1. School of Big Data and Intelligent Engineering, Chongqing College of International Business and Economics, Chongqing 401520, China
2. Chengdu Institute of Metrology Verification and Test, Chengdu 610000, China
| Abstract: | Against the combined background of global climate governance and the digital transformation of healthcare, low-carbon development in the healthcare industry chain has shifted from energy-saving measures within individual medical institutions to coordinated governance across multiple industrial sectors. This study defines a patient-centered boundary for healthcare industry interconnection. On the basis of direct carbon accounting and input-output embodied carbon-flow analysis, it develops a hierarchical collaborative optimization model that integrates critical-path emissions, terminal-sector-induced emissions, and system-stability constraints. Target cascading is adopted to decompose and coordinate the resulting multi-objective optimization problem. Using publicly available sectoral carbon-emission and input-output data from CEADs, macroeconomic data from the National Bureau of Statistics of China, and total health-expenditure data from national and WHO sources, we calibrate the healthcare industry chain for 2018-2022 and conduct scenario simulations. The results show that the critical-path optimization mechanism reduces calibrated carbon emissions by approximately 18.7% relative to the baseline while maintaining an economic output growth rate of about 4.2%. The coordinated critical-path and terminal-sector mechanism performs better in both emission-reduction performance and system stability. These findings indicate that low-carbon transformation in healthcare should not be limited to terminal energy conservation in hospitals; instead, it should identify and compress high-intensity embodied carbon-flow paths transmitted through upstream manufacturing, logistics and warehousing, chemical inputs, and energy supply. |
| Keywords: | Low-Carbon Healthcare; Industry Interconnection; Embodied Carbon Flow; Target Cascading; Scenario Simulation; Supply-Chain Stability |
| DOI: | 10.57237/j.wjmst.2026.03.001 |
| 1. | Natural Science Project of Chongqing College of International Business and Economics (KYZK202306) |
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