International production and trade in a high-tech industry: A multilevel network analysis

•Applies the multilevel exponential random graph model to a novel dataset of international trade and ownership.•Examines the international production in a high-tech sector (medical and precision instruments).•The results from the multilevel ERGM highlight the complex interplay between firm-level act...

Full description

Saved in:
Bibliographic Details
Published in:Social networks 2019-10, Vol.59, p.50-60
Main Authors: Smith, Matthew, Gorgoni, Sara, Cronin, Bruce
Format: Article
Language:English
Subjects:
Corporate ownership network
Exponential random graph models
High tech industries
International organisation of production
International trade
Multilevel networks
Network analysis
Ownership
Value chain
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Applies the multilevel exponential random graph model to a novel dataset of international trade and ownership.•Examines the international production in a high-tech sector (medical and precision instruments).•The results from the multilevel ERGM highlight the complex interplay between firm-level activity and international trade.•This approach could be extended to compare the international organisation of production across different industries. We propose a multilevel network approach as an alternative framework to analyse the international organisation of an industrial sector. We present a novel application of a multilevel Exponential Random Graph Model to a multilevel network of firms linked by ownership at the micro level, countries linked by trade at the macro level, and a firm-county affiliation network linking the two in a high-tech industry. The results from the multilevel ERGM reveal a complex interplay between firm-level activity and international trade patterns. The approach can be extended to other industries to improve understanding of the international organisation of production, to map global value chains and to compare industries.
ISSN:0378-8733
1879-2111
DOI:10.1016/j.socnet.2019.05.003