The “snowball effect” in the transmission of disruptions in supply chains. The role of intensity and span of integration

• Date: 14 November 2016
• Pages: 1002-1038
• DOI: https://doi.org/10.1108/IJLM-08-2015-0133
• Published date: 14 November 2016
• Author: Artur Swierczek
• Subject Matter: Management science & operations,Logistics

The “snowball effect”in the

transmission of disruptions

in supply chains

The role of intensity and span

of integration

Artur Swierczek

Department of Business Logistics, University of Economics in Katowice,

Katowice, Poland

Abstract

Purpose –The purpose of this paper is to explore the link between interorganizational integration

with respect to its intensity and span, as well as the propagation and amplification of disruptions

alongside a supply chain.

Design/methodology/approach –The paper opted for an exploratory study using a survey of

companies. In order to extract the constructs manifesting the span and intensity of integration between

companies in supply chains, the principal component analysis was employed. The obtained factor

scores were then used as classification criteria in the cluster analysis. It enabled to include

similar organizations in terms of intensity and span of supply chain integration. In order to validate the

obtained results, the analysis of variance (ANOVA) was conducted and regression models

were developed.

Findings –The findings of the study show that there is a relationship between the intensity and span

of supply chain integration and the “snowball effect”in the transmission of disruptions. The obtained

findings show that the span of supply chain integration is negatively associated with the strength of

the “snowball effect”in the transmission of disruptions. In addition, the results suggest that more

intense supply chain integration contributes to the “snowball effect”in material flows in the forward

and backward transmission of disruptions.

Research limitations/implications –Although the current study investigates the intensity and

span of integration within the basic, extended and ultimate supply chain structure, it still lacks the

broader analysis of the “snowball effect”in the transmission of disruptions. The study investigates this

phenomenon only within the basic supply chain structure, constituted by the primary members.

Another challenge is to examine if the effects of external risk factors (e.g. natural disasters) may also be

transferred to other links in the supply chain structure, and what are the similarities and differences

(if any) between the mechanism of propagation and amplification of disruptions elicited by internal and

external risk factors. Another future direction of study is to define other ways of identification and

measurement of the “snowball effect”in order to make cross-industrial and international comparisons

of disruptions amplified in the transmission more standardized and objective. In the current study, the

phenomenon of the “snowball effect”is anchored in the subjective opinions of managers who may view

the problem from different angles. Consequently, the study is limited to individual perceptions of the

strength of disruptions affecting the solicited company, its customers and suppliers.

Practical implications –In practical terms, the findings provide crucial information for the

framework of supply chain risk management and therefore enable its more efficient and effective

implementation. The better the managers understand the nature of the “snowball effect”in the

transmission of disruptions, the easier it is for them to allocate resources and apply necessary

managerial tools to mitigate the negative consequences of risk more effectively. The deliverables of the

study also confirm that the interorganizational exchange of information accompanying the supply

The International Journal of

Logistics Management

Vol. 27 No. 3, 2016

pp. 1002-1038

©Emerald Group Publishing Limited

0957-4093

DOI 10.1108/IJLM-08-2015-0133

Received 12 August 2015

Revised 30 October 2015

Accepted 6 December 2015

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

www.emeraldinsight.com/0957-4093.htm

The study was financed by the National Science Centre as a research project no. DEC-2012/05/E/

HS4/01598.

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IJLM

27,3

chain integration enables to mitigate the strength of the “snowball effect”in the transmission of

disruptions. Another important implication is the broadening of practical expertise concerning the use

of integration not only as a means of obtaining and sustaining supply chain effectiveness and

efficiency, but also as the way to mitigate the “snowball effect”in the transmission of disruptions.

Therefore, nowadays the supply chain managers are facing another challenging task –namely, how to

balance supply chain integration in terms of span and intensity to ensure profits from integration and

mitigate the negative risk consequences transmitted among the links in supply chains.

Originality/value –The paper elaborates on the underestimated issue of the “snowball effect”in the

transmission of disruptions and its drivers. In particular, the paper attempts at filling the gap in

empirical studies concerning the relationships between the “snowball effect”in the transmission of

disruptions and supply chain integration.

Keywords Risk management, Supply chain management

Paper type Research paper

Introduction

A great deal of research on risk is conducted within the supply chain framework

(Christopher and Peck, 2004, Tang, 2006; Khan and Burnes, 2007). Interestingly ,

however, most studies still examine risk at the firm level, rather than at the

interorganizational level, although the practical examples prove that risk consequences

at the interorganizational level may be very pricey for supply chains. For instance,

Hendricks and Singhal (2003) use a sample of 519 announcements made during 1989-

2000 to investigate the shareholder wealth effects of supply chain glitches which

resulted in production or shipment delays. The study revealed that glitch

announcements decreased the shareholder value by 11 percent on average. Another

good example is the supply chain of Ericsson, which lost an estimated $2 billion in ten

minutes when a fire that happened at its manufacturer of chips left Ericsson with no

alternative source of supplies (Norrman and Jansson, 2004). In 1996, an 18-day labor

strike at a brake supplier factory halted the operations at 26 assembly plants of the

supply chain of General Motors (Hannah, 1996). On the other hand, the supply chain of

Boeing was affected by the loss of $2.6 billion when its two key suppliers failed to

deliver critical parts on time (Radjou et al., 2002). The aforementioned and other

examples, not cited here, document that the risk and its consequences are the issues of

critical importance for effectiveness and efficiency of contemporary supply chains.

In the literature, the problem of risk at the interorganizational level has been also

addressed by Juttner et al. (2003), who mention the “networkeffect”linked to the negative

consequences of risks arising from relationships among the parties in supply chains.

Similarly, Rapana (2009) acknowledges that supply chain risk is specific and likely to

affect several interdependent companies in a supply chain. Kersten et al. (2012) refer to

supply chain risks which are those risks that affect at least two companies of a supply

chain, and it isirrelevant whether a company is affected directly or indirectly by a supply

chain risk. Consequently, Van Dorp and Duffey(1999) advocate to treat the risk effects as

simultaneous and interdependent elements rather than sequential and statistically

independent.Sodhi and Lee (2007) outline that the companiesin a supply chain should be

aware of potential and actual risk consequences emanating from each link. Cavinato

(2004) mentions the relational risk eliciting from linkages between a supplier,

manufacturer and customers, established to provide a maximum benefit.

The negative outcome of risk takes the form of disruption which is a combination of

unintended and anomalous risk consequences that materialize in a supply chain and

significantly threaten normal business operations of the firms or the whole supply

chain (Wagner and Bode, 2008). The significance of disruptions stems from the fact

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Role of

intensity and

span of

integration

that they may be amplified during the transmission in a supply chain. This

phenomenon may be defined as the “snowball effect”and means that each successive

link in a supply chain can be exposed to stronger effects of risks. However, there has

been little research on how the “snowball effect”in the transmission of disruptions is

driven. Based on the extant literature, we posit that the “snowball effect”can be driven

by an excessive mutual dependence among companies (Peck, 2005; Juttner, 2005;

Swierczek, 2014) that is caused by establishing integrative relationships in supply

chains (Golicic et al., 2003; Svensson, 2002a, b; Mentzer et al., 2001, 2004). Interestingly

enough, integration is paradoxically argued as a pillar that lays a foundation for the

supply chain concept (Lamming et al., 2004; Ellram and Cooper, 1990; Kampstra et al.,

2006; Samaranayake, 2005), which makes the study even more compelling.

Despite its ubiquity, the issue of risk at the interorganizational level within the

supply chain framework has not been a subject of intense research yet. In consequence,

there is a paucity of studies that address the effects of supply chain integration on

the transmission of disruptions. The paper offers a first pass at filling this gap by

examining the role of supply chain integration, with respect to its intensity and span, in

eliciting the “snowball effect”in the transmission of disruptions among companies.

To address this gap, this paper draws on the tenets of three theories –network theory,

contagion theory and systems thinking.

The network theory is used in the paper to elaborate on the issue of supply chain

integration. It posits that numerous connection types are considered in the supply chain

structure. Hearnshaw and Wilson (2013) argue that these connections are based on

contracts and include material flows, information flows and financial flows. Material

flows refer to the transfer of physical products, information flows refer to the transfer

of coordinating data and financial flows refer to the transfer of monetary resources,

all relating to the exchange of products or services performed in supply chains. Brass

(2002) argues that the network theory is about the set of nodes that have multiple links

and may be centrally or locally located. Kim et al. (2011) acknowledge that when

drawing a model of supply chain, a unique network pattern potentially emerges for

each connection type. Accordingly, graphical representations of a network based on the

same set of firms, but analyzing different connection types, should produce different

network topologies (Hearnshaw and Wilson, 2013), from basic and extended to ultimate

supply chain structures.

The second theory –contagion theory –serves to consider the problem of spreading

disruptions in a supply chain. In line with this theory, the contagion effect is generated

if two markets are correlated during periods of stability and a disruption in one market

leads to a significant increase in market co-movement (Forbes and Rigobon, 2002).

Although the whole concept is elaborated from the macroeconomic perspective, there

are also certain prerequisites for investigating the contagion effect within the supply

chain framework. Kolb (2011) asserts that there is a mechanism of transmission from

one infected party to others. The problem here is to identify the channels of contagion

as a means by which risk consequences spread from one arena to others. In this vein,

Glick and Rose (1999) evidence that trade linkages between countries and markets are

the channels of the transmission of disruptions. The trade linkages also prevail in

supply chains, which justify the use of the tenets of contagion theory when exploring

the scope and types of the transmission of disruptions. In addition, the higher the

degree of integration, the more extensive the contagious effects (Morales et al., 2014).

Following this view, we use the contagion theory for our study to identify supply chain

integration as a major driver of the transmission of disruptions.

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