Sustainable Development Goals of the Belt and Road Initiative: progress assessment, influencing factors, and trend prediction framework

Abstract Against the backdrop of sustainable development, the implementation of the green Belt and Road Initiative (BRI) contributes to advancing the achievement of the global Sustainable Development Goals (SDGs). To this end, this study constructs a comprehensive research framework encompassing “assessment-explanation-prediction”. This study examines 64 countries along the Belt and Road route. Based on an assessment of their progress in implementing the SDGs, it explores the factors influencing sustainable development and forecasts the potential for implementation under current development trajectories. The findings reveal: (1) From 2000 to 2023, the level of sustainable development in countries along the route showed a steady upward trend, though regional disparities persisted. (2) Only a handful of countries have achieved the ideal model of coordinated development pace and target alignment. By 2030, significant gaps remain between these countries and the realization of the SDGs. (3) The RF-SHAP model identifies institutional quality, economic growth, and resource endowment as key determinants of SDGs outcomes. This study provides theoretical guidance for developing differentiated sustainable development strategies and advancing the green Belt and Road Initiative.

Authors

Institutions

Publication Details

Journal
Humanities and Social Sciences Communications
Published
2026-07-24
DOI
https://doi.org/10.1057/s41599-026-08373-8
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sustainable Development Goals of the Belt and Road Initiative: progress assessment, influencing factors, and trend prediction framework

Ma Yp, Yiqing Yan, Yiwen Shi
Humanities and Social Sciences Communications
Energy, Environment, Economic Growth
article

Sustainable Development Goals of the Belt and Road Initiative: progress assessment, influencing factors, and trend prediction framework

Ma Yp, Yiqing Yan, Yiwen Shi
article en

Abstract

Abstract Against the backdrop of sustainable development, the implementation of the green Belt and Road Initiative (BRI) contributes to advancing the achievement of the global Sustainable Development Goals (SDGs). To this end, this study constructs a comprehensive research framework encompassing “assessment-explanation-prediction”. This study examines 64 countries along the Belt and Road route. Based on an assessment of their progress in implementing the SDGs, it explores the factors influencing sustainable development and forecasts the potential for implementation under current development trajectories. The findings reveal: (1) From 2000 to 2023, the level of sustainable development in countries along the route showed a steady upward trend, though regional disparities persisted. (2) Only a handful of countries have achieved the ideal model of coordinated development pace and target alignment. By 2030, significant gaps remain between these countries and the realization of the SDGs. (3) The RF-SHAP model identifies institutional quality, economic growth, and resource endowment as key determinants of SDGs outcomes. This study provides theoretical guidance for developing differentiated sustainable development strategies and advancing the green Belt and Road Initiative.

Humanities and Social Sciences Communications
Northeastern University (CN)
Openalex Percentile: Top 4%
Energy, Environment, Economic Growth
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.