Optimization of Strategic Decision Making for Integrated Inventory-Transportation Problem From the Perspective of Voluntary Emission Reduction

With transportation and inventory in logistics being major sources of carbon emissions driving global warming, enterprises face pressing needs to curb their carbon footprint through integrated inventory-transportation optimization and voluntary emission reduction (VER) efforts. This study addresses the core issue of strategic-level integrated inventory-transportation problem (IITP), aiming to provide actionable strategic insights by incorporating a comprehensive fuel consumption model under both VER and involuntary emission reduction (IER) scenarios. Methodologically, it develops optimization models for strategic IITP under both scenarios, implements computational solutions via simulation, and uses paired samples t-tests and regression to assess VER’s impacts on decision outcomes and operational performance, alongside exploring carbon emission-cost relationships. Key findings reveal that VER reduces logistics resource utilization and carbon emissions but increases operational costs; under both VER and IER, carbon emissions and costs exhibit an inverted U-shaped relationship, with VER accelerating the decline in the marginal emission increase relative to costs and lowering the emission peak inflection point. Demand volatility exerts significant negative impacts on supply chain costs, carbon emissions, and inventory capacity, ultimately weakening the supply chain’s uncertainty resilience and robustness, while fuel price fluctuations affect total supply chain costs but have minimal impacts on other operational indicators. Additionally, rising stock-out costs drive increased logistics resource investment, which in turn elevates both operational costs and carbon emissions.