ORIGINAL ARTICLE
Design of agile supply chains including the trade-off between number
of partners and reliability
Chong Wu
1
&
David Barnes
2
Received: 4 December 2017 /Accepted: 14 May 2018 /Published online: 29 May 2018
#
Springer-Verlag London Ltd., part of Springer Nature 2018
Abstract
The reliability of supply partners is particularly vital in agile supply chains as it is vulnerable to the inability of a supply partner to
meet its high responsiveness and flexibility requirements resulting in the disruption of the whole network. Disruption can have
expensive and extensive results for the entire agile supply chain. To mitigate the risk of disruption and improve the reliability of
the whole agile supply chain, decision-makers need to pay more attention to supply chain design and construction while
simultaneously taking into account the sourcing strategy decisions. This paper proposes a series of models for the design of
agile supply chains using dynamic programming modeling. These provide decision-makers with a systematic way of analyzing
one of the key decisions of sourcing strategy, namely the trade-off between the number of supply partners and reliability. The
efficacy of the models is demonstrated through their application to a Chinese bus and coach manufacturer by way of an empirical
illustration. The results show that this approach is effective for this application, and it can be applied in other related decision-
making scenarios. The methods offered in this paper provide managers with a practical tool to design their agile supply chains
while considering the trade-offs between the number of partners and the reliability of the entire agile supply chain.
Keywords Supply chain design
.
Supply chain reliability
.
Agile supply chain
.
Partnership
.
Dynamic programming
1 Introduction
Supply chain disruption is one of the most common problems
in supply chain management [48]. Veysey [57] found that
approximately 85% of companies have experienced supply
disruption at least once. Even if all of the key parameters of
a supply chain are known with certainty, disruptions may still
be experienced from time to time [27, 41]. Disruptive events
may happen anywhere and at any time, affecting any point in
the supply chain from raw materials to end-products [18].
Their causes can include extreme events, such as natural di-
saster, financial crisis, war, terrorism and political instability,
or other more routine, but nonetheless, serious causes, such as
fires, labor strikes, system breakdowns, and material supply
delay [51]. For instance, Hurricanes Harvey and Irma in 2017
on the US Gulf Coast caused extensive disruptions to many
supply chains, including production, processing,
warehousing, transportation, and retailing. Furthermore, dis-
ruptive events may sometimes last for an extended period of
time, as for example in 2010, when disruptions in flight sched-
ules due to the unpredictable spread of volcanic ash from
Iceland had a significant impact on supply chains of
European companies for many months [6]. The earthquake
and subsequent tsunami in northeast of Japan in 2011
disrupted the auto supply chains of Toyota, Honda, and
Nissan and continued to have impacts for several years.
Disruption can have expensive and extensive adverse con-
sequences [3]. Thus, reliability has been a key factor in supply
chain decisions as any supply chain requires high reliability to
ensure both its effectiveness and efficiency [16]. This is be-
cause disruption risks are fundamentally different from other
types of risk, such as customer demand uncertainties. Supply
disruption will completely halt material and production flows
and cause irreparable loss to the whole supply chain.
Therefore, designing reliability into the supply chain is one
of the most effective ways to mitigate disruption risk. Supply
* David Barnes
d.barnes@westminster.ac.uk
Chong Wu
Chong.Wu@xmu.edu.cn
1
School of Management, Xiamen University, Xiamen 361005,
People’s Republic of China
2
Westminster Business School, University of Westminster,
London NW1 5LS, UK
The International Journal of Advanced Manufacturing Technology (2018) 97:3683–3700
https://doi.org/10.1007/s00170-018-2205-5
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