Structural Evolution and Its Determinants of Domestic Value-Added Network of Digital Service Exports Based on Temporal Exponential Random Graph Model

ABSTRACT

Digital service trade has become an important engine of world economic growth, and its competitive landscape is also evolving. We construct domestic value-added networks of digital service exports (DVAN-DSEs) from 1995 to 2018 based on the world input-output table, and explores their structural evolution and determinants using Temporal Exponential Random Graph Model. We find that (a) the DVAN-DSEs present the features of agglomeration, heterogeneity, reciprocity and unevenness. (b) The United States and European countries are the core in DVAN-DSEs. (c) Preference attachment, structural embeddedness, delayed reciprocity, stability, variability, Matthew effect in GDP, population and Internet coverage, geographical proximity, cultural similarities, and regional trade agreements play important roles in the evolution of DVAN-DSEs. (d) Structural embeddedness and geographic proximity only facilitate new relationship construction, while other factors influence both relationship establishment and maintenance. Countries should build network facilities, expand trading partners and promote trade agreement negotiations to facilitate the development of digital service trade.

KEYWORDS:

• Digital service trade
• value-added
• network analysis methods
• Temporal Exponential Random Graph Model

JEL:

• C15
• F14

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Supplementary Material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/1540496X.2024.2341724.

Notes

1. http://www.caict.ac.cn/kxyj/qwfb/bps/202012/t20201216_366251.htm

2. https://www.bea.gov/research/papers/2012/trends-digitally-enabled-trade-services

3. https://www.oecd.org/industry/ind/measuring-trade-in-value-added.htm#access

Additional information

Funding

The work was supported by the Ministry of Education of the People’s Republic of China [19XJA790003]; National Natural Science Foundation of China [72003152]; National Social Science Fund of China [21ZDA093].