data sources, and definitions & Index
2016
Tang C. 6/2/2016. The Data Industry: The Business and Economics of Information and Big Data., Pp. 216. NY: John Wiley & Sons; 1 edition. Publisher's VersionAbstract

Provides an introduction of the data industry to the field of economics

This book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry. It begins by explaining data resources and introduces the data asset. This book defines a data industry chain, enumerates data enterprises’ business models versus operating models, and proposes a mode of industrial development for the data industry. The author describes five types of enterprise agglomerations, and multiple industrial cluster effects. A discussion on the establishment and development of data industry related laws and regulations is provided. In addition, this book discusses several scenarios on how to convert data driving forces into productivity that can then serve society. This book is designed to serve as a reference and training guide for ata scientists, data-oriented managers and executives, entrepreneurs, scholars, and government employees.This book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry. It begins by explaining data resources and introduces the data asset. This book defines a data industry chain, enumerates data enterprises’ business models versus operating models, and proposes a mode of industrial development for the data industry. The author describes five types of enterprise agglomerations, and multiple industrial cluster effects. A discussion on the establishment and development of data industry related laws and regulations is provided. In addition, this book discusses several scenarios on how to convert data driving forces into productivity that can then serve society. This book is designed to serve as a reference and training guide for ata scientists, data-oriented managers and executives, entrepreneurs, scholars, and government employees.
  • Defines and develops the concept of a “Data Industry,” and explains the economics of data to data scientists and statisticians
  • Includes numerous case studies and examples from a variety of industries and disciplines
  • Serves as a useful guide for practitioners and entrepreneurs in the business of data technology
The Data Industry: The Business and Economics of Information and Big Data is a resource for practitioners in the data science industry, government, and students in economics, business, and statistics.
 

Two recent articles (see the link1, link2) published in authoritative journal The Economist, which agreed with all the opinions in this book.

 

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