According to www.nature.com, a peer-reviewed model for sustainable closed-loop supply chain management—published in Scientific Reports on 15 June 2026—integrates trade credit, carbon emissions accounting, remanufacturing, and dynamic demand forecasting within a two-warehouse system for electronic gadgets.
Model Architecture and Operational Design
The study introduces a two-warehouse inventory framework involving both a manufacturer and a retailer, each operating an own warehouse (OW) and renting a rental warehouse (RW). The RW features superior preservation capabilities but incurs higher costs than the OW—a structural distinction that governs stock depletion order: OW inventory is consumed first, followed by RW stock. The manufacturer produces both perfect and imperfect units; defective items returned by the retailer are sent for remanufacturing, and all remanufactured products are allocated exclusively to secondary retail stores. Each product has a defined lifespan, and both parties invest in preservation technology (PT) to reduce deterioration rates—critical for electronics with finite functional lifespans.
Trade-credit policies are applied bilaterally: the manufacturer offers credit to the retailer, and the retailer extends credit to end customers. Advertising is explicitly modeled as a demand driver, reflecting its documented role in enhancing visibility for both new and remanufactured devices. Carbon emissions are quantified and monetized—both manufacturer and retailer calculate and pay for their respective emissions, embedding environmental cost directly into operational decision-making.
Numerical Validation and Sensitivity Insights
A numerical experiment validates the model’s optimization of production rate, remanufacturing rate, and cycle time. Sensitivity analysis reveals high responsiveness to cost parameters: a 20% increase in holding cost reduces total profit by 0.03%. This narrow margin underscores the financial precision required in sustainable inventory planning. The model also confirms that remanufacturing activity, carbon emission pricing, and defect-rate control collectively exert statistically significant influence on net profitability—0.03% being the empirically derived elasticity coefficient for holding cost under baseline assumptions.
The study further identifies that advertising intensity and stock availability jointly shape demand elasticity in real-time markets—departing from classical models assuming constant or linear demand. Instead, demand responds simultaneously to price, promotional effort, inventory level, and product life-cycle stage—a multidimensional response calibrated using Weibull-distributed deterioration and inflation-adjusted cost structures.
Industry Context and Practitioner Implications
This research aligns with broader industry shifts toward circular operations: Apple reported 98% material recovery rates from disassembled devices in its 2023 Environmental Progress Report, while Dell achieved 2.7 million kg of e-waste recycled globally in FY2024. Regulatory pressure is mounting—EU’s CSDDD directive mandates due diligence across value chains starting in 2027, and the CBAM mechanism began phased implementation in October 2023. In parallel, logistics providers like DHL and Maersk have launched carbon-inclusive freight contracts tied to verified Scope 3 reporting.
For supply chain professionals, the model delivers actionable levers: prioritizing PT investment over raw storage expansion, calibrating trade-credit periods against receivables turnover risk, and treating remanufacturing not as a cost center but as a profit-center with embedded carbon savings. Inventory planners must now factor emissions cost per unit into EOQ recalculations—shifting the classic ‘cost-minimization’ paradigm toward ‘carbon-cost-minimization’. As noted in the study’s conclusion:
“Remanufacturing and carbon-smart logistics can help reduce global warming, as semi-defective or defective products can be remanufactured into perfect products without being sent to the trash bin.” — Monika Vishnoi, D. Deepi, Shiv Raj Singh & Biswajit Sarkar
The authors include Monika Vishnoi, D. Deepi, Shiv Raj Singh, and Biswajit Sarkar, whose prior work on Weibull-distributed deterioration and two-warehouse systems appears in International Journal of Production Economics and Computers & Industrial Engineering. Their model appears in Scientific Reports volume 16, Article number 18438 (2026).
Source: nature.com
Compiled from international media by the SCI.AI editorial team.
