Replenishment decision and coordination contract in cluster supply chain
| Published date | 08 July 2019 |
| Pages | 1374-1399 |
| DOI | https://doi.org/10.1108/IMDS-02-2019-0087 |
| Date | 08 July 2019 |
| Author | Bo Yan,Xiaoxu Chen,Yanping Liu,Chang Xia |
| Subject Matter | Information & knowledge management |
Replenishment decision and
coordination contract in cluster
supply chain
Bo Yan, Xiaoxu Chen, Yanping Liu and Chang Xia
School of Economics and Commerce,
South China University of Technology, Guangzhou, China
Abstract
Purpose –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.
Design/methodology/approach –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.
Findings –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.
Originality/value –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.
Keywords Revenue-sharing contract, Third-party logistics, Cluster supply chain, Replenishment decision,
Vendor managed inventory
Paper type Research paper
1. Introduction
We consider a cluster supply chain with multiple vendors –one third-party logistics (TPL)
provider and one retailer. The concept of cluster supply chain comes from industrial
clusters. Companies in cluster supply can use the advantages of industrial clusters to
achieve economies of scale and improve their operational efficiency. However, the cluster
supply chain in developing countries experiences many problems, such as excessive
competition, the bullwhip effect, inventory backlog and lack of innovation ability. Moreover,
the decisions of the three parties involved in such a supply chain are complicated. The main
purpose of this study is to establish a model to address these issues, find out optimal
decisions and choose the suitable contract to coordinate the supply chain.
Over the past decade, an increasing number of studies have combined industry clusters
with supply chain management. Humphrey and Schmitz (2002) argued that industrial
clusters and supply chains have similar characteristics, coordinate economic activities and
improve the market competitiveness of enterprises by managing nonmarket relationships.
By studying the operation of Amish furniture industry, Dewitt et al. (2006) proved that the
Industrial Management & Data
Systems
Vol. 119 No. 6, 2019
pp. 1374-1399
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-02-2019-0087
Received 17 February 2019
Revised 19 May 2019
Accepted 12 June 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
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).
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IMDS
119,6
combination of industrial cluster and supply chain management can improve the
competitiveness and performance of enterprises. Subramanian et al. (2016) considered
the logistics under cluster supply chain. The role of fourth-party logistics in enhancing the
competitiveness of industrial clusters was investigated via importance–performance matrix
analysis. The above papers focused on internal clusters and analyzed the relationship
between industrial clusters and supply chains through qualitative research methods.
However, they lacked quantitative analysis of the optimal strategies of industrial clusters in
supply chain management. Accordingly, the present study develops a mathematical method
to study optimal replenishment decisions and analyze its impact. The model we studied is
suitable for replenishment decision making of industrial clusters in supply chain.
In order to enhance the cooperation of the cluster supply chain and reduce the entire
logistic cost (Waller, 1999), vendor managed inventory (VMI) is used by many companies.
However, a surge in the number of customers increases the demand for the logistic and
information ability of vendors and thus raises the cost and risk for vendors in managing
inventory (Cooke, 1998). So, more and more logistics enterprises integration on VMI system
is used in cluster supply chain, which can enhance information quality and reduce cost (Kuk,
2004; Subramanian et al., 2016; Kayvanfar et al., 2018). Li et al. (2013) found that the
operation of VMI and TPL can greatly reduce the inventory level of the entire system and
effectively improve the production rhythm of vendors and service level of customers. They
used a simulation model to study a centralized VMI and TPL system, where TPL is
responsible for replenishment and delivery decisions throughout the supply chain. The
present study further investigates the VMI and TPL system by using mathematical
programming and optimization theories.
In addition, the industrial cluster and TPL have increased the difficulty of managing the
entire supply chain. Another question that is taken into account is how to coordinate the
distributionof interest and risk among supply chainmembers to enhance cooperation among
enterprises.Through the analysis of the clustersupply chain under the VMI and TPL system,
this study mainly answers three questions: first, what is the optimal replenishment decision
that is beneficial to the overall supplychain? Second, how do parametersaffect replenishment
decisions? Finally, which contract is best suited to coordinate the cluster supply chain and
how are parameters set to achieve supply chain coordination?
To solve these problems, this study discusses the replenishment decisions in the cluster
supply chain under VMI&TPL system. Based on asymmetric Nash negotiation, the study
also designs a “risk sharing–revenue sharing”contract which enhances the operational
efficiency of the entire supply chain and improves the revenues of all its members.
2. Literature review
In this study, we examine the situation of multiple vendors –one TPL provider and one
retailer –and the replenishment decisions made by TPL. Therefore, the content of this study
is summarized as replenishment and batch problems. Harris (1913) proposed an economic
order quantity (EOQ) model to determine the number of one-time orders (outsourced or
homemade). When company orders are in accordance with the EOQ, the sum of the ordering
and storage costs can be minimized. Many studies were then expanded on the basis of this
basic model, including multiple products (Hsu, 1983), quantity discounts (Munson and
Rosenblatt, 2001) and dynamic requirements (Robinson et al., 2009). Numerous works have
considered transportation costs based on the EOQ model, such as Aucamp (1982), Iwaniec
(1979) and Lippman (1969, 1971), which have fixed transportation costs in their models.
Subsequently, a growing number of studies set transportation costs as a variable. McCann
(1996) considered transportation costs when considering logistics and linked transportation
costs to distances. Mendoza and Ventura (2008) extended the EOQ model to two modes of
transport –trucking and less than trucking –setting the transportation cost to be related to
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Cluster supply
chain
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