Global study on the Measurement and Spatial Variation Characteristics of the Level of Development of Digital Trade

Hao Xiong () and Tiantian Lou ()
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Hao Xiong: Henan University of Science and Technology, School of Business
Tiantian Lou: Henan University of Science and Technology, School of Business

A chapter in Proceedings of the 2026 5th International Conference on Big Data Economy and Digital Management (BDEDM 2026), 2026, pp 265-275 from Springer

Abstract: Abstract Digital trade has emerged as a key driver of global economic growth and the transformation of international trade structures. Drawing on data from 67 countries (2014–2022), this study develops a multidimensional evaluation system covering digital innovation, skills, trade scale, infrastructure, trust and risk, barriers, and trade environment. Using the entropy weight-TOPSIS method to measure national digital trade development levels, and integrating the Dagum Gini coefficient decomposition, spatial convergence models, and Markov chain analysis, we systematically examine its spatiotemporal dynamics. Findings reveal:(1)an overall upward trend with distinct spatial heterogeneity—Asia leads while Africa lags; (2) convergence in overall disparity, marked by declining inter-regional contributions and rising hypervariable density, reflecting intensified cross-regional interplay; (3) significant σ- and absolute β-convergence across most regions except North America and Africa, alongside pervasive conditional β-convergence; and (4) strong path dependence and stability in development states, where transitions occur only between adjacent tiers and are significantly influenced by neighboring regions’ development levels.

Keywords: Digital Trade; Spatiotemporal volution; Markov Chain (search for similar items in EconPapers)
Date: 2026
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DOI: 10.2991/978-94-6239-640-1_25

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