首页|生鲜农产品零售商的区块链技术投资决策与订货策略

生鲜农产品零售商的区块链技术投资决策与订货策略

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区块链技术在生鲜农产品供应链中已经得到广泛应用.本文以报童模型为基础,研究了零售商在生鲜农产品市场中订货决策以及区块链投资策略问题.在模型中考虑了需求和农产品新鲜度的随机性、区块链的投资成本以及区块链技术的预测精度水平等特征的基础上,比较零售商在使用区块链前后的订货策略和绩效水平,分析区块链为农产品供应链带来的商业价值以及零售商对于区块链的投资策略.研究表明:零售商利用区块链技术可以及时预测到农产品的新鲜度状态,优化了零售商的订货策略,从而在减少食品浪费和提高供应链绩效水平方面发挥重要作用.然而在一些特定情况下,零售商投入过多资源以实现高精度的区块链预测并不是一个最优选择,此时零售商采用低精度的区块链技术也能实现收益的增长.而当区块链投资成本超过特定阈值时,零售商将不会采用区块链技术.
Blockchain Technology Investment Decision and Ordering Strategy for Fresh Agricultural Product Retailer
Blockchain technology has been widely adopted in the fresh agricultural product supply chain.This paper investigates the retailer's ordering decision and blockchain investment strategy in the fresh agricultural product market based on the newsvendor model.Considering the randomness of demand and freshness of agricultural products,the investment cost of blockchain,and the prediction accuracy level of blockchain technology,we compare retailers'strategies and performances before and after blockchain implementation.Additionally,we analyze the business value that blockchain brings to the agricultural supply chain and the retailer's investment strategy for blockchain.The study demonstrates that retailer can utilize blockchain technology to accurately predict the freshness status of agricultural products and optimize their ordering strategies.This approach plays a significant role in reducing food waste and enhancing supply chain performance.However,in certain scenarios,the retailer's investing excessive funds to achieve high-precision blockchain prediction may not always be the optimal choice.In such cases,adopting low-precision blockchain technology can still yield significant returns.When the cost of blockchain investment exceeds a certain threshold,the retailer prefers to use traditional forecasting methods instead of blockchain.

blockchainfresh agricultural product supply chainnewsvendor modelfreshnessinvestment strategy

向泽华、王明征、李永刚

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浙江大学 管理学院,浙江 杭州 310058

大连理工大学经济管理学院,辽宁 大连 116024

区块链 生鲜农产品供应链 报童模型 新鲜度 投资策略

国家自然科学基金重点资助项目国家自然科学基金重点国际合作资助项目

7193100972010107002

2024

工程管理科技前沿
合肥工业大学预测与发展研究所

工程管理科技前沿

CSTPCDCSSCICHSSCD北大核心
影响因子:1.084
ISSN:2097-0145
年,卷(期):2024.43(5)