IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-15-4944-1_1.html
   My bibliography  Save this book chapter

Global Production and Domestic Divides

In: Big Data Analysis on Global Community Formation and Isolation

Author

Listed:
  • Yuichi Ikeda

    (Kyoto University)

Abstract

In this chapter we aim to study globalization and divides from different disciplines through the flows of commodity, money, and human. First, we demonstrate that economic globalization can simultaneously reduce international economic inequality by fostering successful economic growth in developing countries, and worsen domestic economic inequality, e.g., by increasing relative poverty levels in developed countries. Next, we outline a network analysis of global interdependence as mediated by flows of commodities, money, people, and knowledge. It is vital to acquire different perspectives on globalization and clarify its effects on isolated communities. With these empirical facts to hand, and taking theoretical considerations into account, we simulate how economic globalization reduces international economic inequality in developing countries and at the same time worsen domestic economic inequality in several developed countries by introducing a toy model adapted from condensed matter physics. Finally, we emphasize that data and network science offer a practical methodology for opening up new horizons in interdisciplinary academic research. Such a research methodology is characterized by “understanding the macro world using microscopic data, which is being developed around the world” and aims to provide a new measure of value.

Suggested Citation

  • Yuichi Ikeda, 2021. "Global Production and Domestic Divides," Springer Books, in: Yuichi Ikeda & Hiroshi Iyetomi & Takayuki Mizuno (ed.), Big Data Analysis on Global Community Formation and Isolation, pages 1-19, Springer.
  • Handle: RePEc:spr:sprchp:978-981-15-4944-1_1
    DOI: 10.1007/978-981-15-4944-1_1
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-981-15-4944-1_1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.