The cluster supply chain is widely used in the professional towns in China, and improves the competitiveness of small and medium enterprises through integrating the supply chain with the industrial cluster. The paper aims to discuss this issue.
This paper studies a cluster supply chain under vendor managed inventory (VMI) system, which includes vendors, third-party logistics (TPL) enterprises and retail enterprises, and aims to study the replenishment decisions and coordination contracts in the supply chain. The economic order quantity model is applied to analyze the influence of marginal transportation cost factor under two replenishment modes – direct delivery and milk-run delivery, in order to find out the optimal replenishment decisions corresponding to different marginal transportation cost factors. And then, the revenue sharing contract is used to identify the change of profits of enterprises in the supply chain before and after the coordination contract.
It is concluded that the marginal transportation cost factor is an important factor influencing the replenishment decision especially in milk-run delivery, and the introduction of the revenue sharing contract can improve the revenue in the supply chain.
This is the first study that explores the relationship between a single transport cost and a single transport batch of cluster supply chain in centralized VMI & TPL system. The conclusions of the study have certain theoretical significance for the decision making and coordination of cluster supply chain.
This work was supported by National Natural Science Foundation of China (71871098), Humanities and Social Sciences Research Planning Fund Project of the Ministry of Education (18YJA630127), Natural Science Foundation of Guangdong Province (2017A030313415), Philosophical and Social Sciences Planning Project of Guangzhou (2019GZGJ05), and Fundamental Research Funds for the Central Universities (ZDPY201914).
Yan, B., Chen, X., Liu, Y. and Xia, C. (2019), "Replenishment decision and coordination contract in cluster supply chain", Industrial Management & Data Systems, Vol. 119 No. 6, pp. 1374-1399. https://doi.org/10.1108/IMDS-02-2019-0087
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