Supply chain life cycle

Supplier relationships, supplier performance and supplier development have been mentioned on this blog on several occasions. Two years ago I wrote about a Norwegian PhD dissertation, where the author, Wei Deng Solvang, identified 5 phases in a supply chain life cycle:

1) identification of business opportunity, 2) selection of business partner, 3) formation of the supply chain, 4) operation of the supply chain, and 5) reconfiguration of the supply chain. This is a repetitive cycle. For every new business opportunity or product line these phases spring into action, thus creating a living and dynamic supply chain.

Solvang’s view on supply chains has much in common with what is known as Virtual Enterprise Networks (VENs), as described in The Networked Enterprise by Ken Thompson or in The Agile Virtual Enterprise by Ted Goranson, let alone in  Creative Destruction by Nolan and Croson, all which have been included in my book chapter on managing risk in virtual enterprise networks.

Supplier development and supplier performance

Wagner says that there are several approaches in the literature as to how supplier relationship length, supplier development and supplier performance come together. The dominant view is that of a linear relationship, where performance can only increase. The longer the relationship, the better the performance. However, if one takes the supply chain life cycle  perspective into consideration, performance becomes convex, with a distinct peak and a following decline towards the end of the relationship:

Drawing on other researchers, Wagner states explicitly that

I argue that a more accurate model of supplier development activities should account for the life-cycle of the buyer–supplier relationship by including a squared term for relationship length as a moderator for the relationship between the buying firm’s supplier development activities and the improvement in the buying firm’s performance.

Buyer–supplier relationships are built up over time through legal, formal and informal exchange processes, and relation-specific investments. The relationship life-cycle influences the development of central relationship marketing constructs, such as cooperation, adaptation, information sharing, or commitment.

Supplier development will be more successful if the relationship is in a stage where the levels of cooperation, adaptation, information sharing, commitment, etc. are high (maturity) rather than low (initiation and decline).

Trust is a central organizing construct in buyer–supplier relationships. Trust builds slowly from experience as the relationship progresses and vanishes as the firms seek to leave the relationship.

For more reading on trust in business relationships I suggest Das and Teng (2001) on Trust, Control and Risk in Strategic Alliances, or Cousins (2002), who claims that all firms are snakes.

Relationship properties such as goal congruence, idiosyncratic time investments, idiosyncratic adaptation investments, willingness to take risk, or information exchange – are low in the exploration and decline phases of the relationship and high in the build-up and maturity phases. The effectiveness of supplier development activities will follow such a pattern of increase, zenith, and decline because many of these relationship properties are supportive or necessary for supplier development activities.

What Wagner means here is that supplier development activities must take into account at which stage or phase the relationship is, in order to be effective. Supplier development activities may even be counterproductive if forcefully applied too early or too late in the relationship:

In sum, in established buyer–supplier relationships, a buying firm’s supplier development activities will have the highest impact on its performance improvement. In contrast, supplier development in newer and older buyer–supplier relationships will be detrimental to the buying firm’s performance.

In other words, supplier development activities and supplier performance incentives are dependent on the current relationship life cycle phase.  This means that the  different stages in the supplier relationship life cycle should play an important role in determining how the supply chain can be improved.

Conclusion

This paper raises some interesting issues, particularly the question “Is supplier development always worth the effort?”. Obviously, as far  as Wagner is concerned, it is not always worth the case. While I do agree that decreasing the effort towards the end of the relationship is the correct approach, I am more hesitant in concurring that supplier development activities that start too early are not effective. That said, it is worth to always consider the desired remaining length of the relationship before embarking on developing the supplier relationship.

Reference

Wagner, S. (2011). Supplier development and the relationship life-cycle International Journal of Production Economics, 129 (2), 277-283 DOI: 10.1016/j.ijpe.2010.10.020

Author link

• ethz.ch: Stephan wagner

Supply-side only

It must be said that this article looks exclusively at risk sources on the supply side of the supply chain. While this is perhaps a small limitation as to the number and direction of possible risk sources, it is often the possible disruptions on the supply side that causes most concern, not the demand side. .

Supplier – supply market – supply chain

The supplier risk source consists of potential problems associated with a specific supplier, its management, and systems. Supply market risk sources entail potential problems that exist with the supply market in general – not necessarily only with a specific supplier. The extended extended supply chain risk sources consist of characteristics associated with sourcing from suppliers in locations that are a far proximity to the buying firm’s operations. No less than 14 items were examined, grouped into factors related to the individual supplier, the supply market and the extended supply chain.

The factors listed below were ranked on a 1 to 5 scale by the respondents with a question like: “When making sourcing or supply chain management decisions (for a certain product), to what extent are you are you concerned about said factors, which may contribute to supply chain risk?”, where 1 is “not at all concerned” and 5 is “extremely concerned”.

Supplier

• Ineffective management in the supplier firm
• Financial instability or financial failure of supplier
• Supplier’s incorrect interpretation of requirements
• Incoming product quality problems
• Labor/management porblems at supplier
• Problems in electronic sharing of information (EDI, ERP)

Supply market

• Lack of alternative suppliers
• Inability to influence suppliers
• Inability of suppliers to meet significant increases in required volume

Extended supply chain

• Transportation disruptions in inbound supply channels
• Variability in transportation times in inbound supply chains
• Political instability affecting suppliers’ operations
• Natural disasters affecting suppliers’ operations
• Long distance between company and supplier

The factors above are listed in order of response significance, suggesting that

• Ineffective management in the supplier firm
• Lack of alternative suppliers
• Transportation disruptions in inbound supply channels

are the most important risk factors

Flexibility and redundancy

On the resilience side, flexibility and redundancy are seen as key drivers or contributors for resilience. Personally, I would want to include adaptive capacity and organizational learning as well, albeit for the supply side alone, flexibility and redundancy are perhaps sufficient enough? The factor flexibility consists of auditing supplier processes, monitoring supplier financial conditions, and certifying suppliers. In contrast, the items loading on the second factor, redundancy, includes using dual or multiple supply sources, ensuring excess supplier capacity exists, having supply continuity plans in place, requiring suppliers to report disruptions, and having suppliers hold inventory to prevent stockouts.

The factors listed below were ranked on a 1 to 5 scale by the respondents with a question like: “To what degree do you use said practices specifically to manage supply chain risk for a certain product”, where 1 is “not at all” and 5 is “very high”.

Flexibility

• Audit suppliers’ internal systems and processes
• Monitor the financial condition of suppliers
• Supplier certification program

Redundancy

• Dual or multiple supply sources
• Ensure that excess supplier capacity exists to handle unplanned increase in demand
• Supply continuity/contingency plans
• Require supplier to immediately report disruptions regardless of (little or large) impact
• Require supplier to hold inventory to prevent stockout

The factors above are listed in order of response significance, suggesting that

• Audit suppliers’ internal systems and processes
• Dual or multiple supply sources

are the most important flexibility and redundancy factors

Research model

According to the authors, one purpose of the study is to investigate the relationship between management perceptions of supply risk and the frequency of experiencing the effects of supply disruptions, that is, whether supply management professionals’ judgements about risk stemming from various  risk sources on the supply side are accurate and in fact materialize in disruptions.

H_{1 a – b} Supply management professionals perceiving risk from (a) suppliers, (b) supply markets, and (c) extended supply chains, experience the effects of supply disruptions more frequently.

The other purpose of this study is to investigate whether the use of various supply chain resiliency practices serves a moderating role in reducing the frequency with which buying firms experience the effects of supply disruptions.

H_{2 a – b} Supply management professionals that create supply chain resiliency through (a) flexibility and (b) redundancy in response to risk perceptions, experience the effects of supply disruptions less frequently.

The figure below illustrates the research model and the hypotheses.

And what did they find?

Results

One interesting finding in this study is that supply management professionals’ perceptions of risk from extended supply chains are negatively associated with disruption occurrence. In other words, the more at risk you think you are, the less often do you experience disruptions. Reason: If you consider yourself at risk, you are more likely to engage in proactive measures to reduce the probability of disruptions.

The authors also find that the supply resiliency practices of flexibility and redundancy do not moderate the relationship between the perceived risk from suppliers and disruption occurrence, and that the supply resiliency practice of flexibility does not moderate the relationship between perceived supply market risk and disruption occurrence. Disruptions occur, and neither flexibility nor redundancy can prevent them from happening. However, as they note, the biggest benefits to creating resiliency with flexibility appear to come from the risk that exists from extended supply chains. The constant monitoring of suppliers can uncover “hidden” problems that may exist when sourcing from far-off locations.

Pursuing supply chain resiliency through redundancy moderates the risk perceived from the supply market on disruption occurrence, while flexibility was not found to moderate the relationship between supply market risk and disruption occurrence. So redundancy works with a supply market, but not flexibility, or at least not to the same degree.

Reference

Zsidisin, George, & Wagner, Stephan (2010). Do Perceptions Become Reality? The Moderating Role of Supply Chain Resiliency on Disruption Occurrence Journal of Business Logistics, 31 (2), 1-20

Author links

• bgsu.edu: George Zsidisin
• ethz.ch: Stephan Wagner

Read online

• findarticles.com: Do Perceptions Become Reality?

Critique

This article excellently highlights some of the supply-side risks that supply chain managers concern themselves with. While I agree with the second hypothesis, I found the argument of the first hypothesis a bit puzzling at first. That said, they did prove it wrong, and it is true that perceived disruption risk and actual disruption risk are often far from each other. On a sidenote, the article by Ellis, Henry and Shockley (2010) provide another interesting article on buyer perceptions of supply disruptions risk. I am also struggling with the factors used to describe flexibility. Admittedly, a supplier certification program may make it easy to switch

Predictable disruptions?

That one supplier takes another with him in the fall, like a chain of dominoes, should not come as a surprise, particularly not in the automobile industry, where one supplier may not only supply parts for different models of the same brand, but perhaps even supply parts for several models made by different car manufacturers. Many suppliers in the automobile industry are very much linked to each other, even though they may not realize it, and a car manufacturer who has spent time and effort in creating a diversified supplier portfolio may find that his portfolio is not so diversified after all, if it all falls apart just because one supplier defaults.

The copula approach

This is a highly empirical and analytical paper, and the core of model consists of copulas. A copula is a function that links univariate marginals to their full multivariate distribution. Thus, the marginal distributions and the dependence structure of the random variables can be modeled separately.

Copulas been extensively used for dependence modeling in finance-related problems.  However, the authors note that

The selection of the appropriate copula is crucial. In this paper we highlight the flexible modeling using copulas and the consequences from different copula choices. The ultimate choice of the appropriate copula should reflect the dependence structure and risk profile of the supplier portfolio.

I must honestly admit that I do not fully understand the statistics and probability theory that works behind the scenes, which is why I will refrain from discussing it in this review, but I am able to appreciate the results.

Multi-sourcing does not equal redundancy in supply

What this paper tells is that simply adding more suppliers isn’t always better if safeguarding against disruptions is the objective:

From our analysis, several important implications for automotive OEMs in particular and buying firms in other industries in general can be derived. Most important, firms should revisit the commonly used ex-ante strategy of multiple-sourcing when aiming for a safeguard against the consequences of sudden supplier default, and take their suppliers’ default dependence into consideration. Purchasing managers should be aware that positive default dependence between suppliers is not an exceptional phenomenon. Therefore, our research questions the ‘‘hedging power” of multiplesourcing arrangements.

If a supplier portfolio analysis shows a hight default dependency among suppliers, there are several steps a buyer firm can take:

For single sourcing,

• Keep, but develop existing suppliers in order to increase their performance
• Switch to alternative, less default-dependent suppliers

For multiple sourcing,

• Create a portfolio of  independent suppliers without ties to each other

The authors suggest that firms should align their supplier portfolio with the product development cycles and the life-cycles of their products on the market, which also reduces the probability of a supplier default spilling over from one product to the other.

Conclusion

As already mentioned, the paper is best suited for a reader with a quantitative mind, i.e. not me. That said, since I cannot vouch for the approach taken, the results speak for themselves. However, the data needed for running the analysis and simulations may not be easy to find, as

it requires market data – corporate bond data and corresponding market values in particular – to derive the suppliers’ individual default intensities.

Nonetheless, this paper shows that supply chain risk management must look beyond the individual supplier and look at dependencies within the entire supplier portfolio. Such dependencies may not be obvious at first sight, and this paper presents one very good approach towards discovering these dependencies.

Reference

Wagner, S., Bode, C., & Koziol, P. (2009). Supplier default dependencies: Empirical evidence from the automotive industry European Journal of Operational Research, 199 (1), 150-161 DOI: 10.1016/j.ejor.2008.11.012

Author links

• ethz.ch: Prof. Dr. Stephan M. Wagner
• ethz.de: Dr. Christoph Bode
• uni-goettingen.de: Philipp Koziol

Related

• husdal.com: Managing risk together

Contents

The book contains nine chapters written by 20 leading academics. Some of them are known to me and already have publications  reviewed on this blog, others are new acquaintances and promising review subjects that I will take a closer look at in my future posts.

1 Risk and Security – A Logistics Service Industry Perspective by Christoph Bode and Stephan M. Wagner serves as an introductory chapter, discussing various aspects of risk management and security, but first and foremost it is aimed at establishing a nomenclature for supply chain risk management by describing and defining supply chain risk source, supply chain risk, supply chain disruption and supply chain vulnerability.

The same figure appears in Wagner, S., & Neshat, N. (2009) Assessing the vulnerability of supply chains using graph theory

2 Risk Management in Supply Chains under Uncertainty by Robert de Souza, Mark Goh, and Fanwen Meng is an innovative framework for supply chain risk management.

3 Risk and Security Management for Logistics Service Providers: Trends, Challenges, and Opportunities by Eleftherios Iakovou, Dimitrios Vlachos, and Anastasios Xanthopoulos presents an analytical methodological framework for the design and execution of efficient and resilient logistics processes in an adverse environment.

4 Understanding Context Risk in Southeast Asia: A Logistics Industry Perspective by Ruth Banomyong describes and compares the complex risk issues faced by the logistics service industry in the ASEAN countries.

5 Global Supply Chain Security for Logistics Service Providers by Zachary Williams, Robert Lorin Cook, and O. Keith Helferich explains how to deal with catastrophic incidents in supply chains, and discus what risk management tools are applicable to what kind of companies.

6 Security, Risk Management, and Crime Prevention in Supply Chains
by Daniel Ekwall
examines the relationship between security, risk management and crime prevention in supply chains.

Much of this article is based on Ekwall’s previous work on the difference between legal and illegal supply chains.

7 Business Risk in Container Shipping by Tsz Leung Yip and Y. H. Venus Lun discusses the impact of economies of scale and how the optimal size of business in the container shipping industry.

This is a topic I felt was missing when I was reviewing this article on security in maritime supply chains.

8 Applying Risk Assessment to Secure the Containerized Supply Chain by Maarten van de Voort, Henry H. Willis, David S. Ortiz, and Susan E. Martonosi weighs costs and benefits of security measures and show how to judge the efficiency and feasibility of such measures.

This framework is very similar to Peck’s 4-level supply chain in her integrated framework for drivers of supply chain vulnerability.

9 Technology-Enabled Risk Management along the Transport Logistics Chain by Alexander C. H. Skorna, Christoph Bode, and Stephan M. Wagner points out that a smart combination of positioning, sensor and communication technologies offers interesting capabilities to reduce theft and damages in transportation and warehousing.

Conclusion

Many papers (and books) on supply chain risk do not deal explicitly with supply chain security; at best it is one of many aspects of discussion. This books takes supply chain security a long step forward, as it provides a cross-section of current research and future issues that are bound to receive not less but more attention in an increasingly uncertain and perhaps insecure world. Supply chain security is not something that is added on to a supply chain, it ought to be something that is integrated into every supply chain.

Reference

Wagner, S. & Bode, C. (Eds.) (2009) Managing Risk and Security: The Safeguard of Long-Term Success for Logistics Service Providers. Bern: Haupt Verlag.

Author links

• ethz.ch: Prof. Dr. Stephan M. Wagner
• ethz.de: Dr. Christoph Bode

Publisher link

• haupt.ch: Managing Risk and Security

Related

• husdal.com: An empirical investigation into Supply Chain Vulnerability

Not the first time

Honestly, I must admit, first time I came across Stephan Wagner was in Wagner & Bode (2006) An empirical investigation into supply chain vulnerability, and at that time I wasn’t really taken aback by what I read. This time, however, is very different. While I’ve always struggled with the Graph Theory Concept (I’m a qualitative much more than a quantitative thinker), and I still struggle when reading this paper, I have to give my sincere laud for developing a totally novel approach towards analyzing supply chain vulnerability.

Supply Chain Vulnerability Index

Why are supply chains more vulnerable now than before? Wagner and Neshat list four reasons:

• Disasters (man-made and natural) have increased in number and in intensity during the last decades.
  I’m not sure this counts as a valid reason, but OK.
• Today’s supply chains are more complex than they used to be.
  Yes, no question there.
• Efficiency-driven supply chain management measures have made operations leaner and more efficient in a stable environment, they also make them more prone to disruptions in an unstable environment.
  True. A very valid reason.
• With competition becoming fiercer, competitive pressures often force companies to assume “calculated risks”.
  Has the acceptance bar been lowered too much? Perhaps.

Despite these reasons, so claim Wagner and Neshat, the understanding of the supply chain vulnerability concept still remains on a conceptual and normative level in most of the literature, so they say, and I have to concur here. That is why the main thrust of the research described in the paper is to develop a quantitative approach, were graph modeling is used to measure vulnerability using its drivers and their inter-dependencies. The result: a Supply Chain Vulnerability Index, SCVI.

Supply Chain Vulnerability Definition

While others have defined supply chain vulnerability in a succinct manner, e.g. Christopher’s “exposure to serious disturbance”, Wagner & Neshat describe supply chain vulnerability “precisely” as:

While a supply chain disruption is the trigger that leads to the occurrence of risk, it is not the sole determinant of the final loss. It seems consequential that also the susceptibility of the supply chain to the harm of this situation is of significant relevance. This leads to the concept of supply chain vulnerability. The basic premise is that supply chain characteristics are antecedents of supply chain vulnerability and impact both the probability of occurrence as well as the severity of supply chain disruptions.

Verbose, yes, but precise? Nonetheless, the definition carries within it all the necessary ingredients that need to be measured.

Supply Chain Vulnerability Drivers

Wagner and Neshat categorize supply chain vulnerability drivers (SCVD) into three groups: supply side, demand side, and supply chain structure.

Vulnerability drivers on the demand side reside in the downstream supply chain operation, including the customer (e.g., customer dependence, financial situation of the customer), the product and its characteristics (e.g., its complexity and life-cycle), the outbound supply chains (e.g., the physical distribution of products to the end-customer), the distribution and transportation operation required for serving the customer.

Vulnerability drivers on the supply side can reside in the supply base, the supplier portfolio or the supplier network (e.g., supplier-supplier relationships, supply base complexity, supply base structure).

Vulnerability drivers in the supply chain structure stem to a large degree from the disintegration of supply chains and the globalization (and off-shoring) of value-adding activities.

This encompasses the division of risk sources in Christopher (2005) and in Jüttner et al. (2003).

Supply Chain Vulnerability Levels

Wagner & Neshat contend that supply chain vulnerability exists and interconnects at many levels, something that is very reminiscent of Peck (2005) and Peck (2006).  Supply chain vulnerability can be thus measured and managed at different levels:

• an entire economy
• an industry
• an entire supply chain
• the focal firm

While Peck makes her argument from the bottom up, Wagner & Neshat start from the top, indicating that this is where supply chain vulnerability has the greatest effect and where efforts to reduce vulnerability should focus on, because the firm level of analysis is narrower and fails to consider the risks stemming from a firm’s involvement in networks of production and supply.

Decision makers at these different levels are likely to have a different understanding of  supply chain vulnerability. And, the higher the decision level, the more difficult it is for an individual firm to influence supply chain vulnerability.

Supply Chain Vulnerability Graphs

Graph theory may seem like a stranger to supply chain modeling, but Wagner & Neshat are not the first to apply graph theory to supply chain risk and related subjects. Faisal, Banwet & Shankar (2007) used graph theory for the quantification of risk mitigation environment of supply chains. The reason for using graph theory with supply chain vulnerability are the inter-dependencies among the supply chain vulnerability drivers .

Graphs have two basic elements: the node (or vertex) and the edge (or link). By considering vulnerability drivers as vertices and the inter-dependencies between them as edges, a graph can be plotted for a specific supply chain.

Thus, graph modeling does seem an appropriate method to quantify vulnerability and tap the inter-dependencies.

Wagner & Neshat propose that

a weighted directed graph and its adjacency matrix can be applied to calculate the SCVI. The interactions among the vulnerability drivers as considered in this article are direction-dependent and thus these interactions and their intensities are represented by a weighted directed edge.

Translated into a graph and an adjacency matrix, it looks like this:

While the graph representation clearly shows variables and their inter-dependencies, the adjacency matrices can easily be stored, retrieved and processed by computer programs. Truly an ingenious approach to modeling supply chain vulnerability. The Supply Chain Vulnerability Index SCVI can be thus calculated as follows:

• Step 1: Finding graph nodes
• Step 2: Finding graph’s weighted and directed edges
• Step 3: Calculating adjacency matrix permanent
• Step 4: Comparing different SCVIs (for different risk mitigation efforts)

Implications

Wagner and Neshat even go as far as providing solid pros and cons of their method: First, the applicability of the proposed approach  depends heavily on the availability of quantified data for the drivers of supply chain vulnerability.  Without grounded data this method will not work. Second, the reliability of the direction of the edges in the graphs depends on expert judgment. Bias beware. Third the graph theoretical approach may not fully take into account the dynamic nature of supply chain vulnerability.  Things change and graphs are perhaps too static. Fourth, while this is a novel method to measure and illustrate supply chain vulnerability, other methods are not necessarily worse suited. Humble, indeed.

Critique

Yes, this is a novel approach. I personally may still be struggling with the intricacies of graph theory, but the method is immediately attractive because of its illustrativeness. That said, the lack of quantifiable data on the interdependencies of the supply chain drivers may pose a serious hurdle in making this method generally applicable.

Reference

Wagner, S., & Neshat, N. (2009). Assessing the vulnerability of supply chains using graph theory International Journal of Production Economics 121 (6), 121-129 DOI: 10.1016/j.ijpe.2009.10.007

Author links

• ethz.ch: Stephan M. Wagner
• ethz.ch: Nikrouz Neshat

Related

• husdal.com: Book Review: Supply Chain Risk

]]> http://www.husdal.com/2009/11/04/graph-theory-to-the-rescue/feed/ 0 http://www.husdal.com/2008/06/19/an-empirical-investigation-into-supply-chain-vulnerability/ http://www.husdal.com/2008/06/19/an-empirical-investigation-into-supply-chain-vulnerability/#comments Thu, 19 Jun 2008 05:46:00 +0000 Jan Husdal http://scrisk.wordpress.com/2008/06/19/an-empirical-investigation-into-supply-chain-vulnerability/ Today’s journal article is from Germany. In An empirical investigation into supply chain vulnerability Stephan M. Wagner and Christoph Bode examine the relationship between a selection of supply chain characteristics and supply chain risks, and provide an empirical investigation into the supply chain vulnerability construct, based on a surveys and interviews of close to 5000 top-level executives.

First they set out to define supply chain risk, equating it with the detriment of supply chain disruption, that is realized harm or loss. Interestingly, supply chain disruption is seen as a cause of supply chain risk, and not as a kind of risk per se.

Looking at supply chain vulnerability, they posit that supply chain vulnerability is a function of certain supply chain characteristics and that the loss a firm incurs is a result of of its supply chain vulnerability to a given supply chain disruption.  In essence, disruption > risk > vulnerability.

As drivers of supply chain vulnerability they focus on 1) supply-side risk and 2) demand-side risk, as well as 3) catastrophic risk, listing a) customer dependence and b) supplier dependence, d) supplier concentration and d) single sourcing and e) global sourcing as sources of risk.

In a) the firm is on one hand dependent on its source as a supplier, but should b) not forget that at the same time its customers are equally dependent on it as their supplier. Thirdly, c) and d) imply that the advantage of a too close relationship with a small supplier base is offset by the disadvantage of not being able to switch to contingency suppliers in a disruptive situation. Lastly, e) implies that global sourcing contributes to the structural complexity of the chain, hence increasing uncertainty and decreasing visibility and transparency.

The hypothesis to be tested is that the five (a-e) drivers of supply chain vulnerability are positively related to the three (1-3) supply chain risk sources.

The results show that customer dependence is positively related to demand-side risk as in volatile demand or customer dissatisfaction. Risk derived from supply side risk sources is elevated by supplier dependence as in poor quality, product shortages, and poor supplier logistics. The latter is further elevated by global sourcing, adding long lead times and more complex problems the further upstream in supply chain disruptions occur. Catastrophic risks, obviously, are not very prevalent in Germany, but the research shows that supplier dependence decreases the risk exposure to catastrophes, provided sufficient cooperation at the supply base.

In conclusion, the article has a substantial bibliography, nothing amiss there. Add to that a clear structure,and clear language, this is a very interesting and rewarding read.

Reference

WAGNER, S., & BODE, C. (2006). An empirical investigation into supply chain vulnerability Journal of Purchasing and Supply Management, 12 (6), 301-312 DOI: 10.1016/j.pursup.2007.01.004

Author links

• ethz.ch: Prof. Dr. Stephan M. Wagner
• ethz.de: Dr. Christoph Bode

Related

• husdal.com: Book Review: Supply Chain Risk