Network resilience modelling: a New Zealand forestry supply chain case

• Date: 21 March 2020
• Published date: 21 March 2020
• Pages: 291-311
• DOI: https://doi.org/10.1108/IJLM-12-2018-0316
• Author: Paul Childerhouse,Mohammed Al Aqqad,Quan Zhou,Carel Bezuidenhout
• Subject Matter: Management science & operations,Logistics

Network resilience modelling: a

New Zealand forestry supply

chain case

Paul Childerhouse and Mohammed Al Aqqad

Department of Operations and Engineering Innovation, Massey University,

Palmerston North, New Zealand

Quan Zhou

School of Management, Operations and Marketing, Faculty of Business,

University of Wollongong, Wollongong, Australia, and

Carel Bezuidenhout

Department of Operations and Engineering Innovation, Massey University,

Palmerston North, New Zealand

Abstract

Purpose –The objective of this research is to model supply chain network resilience for low frequency high

impact disruptions. The outputs are aimed at providing policy and practitioner guidance on ways to enhance

supply chain resilience.

Design/methodology/approach –The research models the resilience of New Zealand’s log export logistical

network. A two-tier approach is developed; linear programming is used to model the aggregate-level resilience

of the nation’s ports, then discrete event simulation is used to evaluate operational constraints and validate the

capacity of operational flows from forests to ports.

Findings –The synthesis of linear programming and discrete event simulation provide a holistic approach to

evaluate supply chain resilience and enhance operational efficiency. Strategically increasing redundancy can

be complimented with operational flexibility to enhance network resilience in the long term.

Research limitations/implications –The two-tier modelling approach has only been applied to New

Zealand’s log export supply chains, so further applicationsare needed to insure reliability. The requirement for

large quantities of empirical data relating to operational flows limited the simulation component to a single

region

Practical implications –New Zealand’s log export supply chain has low resilience; in most cases the closure

of a port significantly constrains export capacity. Strategic selection of location and transportation mode by

foresters and log exporters can significantly enhance the resilience of their supply chains.

Originality/value –The use of a two-tiered analytical approach enhances validity as each level’s limitations

and assumptions are addressed when combined with one another. Prior predominantly theoretical research in

the field is validated by the empirical investigation of supply chain resilience.

Keywords Australia, Supply chain risk, Asia, Modelling, Supply chain processes, Global logistics

Paper type Research paper

Introduction

The elongated nature of modern supply chains puts them at risk to spatially dispersed

disruptions that can have unforeseen and dramatic consequences. Political, economic,

infrastructural and cultural risks need due consideration when operating globally. Tsunamis,

strikes, hurricanes, biosecurity threats and wars can have significant impacts on logistical

networks. The labour strike in October 2002 resulted in 29 ports in America’s west coast

Network

resilience

modelling

291

This paper forms part of a special section “ISL 2018 23rd Symposium on Logistics”, guest edited by

Shams Rahman and Nyoman Pujawan.

The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/0957-4093.htm

Received 20 December 2018

Revised 24 October 2019

Accepted 17 February 2020

The International Journal of

Logistics Management

Vol. 31 No. 2, 2020

pp. 291-311

© Emerald Publishing Limited

0957-4093

DOI 10.1108/IJLM-12-2018-0316

shutting down (Wilson, 2007) whilst in 2011 Toyota’s production capacity dropped by 40,000

vehicles due to Japan’s tsunami and the consequent nuclear crisis (Pettit et al., 2013). These

events and their disastrous consequences show the importance of having contingency plans

for such events to minimise their effect along supply chains.

Supply chain resilience has developed as an approach to counter the risks inherent in

globally dispersed networks. The literature provides a good coverage of the types of supply

chain resilience (J€

uttner et al., 2003;Cox et al., 2011), resilience assessment techniques (e.g.

Wang and Ip, 2009) and management strategies and conceptual frameworks to facilitate

supply network resilience (Soni et al., 2014). As previous research proposes redundancy as a

means to deal with high frequency low impact risks (e.g. Chowdhury and Quaddus, 2017), this

strategy is less applicable to more disruptive risks that have longer term affects and typically

occur less frequently, such as earthquakes. Meanwhile, despite the significant conceptual

advances, there is a dearth of empirical applications and practitioner focused approaches to

mitigating supply chain risks (Brandon-jones et al., 2014), particularly those relating to

transportation (Ho et al., 2015).

Researchers have used different modelling tools to simulate systems under different

conditions to prepare for disruptions and accordingly improve their responsiveness and

resilience. These modelling tools include linear programming (Santoso et al., 2005), fuzzy

modelling (Petrovic et al., 1998), discrete event simulation (Terzi and Cavalieri, 2004) and

hybrid models (Umeda and Zhang, 2006). Some researchers focus on aggregate level analysis

(e.g. Meepetchdee and Shah, 2007;Towill, 1996) while other researches address the micro

level by isolating a certain part of the supply chain to be studied in depth (e.g. Legato and

Mazza, 2001;Cheng and Duran, 2004). The integration of multiple tools in one approach

would capture both strategic and operational considerations in the decision-making process

in order to produce more valid recommendations.

Globalisation has significantly increased the number of international trade transactions,

as many customers now compare products and services offered by suppliers from all around

the world. Consequently, marine traffic has witnessed a constant growth that is expected to

continue into the future (Huang et al., 2016). This trend had increased the importance of ports

within logistical networks. Local and central governments make significant investments and

develop infrastructure dedicated to enabling the import and export of goods. Through the

resilience modelling of a nation’s logistical network current vulnerabilities and contingencies

can be identified. In particular, port capacity constraints and associated risks could be

highlighted for island nations such as New Zealand.

New Zealand is a major exporter of logs in the global market, and it relies on its ports to

deliver these products to its international customers. The forestry industry is a major

contributor to New Zealand’s economy providing more than 18,000 jobs in 2014 (NZFOA,

2017). In 2013, New Zealand made up more than 20% of the world’s softwood log trade

and became the world largest exporter of softwood logs (SCOOP, 2014). The log industry is

a large part of New Zealand’s exports contributing more than 16 million m

3

of logs in

2014 (NZFOA, 2017). The disruption of this supply chain by a port closure could have

catastrophic consequences on New Zealand’s economy, necessitating the creation of

contingency plans for such events. Thus we plan on modelling the network resilience of New

Zealand’s log exports.

The resilience modelling of an entire country’s logistical network will provide a novel

empirical application.Our aim is to not only model the aggregate resilienceof the network but

also evaluate the operationalproduct flows of this economically significant industry. This will

provide a novel contributionby focussing on operational resilience of a real world networkin

regard to port capacity and system flexibility. This operational information will have more

potential valuefor commercial decision makers in regard to port allocationand inland routing

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