Author
Listed:
- Lingxiang Jian
(School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)
- Yuefeng Bai
(School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)
- Xinyue Zhang
(School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)
- Qingyu Zhao
(School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)
Abstract
Against the backdrop of the “Dual Carbon” strategy and global shipping digitalization, data elements have emerged as the key enabling factor and predictive correlate of coastal port smartness. Using panel data for seven coastal provinces/municipalities and eight coastal ports in China from 2017 to 2024, this paper constructs a “base-supply-flow-use” data element development index (DEDI) and a “WSR” coastal port smartness index (CPSI), employing VHSD-EM dynamic model, random forest algorithm, and partial effect model to examine the association patterns, nonlinear responses, and differentiated enhancement pathways between data elements and port smartness. Findings reveal: (1) CPSI and DEDI exhibit a high positive correlation with narrowing regional disparities; (2) CPSI shows stepwise spatial differentiation, with Shanghai and Ningbo-Zhoushan Ports leading, while Guangdong demonstrates “data advancement but smartness lag”; (3) in the random forest model, the predictive contribution of DEDI to CPSI is 13.586%, which ranks behind digital inclusive finance and openness level but is higher than regional economic strength and innovation output. The combined predictive contribution of the DEDI main effect and its interaction terms reaches 32.567%; (4) the univariate partial effect of DEDI on predicted CPSI followed a three-stage nonlinear pattern of initial accumulation, accelerated improvement around a threshold of DEDI ≈ 0.215, and diminishing marginal effects at higher levels; and (5) the joint partial effects of DEDI with digital inclusive finance, economic development, fiscal transportation expenditure, and innovation output showed clear dimensional and regional heterogeneity. Accordingly, four policy pathways are proposed: constructing a full-chain data element system, enabling synergistic empowerment of data and supporting elements, formulating regionally differentiated catch-up strategies, and strengthening the dual-wheel support of digital inclusive finance and opening-up—all aimed at advancing the development of world-class ports.
Suggested Citation
Lingxiang Jian & Yuefeng Bai & Xinyue Zhang & Qingyu Zhao, 2026.
"Research on the Association and Pathways Between Data Elements and Coastal Port Smartness Enhancement,"
Sustainability, MDPI, vol. 18(12), pages 1-31, June.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:12:p:5989-:d:1964949
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