Modelling resilience in supply chain
Dissertação para obtenção do Grau de Doutor em Engenharia Industrial
Orientador: Virgílio António Cruz Machado
Professor Catedrático, Faculdade de Ciências e Tecnologia
da Universidade Nova de Lisboa
Júri:
Presidente: Prof. Doutor Fernado José Pires Santana
Arguente(s): Prof. Doutor Rui Manuel Soucasaux Meneses e Sousa Prof. Doutor Kannan Godivan
Vogais: Prof. Doutora Susana Maria Palavra Garrido Azevedo
Prof. Doutora Virgínia Helena Arimateia de Campos Machado Prof. Doutora Ana Paula Ferreira Barroso
Prof. Doutor Luís Miguel Domingues Fernandes Ferreira
Prof. Doutor Virgílio António Cruz Machado
Modelling resilience in supply chain
Helena Carvalho Remigio
20
Modelling resilience in supply chain
Dissertação para obtenção do Grau de Doutor em Engenharia Industrial
Orientador: Virgílio António Cruz Machado
Professor Catedrático, Faculdade de Ciências e Tecnologia
da Universidade Nova de Lisboa
Júri:
Presidente: Prof. Doutor Fernado José Pires Santana
Arguente(s): Prof. Doutor Rui Manuel Soucasaux Meneses e Sousa Prof. Doutor Kannan Godivan
Vogais: Prof. Doutora Susana Maria Palavra Garrido Azevedo
Prof. Doutora Virgínia Helena Arimateia de Campos Machado Prof. Doutora Ana Paula Ferreira Barroso
Prof. Doutor Luís Miguel Domingues Fernandes Ferreira
Prof. Doutor Virgílio António Cruz Machado
© 2012 Helena Maria Lourenço Carvalho Remigio
Faculdade de Ciências e Tecnologia and Universidade Nova de Lisboa
Copyright
My sincere gratitude goes to Professor Virgílio Cruz-Machado who was not only my thesis supervisor but also believed in me and always had motivated me to go further. A special thanks to Professor Susana Azevedo, who was always willing to give me sound advice and constantly challenge me to explore new research topics and methodologies.
The support and encouragement provide by Professor Virgínia Machado and Professor Ana Paula Barroso was essential complete this study. I also desire to express my gratitude to UNIDEMI researchers, in particular Professor António Grilo, Professor Isabel Nunes, and Professor Alexandra Tenera for their incentive during the thesis development.
I also want to express my gratefulness to faculty and staff in the DEMI/FCT/UNL department for being extremely supportive during this journey.
A deeply thank to my PhD colleagues Susana Duarte, Fernado Grilo, Natacha Correia, Rui Pulido Valente, Sara Figueira, Izunildo Cabral, Pedro Espadinha and Meysam Maleki for all the productive discussions and motivation.
Thanks to all companies’ managers and collaborators involved in the research for giving their time and for how much I learned through them.
I also like to express my gratitude to Professor Fátima Raposo and Paulo Ribeiro, from DF/FCT/UNL, for guiding me through my first steps in research.
A great thank to my family for their never ending support and lovely understanding. Finally to my parents that always support me and push me to go higher, as higher as I want.
As cadeias de abastecimento globais são vulneráveis a inúmeras perturbações que podem afetar negativamente o desempenho operacional e financeiro das empresas. A capacidade das empresas em responder adequadamente às perturbações da cadeia de abastecimento, isto é, a capacidade de serem resilientes, é vital para se manter um elevado nível de competitividade, quer das empresas quer das respetivas cadeias de abastecimento. O propósito desta tese é a modelação da resiliência no contexto da cadeia de abastecimento. Mais especificamente, o objetivo consiste no desenvolvimento de um modelo explicativo da resiliência da cadeia de abastecimento e na modelação de índices de resiliência para avaliar a capacidade das empresas quanto à sua resiliência. Usando uma abordagem centrada na “construção de teoria”, foi conduzida uma investigação suportada pelo método de estudo de caso em sete empresas pertencentes ao sector upstream da cadeia de abastecimento da indústria automóvel Portuguesa. Verificou-se que os gestores não associam as perturbações da cadeia de abastecimento a eventos específicos, mas sim aos efeitos negativos que estes provocam. O conjunto de práticas resilientes adotadas pelas empresas depende do tipo de perturbações e respetivos efeitos negativos, tendo-se constatado que os principais modos de falha que emergem do estudo de caso são “escassez de capacidade” e “escassez de material”. A partir das evidências do estudo de caso foram propostas oito proposições, as quais foram utilizadas no desenvolvimento de um modelo explicativo das relações existentes entre perturbações, modos de falha e práticas resilientes da cadeia de abastecimento. Para sustentar a avaliação de resiliência das empresas, dois índices de resiliência foram modelados e desenvolvidos. Estes índices pretendem medir a capacidade das empresas em manter o seu desempenho em termos de “entrega no prazo” quando ocorre uma “escassez de capacidade” e/ou uma “escassez de material”. Finalmente, os índices foram testados nas empresas. A dissertação contribui para a literatura existente ao investigar empiricamente os principais efeitos das perturbações na cadeia de abastecimento; por outro lado, abre perspetivas quanto à forma de aumentar a resiliência das empresas e, por conseguinte, das cadeias de abastecimento em que estão inseridas. Neste sentido, é proposta uma abordagem para avaliar a resiliência das empresas sendo identificado um conjunto de variáveis de estado da cadeia de abastecimento, as quais poderão ser monitorizadas com vista à melhoria da resiliência das empresas e das respectivas cadeia de abastecimento.
Global supply chains are vulnerable to a number of disturbances that may affect negatively company’s operational and financial performance. The company’s ability to cope with supply chain disturbances, i.e. the ability to be resilient, is vital to sustain the company and respective supply chain competitiveness. The aim of this thesis is modelling resilience in a supply chain context. More specifically, it is intended to develop an explanatory framework of the supply chain resilience phenomena and to model supply chain resilience indices to be deployed at individual company level. These indices intend to measure the companies’ ability to be resilient in a supply chain context. Using a theory building approach, a case study was conducted in seven companies’ belonging to the Portuguese automotive upstream supply chain. It was found that managers do not associate supply chain disturbances to a particular type of events, but with the negative effects that events provoke. When companies experience a disturbance, its ability to deliver on-time may be compromised. The resilient practices, adopted by companies, depend on the type of supply chain disturbances and their negative effects. The main failure modes arising from the case study are “capacity shortage” and “material shortage”. Eight propositions were derived from the case study empirical findings. They were used to develop the supply chain resilience explanatory framework, to provide additional understanding regarding the relationships between supply chain disturbances, supply chain failure modes and resilient practices. To support the assessment of companies’ resilience, two resilience indices were modelled and developed. These indices intend to measure the companies’ ability to sustain its performance in terms of “on-time delivery” when a “capacity shortage” or “material shortage” occur. Finally, the indices were tested in companies belonging to the Portuguese automotive upstream supply chain. The dissertation contributes to the existing literature by empirically investigating the main effects of supply chain disturbances and how companies can increase supply chain resilience. It suggests an approach to assess companies’ resilience and identifies a set of supply chain state variables that companies may control to improve supply chain resilience.
1 Introduction...1
1.1 Aim ...1
1.2 Objective and research questions ...5
1.3 Methodology...6
1.4 Contents...7
1.5 Conclusion ...9
2 Supply Chain Resilience ... 11
2.1 Supply chain management... 11
2.1.1 Supply chain...11
2.1.2 Management practices ...13
2.2 Supply chain performance ... 22
2.3 Supply chain disturbances ... 24
2.3.1 Uncertainty and risk...24
2.3.2 Vulnerability, disruptions and disturbances ...26
2.4 Supply chain failure modes... 29
2.4.1 Failure modes categories...29
2.4.2 Failure mode analysis ...33
2.5 Supply chain resilience... 38
2.5.1 Definition ...38
2.5.2 Resilient practices...42
2.6 Resilience triangle... 45
2.7 Conclusions... 48
3 Supply Chain Design for Resilience ... 49
3.1 Contribution of lean and agile strategies for supply chain resilience... 49
3.1.1 Lean supply chain strategy...50
3.1.2 Agile supply chain strategy...51
3.1.3 Supply chain attributes...52
3.2 Resilient capabilities... 52
3.3 Resilience in supply chain design ... 57
3.4 Conceptual model for resilience assessment... 61
3.5 Conclusions... 65
4 Research Methodology ... 67
4.1 Selected research methodology... 67
4.1.1 Inductive research approach...67
4.1.2 Theory building and case study method ...68
4.2 Case selection... 71
4.3 Data collection ... 73
4.4 Data analysis ... 76
4.5 Case study quality and limitations ... 78
5 Case Study ... 81
5.1 Case study... 81
5.1.1 Automotive supply chain ...81
5.1.2 Automaker...84
5.1.3 First tier suppliers ...85
5.1.4 Logistic providers...86
5.1.5 Supply chain operations...87
5.2 Supply chain management practices deployed by companies ... 88
5.2.1 Implementation level ...88
5.2.2 Relationships between practices and performance ...92
5.3 Disturbance definition ... 94
5.3.1 Supply chain disturbances examples ...95
5.4 Supply chain failure modes... 97
5.5 Resilient practices deployed by companies ... 101
5.6 Conclusions... 104
6 Supply Chain Resilience Modelling... 107
6.1 Framework for resilience modelling in supply chain ... 107
6.2 Resilience assessment... 111
6.2.1 Resilience metric ...111
6.2.2 Resilience indices ...111
6.3 Resilience indices modelling ... 112
6.3.1 Aggregation...114
6.3.2 Index development ...114
6.3.3 State variables ...116
6.3.4 Indices formulation...120
6.4 Resilience indices application: a case study in the automotive supply chain ... 121
6.4.1 Capacity shortage: state variables scores ...121
6.4.2 Material shortage: state variables scores...124
6.4.3 Capacity shortage and material shortage: shared state variables score...127
6.4.4 Resilience indices scores...129
6.4.5 Results discussion...130
6.5 Conclusions... 131
7 Conclusions... 133
7.1 Thesis overview ... 133
7.2 Main results ... 134
7.3 Theoretical and managerial implications... 137
7.4 Recommendation for future research ... 138
8 References ... 141
Appendix A - Interview protocol on lean, agile and resilient supply chain management practices155 Appendix B - Interview protocol on supply chain disturbances and failure modes ... 161
Figure 1-1 Research methodology overview...6
Figure 1-2 Organization of the thesis...8
Figure 2-1 Effect of disturbances in the supply chain performance ...29
Figure 2-2 Supply chain failure modes ...32
Figure 2-3 Cause-effect diagram for product not delivered on-time ...32
Figure 2-4 “Resilience triangle” ...46
Figure 2-5 “Resilience triangle” pattern in simulation results...46
Figure 2-6 Example where the supply chain final state is different from the initial state...47
Figure 2-7 Disturbance effect in different supply chain performance measures (example)...47
Figure 3-1 Supply chain resilience as a property...62
Figure 3-2 Supply chain resilience as a strategy...63
Figure 3-3 Conceptual model for supply chain resilience assessment...64
Figure 4-1 Inductive and deductive research approaches ...67
Figure 4-2 Case design in supply chain context ...71
Figure 4-3 Methodology overview ...73
Figure 5-1 Supply chain under study ...83
Figure 5-2 Supply chain disturbances...95
Figure 5-3 Disturbances sources along the supply chain ...97
Figure 5-4 Resilient practices used by companies...101
Figure 6-1 Framework for resilience modelling in supply chain...110
Figure 6-2 State variables proposed for modelling the supply chain resilience indices ...113
Table 2-1 Supply chain state variables...13
Table 2-2 Dimensions of supply chain management practices...14
Table 2-3 Supply chain management practices ...16
Table 2-4 Supply chain measures and indicators...22
Table 2-5 Disturbance categories ...28
Table 2-6 Failure mode categories...31
Table 2-7 Failure mode analysis for finished product not delivered ...35
Table 2-8 Failure mode analysis for labour and capacity shortage...35
Table 2-9 Failure mode analysis for raw material shortage ...36
Table 2-10 Failure mode analysis for scrap and rework ...37
Table 2-11 Supply chain resilient practices...44
Table 3-1 Lean, agile and resilient supply chain attributes ...53
Table 3-2 Supply chain resilient capabilities...56
Table 3-3 Relationship between supply chain resilient capabilities and state variables ...59
Table 4-1 Sample main characteristics ...73
Table 4-2 Case study data sources...75
Table 4-3 Data analysis techniques...78
Table 4-4 Case study research design...80
Table 5-1 Companies profile...84
Table 5-2 Implementation level of supply chain management practices ...89
Table 5-3 Relationships among supply chain management practices and performance...93
Table 5-4 Empirical evidences supporting the identification of failure modes ...99
Table 5-5 Resilient practices, disturbance severity and recovery time: empirical evidences...102
Table 6-1 Variables for assess the supply chain resilience index...117
Table 6-2 Capacity shortage severity and recovery time: state variables score ...122
Table 6-3 Material shortage severity and recovery time: state variables score ...125
Table 6-4 Capacity and material shortage: shared state variables score ...128
List of abbreviations and symbols
b - Length of the triangle
b1 - Damping time
b2 - Recovery time
EDI - Electronic data interchange
FGI - Finish goods inventory
h - Depth of the triangle
IT - Information technology
JIT - Just-in-time
JIT suppliers - Just-in-time suppliers
Nzs - Number of state variables contributing to minimize severity of failure mode z
Nzr - Number of state variables contributing to minimize the recovery time for failure mode z OEM - Original equipments manufacture
RCn - State variable n that contributes to minimize the “capacity shortage” as well as “material shortage” recovery time
RCSl - State variable l that contributes to minimize the “capacity shortage” recovery time RMSm - State variable m that contributes to minimize the “material shortage” recovery time Resilience Index CS - Company resilience “on-time delivery” to “capacity shortage”
Resilience Index MS - Company resilience “on-time delivery” to “material shortage”
Resilience Index z - Resilience index for a failure mode z
SCk - State variable k that contributes to minimize the “capacity shortage” as well as “material shortage” severity
SCSi - State variable i that contributes to minimize the “capacity shortage” severity SMSj - State variable j that contributes to minimize the “material shortage” severity WIP - Work in process
This chapter serves as an introduction to the dissertation. It covers the research aim, describing the motivation, objectives and research questions. It contains a brief description of the research methodology used in the research and it concludes with an outline of the dissertation structure.
1.1
Aim
In a global economy companies are no longer competing simply against each others but throughout the whole network of companies that are responsible to transform raw materials in final product and deliver it to the end users (Mills, Schmitz, and Frizelle, 2004). This network of entities responsible for different process, from materials production, components and products assembly, storage, transportation to delivery, is known as supply chain. The supply chain entities can be located in different geographic locations, e.g. a manufacturing plant located in South Europe can receive materials from local suppliers, but may receive materials coming from suppliers located in nearby countries or even different continents like Asia and America. Companies can supply products to customers that are spread around the globe and have to guarantee, at the same time, short lead times, high quality levels and low-cost. Therefore, it is critical to assure a smooth flow of materials between all the network entities. The management of the complex flow of materials and information between companies involve as well the coordination of the individual companies’ processes, which is the heart of supply chain management (Mentzer et al., 2001). Supply chain management is crucial for increasing companies’ effectiveness as well as for enhancing competitiveness, customer service and profitability. Diverse supply chain management strategies like lean and agile are intended to reduce cost, through process improvements to reduce and eventually eliminate all “wastes” (non-value adding operations) and increase flexibility, i.e., developing the supply chain ability to rapid responding to changes in customer’s demand (Christopher and Towill, 2000).
compromising the ability to meet previously made commitments. Several companies, when subjected to disturbances occurrences, can not sustain the productivity level losing their competitiveness; therefore, the financial losses due to disturbances are growing significantly (Sheffi, 2005). The Japan earthquake in March 2011 is an illustrative example of how an unexpected event can affect global supply chains. We come across numerous media news describing this event negative outcome in companies and respective supply chains (Carvalho, Azevedo, and Cruz-Machado, 2012a). The automotive sector is referred to as one of the more affected by this event. The following quotations provide elucidative descriptions about the negative effects of this event:
“With some 500 parts firms affected in the quake and tsunami-devastated northeast, cutting off supply of electronic parts, resin-based products and more, Japan’s auto industry is especially vulnerable to a ruptured supply chains”1
“About 13% of worldwide auto output has been lost due to parts shortages and IHS Automotive has estimated it may cut output by as much as 30% within six weeks in a worst-case scenario.”2
“(...) there are 30,000 parts to build a car. We might see an impact on practically every production line in North America and most of Europe because of this supply interrupt, this black swan for the global auto industry in Japan”3
The tendencies of many companies to seek out low-cost solutions, because of pressure on margins, may have led to leaner but more vulnerable supply chains (Azevedo et al., 2008; Peck, 2005). As a result, supply chains are exposed to disruption and, in consequence, the risk to business continuity has increased. In a preceding research related to agile and resilient supply chains we argue that companies and supply chain competitiveness depend not only on the lowest-cost, higher quality, reduced lead time and higher service level; they should have the ability to avoid and overcome several disturbances that may jeopardize their performance, i.e., they should be resilient (Carvalho, Azevedo, and Cruz-Machado, 2012b).
The resilience seems to be, apparently, in conflict with an efficient use of resources in supply chain: the redundancies in resources and processes allow an increase in the system resiliency, but redundancies should be minimized to reduce operational cost systems. It seems that what can be
1 “Analysis - Japan car recovery may take months”. Available at:
good from the competitive point of view, can cause a disaster on crisis situations; it may be worst if the companies can not be resilient and robust enough to recover the loosed competitiveness. The ability to react appropriately to disruptions, whether natural or man-made, is a strategic necessity for business survival; this becomes more relevant when the company is a member of an interdependent network of entities (Hanna, Skipper, and Hall, 2010; Ponomarov and Holcomb, 2009; Sheffi and Rice, 2005). The creation of resilience attributes in companies, and therefore in supply chain, will contribute to enhance the supply chain performance and competitiveness.
Interest in supply chain disruptions and respective negative consequences has been growing in last years and the topic is become a main stream (Stock, Boyer, and Harmon, 2009). Whereas in the past the principal objective of supply chain design was cost minimization or service optimization, the emphasis today has to be upon resilience (Blackhurst, Dunn, and Craighead, 2011; Pettit, Fiksel, and Croxton, 2010; Ponomarov and Holcomb, 2009; Tang, 2006a). Resilient supply chains may not be the lowest-cost supply chains but they are more capable of coping with the uncertain business environment. The automotive supply chain is a typical example of high vulnerability levels to disturbances (Svensson, 2000). According to Thun and Hoenig (2011) the trends in globalization and the necessity to offer many products variants are the key drives to increase the vulnerability of this industry. Therefore, in the automotive supply chains the management focus should consider as well resilience and not only cost minimization.
The present thesis intends to study the supply chain resilience thematic. The research was integrated in two comprehensive research projects:
“Lean, agile, resilient and green supply chain management” (funded by Fundação para a Ciência e Tecnologia - Project MIT-Pt/EDAM-IASC/0033/2008). The main objective of this project is to develop a deep understanding of the relationships required for the compatibility of lean, agile, resilient and green (manufacturing) in order to contribute to better production systems and supply chains.
“Supply Chain Management: design for resilient systems” (funded by Fundação para a Ciência e Tecnologia - Project PTDC/EME-GIN/68400/2006). The main objective is to develop a management support system prototype to help managers to react quickly and efficiently to the effects of disruptions that can occur in a supply chain, sustaining a high service level to customers and to merge the necessary information to mitigate plans if the disruption became repetitive.
to the development of the resilience thematic in supply chain context (Azevedo et al., 2012; Carvalho, Azevedo, and Cruz-Machado, 2012a; Carvalho, Azevedo, and Cruz-Machado, 2012b; Carvalho et al., 2012; Carvalho, Maleki, and Machado, 2012; Carvalho, Tavares, and Cruz-Machado, 2012; Carvalho et al., 2011; Carvalho, Duarte, and Cruz-Machado, 2011). These works disclose the relevance of supply chain resilience thematic in academics, but also in managerial domains. However, it was found that there are still some research gaps that need to be addressed.
First, much of the existing research is focused on the question on “why the companies are vulnerable to supply chain disruptions” (Peck, 2005; Svensson, 2000; Wagner and Neshat, 2010). However, it is increasingly clear that companies need to deal with supply chain disruptions no matter if they are more or less vulnerable. The Japan earthquake in March 2011 is an example of how an unexpected event can affect global supply chain. Second, the development of the field tends to focus on anecdotal studies and there is a lack of empirical evidences on how companies can improve the resilience of the network where they are inserted. Blackhurst et al. (2005) state that there is a limited amount of information on how to deal with supply chain disturbances from a practical point of view, in both the short and the long term.
A high level of analysis of disruptions in supply chain, generally focused in uncertainty, risk perceptions and hazards, might prevent the “drilling down” of key variable and relationships among them and prevent the development of new methodologies to manage these issues (Blackhurst et al., 2005). As state by Hintsa et al. (2009), in the supply chain security context, the academic research community has a clear mission to bridge the gap between theoretical supply chain security studies, emerging security standards and practical managerial actions. One way of doing it is to proceed with pragmatic case studies on supply chain models in the context of real world supply chains.
chain resilience level depends on a set of seven resilient practices that reflects the company ability to cope with unexpected disturbances. The resilient practices were selected using evidences from literature and experts knowledge, but no explanatory framework was developed. In parallel with the development of resilience measures, Wagner and Neshat (2010) propose a novel approach based on graph theory to quantify and mitigate supply chain vulnerability. Recently, the same authors perform an empirical study to compare supply chain vulnerability indices of different firms (Wagner and Neshat, 2012). Moreover, these authors stress out the need to address measurement and implementation issues in supply chain resilience context.
1.2
Objective and research questions
While the existing research is valuable, models to support supply chain resilience management are needed. In particular, the issue on “how to assess the supply chain resilience” still has no answer. Therefore, this dissertation purpose is modelling resilience in a supply chain context. Namely, the objective is to develop theory that can be used to support the assessment of supply chain resilience of a company. To attain this objective it is necessary to develop an explanatory framework that capture all the relevant variables describing the supply chain resilience phenomena and clarifying the pathways by which supply chain resilience should be addressed. More specifically, the objectives are:
To propose a supply chain resilience assessment model.
To propose an framework for supply chain resilience modelling.
To model indices to assess company’s supply chain resilience.
In a first step, it is necessary to understand how companies manage their processes within a supply chain context and characterize the main supply chain management practices deployed by companies. In particular, the identification of resilient practices used to avoid or minimize the disturbance negative effects is crucial for a better understanding of the resilience phenomena. The following research questions are addressed:
1. Which practices companies deploy to manage their supply chain? What are the consequences of those practices on supply chain performance?
3. How the supply chain disturbances affect the company’s performance? And why companies do not sustain their performance level when a disturbance occurs?
4. Which resilient practices companies deploy to avoid or minimize the negative effects of the supply chain disturbances?
1.3
Methodology
The research methodology comprises two main research phases as illustrated in Figure 1-1. Since there are few theoretical developments in the supply chain resilience field, the research adopts an explorative character. A theory building methodology based on case studies was selected. In a first research phase, a case study is developed to understand the effect of disturbances on supply chains and how companies overcome its negative effects.
The field work was focused in the automotive supply chain, namely in the upstream supply chain taking into consideration the dyad manufacture – 1st tier suppliers and logistic service providers. From this case study an empirical data platform emerged to identify the critical components describing supply chain resilience phenomena.
Case study
Which practices companies’ deploy to manage their supply chain? What is those practices consequence on supply chain performance
What is a supply chain disturbance? How managers perceive the effects of a supply chain disturbance?
How the supply chain disturbances affect the company’s performance? And why companies do not sustain their performance level when a disturbance occurs?
Which resilient practices companies deploy to avoid or minimize the negative effects of the supply chain disturbances?
Phase I
Critical variables to asses supply chain resilience
Supply chain resilience explanatory framework Resilience indices
Phase II
Case study
Indices testing
Figure 1-1 Research methodology overview
theory driven, i.e., the main variables describing the resilience phenomena emerge from empirical data. Using this framework, two supply chain resilience indices are modelled. Finally the indices were tested using a case study approach.
Since the supply chain resilience thematic covers a large scope of research topics including vulnerability, supply chain risk, organizational structure, among others, in this dissertation the focus will be on the companies’ behaviour and how they overcome the negative effects of supply chain disturbances keeping the focus on company’s supply chain. Another delimitation of this dissertation is related to the type of supply chain under study: the empirical work will be focus on a Portuguese automotive upstream supply chain.
1.4
Contents
The thesis results from theoretical and methodological explorations within the scope of supply chain resilience. In Figure 1-2 the organization of the thesis is presented, highlighting the theoretical, methodological and empirical steps used to reach the thesis results.
This thesis consists of seven chapters. The first one introduces the thesis underling motivation and main objectives. In the second and third chapter, the relevant literature on supply chain resilience is enfolded to provide clarifications regarding the research thematic. In Chapter 2, the topics related to supply chain management, supply chain performance, disturbances, failures modes and resilience are discussed. This chapter contains a review of main supply chain management practices and performance measures found in the literature. In addition, it provides an overview on supply chain disturbances and failure modes and the identification of supply chain resilient practices. The chapter is concluded with the characterization of supply chain resilience using the “resilience triangle”. In Chapter 3 the lean, agile and resilient practices are studied in detail, their attributes are identified and related to these management strategies. Moreover, a relevant set of supply chain resilient capabilities are identified. The design for supply chain resilience is also explored. The chapter concludes with a conceptual model for supply chain resilience assessment.
Figure 1-2 Organization of the thesis
In Chapter 5, the data collected in research Phase I of the case study will be presented. The chapter begins with a detailed description of the studied sample; the main supply chain management practices used by companies in the sample are identified. Supply chain disturbances and failure modes are identified using empirical evidences collected in the case study. The chapter terminates with the identification of main practices used by companies to overcome the disturbances negative effects.
Finally, Chapter 7 provides a general discussion in theoretical, methodological and empirical issues relevant to supply chain resilience thematic. The chapter finishes with the main conclusions of the thesis and future work proposals.
The thesis includes relevant references about supply chain resilience and others supporting topics, e.g. supply chain management, supply chain vulnerability, security and disruption, along with lean and agile supply chain strategies. The literature reviewed follows a purposive sample of articles, i.e., the literature included in this thesis was based on central and pivotal articles published in the top journals in the field. In addition, four annexes, containing the interview protocols, and one example of a technical report, to support the case study development, are included.
1.5
Conclusion
2
Supply Chain Resilience
This chapter reviews the relevant literature on supply chain resilience. The review starts with a discussion on supply chain management, namely, the main supply chain practices and performance measures. A more deeply focus is given to supply chain disturbances, failures modes and resilience. Along this chapter research questions that will guide the empirical work are suggested. It concludes with a discussion on the “resilience triangle” as a proper tool to assist the quantification of supply chain resilience.
2.1
Supply chain management
2.1.1 Supply chain
In the literature there are several definitions for supply chain. Christopher (2005) defines supply chain as “a network of companies that are involved, through upstream and downstream linkages, in the different processes and activities that produce value in the form of products and services delivered to the ultimate customers”. Mentzer et al. (2001) define supply chain as “a set of three or more entities directly involved in the upstream and downstream flow of products, services, finances, and/or information from a source to a customer”. Krajewski and Ritzman (2004) propose the following definition “a set of linkages between suppliers of materials and services that spans the transformation of raw materials into products and services”.
In this thesis, the supply chain definition proposed by Lambert, Stock, and Ellram (1998) will be adopted: “the supply chain is usually defined as a set of interdependent companies that act together to control, manage and improve the flow of materials, products, services and information, from the origin point to the delivery point (the end customer) in order to satisfy the customer needs, at the lowest possible cost to all members”. This definition integrates network configuration and management elements with the supply chain objective: “satisfy the customer needs, at the lowest possible cost to all members”.
service providers, carriers, manufactures, among others, towards the customers (at the downstream level). Lambert and Cooper (2000) argue that the supply chains are different from each company’s perspective; a company manager sees its firm as the focal company, he perceives membership and network structure differently. However, because each firm may be a member of several supply chains, it is important for managers to understand their companies’ roles. Moreover, those authors also support that the integration and management of business processes across company boundaries is only possible if it makes sense from each company’s perspective. Mills, Schmitz, and Frizelle (2004) endorse the supply chain management analysis from the company point of view; they suggest four perspectives for researchers and academics to perform supply chain analysis:
1. Upstream: considering the point of view of a purchaser that need to manage its relationships’ with suppliers.
2. Downstream: considering the point of view of as supplier that have to supply the right products to the customers.
3. Static network: where the managers assume the auditor role of its position in its supply network, typically it comprises the analysis of several supply chains where the company is involved. This perspective provides a static and comparative view.
4. Dynamic network: as strategist, where managers look for opportunities to improve the company’s position in an existing network or even creating a new network. This perspective provides a strategic, dynamic and long-term view.
The supply chain can be viewed as a dynamic system (Angerhofer et al., 2000). The state of the system can change continuously as time goes by, e.g., deliver frequencies can be changed or inventory levels can be modified. Therefore, the system state is related to system characterization in a specific time instant. However, there is not a consensual definition for the state of the supply chain. To Kelton et al. (2003) a system’s state can be regarded as a snapshot of the system showing all relevant details. Banks et al. (2004) define system’s state as the collection of variables necessary to describe a system at any time, taking into consideration to the objectives of a study. In a prior research we propose the following definition for the state of the supply chain:
To characterize the supply chain state we proposed the following dimensions: i) supply chain entities or companies that belong to the network including supplier sites, manufacture sites, assembly sites, distribution sites, and service providers; ii) relational links between supply chain entities allowing dispersed entities to act together; iii) material flow between the supply chain members including the way the materials are delivered, e.g. transport modes and distributions channels; iv) information flow between the supply chain members; v) management policies used to control processes and that support decision making in the supply chain; vi) lead times which reflect the time necessary to deliver a product to the customer. Table 2-1 contains an illustrative collection of supply chain variables.
Table 2-1 Supply chain state variables In Carvalho, Tavares, and Cruz-Machado (2012)
Supply chain state
variables dimension Examples
Supply chain entities Typology (function/role); Geographic localization; Number of available alternatives
Relational links Type of relation between entities: collaboration, channel leader at dot end, buying-selling relation, bilateral extensive coordination, long-term partnership, preferred suppliers, among others
Material flow Quantity; Deliver frequency; Transport mode
Information flow Frequency; Type (manual or electronic)
Management policies Inventory type and level; Overall process description: number of operations, lot size, capacity for extra orders, % of defects, strategy type (make-to-order or make-to-stock)
Lead times Production lead time; Transit time; Time to supply for new suppliers (time required for a new supplier to complete a single cycle, beginning with the receipt of an order and ending with the fulfilment of that order)
2.1.2
Management practices
Since the supply chain is a network of companies, it is necessary to manage properly the information and material across companies’ boundaries to achieve customer value and satisfaction. Lambert, Stock, and Ellram (1998) propose that, to successfully implement supply chain management, all companies within a supply chain have to overcome their own functional silos and adopt a process approach.
coordination of the traditional business functions and the tactics across these business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long-term performance of the individual companies and the supply chain as a whole”; this definition considers that the supply chain is viewed as a network of individual companies that manage their material and information flows at the upstream, internal and downstream levels.
For Wong, Arlbjørn, and Johansen (2005) supply chain management practices are define as approaches applied in managing integration and coordination of supply, demand and relationships in order to satisfy consumers in effective and profitable manners. Li et al. (2005) define supply chain management practices as the set of activities undertaken by a company to promote effective management of its supply chain. Once more, the perspective of a single company is adopted by these authors; the “set of activities undertaken by a company” embrace the management of upstream, downstream and also the internal company processes.
Cohen and Roussel (2005)state that supply chain practices should be aligned with the supply chain strategy. Autry, Zacharia, and Lamb (2008) assess supply chain strategies using a set of supply chain practices. Li et al. (2005) propose that supply chain management practices are a multi-dimensional construct that includes both upstream and downstream sides of the supply chain as showed in Table 2-2.
Table 2-2 Dimensions of supply chain management practices Adapted from Li et al. (2005)
Dimensions of practices Definition
Customer relationship The entire array of practices that are employed for the purpose of managing customer complaints, building long-term relationships with customers, and improving customer satisfaction
Internal lean practices The practices of eliminating waste (e.g. cost and time) in a manufacturing system, characterized by reduced set-up times, small lot sizes, and pull-production
Postponement The practice of moving forward one or more operations or activities (making, sourcing and delivering) to a much later point in the supply chain
Information sharing The extent to which critical and proprietary information is communicated to one’s supply chain partner
Information quality Refers to the accuracy, timeliness, adequacy, and credibility of information exchanged
Strategic supplier partnership
There is a clear difficulty in the identification of what is a supply chain management practice. Depending on the position on supply chain network, the point of view and the level of abstraction, different levels of detail can be attributed to supply chain practices. For example some authors consider postponement as a supply chain practice and others consider it as a supply chain strategy.
Some authors deploy supply chain management practices in a set of “sub-practices”, or activities or even in tools. Different perspectives of what are the supply chain practices can be found in the literature. Wisner (2003) identifies the relevant practices comprising the supplier management, customer relationship, and supply chain management strategies. Tan, Lyman, and Wisner (2002) identify 25 supply chain management practices and then reduce them to 6 underlying factors: customer service management, just-in-time capability, geographic proximity, supply chain characteristics, information sharing and supply chain integration.
Table 2-3 gives an overview of more 150 supply chain management practices that can be found in literature. The practices were classified according to the supply chain state variables dimensions (as it can be found in Table 2-1): supply chain entities; relational links; material flow; information flow; management policies (customer service, inventory, order management, process and product development); and lead times.
The practices associated to the management of supply chain entities are related to decisions about facilities number and location, inclusion of logistics providers in the supply chain, selection of partners, among others. The literature provides a set of practices to manage the relationships among entities with the intention to develop trust and collaborative arrangement among companies, as well as to promote integration and coordination of activities among companies. The management of material flow is mainly supported by practices related to the selection of suitable transport, but also by assuring coordination of moving goods among companies. To manage the information flow, it was found, in the literature, a number practices that support information electronic sharing among partners.
Table 2-3 Supply chain management practices
Supply chain state
variables Supply chain management practices References
Carrier cost/pricing analysis, performance measurement and routing
analysis (j)
Contract storage (j)
Extending supply chain to include members beyond immediate suppliers (c) (k)
Facility location analysis (b) (j)
Identifying additional supply chains where company can establish a
presence (c) (d) (k)
Inbound freight cost analysis (j)
Locating closer to your customers (c) (k)
Maintaining geographic proximity with suppliers (b) (c) (d) (k)
Number of facility analysis (j)
Outsourcing (a) (b) (g)
Reducing supplier base (e) (k)
Retail strategy (h)
Supplier selection (j)
Using freight forwarders/consolidators (j)
Supply chain entities
Using third-party service providers (d) (k)
Aiding suppliers to increase their just-in-time capabilities (c) (d) (k)
Coordinating activities with partners (j)
Creating a greater level of trust among supply chain members (c) (d) (k)
Creating cross-functional teams (e)
Creating informal information sharing agreements with suppliers/customers (c) (d) Creating supply chain management teams that include members from
different companies (c) (d) (k)
Design chain / supply chain integration (i)
Developing buyer-seller relationships (h)
Developing collaboration to achieve collective goals (j)
Developing collaboration with customers (i) (j)
Developing collaborative innovation with suppliers (i) Developing cooperation with trading partners (f) (j)
Developing customer relationship (g)
Developing long-term relationship (e) (f)
Relational links
Table 2-3 Supply chain management practices (cont.)
Supply chain state
variables Supply chain management practices References
Developing organization ethical standards at downstream level (k) Entering into long-term contract arrangements at downstream level (d) (k) Improving the integration of activities/processes across your supply chain (c) (d) (f) (j)
Influencing behaviour of trading partners (j)
Interacting with customers to set reliability, responsiveness, and other
standards (d)
Involving all members supply chain in product/service development (c) (d) (k)
Negotiation (j)
Sharing risk and award (f)
Sharing vision and goals (f)
Supplier involvement (e)
Supply chain leadership (f)
Relational links
Using collaborative planning, forecasting and replenishment (CPFR) (j) Delivering materials into production line using flexible transportation
equipment and containers (b)
Improving distribution and logistics (h)
Increasing delivery frequencies (d) (k)
Internal distribution center layout analysis (j)
Synchronizing and sequencing transportation with production (b) Using value-added distribution center services (j)
Using just-in-time procurement (j)
Using transportation management systems (j)
Material flow
Vehicle scheduling analysis (j)
Communicating organization future strategic needs to your suppliers (c) (d) (k)
Computerized transportation rates/tariffs (j)
Creating a compatible supply chain communication and information systems (c) (d) (k)
Creating information quality (g)
Creating visibility and tracking systems (j)
Developing communication skills/systems (phone, fax, email, internet) (k) Establishing more frequent contact with members of your supply chain (c) (d) (k)
Sharing information with suppliers and customers (a) (c) (f) (g) (h) (j) (k)
Using electronic data interchange (EDI) (d) (k)
Using electronic solutions to routine customer problems (j)
Information flow
Table 2-3 Supply chain management practices (cont.)
Supply chain state
variables Supply chain management practices References
Contacting the end users of your products to get feedback on performance
and customer service (c) (k)
Customer segmentation analysis (i)
Customer service management (c) (j)
Determination of future customer expectations (c) (d) (k) Employing a customer satisfaction measurement system (downstream) (d) (k) Employing routine follow-up procedures for customer complaints (d)
Establishing customer service standards (j)
Making it easier for customers to seek assistance (d) (k)
Overall service level provided analysis (d)
Participating in the marketing efforts of your customers (c) (d) (k) Presence of certification or other documentation (k)
Service level analysis (k)
Successful resolution of customer complaints (d) (k)
Management policies - Customer service
Using credit checking (j)
Employing order planning for demand smoothing (j) Order checking (internal and outbound) management (j)
Order entry management (j)
Management policies - Order management
Order picking/assembly management (j)
Automated inventory handling (j)
Employing supplier-managed inventories (j)
Employing vendor-managed inventories (j)
Inventory and cost management (h) (j)
Inventory order management (j)
Reducing inventory to expose manufacturing and scheduling problems (k) Reducing inventory, which in turn frees up capital investment (k)
Management policies - Inventory
Using private storage (j)
Appling statistical process control (k)
Bullwhip effect minimization (h)
Buying from just-in-time suppliers (k)
Creating a continuous process flow (a)
Creating product and lot-level traceability (i)
Management policies - Process
Table 2-3 Supply chain management practices (cont.)
Supply chain state
variables Supply chain management practices References
Developing customer value-added activities (j)
Developing flexibility to meet your customers’ changing needs (d) (k) Developing flexibility to respond to unexpected demand changes (d) (k) Developing postponement and customization (b) (h) (i)
Developing security initiatives (j)
Early supplier involvement in new product design and development (k) Effort in striving for continuous cost reduction (k) Emphasis on quality instead of price in the supplier selection process (k) Employee training in quality management and control (k) Employing process improvement (modification of process) (k) Empowerment of shop operators to correct quality problems (k)
Environmentally conscious packaging (j)
Improving quality level (k)
Increasing organization just-in-time capabilities (c) (d) (k)
Inspection (k)
Integrated factory planning and scheduling (i)
Internal lean practices implementation (g)
Life cycle tracking of sold products (i)
Marketing plans (k)
Packaging of hazardous materials (j)
Participating in the sourcing decisions of suppliers (c) (d) (k)
Purchasing at lowest possible total cost (j)
Reducing lot size (k)
Using accounting/cost controls (j)
Using cross-docking operations (b)
Using labelling (j)
Using material requirements planning (j)
Using palletization (j)
Using preventive maintenance (k)
Using quality control techniques (k)
Using recycling (j)
Management policies - Process
Table 2-3 Supply chain management practices (cont.)
Supply chain state
variables Supply chain management practices References
Using benchmark data (k)
Using quality control techniques (k)
Using reusable packaging (j)
Using worker productivity controls (j)
Management policies - Process
Waste management (j)
Dedicated new product introduction in the supply chain (i) Designing for manufacturing, procurement, order (i)
Designing quality into the product (k)
Developing product differentiation (h)
Employing raw materials and manufacturing process standardization (i)
Increasing quality of products and services (k)
Product design for manufacturability and assembly (k) Quick product development and introduction time (k)
Simplification of component parts (k)
Simplifying the product (k)
Standardization of component parts (k)
Using modular design of parts (d) (k)
Using of concurrent engineering parts (k)
Using quality function deployment (QFD) (k)
Management policies - Product development
Using value analysis/value parts engineering (k)
Achieving on-time delivery (c) (k)
Developing in transit acceleration and deceleration to regulate flows (b)
Employing lead time management (h)
Meet due dates (d)
On-time delivery of products directly to your customers’ points (k) On-time delivery purchased materials directly to company points (c) (d) (k) Quick response time in case of emergency, problem, or special request (d) (k) Reducing response time across the supply chain (c) (d) (k)
Reducing setup time (k)
Lead times
Using cycle time compression (a)
References: (a) - Donlon (1996); (b) - Morash (2001); (c) - Tan, Lyman, and Wisner (2002); (d) - Wisner (2003);
In the supply chain context the companies also employ a set of practices related to the product development, like standardization of parts, to simplify material flows in supply chain. Finally, a set of practices to manage the lead times and accelerate the material flows was identified.
The practices in Table 2-3 are related to three levels in supply chain: some practices are deployed at company level, e.g., “creating cross-functional teams” or “delivering materials into production line using flexible transportation equipment and containers”; others are related to the practices deployed at the downstream level, e.g., “using electronic solutions to routine customer problems” or “employing routine follow-up procedures for customer complaints”; and finally the practices can be related to the upstream level, e.g., “early supplier involvement in new product design and development”.
The set supply chain management practices also reflect the manager’s possible actions in what is concerned to values of supply chain state variables. The number, type and location of the supply chain entities is determined by practices as “outsourcing”, “reducing supplier base”, “maintaining geographic proximity with suppliers” and “facility location analysis. Therefore these practices will support the decision making in the future. For example, the practice “reducing supplier base” supports improvements in cost and supplier efficiency, however it will restrict the number of supply chain entities; if a problem happens with one supplier, it could be difficult to find out an alternative. In opposition, the practice “outsourcing” contributes to a more flexibility in the production process. The practice “maintaining geographic proximity with suppliers” and “facility location analysis” will decide the localization of plants. But also will limit the manager’s options in case of necessity to transfer the operations to a different geographic area.
Since there is a vast set of supply chain practices that could be deployed by managers to improve the material and information flow along the supply chain, and that these practices will affect the supply chain behaviour, it is required the identification of most appropriate supply chain management practices.
Since this thesis is focused in the automotive supply chain it is important to characterize how companies in the automotive supply chain manage their supply chain. Therefore, the first research question is addressed:
Research question 1: Which practices companies deploy to manage their supply chain? What are the consequences of those practices on supply chain performance?
2.2
Supply chain performance
Performance measurement is crucial to better supply chain management (Wong, 2009). It can facilitate the inter-understanding and integration among the partners in the supply chain while revealing the effects of strategies and potential opportunities in supply chain management. There are sets of research studies that address the design and implementation of performance measures in the supply chain context (Beamon, 1999; Cagnazzo, Taticchi, and Brun, 2010; Gunasekaran, Patel, and Tirtiroglu, 2001; Keebler and Plank, 2009; Yang and Su, 2009). For example, Gunasekaran, Patel, and Tirtiroglu (2001) argue that supply chain performance should be measured from the strategic, tactical and operational levels and the perspective of finance versus non-finance contexts. Taking into consideration this line of thought, some of the measures proposed by such authors are: total cash-flow time, rate of return on investment, flexibility to meet particular customer needs, delivery lead time, total cycle time and degree of buyer-supplier partnership, customer query time, extent of cooperation for improved quality, total transportation cost, accuracy of demand predictability/forecasting methods, product-development cycle time, manufacturing cost, capacity utilization, information carrying cost and inventory carrying cost. In a previous research works we presented an overview of the measures that can be used to evaluate supply chain performance (Table 2-4).
Table 2-4 Supply chain measures and indicators Adapted from Carvalho, Azevedo and Cruz-Machado (2012b)
Measures Indicators References
Defect fallow rate (a) (b)
Defect-free delivery (c)
Quality of delivery goods (c)
Order fulfilment rates (d)
Quality
Rate of customer complaints (e) (c)
Delivery speed (f) (c)
On-time delivery (e)
Perfect order fulfilment (e)
Delivery reliability (c)
Responsiveness to urgent deliveries (c)
Service level
Customer satisfaction (e) (g)
Lead time (h)
Cycle time (i)
Delivery lead time (c)
Table 2-4 Supply chain measures and indicators (cont.)
Measures Indicators References
Finished goods equivalent units (m)
Inventory
levels Safety stock level (i)
Supply and procurement flexibility (i)
Conversion flexibility (i)
Excess capacity (j)
Mix flexibility (k)
Delivery flexibility (k)
Volume flexibility (k)
Logistics flexibility (e)
Transport flexibility (c)
Flexibility
New product flexibility (e)
Manufacturing cost (m) (e)
Inventory carrying cost (m) (d) (e)
Redundancy cost (i)
Economic value added (n)
Profit margins (o) (n)
Return on global assets (o) (d ) (l)
Financial
Cash-to-cash cycle (p)
Cycle efficiency (l)
Overhead expense (q)
Efficiency
Operating expense (q)
References: (a) - Kumar, Vrat, and Shankar (2006); (b) - Wang, Huang, and Dismukes (2004);
(c) - Soni and Kodali (2009); (d) - Martin and Patterson (2009); (e) - Cai et al. (2009); (f) - Agarwal, Shankar, and Tiwari (2007); (g) - Sambasivan, Nandan, and Mohamed (2009);
(h) - Naylor, Naim, and Berry (1999); (i) - Azevedo et al. (2008); (j) - Harrison and Skipworth (2008); (k) – Beamon (1999); (l)- Brewer and Speh (2000); (m) - Goldsby, Griffis, and Roath (2006);
(n) - Pohlen and Coleman (2005); (o) - Swafford, Ghosh, and Murty (2008); (p) - Hutchison, Farris, and Fleischman (2009); (q) - Jiang, Frazier, and Prater (2006)
individual costs but not to maximize the value to the end customer. Lambert and Pohlen (2001) also criticized the measures used to evaluate supply chain performance. From their perspective, the supply chain performance measurement systems are focused on logistics measures (e.g. lead time, fill-rate, on-time performance) but do not provide information on how well the key business processes have been performed or the extent to which the supply chain has to meet customer needs. Moreover, the same authors argue that these measures do not provide information on how the overall supply chain have performed and fail to identify opportunities to increase competitiveness, customer value and shareholder value for each company in the supply chain.
The selection of the most adequate set of measures to be deployed in the supply chain context is not a trivial issue. Johansson et al. (1993) propose a total performance metric in terms of value to the customer as follows: total value = (quality x service level) / (costs x lead time). Kainuma and Tawara (2006) refer that “there are a lot of metrics for evaluating the performance of supply chains. However, they may be aggregated as lead time, customer service, cost, and quality”.
The measures are much correlated, for example if the lead time increases, the service level can decrease, being difficult to combine measures (Cai et al., 2009). As Sambasivan, Nandan, and Mohamed (2009) argue the performance measures must reflect the supply chain objectives of the company. For example, to a particular supply chain, the critical measure could be the financial performance but, for another one could be the service level, or a combination of both. In a study covering the lean, agile, resilient and green supply chain management paradigms we propose cost, service level (availability in the right place at the right time) and lead time as measures to evaluate the effect of each paradigm in the supply chain performance (Carvalho, Duarte, and Cruz-Machado, 2011).
2.3
Supply chain disturbances
2.3.1 Uncertainty and risk
information (or understanding) of the supply chain; it does not exist capacity of information processing; it is incapable to foresee the impact of possible control actions in the behaviour of the chain; or there are no actions of effective control”.
It is possible to infer that the ability to cope with uncertainties will determine supply chain performance. However, to manage uncertainties, it would be necessary to identify the uncertainties sources. Towill, Childerhouse, and Disney (2000) classify supply chain uncertainty sources in four groups: i) process uncertainty: it affects the internal capacity of the company to reach the planned production; ii) supply uncertainty: the supplier can not carry out with the requirements of the company, namely, on-time, and in the right quantity and specifications (e.g. quality or price); iii) demand uncertainty: it concerns to the predictability of the demand amount and the variety of product; and iv) control uncertainty: it concerns to the information flow in the company and the way the company transforms orders into goals of production and material requests. In addition, Vorst and Beulens (2002) propose three categories for supply chain uncertainty sources: i) inherent characteristics of supply chain that cause more or less predictable fluctuations; ii) chain characteristic features that result in potential loss of performance; iii) exogenous phenomena that disturb the system such as changes in markets, products, technology and governmental regulations. However these typologies do not focus on the disruptive event but on supply chain process that create the uncertainty or putting the focus on supply chain internal or exogenous characteristics that origin disruptive events.
2.3.2 Vulnerability, disruptions and disturbances
Jüttner (2005) defines supply chain vulnerability as “an exposure to serious disturbance arising from supply chain risks and affecting the supply chain’s ability to effectively serve the end customer market”. According to Azevedo et al. (2008) supply chain vulnerability is the incapacity of the supply chain, at a moment, to react to the disturbances and consequently to attain its objectives. Rupture conditions in supply chain are observed when companies are subject to disruptions, caused by sudden and unforeseen events like economic and politic crisis or environmental catastrophes (Bhamra, Dani, and Burnard, 2011; Ponomarov and Holcomb, 2009). Examples of unpredictable events are:
September 11, 2001: terrorist attacks destroyed New York’s World Trade Center Towers. Not only were some 3000 lives lost, but also companies such as American Express experienced significant losses in terms of their information databases (Zsidisin, Ragatz, and Melnyk, 2005). In addition automakers like Ford and Toyota had to stop their production lines in US facilities due the delays in the delivery of parts coming from foreign countries (Sheffi, 2001).
August 14, 2003: electrical power distribution in the American Midwest and Ontario was disrupted, with power outages lasting up to several days. The effects of this disruption were felt as far away as California, where Apple Computer was preparing to launch its much anticipated G5 computer. This launch was affected by the fact that IBM in New York manufactured the microprocessor chips required by Apple. The power disruption resulted in large-scale losses of chip production (eWEEK, 2003).
In 2003: a number of companies suffered serious disruption because of severe acute respiratory syndrome. 8000 people were infected, with one in ten dying; it still costs an estimated US$60 billion in lost output in South and East Asia (The Economist, 2006).
disturbance thematic to a crises perspective. Despite all these types of events may provoke rupture conditions or failures in supply chain, different notations and definitions can be found in literature:
Craighead et al. (2007) define supply chain disruption as unplanned and unanticipated events that disrupt the normal flow of goods and materials within a supply chain.
Wu, Blackhurst, and O’grady (2007) define disruptions as unexpected events occurring in a supply chain.
Blackhurst, Dunn, and Craighead (2011) consider the disturbance as a random quantitative or qualitative deviation from what is normal or expected and the negative consequence of disturbance as a deteriorated goal accomplishment in terms of economic cost.
Barroso, Machado, and Cruz-Machado (2008) define disturbance as an unforeseeable event, which affects usual operation and stability of a company or a supply chain.
Greening and Rutherford (2011) distinguish disturbance from disruption: disturbances are related to connected supply chain actors adaptation to variations in material flow or information; and disruption imply the removal of ties/nodes from the network (either permanently or temporarily) as a consequence of some unanticipated critical event.
Natarajarathinam, Capar, and Narayanan (2009) define supply chain crisis when one or more supply chain members’ activities are interrupted, resulting in a major disruption of the normal flow of goods or services.
The concept of unexpected is embedded in the disturbance concept in the sense that some events are unpredictable or enable to foresee. Nevertheless the event occurrence can be predictable with some accuracy, the real consequences for the supply chains are difficult to assess. The Hurricane Katrina is a good example: despite the annunciate catastrophe, most companies were not prepared to the devastating effects of this disturbance. Some events, like strikes, can be previously anticipated; but if their consequences are disregarded, a supply chain uncertainty will be generated. Other events, like terrorism or vandalism acts, can not be foreseen. The frequency of some disasters and operational disturbances occurrence, like human errors, fires, machines breakdowns, among others, can be minimized by promoting best practices to increase safety. However, it is impossible to control all risk factors and accidents, eventually, may happen, e.g., the Chernobyl disaster.
