The global supply chain has been severely impacted with the outbreak of COVID-19. The continuous supply of essential products in the post-COVID-19 world is a truly effective and strategic contest. The security and useability of inventory management are a main burden for industries along with the pressure from the government to fulfil the targets of net-zero economy in an uncertain circumstance. One of the most potential keys to these issues is an accurate demand forecasting process by blockchain technology. This article addresses a basic outline for blockchain-based supply chain (SC) and reveals how blockchain technology (BCT) can aid policymakers to cut carbon footprint during and postpandemic time in a fuzzy environment. This study fuzzifies all the carbon factors as intuitionistic triangular fuzzy numbers and uses a signed distance method to defuzzify the model. We consider that the retailer can embrace BCT to enhance demand forecasting. The planned scenario is modeled as an optimization problem to maximize the profit with low carbon emissions and suggest a solution method to solve it. A numerical example is also given to validate the model. We compare the optimal decisions of the SC with and without BCT. We discover that the pandemic and BCT have considerable influences on the optimal results. The study also shows that practitioners should exercise caution when developing operational strategies for maximizing profit with the least amount of carbon emissions during and postpandemic time.

中文翻译：

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考虑不确定的碳足迹和流行病影响的基于区块链的库存系统

COVID-19 的爆发严重影响了全球供应链。在后 COVID-19 世界中，必需品的持续供应是一场真正有效的战略竞赛。库存管理的安全性和可用性以及政府在不确定的情况下实现净零经济目标的压力是行业的主要负担。这些问题最潜在的关键之一是通过区块链技术进行准确的需求预测过程。本文介绍了基于区块链的供应链 (SC) 的基本轮廓，并揭示了区块链技术 (BCT) 如何帮助政策制定者在模糊环境中减少大流行期间和大流行后的碳足迹。本研究将所有碳因子模糊化为直观的三角模糊数，并使用符号距离方法对模型进行去模糊化。我们认为零售商可以采用 BCT 来增强需求预测。将计划的场景建模为优化问题，以实现低碳排放利润最大化，并提出解决方案。还给出了数值例子来验证模型。我们比较了有和没有 BCT 的 SC 的最佳决策。我们发现，疫情和 BCT 对最佳结果有相当大的影响。研究还表明，从业者在制定运营策略时应谨慎行事，以在疫情期间和疫情后以最少的碳排放实现利润最大化。