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绿色农产品供应链补贴计划,具有绿色可追溯性和平台的数据驱动营销。

Green Agricultural Products Supply Chain Subsidy Scheme with Green Traceability and Data-Driven Marketing of the Platform.

机构信息

School of Business, Qingdao University, Qingdao 266071, China.

出版信息

Int J Environ Res Public Health. 2023 Feb 9;20(4):3056. doi: 10.3390/ijerph20043056.

DOI:10.3390/ijerph20043056
PMID:36833775
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9960969/
Abstract

Government subsidies have played an important role in the development of green agriculture. In addition, the Internet platform is becoming a new channel to realize green traceability and promote the sale of agricultural products. In this context, we consider a two-level green agricultural products supply chain (GAPSC) consisting of one supplier and one Internet platform. The supplier makes green R&D investments to produce green agricultural products along with conventional agricultural products, and the platform implements green traceability and data-driven marketing. The differential game models are established under four government subsidy scenarios: no subsidy (NS), consumer subsidy (CS), supplier subsidy (SS), and supplier subsidy with green traceability cost-sharing (TSS). Then, the optimal feedback strategies under each subsidy scenario are derived using Bellman's continuous dynamic programming theory. The comparative static analyses of key parameters are given, and the comparisons among different subsidy scenarios are conducted. Numerical examples are employed to obtain more management insights. The results show that the CS strategy is effective only if the competition intensity between two types of products is below a certain threshold. Compared to the NS scenario, the SS strategy can always improve the supplier's green R&D level, the greenness level, market demand for green agricultural products, and the system's utility. The TSS strategy can build on the SS strategy to further enhance the green traceability level of the platform and the greenness level and demand for green agricultural products due to the advantage of the cost-sharing mechanism. Accordingly, a win-win situation for both parties can be realized under the TSS strategy. However, the positive effect of the cost-sharing mechanism will be weakened as the supplier subsidy increases. Moreover, compared to three other scenarios, the increase in the environmental concern of the platform has a more significant negative impact on the TSS strategy.

摘要

政府补贴在绿色农业发展中发挥了重要作用。此外,互联网平台正成为实现绿色可追溯和促进农产品销售的新渠道。在此背景下,我们考虑了一个由一个供应商和一个互联网平台组成的两级绿色农产品供应链(GAPSC)。供应商进行绿色研发投资,生产绿色农产品和传统农产品,平台实施绿色可追溯和数据驱动的营销。在四种政府补贴情景下(无补贴(NS)、消费者补贴(CS)、供应商补贴(SS)和供应商补贴与绿色可追溯成本分担(TSS))建立了微分博弈模型。然后,使用贝尔曼连续动态规划理论推导出每个补贴情景下的最优反馈策略。给出了关键参数的比较静态分析,并对不同补贴情景进行了比较。通过数值例子获得了更多的管理见解。结果表明,CS 策略只有在两种产品之间的竞争强度低于一定阈值时才有效。与 NS 情景相比,SS 策略总能提高供应商的绿色研发水平、绿色水平、绿色农产品的市场需求和系统效用。TSS 策略可以在 SS 策略的基础上进一步提高平台的绿色可追溯水平和绿色水平以及对绿色农产品的需求,因为成本分担机制具有优势。因此,在 TSS 策略下可以实现双赢局面。然而,随着供应商补贴的增加,成本分担机制的积极作用将减弱。此外,与其他三种情景相比,平台对环境的关注增加对 TSS 策略的负面影响更大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/e5a01411e60d/ijerph-20-03056-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/615ea070d644/ijerph-20-03056-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/1cd10b5a9975/ijerph-20-03056-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/bd377173c512/ijerph-20-03056-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/4a94994a2794/ijerph-20-03056-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/6c881774569f/ijerph-20-03056-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/77f38698a860/ijerph-20-03056-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/e5a01411e60d/ijerph-20-03056-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/615ea070d644/ijerph-20-03056-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/1cd10b5a9975/ijerph-20-03056-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/bd377173c512/ijerph-20-03056-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/4a94994a2794/ijerph-20-03056-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/6c881774569f/ijerph-20-03056-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/77f38698a860/ijerph-20-03056-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d98/9960969/e5a01411e60d/ijerph-20-03056-g007.jpg

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