LOGISTICS DISPROPORTIONS IN CHINA’S CONSTRUCTION AND THE DIGITAL TOOLS TO NARROW THEM
DOI:
https://doi.org/10.36773/1818-1112-2025-138-3-193-196Keywords:
construction logistics, digitalization, supply-chain BIM, digital twins, e-procurement, IoT tracking, TMS, inland hubs, ChinaAbstract
This article reframes China’s inland-coastal gap in construction as a logistics disproportions problem and builds a logistics-first digital agenda to address it. First, it defines logistics disproportions as systematic differences in end-to-end lead-time predictability, the transport mode mix for heavy modules, and the stability of payment cycles. It then synthesizes peer-reviewed literature on coastal logistics, Building Information Modeling (BIM) and digital twins, national policy on prefabrication, and international rankings/benchmarks to establish the evidence base and bound plausible effect sizes. Second, it translates that evidence into an operational toolbox: supply-chain BIM (SC-BIM) that models routings and staging; factory-yard-site digital twins for re-sequencing and buffer sizing; standardized e-procurement with product data templates; Internet of Things (IoT) tracking with a transportation management system (TMS); verifiable shipment/installation milestones to align cash with events; artificial-intelligence (AI) risk forecasting; and inland consolidation hubs positioned near railheads. Third, it converts the agenda into a testable plan. A SWOT analysis identifies assets and frictions; a transformation roadmap assigns owners, instruments, and target indicators – on-time delivery, rail/water share of ton-kilometres, re-handling reduction, P90 – P50 delivery-window spread, and days sales outstanding (DSO) – with staged horizons of 9–36 months. Fourth, it specifies governance conditions: shared data schemas, open APIs, and product data templates to ensure interoperability across provinces and portfolios. A brief vignette illustrates how the playbook scales from a single inland project to programs. Finally, it acknowledges limits (secondary data, uneven provincial granularity) and sets a research agenda: open lead-time datasets, PDT-based public-procurement pilots, and causal evaluation of rail-hub deployments. In terms of China's construction logistics, the SWOT configuration in the table revealed precisely these imbalances: strong coastal logistics corridors and mature digital platforms coexist with structurally weaker domestic networks, higher turnaround time volatility, and slower adoption of smart logistics tools. In practice, this means that strengths and opportunities are locally concentrated, while weaknesses and threats accumulate in inland regions and small towns, where construction projects depend on smaller and less sustainable supply routes.
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