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Trends of research on supply chain resilience: a systematic review using network analysis.

1. Introduction

2. sc resilience, 3. analyzing research trends with network analysis, 4. analysis, 4.1. subjects, 4.2. coauthorship, 4.3. pagerank analysis, 4.4. cocitation analysis, 4.5. keyword analysis, 4.5.1. analysis of papers published by 2012, 4.5.2. analysis of papers published in 2013–2017, 5. conclusions, conflicts of interest.

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Rha, J.S. Trends of Research on Supply Chain Resilience: A Systematic Review Using Network Analysis. Sustainability 2020 , 12 , 4343. https://doi.org/10.3390/su12114343

Rha JS. Trends of Research on Supply Chain Resilience: A Systematic Review Using Network Analysis. Sustainability . 2020; 12(11):4343. https://doi.org/10.3390/su12114343

Rha, Jin Sung. 2020. "Trends of Research on Supply Chain Resilience: A Systematic Review Using Network Analysis" Sustainability 12, no. 11: 4343. https://doi.org/10.3390/su12114343

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Supply chain disruptions and resilience: a major review and future research agenda

K. katsaliaki.

1 School of Humanities, Social Sciences and Economics, International Hellenic University, 14th km Thessaloniki-N.Moudania, 57001 Thessaloniki, Greece

2 Opus College of Business, University of St. Thomas Minneapolis Campus, 1000 LaSalle Avenue, Schulze Hall 435, Minneapolis, MN 55403 USA

Our study examines the literature that has been published in important journals on supply chain disruptions, a topic that has emerged the last 20 years, with an emphasis in the latest developments in the field. Based on a review process important studies have been identified and analyzed. The content analysis of these studies synthesized existing information about the types of disruptions, their impact on supply chains, resilience methods in supply chain design and recovery strategies proposed by the studies supported by cost–benefit analysis. Our review also examines the most popular modeling approaches on the topic with indicative examples and the IT tools that enhance resilience and reduce disruption risks. Finally, a detailed future research agenda is formed about SC disruptions, which identifies the research gaps yet to be addressed. The aim of this study is to amalgamate knowledge on supply chain disruptions which constitutes an important and timely as the frequency and impact of disruptions increase. The study summarizes and builds upon the knowledge of other well-cited reviews and surveys in this research area.

Introduction

Driven by the globalization of markets and the competitive business environment, lean supply chain management (SCM) practices have become very popular (Blackhurst et al. 2005 ) calling for continuous flow processing with low inventory volumes, levelled and just-in-time production and accurate scheduling of transport for cross-docking operations leading to more cost-effective and responsive supply chains (SCs). Furthermore, the pressure for cost reductions has led to the outsourcing and offshoring of many manufacturing and R&D activities, especially the sourcing from low-cost countries. These trends place enormous pressure for undistracted operations and stable environments, but also increase their vulnerability to disruptions which consequently increases the operational and financial impact of supply chain (SC) disruptions (Zsidisin et al. 2005 ). Given that more than 56% of companies globally suffer a SC disruption annually, firms have started taking SC disruptions more seriously (BCI-Business Continuity Institute 2019 ). Therefore, the need for designing resilient SCs and preparing contingency plans is of paramount importance.

Supply chain disruptions may occur due to climate change or human factors. Based on the site of the National Oceanic and Atmospheric Administration (NOAA), which keeps a record regarding the number of disasters and their associated costs in the U.S, there have been 212 disasters since 1980 resulting in approximately $1.2 trillion in damage. A typical year in the 1980s experienced, on average, 2.7 such disasters in the U.S, 4.6 in the 1990s, 5.4 in the 2000s, and 10.5 in the 2010s. The occurrence of costly disasters has mounted. The same phenomenon is observed globally based on the OFDA/CRED International Disaster Database with less than 200 disasters per year in the 1980s and over 300 in the 2010s. Natural disasters like the Thailand flood and Japan’s earthquake and tsunami in 2011 immediately affected the SCs of several products from firms such as Apple, Toshiba, General Motors, Nissan Motor and Toyota Motor causing negative results in these companies’ reputations and earnings (Chongvilaivan 2011 ). Statistics show that about 40–60% of small businesses never reopen following a disaster (FEMA 2015 ).

On the other hand, recent examples of human factor disruptions include the tariffs imposed on billions of products for US importers in 2018–19, specifically to steel and aluminum, which led to import delays due to an inability of companies to adjust their current customs clearance programs and absorb the extra cost. This left a negative impact on the relations of the US with China, whose companies have been affected the most. Moreover, the wake of Brexit at the beginning of 2020 increases production failure risks to just-in-time auto manufacturers and others with similar operations (Banker 2019 ). The civil war in Syria has created humanitarian logistics problems with refugees’ flows in Turkey and EU which based on the situation had to change supply chain strategies from serving populations on the move to serving dispersed but static groups of people, by supplying refugee camps, etc. (Dubey et al. 2019a , b , c ). Recently, the deadly coronavirus outbreak in a major industrial and transport hub of central China has triggered lockdowns in Chinese (and many other) cities and factories which have severely restricted production and transport routes globally (Araz et al. 2020 ).

The issue of SC disruptions has been greatly emphasized in the literature. It is a topic that increasingly challenges the SC of products and their focal firms, as SCs have become very complex and interdependent and disruptions create a snowball effect with serious consequences to all related SC echelons. This propagation, the ripple effect as is denoted in the literature (Ivanov et al. 2014a , b ) amplifies the impact of disruptions.

Although companies have high awareness about SC risks, more than 80% have been concerned about SC resilience (Marchese and Paramasivam 2013 ; Wright 2013 ), about 60% believe they have not yet developed and applied effective SC risk management practices (Sáenz and Revilla 2014 ). Therefore, managing risk in SCs is an important topic of supply chain management and has been the focus of research through reviews (Ho et al. 2015 ; Kleindorfer and Saad 2005 ), case studies (Ferreira et al. 2018 ) and an analysis of management models (Tomlin 2006 ). Related studies have exhibited a rich academic structure that encourages research in the field by identifying SC risks’ types, ways to detect and assess them and apply the right methods to react to them by linking theory with strategy and managerial practices (Nakano and Lau 2020 ).

However, there is evidence of a shift away from traditional risk management thinking as a reactive tactic to disruptions and towards more proactive strategies such as building SC resilience which increases the chances of achieving business continuity in turbulent cases (Christopher and Peck 2004 ). Building resilience is a capability that enables the SC to anticipate, adapt and promptly respond to unpredictable events (Blackhurst et al. 2005 ), and therefore greatly appeals to the firms. However, its effective application requires the development of certain operational capabilities aligned across the SC partners (Ali et al. 2017 ).

Supply chain disruptions and resilience have developed to become a well-defined research area, exhibiting a rich academic output. Indicative are the special issues in prestigious journals such as in the Supply Chain Management: An International Journal in 2019 on “New Supply Chain Models: Disruptive Supply Chain Strategies for 2030” (Wilding and Wagner 2019 ) and in the International Journal of Production Research (IJPR) in 2016 on “supply chain dynamics, control and disruption management” (Ivanov et al. 2016a , b ). Among the publications, numerous theoretical developments as well as review studies can be found exploring certain aspects of SC disruptions. There are also a few scientometric studies investigating mitigation methods (Bier et al. 2019 ), methods for building resilience (Centobelli et al. 2019 ; Hosseini et al. 2019a ) and the connection between SC risk and artificial intelligence (Baryannis et al. 2019a , b ).

From an academic standpoint, it is significant to classify and synthesize the output of research in a specific field, so that those interested can follow the field’s developments and trends (Merigó and Yang 2017 ). Bibliometrics is one method of conducting such a classification, which guides academics toward a discipline’s most influential studies (Gaviria-Marin et al. 2019 ; Godin 2006 ). On the other hand, the synthesis of knowledge can be performed through review and content analysis methods for classifying research and presenting a more analytical view of the developments of the field.

Our study examines the literature published in important journals on SC disruptions and resilience, a topic that has emerged the last 20 years, with an emphasis in the latest developments in the field.

The methodology is comprised of a profiling of our article pool, which is followed by a thorough review of advances in the field, completed by combining knowledge and providing information about supply chain disruptions, their impact and remedies, with a special focus on the ripple effect reduction, through the analysis of state of the art literature and comparisons. Finally, a review of the related technology advances draws a picture for the future of supply chain management against disruptions and provides a list of research ideas to gain a further understanding of the phenomenon, helping to better develop the field and prepare firms. Through this process managerial insights are offered for decision makers in the industry. Therefore, the manuscript aims to address: (1) how the literature has helped to advance theoretical debates and influence decision-making and (2) how the future is shaped, what the research gaps are that published papers have not yet addressed and constitute the future research agenda on SC disruptions. The study’s contribution is to complement prior research and provide a broad picture of SC disruptions and remedies at a time when the existing literature has matured, the interest of firms on the topic has mounted, especially due to the COVID19 pandemic lockdowns, and there are new ways emerging that require further investigation.

The remainder of the paper is organized as follows. The second section discusses the study’s methodology. The third section presents the profile of research on SC disruptions with an emphasis on the most influential papers. The findings from the content analysis of the related papers are described in the fourth section under eight subsections, focusing on the types of disruptive events, SC propagation-ripple effect, the impact of SC disruptions, resilience methods and recovery strategies, modeling approaches for SC disruptions, cost–benefit analysis of SC resilience, popular IT tools for resilience and response to disruptions and finishing with a future research agenda. The last section on discussion presents the research and managerial implications of this study.

Methodology

The paper’s main research methodology follows a step by step review approach by using explicit methods and adopts a bibliometric technique to identify research streams in the analyzed literature and also a content analysis method to provide a description of research evidence.

The data collection process of the relevant articles on SC disruptions is described below. The Web of Science (WoS) database was queried for articles and reviews written in English that were published between the years of t and 2019 inclusive and contain in their title the terms “supply chain*” AND in the topic (title, abstract or keywords) the term disrupt* (*with its derivatives). The search identified 951 studies, which were analyzed based on their profile. Figure  1 presents a detailed schema of the methodology which is divided in three stages: preparation of dataset, profiling and content analysis and paper writing. The tools of the WoS database were utilized to derive profiling results such as the distribution of papers per year, the journals and affiliations with the most published papers and the citation report. The content analysis was completed with the help of EndNote capabilities and two of the authors reading a selection of the articles. The criteria for an article’s participation in the content analysis was based on the thematic area under investigation. A positive inclination was towards papers belonging to the top 10 journals that publish relevant subjects or towards highly cited papers (based on total citation or average citations per year). Around 250 papers were read in full and a number of them sketched the content of the specific categories. The content analysis categories include the types of disruptions (hierarchized by reason and frequency of occurrence), the impact that SC disruptions create (e.g. ripple-snowball effect), resilience, response and recovery methods, cost–benefit analysis of responses to disruptions, the most popular modeling approaches for applying resilience and mitigation strategies (topped with indicative examples and a special focus on the ripple effect), the IT tools and technological trends that enhance resilience and response to disruptions and research gaps that require further investigation. For this last section of future research, we also included ideas from 5 studies published in 2020 which cover issues related to the enormous SC disruption caused by the COVID19 pandemic.

Methodology schema

Profiling research on SC disruptions

A look into the yearly distribution of the 951 related articles shows that the first papers on the topic were published as recently as in 2004, followed by continuous interest after that year. After 2015 there is a dramatic annual increase in the number of papers in the subject by around 30% from year to year. Around 30% of these papers are published in the following 10 journals: International Journal of Production Research, International Journal of Production Economics, Supply Chain Management: An International Journal, International Journal of Logistics Management, International Journal of Physical Distribution and Logistics Management, Omega: International Journal of Management Science, Transportation Research Part E Logistics and Transportation Review, European Journal of Operational Research, Computers & Industrial Engineering, and Annals of Operations Research. A lot of the work in the subject is conducted in the Russian Academy of Sciences, the University of Tehran and the Berlin School of Economics and Law.

Most influential papers and their contribution

If we assume that citation reports indicate the most read and referenced papers in the field, the most popular paper in the subject as of March 2020, is a framework for classifying SC risk management literature (Tang 2006 ), followed by one discussing SC disruptions in particular (Kleindorfer and Saad 2005 ).

Overall, the analysis of the 10 most important papers’ contribution (Appendix Table  3 ) indicate that in their great majority are a) review papers about: (1) managing SC risks [either through a conceptual framework (Tang 2006 ) or as a textbook style (Chopra and Sodhi 2004 ) or a citation-review analysis (Tang and Musa 2011 )], (2) managing SC disruptions (Kleindorfer and Saad 2005 ), (3) explaining SC resilience (Ponomarov and Holcomb 2009 ) and (b) survey papers discussing about: (1) the different levels of severity of SC disruptions through interviews (Craighead et al. 2007 ), (2) the impact of disruptions’ announcements to the firms’ stock price performance (Hendricks and Singhal 2005 ), (3) the perceptions of SC professionals of how SC agility is achieved (Braunscheidel and Suresh 2009 ) and (4) of their approaches to risk in global SCs (Manuj and Mentzer 2008 ). There is also one paper in this list which presents an inventory optimization model to assess sourcing strategies under disruptions (Tomlin 2006 ). Almost all of these papers have been published before 2010 (only one in 2011). Therefore, apart from their important content, the time that have been available is also a crucial parameter of their popularity.

Table 3

Top 10 referenced articles in supply chain disruptions

A further investigation on trending WoS papers* (10 more recent papers with increasing citations - Appendix Table  4 ) revealed a focus on the digitalization of SCs and its impact on SC risk control, such as the effect of digital technology and Industry 4.0 on SC disruptions (Ivanov et al. 2019 ), the effect of the use of blockchain (Saberi et al. 2019 ) and employees’ perceptions in using it (Queiroz and Wamba 2019 ). Altogether these 10 studies constitute a collection of (1) reviews about quantitative methods for modelling SC disruptions and aiding decision-making (Dolgui et al. 2018 ; Heckmann et al. 2015 ; Ho et al. 2015 ; Hosseini et al. 2019a ; Snyder et al. 2016 )], (2) conceptual frameworks of certain approaches on the subject (Ivanov and Dolgui 2019 ) and (3) surveys of professionals’ knowledge on SC disruptions and adoption of mitigation tactics (Queiroz and Wamba 2019 ; Sodhi et al. 2012 ).

Table 4

Top 10 trending* papers on supply chain disruptions

*(6 hot papers as characterized by WoS because were published in the past 2 years and received enough citations to be in the top 0.1% of papers in their academic field and 4 papers with a high average citation per year index)

Content analysis results

In this section, a review of the selected studies is presented. The review is organized under the following areas: types and reasons of disruptions, the ripple effect, impact analysis of SC disruptions, resilience-response-recovery strategies to disruptions, popular quantitative approaches for the analysis of SC disruptions, cost–benefit analysis of resilience Vs disruptions, IT tools for enhanced resilience and research gaps for future research directions. All the subsections’ information is generated through a content analysis of the important papers of our dataset that is enhanced with other external sources when necessary. Many sections are supported by tables that provide an account of the reported analysis.

Types of disruptive events

There is a vast literature which names and analyses the reasons for disruptions in SCs. Selectively, some of the most relevant studies are the following: (Baryannis et al. 2019a , b ; Chopra and Sodhi 2014 ; Christopher and Peck 2004 ; Dolgui et al. 2018 ; Ivanov 2017 ; Ivanov et al. 2014a , b ; Rao and Goldsby 2009 ; Tang and Tomlin 2008 ; Thun and Hoenig 2011 ; Vilko and Hallikas 2012 ; Zsidisin et al. 2016 ) which reveal the main reasons for the disruptions’ occurrence. There are also a number of annual surveys on SC disruptions and resilience which are triggered by the Business Continuity Institute (BCI-Business Continuity Institute 2019 ) and other older surveys from Hendricks and Singhal ( 2005 , Hendricks et al. ( 2009 ).

The literature provides several ways of grouping the reasons for disruptions/glitches:

• Based on the SC echelons are clustered under (a) production, (b) supply and (c) transportation disruptions (Ivanov et al. 2017 );
• Based on the reason that caused the disruption, form 9 groups: (a) disasters (e.g. natural disasters, terrorism, war, etc.), (b) delays (e.g. inflexibility of supply source), (c) systems (e.g. information infrastructure breakdown), (d) forecast (e.g. inaccurate forecast, bullwhip effect, etc.), (d) intellectual property (e.g. vertical integration), (e) procurement (e.g. exchange rate risk), (f) receivables (e.g. number of customers), (g) inventory (e.g. inventory holding cost, demand and supply uncertainty, etc.) and (h) capacity (e.g. cost of capacity) (Chopra and Sodhi 2014 );
• Based on their frequency of occurrence, SC risks that occur regularly are: supply risks, process risks, demand risks, intellectual property risks, behavioral risks, and political/social risks (Tang and Tomlin 2008 );
• Based on their nature and their source are classified under 5 categories: (a) process risk, (b) control risk, (c) demand risk, (d) supply risk and (e) environmental risk (Christopher and Peck 2004 );
• Based on who they affect, from broad to specific, disruptions are: (a) external to the SC network and are termed environmental, (b) internal to the SC network but external to the focal firm, called network or industry risks (c) internal to the firm, called organizational disruptions, (d) problem-specific and (e) decision-maker specific (Rao and Goldsby 2009 ).

Moreover, disruptive events are characterized by their type, intensity, duration (Dolgui et al. 2019 ), source and impact. Below we provide examples from the literature based on these characterizations.

The disruptive events may have an individual impact (e.g. affect only one supplier, e.g. equipment breakdown, fire etc.), a local impact for suppliers in a geographic area (e.g. labor strike triggered by new worker’s legislation of a State, etc.) or a global impact that affects all suppliers or SC echelons simultaneously. Such global events may include an economic crisis, a widespread labor strike in a transportation sector, etc. Suppliers may suffer all three types (individual, local, global) of disruption risks (Sawik 2014 ).

Natural disasters and catastrophic events are considered to have low probability, but are high impact events with significant consequences to the SC network. On the other hand, high probability and moderate impact disruptions are: unanticipated demand, rush orders, shortage in supply, company buyouts, delivery coordination and sourcing constraints (Scheibe and Blackhurst 2018 ). 589 professionals who participated in a survey in 2011 indicated that delivery chain disruptions were higher in their organizations than most other risks, but with less than average impact (Thun and Hoenig 2011 ). Aligned with the latter, the results of a Finish survey identified time delays (as opposed to financial and quality risks) as the most serious in terms of likelihood of occurrence (Vilko and Hallikas 2012 ). Earlier, Hendricks and Singhal ( 2003 ) reported that of the 14 primary SC disruption categories that were identified, parts shortages was by far the most frequent reported cause, and delivery disruptions was one of the leading causes of parts shortages. Another survey showed that infrastructural events are the cause of more than half of the disruptions (Zsidisin et al. 2016 ). The latest reports show that SC disruptions, such as cyber-attack, data breach and loss of talent/skills have become more evident since 2014. Consistently high rated causes of disruption in the 2010s include unplanned IT and telecommunication outages, as well as adverse weather, transport network disruption and outsourcer failure which have rarely dropped from the top five causes (BCI-Business Continuity Institute 2019 ).

Synthesizing the analysis of the individual papers referring to the types of disruptions, and survey papers and reports that have estimated their frequency of occurrence, in Table  1 we provide a summary of disruptive event categories, hierarchized by frequency of occurrence, from low to high. We also provide indicative references from our review database which refer to the specific category’s events.

Table 1

Reasons for supply chain disruptions from low to high frequency of occurrence

Supply chain propagation and the ripple effect

Given the geographical diversification, the number of tiers and the nature of product failure in an echelon of the SC may not only be a local problem but a far-reaching one which affects many echelons of the SC, but most importantly the end-customer. Perturbations originating in a localized point have the potential to be passed onto subsequent tiers of a SC with possible amplification effects (Wu et al. 2007 ).

The most-known such SC amplification effect is the bullwhip effect, which is caused by changes in customer demand that can propagate through the SC, amplifying in magnitude as the change passes to adjacent tiers (Lee et al. 1997 ). However, the bullwhip effect only describes one type of demand-side disruption which is caused by order batching, promotions, shortage gaming and mainly from a lack of coordination among the SC tiers as well as the lack of information sharing and transparency. This is a problem that has been cured in recent years with the use of enterprise resource planning (ERP) software, cloud services and other online sharing means.

On the other hand, the amplification effect which is caused by any type of disruption in the SCs is called the ripple effect (Ivanov et al. 2014a , b ; Liberatore et al. 2012 ). The ripple effect describes the disruption propagation in the SC, the resulting SC structural dynamics and the performance impact of this propagation (Sokolov et al. 2016 ). Disruptions may occur upstream from interruptions in the supply-side (supplier/production failure, product quality problems, resource constraints) or downstream originated from demand-side and legal, regulatory and financial unexpected changes in the markets. An upstream example is the case of a supplier that has produced some components with harmful properties for the environment, which are supplied to the next upstream tier and further to tier-one, where the component should be suspended and recalled, resulting in delays for the whole SC of the final product (Levner and Ptuskin 2018 ).

The ripple effect describes the SC amplification and propagation effects of unpleasant events in broader terms and its consequences which may be much more severe than these of the bullwhip effect (Ivanov et al. 2017 ). The disruption frequency is usually lower, but the performance impact is higher than this of the bullwhip effect (Dolgui et al. 2018 ). The ripple effect has also been regarded with the snowball effect (Swierczek 2016 ) and domino effect (Khakzad 2015 ), which have similar definitions. However, the term ripple effect has dominated the literature and in many papers has been related with low-frequency high-consequence chains of accidents (Ivanov et al. 2017 ). Often, the ripple effect has a tremendous impact on the whole supply chain’s performance, its ability to deliver to the end-customer and ultimately to the financial survival of its network of companies (Ivanov et al. 2014a , b ; Kamalahmadi and Mellat-Parast 2016 ).

The impact of SC disruptions

Companies find it difficult to measure the effects of supply-chain disruptions and empirical evidence remains limited (Wagner and Neshat 2012 ). However, there are a few surveys and case studies that have attempted to shed some light and quantify the impact of disruptions. Additionally, there is a list of notable large scale disruptive events and their consequences (Dolgui et al. 2018 ) which are often used in the literature as outstanding examples. Indicative is the plant fire (infrastructural event) of Philips microchip in 2000 in New Mexico which caused a shortage of chips in the market. The undelivered supplies resulted in $400 million lost sales for the cellphone producer Ericsson. Similarly, in 2011 the flood in Thailand and the earthquake-tsunami in Japan (catastrophic event), where many component manufacturers are concentrated, resulted in huge losses for these companies. This also affected the reputation, earnings and shareholder returns of several international industries such as Apple, Toshiba, General Motors, etc., as companies are increasingly dependent on the supply chains’ business continuity (Chongvilaivan 2011 ). In 2016, a contact dispute (legal event) between Volkswagen and two of its parts suppliers caused a production halt in 6 of the carmaker’s German plants. Around 28,000 workers were laid off or made part-time (Dolgui et al. 2018 ).

Therefore, taking also into account the ripple effect, it is understood that disruptions cause many negative consequences to the entire SC and the individual firms involved. The relevant literature analyses a number of these consequences. Also, the accumulated knowledge from surveys of the last decade show that loss of productivity is the number one consequence followed by increased working cost, impaired service, customer complaints, loss of revenue and damage to brand reputation (BCI-Business Continuity Institute 2019 ).

In broad terms, the effect of SC disruptions may include a sales decrease and cost increase (Ponomarov and Holcomb 2009 ), from which many companies never recover (Wagner and Neshat 2012 ).

Sales decreases occur due to failure to meet end-customer demand as a result of product unavailability, partially fulfilled orders in terms of quantity and late deliveries. These lead to customer complaints, damaged image and brand reputation and loss of customers. The financial consequences then follow with lower sales, loss of revenues and reduced market share.

On the other hand, higher costs may occur (a) due to the use of alternative transportation means for product deliveries, and higher administrative costs for dealing with backorders, (b) due to premium supplier contacts for ensuring delivery of the limited resources from alternative geographical areas and firms, (c) due to production rescheduling as a consequence of stockouts of certain resources, or worse (d) due to production shutdowns (e.g. fire) and hampered productivity (e.g. labor strike, slack times in manufacturing) and lower assets and capacity utilization (Jabbarzadeh et al. 2018 ). Extra costs may incur also e) due to penalties for breaching contracts and failure to meet legal or regulatory requirements (Wagner and Neshat 2012 ). Overall the decreasing sales and increasing costs ultimately lead to loss of profitability and a decrease in the company’s value (Ivanov 2017 ). Table  2 presents this degradation process.

Table 2

SC disruptions impact

Empirical research has shown that SC disruptions cause on average of a 107% drop in profitability (operating income), bring about 7% lower sales growth and an 11% growth in costs (Hendricks and Singhal 2005 ).

Poor firm performance is one of the most acknowledged effects of disruptions, but its negative impact is not consistent across all types of risks (Wagner and Bode 2008 ). Empirical research has shown that if recovery is possible, it takes up to 50 trading days (e.g. restart production) (Knight and Pretty 1996 ) and lower performance is observed for a period of two years after disruptions (Hendricks and Singhal 2005 ). The non-recoverers suffer a net negative cumulative impact of almost 15% up to one year after the catastrophe. Moreover, the more frequent the occurrence of a disruption within a focal manufacturing firm, the more likely it is that plant performance, relative to its competitors, will diminish. Consequently the higher the frequency of supply disruptions, the lower the plant performance (Brandon-Jones et al. 2015 ).

Another major impact that has been extensively studied is the financial impact of disruptions. Empirical findings indicate that financial markets react more dramatically to catastrophic and restrictive regulatory events, factors that usually cannot be easily controlled or avoided by firms, as compared to supply-side reasons, where some of them may be controlled or mitigated by firms through process improvement and early identification (Zsidisin et al. 2005 ).

At first sight, these findings indicate that managers should prioritize actions for contingency plans and the mitigation of catastrophic and regulatory-related disruptions, as these seem to have the highest financial impact. Nevertheless, apart from the severity of events, another factor that managers should consider when prioritizing actions related to disruptions is the frequency of occurrence of these disruptions and their cumulative financial impact. Therefore, low-impact but frequently occurring disruptions, combined, may have a more severe impact on shareholder wealth than infrequent high-impact events. Consequently, it is not irrational for managers to prioritize actions that could mitigate low-impact, high-likelihood events and especially these, mainly supply-side disruptions, that could be prohibited through process improvements (Zsidisin et al. 2016 ), good scheduling, appropriate maintenance and training, balancing inventory and capacity across the SC, etc. It is also empirically supported that firms with more operational slack, more days of inventory (inventory on hand) and a smaller sales over assets ratio (unutilized capacity), experience a less negative stock market reaction when disruptions occur, as slack provides resources and the required flexibility to handle disruptions (Hendricks et al. 2009 ).

Nonetheless, comparative surveys (Hendricks and Singhal 2003 ; Zsidisin et al. 2016 ) show that disruptions have a less detrimental impact to firm financial performance than in the past. The investigation of the impact to the firms’ stock price of SC glitches’ announcements (> 500) showed a dramatic fall that has smoothed throughout the years. Specifically, the effect of a SC disruption announcement (resulting in a production or shipment delay) on shareholder value meant an average reduction of above 10% on the stock market in the 90s (Hendricks and Singhal 2003 ), which has reduced to 2% in the 2000s (Zsidisin et al. 2016 ) probably due to an increased awareness and mitigation actions regarding disruptions and fast recovery (Wagner and Neshat 2012 ). Albeit the considerable advancements that have been achieved, disruptions now occur in greater frequency and intensity, therefore the consequences are still, in many cases, dramatic (Wagner and Neshat 2012 ). Realizing this negative impact, businesses are recognizing the importance and are attempting to create and be part of more resilient SCs (Jabbarzadeh et al. 2018 ).

Resilience methods and recovery strategies

To successfully recover from a SC disruption, a firm needs to activate effective methods (Blackhurst et al. 2005 ). According to the literature, managers need to respond to such incidents by following three identified stages of response: first detecting the volume of disruption, then designing or selecting a predesigned recovery method to tackle the disruption and finally deploying the solution (Chopra and Sodhi 2014 ). Several literature reviews have described the stages, methods and techniques of firm reaction and recovery after a disruption (Dolgui et al. 2018 ; DuHadway et al. 2019 ; Ivanov 2020b ; Ivanov et al. 2017 ; Sawik 2019 ).

According to the literature (Chowdhury and Quaddus 2017 ; Dolgui et al. 2018 ) resistance (proactive approach) and recovery (reactive approach) are included in the resilience concept. A firm needs to maintain redundancy (high safety-stock, additional production capacity) and flexibility (alternative suppliers for sourcing, alternative transportation depots and modes for delivery) to resist against disruptions and use them effectively to reduce their impact. Likewise, the recovery stage incorporates some of the same tactics as the resistance approach, such as the use of backup suppliers for sourcing, the use of the buffer stock for satisfying customer orders and redundant capacity for continuing the production (Ivanov et al. 2017 ).

Other important mitigation strategies for disruptive events focus on better demand forecasting (Scheibe and Blackhurst 2018 ), better coordination amongst the SC echelons before and after the disruption with the use of information-sharing (Dubey et al. 2019a , b , c ), joint relationship efforts, and decision synchronization (Nakano and Lau 2020 ) by deploying supply chain management software (such as warehouse and transport management systems and vendor managed inventories) connected to the ERP and business intelligence software add-ons (Brusset and Teller 2017 ).

However, surveys show that firms address disruptions most commonly with increased safety-stock, dual or multi-sourcing, and better forecasting. Although they consider coordination between the SC nodes very significant to recover from disruptions, in reality they act in isolation and their visibility of the SC extends only to one tier above and one tier below (Scheibe and Blackhurst 2018 ). Low collaboration and responsiveness has emerged as a great vulnerability (Pettit et al. 2013 ). Real-time supply-chain reconfiguration software could enhance responsiveness against specific situations (Blackhurst et al. 2005 ) and improve coordination and decision-making by recomputing, for example, optimal routes and facility selection to maximize demand fulfillment and minimize penalties and delay costs due to the disruption (Banomyong et al. 2019 ).

A representative example of the backup sourcing recovery option is the incident concerning the fire at the Philips microchip plant in Albuquerque. Ericson experienced a production shutdown because its materials were sourced only from that plant while Nokia took advantage of its emergency backup sourcing strategy to obtain chips from other suppliers (Chen and Yang 2014 ). A resilient design of a SC that promotes flexibility is described through the BASF example. BASF built a resilient SC with safety and risk prevention measures that included globally valid guidelines and requirements for capacity and security trainings for staff. In 2016 a pipeline at BASF facility in Germany exploded and destroyed a terminal for the supply of raw materials, limiting the access to key raw materials and product inventories. During this time, logistics was temporarily shifted from ships and pipelines to trucks and trains. BASF was prepared for an incident and was in close contact with its customers to keep them informed about the current availability of products to minimize the impact on customer deliveries, which resulted in smaller than expected economic consequences from the accident (Dolgui et al. 2018 ). Another example of flexibility importance is the case of the 2015 Nepal earthquake in which humanitarian organizations offering aid to locals were met with great disruptions (delays) in relief delivery. They identified the significance of developing a flexible network with the most influential factors being IT support, fleets’ (re)scheduling, and relief packages’ volume (Baharmand et al. 2019 ).

Firms belonging to specific SCs can utilize practical assessment tools from the literature that were developed to measure their own SC resiliece (Chowdhury and Quaddus 2017 ; Pettit et al. 2013 ). This is a first step to ackowledge their readiness to resist and respond to disruptions and understand where they should make efforts to improve.

Popular modeling approaches

Modeling approaches for sc disruptions.

Mitigation and recovery are very important procedures and the adoption of these “recovery strategies” include processes based on quantitative methods (Ivanov et al. 2014a , b ), which usually evaluate the effectiveness of each strategy prior to its implementation. Quantitative analysis methods for anticipating operational and disruption SC risks mainly include mathematical optimization, simulation, and control theory to control risk, respond and stabilize the execution process in case of disruptions and to recover or minimize the middle-term and long-term impact of deviations (Ivanov et al. 2017 ). Mathematical optimization offers optimal solutions by using algorithmic models; simulations are models that provide the “what if’ scenarios” and control theory provides additional analytical tools often used to analyze system dynamic performances over time (Yang and Fan 2016 ).

More specifically, optimization models offer analytical solutions which determine the impact of disruptions and identify resilient SC policies. Such models can incorporate a large variety of parameters and objectives (e.g. minimization of disruption cost). Mixed-integer programming (MIP) is a category of optimization problems that has been repeatedly used to model SC disruptions (Ivanov et al. 2017 ). However, a major limitation of optimization models is that they cannot capture the dynamic nature of SCs (e.g. disruptions are modeled as static events, without considering their duration or erratic impact) and therefore make a high number of assumptions (e.g. known demand, suppliers’ reliability, etc.). On the other hand, stochastic programming modeling allows for the insertion of some uncertainty through probability distributions depicting disruption event scenarios and leads to optimal solutions by taking into account multiple objective functions (Sawik 2014 ). Stochastic programming models incorporate a set of discrete scenarios with a given probability of occurrence. The probability distributions may describe demand uncertainly, disruption impact uncertainly, costs uncertainty for applying response and recovery strategies, etc. Stochastic programming techniques have also been used to model disruptions in SC, however, the scenario-based approach of stochastic programming modelling exponentially increases the number of variables and constraints and makes these models difficult to implement and run.

Simulation methods are more flexible than stochastic optimization models as they are used to replicate system behavior and allow for a dynamic approach of randomness in disruption and recovery policies, as well as they incorporate and handle more complexity (more probabilistic scenarios for more variables simultaneously), incorporate the time dimension and even offer real-time analysis, and multiple results under each what-if scenario. Simulation can also be applied to enhance the optimization results or be used as a simulation-based optimization technique. Simulation techniques such as discrete-event simulation, system dynamics, agent-based modeling, optimization-based simulation and graph theory-based simulation have been applied to describe and model the impact of the ripple effect in SC disruptions (Ivanov et al. 2017 ) among other things.

Control theory has also the analytical ability to execute SCs over time and is used to analyze eventual system dynamic performances. The development of control models is usually related to specific operational risks which constitute the key control metrics (such as, demand fluctuation, degree of information sharing, speed of convergence) for quantifying disruption recovery performance (Ivanov and Sokolov 2019 ; Yang and Fan 2016 ).

Another technique which is apparent in the analysis of SC disruptions is graph theory (e.g. Bayesian network, decision trees) which, through mathematical structures, describes the interrelationships of the SC and based on the predictions and decision scenarios model pairwise relations between entities (Hosseini and Ivanov 2019 ). Finally, game theory (e.g. Stackelberg game) is another type of mathematical modeling which focuses on the strategic interaction among rational decision-makers and, given the order of decisions from decision-makers, certain scenarios are deployed about their reactions in SC disruptions.

Needless to say, inventory theory is dominantly used for modeling SC disruptions. It incorporates popular inventory models (deterministic or stochastic optimization models), such as economic order quantity models and periodic review models which determine safety stock, optimal ordering and production quantities during the design of resilient SCs and the recovery period to minimize total costs, capturing the trade-offs between inventory policies and disruption risks. These models can be two-echelon or multi-echelon models based on the length of the SC.

In the examined articles, we have identified that most papers use optimization methods, followed by papers that apply simulation techniques. There are also studies that present statistical analysis of database data or survey, e.g. (Brusset and Teller 2017 ) or that use graph theory, e.g. (Nakatani et al. 2018 ) and game theory, e.g. (Fang and Shou 2015 ). From the optimization methods notable is the use of stochastic programing e.g. (Snoeck et al. 2019 ), mixed-integer programming, e.g. (Amini and Li 2011 ) and multi-objective programing e.g. (Teimuory et al. 2013 ). The simulation methods used are discrete-event simulation, e.g. (Ivanov et al. 2017 ), system dynamics, e.g. (Kochan et al. 2018 ) and agent-based modeling, e.g. (Hou et al. 2018 ). Looking into our article pool, the papers that have developed quantitative analysis methods model resilience, response and recovery strategies. (Appendix Table  5 shows 10 indicative papers as examples of the variety of quantitative methods used in the relevant literature with a brief explanation of the model’s purpose.)

Table 5

Ten indicative examples of papers applying quantitative techniques

Quantitative techniques offer a great range of analysis which varies from solving single, simple problems to very complex and interrelated ones. The latter more precisely describes the need of SC modeling. Operations and supply chain managers can choose from the available quantitative tools for different application areas of SC disruptions and determine an optimal or near optimal solution.

Modeling approaches for the ripple effect

Special attention is given in the most recent literature (after 2014) with regards to the ripple effect and the ways to manage it/reduce it through tactics that are tested in quantitative models. From a search in the Web of Science database regarding the literature on the ripple effect of SCs (keywords: “ripple effect” and “supply chain”), 31 journal papers have been identified, 18 of which are published in the IJPR, 3 in the International Journal of Production Economics (IJPE) and the remaining 10 each in different journals. Prof Ivanov is the author in 21 of these, establishing the ripple-effect as a scientific topic in the area of SC disruption management, by using an analogy to computer science where ripple effect determines the disruption-based scope of changes in the system (Ivanov et al. 2014a , b ).

Α thorough analysis of the ripple effect in SCs is given in a review paper (Ivanov et al. 2014a , b ) and its follow-up (Dolgui et al. 2018 ) which provides a framework for the reasons of the ripple effect (sourcing strategy, production planning, inventory management, and control), presents its quantitative modelling approaches (including mixed-integer programming, simulation, control theory, complexity and reliability theory) and provides an analytic count down of future research avenues. Adding to the latter an overview paper demonstrates the positive impact of technology (big data analytics, 3D printing, blockchain, etc.) on the ripple effect mitigation (Ivanov et al. 2019 ). Attention is also drawn to case studies. For example a highly cited paper published in IJPE (Koh et al. 2012 ), assesses impact of actions for greening the SC and the triggering of the ripple effect and another one based on the analysis of the 2009 Italian earthquake uses MIP to model protection plans of regional disruptions by identifying which facilities to protect first (Liberatore et al. 2012 ).

The majority of the remaining papers in the literature on ripple effect are focused on modelling the phenomenon, which requires the inclusiosn of many SC echelons and thus more complex processes in the model, and exploring mitigation tactics. This is done by the use of mathematical models e.g. (Hosseini and Ivanov 2019 ; Ivanov et al. 2015 ; Ivanov et al. 2013 ; Kinra et al. 2019 ; Pavlov et al. 2019 ; Sokolov et al. 2016 ) or by simulation techniques which are frequently used to present the ripple effect phenomenon (Dolgui et al. 2019 ; Hosseini et al. 2019b ; Ivanov 2017 ; Ivanov et al. 2016a , b ). (Appendix Table  6 gives an overview and a categorization of the main papers focusing on the phenonmenon and their contribution).

Table 6

Contribution of literature on the ripple effect

Research on papers that focus on the ripple effect is dominated by the performance analysis of disruptions probabilities, especially for supplier failure. There is an urge for studies to explore other characteristics too by applying new modelling approaches with real company data and visualization techniques (Dolgui et al. 2018 ; Kinra et al. 2019 ). Forward and backward propagation analysis with the use of Bayesian networks and inclusion of the dynamic recovery time and cost by applying multi-objective stochastic optimization and agent-based models are some of the approaches that can be tried out (Hosseini et al. 2019a ).

Cost–benefit analysis of supply chain resilience

Since disruption implies serious commercial costs, the mechanisms for resilience, response and recovery are of vital importance to all SC echelons. An approach to reducing the costs of disturbance events is to highly motivate the managers to implement risk mitigation programs in the firm and engage in knowledge development activities (Cantor et al. 2014 ). Therefore, SCs should be protected in anticipation of disruptions by means of mitigation actions such as having safety stock, capacity reservations, backup sources and other methods, which nevertheless raise the level of management complexity and end-up being costly solutions themselves, especially if no disruption happens (Ivanov et al. 2019 ). So, resilient SC designs result in costly systems, which could negatively influence SC’s financial performance. To overcome the resulted costs, an efficient combination of resilient elements must be implemented, such as structural variety and complexity reduction, process and resource utilization flexibility and non-expensive parametric redundancy together with decision-support systems for SCs (Ivanov et al. 2019 ). Nevertheless, researchers have come to the conclusion that the cost for building resilience by using slack resources and visibility is smaller than the cost of SC disruptions (Jabbarzadeh et al. 2018 ).

Unfortunately, cost–benefit analysis (CBA) is not common in studies that present SC control models (Ivanov et al. 2019 ). The beneficial portion of the CBA can be modelled via the reduction of the disruption risk by a given percentage or its incurring costs, the shortening of the period of the disruption impact or via sustaining the service level (Namdar et al. 2018 ). On the other hand, although the cost of risk mitigation is considered visible (e.g. performance measures include fixed and variable costs, disruption costs, recovery cost), its accurate calculation is made difficult by the fact that recovery costs are generated by the adoption of a combination of proactive and reactive policies while cost analysis can also be extended to the operative losses and long-term future impact of deviation and recovery (Ivanov et al. 2017 ).

Nevertheless, there are many studies in the literature that, in their modeling approach, incorporate in the objective function the cost element and then by running what-if scenarios can measure the impact of certain policies and the overall benefit. For example, a study (Mori et al. 2014 ) developed a risk simulator for a multi-tier supply chain to evaluate the cost of retailer’s decentralized ordering and the effect of risk mitigation, identifying the cost–benefit relationship. Another study used a MIP which enables what-if analyses of cost and performance trade-off options in the SC (Das and Lashkari 2015 ).

Therefore, the use of quantitative models are viable methods for testing ways of minimizing costs of disruptions and contributing to the responsiveness and flexibility of the entire SC. Another identified way is for companies to choose to invest in social responsibility in order to balance disruption costs and resilience planning. Even though investment in corporate social responsibility activities could bring more cost to the company, it is also capable of increasing profit and reducing risk by decreasing production inefficiencies and increasing sales, access to capital and new markets (Cruz 2009 ). In line with this, it is the firm’s investment in good communication infrastructure, with the help of professionally qualified marketing agencies, that help problems with demand risks (e.g. demand decline) be mitigated (Diabat et al. 2012 ) or the implementation of pre-disaster/pre-disruption defense measures, such as insurance purchasing (Song and Du 2017 ). In any of these cases top management commitment is essential for building robust SC connectivity and information sharing systems to accomplish efficient SC integration (Shibin et al. 2017 )

Popular IT tools for resilience and response to disruptions

Modeling methods paired together with digitization enabled the development of tools that have led to many interesting applications for aiding SCs in general and SC resilience and real-time response to disruptions in specific. Many papers in our database offer very interesting overviews of digital technologies and their impact in mitigating disruption risks in the SC.

Computerized planning systems tools, such as materials requirements planning, manufacturing resource planning and enterprise resource planning (ERP) were the first software to help with the scheduling of operations and timely rescheduling in the case of disruptions and the retrieval of enterprise data from a single access point for informed decision-making (Baryannis et al. 2019a , b ), especially in cases of emergency interventions. Moreover, flexible manufacturing systems with sensors and advanced robots for more precise, reliable and easily adaptable production processes; automated guided vehicles and automated tracking and tracing technologies for safe, accurate and fast fulfillment of orders from wholesalers; radio frequency identification (RFID) for inventory control; geographic positioning systems (GPS) for timely and less costly distribution of goods are all technologies that have highly been adopted in the last decades and have greatly aided the SCs and reduced their response time, especially with their real-time capabilities for fast implementation of contingency plans (Blackhurst et al. 2005 ).

Then, the Internet of Things (IoT) have taken these technologies a step forward. The IOT is a dynamic network infrastructure with self-configuring capabilities of interoperable physical devices (Things), such as wireless sensors, smart devices, RFID chips, GPS, which can monitor, report and exchange data using intelligent interfaces seamlessly integrated into the information (Wi-Fi or data) network (Kranenburg 2008 ). The IOT can effectively track and authenticate products and shipments and inform on the location of goods, their storage condition and their time of arrival. Enhanced with augmented reality, which adds digital elements to a live view by using a camera, the IOT combines the real with the virtual world. A few examples of the uses of augmented reality in SCs are: the easier navigation of workers or tracing systems in the warehouse with the help of a graphic overlay of the space and its products, the reduction in the searching time of courier drivers for a box in the truck for the next delivery with a graphic overlay of the initial loading of products in the truck, informing the customers in real-time about prices and stock availability of items on the shelves by incorporating virtual labels viewable from smartphone cameras or google glasses. Like this, IoT and augmented reality technologies offer SC visibility and traceability, sending early warnings of internal and external disruptions that require attention, reducing uncertainty and enhancing effective internal operations and collaboration among all SC players (Ben-Daya, Hassini, & Bahroun, 2019 ).

Moreover, Industry 4.0, 3D printing, big data analytics (BDA), as well as blockchain also constitute tools of the new era that quickly find their way into the business world.

With the help of the IOT, Industry 4.0 is the smart factory of cyber-physical systems, like internet-connected workstations, conveyors and robotics, which autonomously control and monitor the route of products in the assembly line offering customized configuration (Katsaliaki and Mustafee 2019 ). Hence, Industry 4.0 enables the production of customized goods at the cost of mass production, with shorter lead times and better capacity utilization. Cost risks are minimized while higher market flexibility and responsiveness to customers is offered with customized products and risk diversification (Ivanov et al. 2019 ). On the other hand, 3D printing (additive manufacturing) builds a 3D object from a computer-aided design model by sequentially adding material layer by layer. This method of production, which progressively broadens the range of products it offers, constitutes a disruptive technology to the traditional SC configuration as products can be manufactured to SC echelons closer to the customer and even at the retailer’s site. The shorter lead times and the reduction in demand risks as manufacturing comes closer to the customer are the main contributions made by this technology (Ivanov et al. 2019 ) to aid in the reduction of disruptions.

With recent revolutions in technology, data is generated much quicker from different sources and technologies are in place capable for their storage, categorization and analysis. Statistical analysis and reliability become stronger with the increased data volume and the high number of factors for analysis. Therefore, predictive methods have better explanatory power (Gunasekaran et al. 2016 ) and together with machine learning algorithms, artificial intelligence (AI) that allows computers to evolve behaviors based on empirical data (Chen and Zhang 2014 ) offer answers to demanding questions and what-if scenarios through prescriptive analytics. Big data analytics and machine learning methods came to the foreground as enablers of value creation from massive data, offering new competitive advantages to companies (Chen et al. 2012 ). They have increased SC data visibility and data transparency and can reduce information disruption risks and behavioral uncertainty as well as demand risks through predictability (Baryannis et al. 2019a , b ; Brintrup et al. 2019 ); all of which are positively linked to SC resilience.

Blockchain technology is a distributed database of records or shared public/private ledgers of all digital events that have been executed and shared among participating blockchain agents (Crosby et al. 2016 ). Blockchains can be considered a disruptive technology for the general management of SCs, specifically in the field of suppliers’ contracts. Distributed contract collaboration platforms using blockchain technology could guarantee the traceability and authenticity of information, along with smart contracts (computer protocols which digitally verify or enforce the agreed terms between the members of a contract without third parties’ involvement). These transactions are trackable and irreversible and validate transactions (Saberi et al. 2019 ). This brings a new era in SCs and a remedy to fraudulent acts and security risks (Wang et al. 2019 ).

Especially for the ripple effect, information technology can have a very positive mitigation influence. RFID technology can offer feedback control and SC event management systems can communicate disruptions to the other SC tiers and assist in revising and adapting schedules. For example, Resilience360 at DHL is a cloud-based analytics platform for managing disruption risks by mapping end-to-end SC partners, building risk profiles, identifying critical hotspots in order to initiate mitigation actions and alert in near-real time mode about events that could possibly disrupt the SC (Dolgui et al. 2018 ).

Future research agenda

Following a content analysis of selective papers on SC disruptions, future directions have been identified which we hope will inspire new scholars to establish their research agenda in this field. The selection of the research topics was made primarily on the grounds of managerial applicability without diminishing the importance of theory advancements. The great majority of the papers include a shorter or longer future research section but, in many cases, this is targeted to the advancement of their modelling technique, of their data collection approach, or the hypothesis testing which are out of the scope of this study’s agenda. Below we take a practical approach of the field and we try to map research on SC disruptions especially with regards to the use of new tools and resilience approaches. There is a list of 34 research directions organized in seven themes. These relate to research about (a) effective resilience strategies, (b) SC disruptions in specific sectors, (c) a special focus on human resources management (HRM) and behavioral analysis, (d) modelling approaches with an emphasis on the ripple effect, e) combination of modeling approaches with new information technologies (IT), f) research about the implementation of these new IT/digital technologies and g) research driven by the recent enormous disruptions due to the COVID19 pandemic. It is notable that about 1/3rd of these topics are related to the use of digital technologies which greatly enhance modeling capabilities and decision-making to tackle and resist SC disruptions. Each research direction begins with a short title in bold, depicting its aim and its methodology approach.

Resilience strategies

• Resilience Strategies—Multi-method (modelling, survey) Which strategy or combination of strategies: redundancy (excess inventory, spare capacity, multiple sourcing), flexibility (flexible production systems and distribution channels, multi-skilled workforce), collaborative planning (information-sharing, joint relationship efforts, decision synchronization), contingency planning (back-up suppliers-transportation modes) is most effective for building resilient SCs to disruption risks? (Centobelli et al. 2019 )
• Resilience Strategies—Survey, case study Is it true that SCs that adopt a flexibility strategy utilize a higher degree of information sharing and collaboration through higher ICT utilization in comparison to adopting a redundant strategy? Is it true that redundant strategies are more expensive to implement (need more capital and operating cost) than flexibility strategies? (Nakano & Lau, 2020 ).
• Resilience Strategies—Survey What is the effect and relative importance of specific disruptions (such as, ineffective suppliers’ management, lack of information sharing and risk assessment) so managers can prioritize the allocation of resources to tackle them? (Centobelli et al. 2019 ).
• Risk metrics—Survey What are the most effective, as opposed to the most used SC risk metrics (performance measurement system), among recovery time, safety stock, customer service level, total cost and others, for managers to focus on and under which circumstances (e.g. ripple effect)? (Dolgui et al. 2018 ).

Certain sectors of SC disruptions’ application areas

• (5) Military—Mixed methods Exploring effective disaster resilience approaches for the military (Centobelli et al. 2019 ).
• (6) Perishable products—Modelling Modelling disruptions in the SC of perishable products and their limited resilience strategies as redundancy strategies may not be an option (freshness, write-offs) but others may be, such as customer segmentation by requirements for freshness and product batching (Dolgui et al. 2018 ).
• (7) Food—Mixed methods Analysis of the use of the IoT and other recent technologies for preventing avoidable food waste generation, food safety and efficiency throughout the food SC (Ben-Daya et al. 2019 ).
• (8) Information Systems disruptions—Mixed methods Research on disruptions in the information systems and the networked cloud-based digital SC environment (Dolgui et al. 2018 ).
• (9) Reverse logistics—Modelling Studying the disruptions that take place in the reverse logistics flows of SCs (e.g. unavailability/limited space in the warehouse that stores the collected recyclable materials) for analyzing their impact to the overall SC performance and identifying effective response and mitigation strategies (Dolgui et al. 2018 ).
• (10) Humanitarian aid—Modelling Analysis of the fair allocation of the limited resources in situations of severe regional disasters which usually simultaneously lead to humanitarian emergency and industrial crisis, in order to balance human life rescue, everyday life and the recovery of the industrial sector (Dolgui et al. 2018 ).
• (11) Behavioral analysis—Modelling Employing agent-based simulation to model managerial decisions subject to individual risk perceptions, such as collaboration issues (trust and information sharing) and SC risk management culture (leadership and risk-averse behavior) (Dolgui et al. 2018 ).
• (12) Behavioral analysis—Mixed methods Analysis of the patterns of human behavior when managers are faced with real data or the dashboards of big data and visualization/cognitive computing approaches (that their development mechanisms may or may not be trusted) and the nature of their governance and decision-making, especially when related decision refer to disasters causing humanitarian crises (de Oliveira and Handfield, 2019 ).
• (13) Training—Survey Analyzing ways that offer successful training to company staff in the related departments to effectively cope with SC disruptions, which create a stressful environment and require preparedness (Dolgui et al. 2018 ).

Modelling methods about SC disruptions

• (14) Ripple effect—Multiple models Modelling SC disruptions by considering the dynamic recovery time/cost. More modelling approaches are needed for capturing the disruption propagation and SC design survivability and for evaluating recovery policies and their implementation (Dolgui et al. 2018 ).
• (15) Ripple effect—Stochastic modelling Development of two-stage stochastic models with the first-stage objective function to minimize the traditional SC cost (procurement, supplier evaluation, transportation costs) and the second-stage objective function to measure the SC resilience under all possible disruption scenarios (Hosseini et al. 2019a ).
• (16) Ripple effect—Model validation Practical validation of the simulation and optimization models for preventing and mitigating the ripple effect in the SC with real company data, such as coordinated contingency plans (Dolgui et al. 2018 ).
• (17) Ripple effect—Model visualization Adding visualizing features to the simulation models of the ripple effect (Dolgui et al. 2018 ).
• (18) Ripple effect—Bayesian Networks Forward and backward propagation analysis using Bayesian Networks (a unique capability of this method) by entering any number of disruption observations to analyze the ripple effect in complex supply networks with a large number of nodes and links (Hosseini et al. 2019a ).
• (19) Resilience Vs Sustainability—Multi-objective stochastic optimization Developing multi-objective stochastic optimization models capable of making trade-offs between resilience (that requires capacity buffer, surplus inventory, multiple sourcing) and sustainability decisions (which on the contrary requires less redundancy) (Hosseini et al. 2019a ).
• (20) Large supply networks—Modelling Toolbox Development of a common language to facilitate the development of reference models for supply networks with a standardized toolbox of supply network representations and identification of suitable methods for analyzing risks in complex supply networks (Bier et al. 2019 ) and will accelerate comprehension and execution.

Hybrid models combined with IT

• (21) Predicting SC disruptions—Prediction and machine learning algorithms Development of prediction models and adaptation of SC disruptions management practices with the use of prediction algorithms and machine learning techniques such as unsupervised learning algorithms which can be used to mine SC data, identify patterns related to certain risks and be trained to recognize risk patterns and their incurring probability (Baryannis et al. 2019a , b ).
• (22) Risk management practices—Mathematical programming, Multi agent systems, Semantic reasoning, Machine learning techniques and BDA Development of hybrid models to analyze risk management practices by combining mathematical programming (effective in modelling highly complex systems for SC risk avoidance and mitigation), with agent-based approaches, BDA and machine learning techniques (capable of automated decision-making by creating automated rule-based reasoning and learning and handling of big and variable data) in order to select an appropriate response strategy (Baryannis et al. 2019a , b ; Hosseini et al. 2019a ).
• (23) Digital SC twin—Simulation, optimization and BDA Analysis of the combination of simulation, optimization and data analytics to create a digital SC twin – a model that represents the state of the network in real-time (Ivanov et al. 2019 ) offering end-to-end SC visibility when all players are included. A disruption in a SC echelon can be reported by a risk data monitoring tool and transmitted to the simulation model. The simulation model in the digital twin can measure disruption propagation and impact, test recovery policies and adapt the contingency plans based on the situation (e.g. considering back-up routes on-the-spot) (Hosseini et al. 2019a ; Ivanov et al. 2019 ).
• (24) IoT – Modelling Modelling SC problems (procurement, production planning, inventory management, quality, maintenance) in an IoT environment. Decision-making in an IoT context requires new tools and models to exploit the new environment, such as big data generated from sensors and connected things (Ben-Daya et al. 2019 ).
• (25) Resilience strategies—BDA and AI Analysis of how BDA and AI techniques can help with SC disruptions and the mechanics for achieving it. For example in global SCs where sales volumes and product variability are high and disperse, the analysis of SC big data (sales, buying behavior, product inventory, transportation channels, distribution frequency and production rates) can reduce demand uncertainty and sensor data in distribution centers which can mitigate logistics risks and increase visibility and trust among suppliers (Baryannis et al. 2019a , b ). Some evidence also exists (Griffith et al. 2019 ) that the BDA and AI technologies can assist visibility (e.g. with open-source imagery tools and analytic mapping tools) in disaster relief chains and humanitarian logistics but how this can be done is a question that requires further investigation (Dubey et al. 2019a , b , c ).
• (26) Identification of suppliers based on proximity—machine learning algorithm Development of a learning algorithm to deduce location-based relationships of suppliers by identifying the localization of suppliers from public data sources (Brintrup et al. 2019 ).
• (27) Large supply chain networks—BDA Analysis of large-scale complex supply networks and their risks (as in their majority researchers illustrate their contributions using small cases) with the use of current digital technologies which facilitate collection of big data from across the SC. Having such test datasets of realistic size and complexity for SCs would result in more empirical insights (Bier et al. 2019 ).

Digital technologies

• (28) Blockchain—Survey, case study Testing the hypothesis that implementing blockchain technology in SCs decreases opportunistic behavior of SC players like subtle violation of agreements and concealing of critical information due to the transparency, security, and auditability that the technology promotes (Saberi et al. 2019 ).
• (29) Blockchain—Survey, case study Supply chain governance structure characteristics need to be evaluated for effectiveness in understanding blockchain-based SCs where no central authority is responsible for information management and validation. Analysis is required regarding who and what governs transactions, rules, and policies. Will operational relationships improve their outcome due to the features of blockchain technology, which do not require strategic formal coordination (Saberi et al. 2019 )?
• (30) IoT—Survey, case study Provision of guidance for IoT adoption from companies as to which process and where in the SC they should deploy IoT, given that SC partners may be at different stages of the IoT implementation (Ben-Daya et al. 2019 ).

Disease outbreaks/pandemics/COVID19

• (31) Pandemic—Mixed Methods Measuring how the Covid-19 or other pandemics affect firms, employees, consumers, and markets for formulating effective policy responses to the challenges posed by the crisis (Hassan et al. 2020 ).
• (32) Pandemic—Modelling Development of a contingency plan framework with operating policies for specific SCs deriving from the analysis of modeling techniques that simulate disease breakouts, as unlike other disruption risks, epidemic outbreaks start small but spread fast and disperse over many geographic regions creating increased uncertainty (Ivanov 2020a ). A special case are products with high demand during disease outbreaks such as medical face masks, sanitizers, etc. Evaluation of the SC behaviors of adaptation, digitalization, preparedness, recovery, ripple effect, and sustainability during and after pandemics (Queiroz et al. 2020 ).
• (33) Pandemic—Modelling, case study How do changing regulations due to the pandemic (lockdowns, changing working patterns, etc.) impact productivity throughout the supply chain? How do dark (fully automated) warehouses and other operational solutions for contactless or zero interaction among employees or employees with customers impact firms’ performance, employees’ work environments and customer experience? (Mollenkopf et al. 2020 )
• (34) Pandemic/digital technologies—Modelling, case study Investigation of the utilization of digital technologies, such as digital SC twins, omnichannel, additive and digital manufacturing, to support decision-making in long-term disruptions caused by pandemic outbreaks (Ivanov and Dolgui 2020 ).

In this study, we aimed to present an overview of the literature in order to provide a picture of SC disturbances and resilience methods. We first mapped all relevant studies and provided a profile of the popular articles. The second part of the paper, through content analysis, presented the knowledge offered in selected articles in a comprehensive and narrative way. Both methods concluded in a synthesis of knowledge about SC disruptions and resilience methods which we believe are useful to researchers and managers alike.

Research implications

Our study has numerous implications for researchers. First, it provides a useful introduction to the field through the profiling study which focuses on the key literature. It shows that publications about SC disruptions started appearing after 2004 but the field has matured fast and in these 15-20 years is populated by many studies which explain and evaluate the impact of the adoption of certain response strategies to SC disruptions and risks. However, this is not to say that the field has been over-researched but on the contrary it has become as hot as ever due to the recent pandemic of COVID19 and the enormous disruptions that has caused to the whole world. Therefore, more research is required for specific and new types of disruptions but also in general for all types as innovative ways of building resilience are created by utilizing modelling techniques and new digital technologies. Two popular review studies on SC disruptions and risks are (Kleindorfer and Saad 2005 ; Tang 2006 ) and two more trending papers deal with Industry 4.0 (Ivanov et al. 2019 ) and blockchain (Saberi et al. 2019 ).

As SC disruptions occur in greater frequency and intensity (Zsidisin et al. 2016 ), we hierarchized them based on the literature by type, impact and occurrence, starting from the catastrophic events of low frequency and high impact and concluding with the infrastructural events of high occurrence but lower impact. Although the urge so far has been to research high occurrence but lower impact SC disruptions which cumulative cause a nonnegligible and continuous problem to SCs (Zsidisin et al. 2016 ), the new unforeseen pandemic seems to rush research towards the other direction as already in 2020 a number of papers have been published in the particular topic, e.g.(Ivanov 2020a ; Queiroz et al. 2020 ). Our study also examined the growing research on the ripple/snowball effect of perturbations originating in a localized point which amplifies consequences for the downstream SC echelons, as opposed to the bullwhip effect which impacts the SC upstream. The realizations of the ripple effect consequences is another reason for more research in SC disruptions with models that take into considerations many echelons across the SC.

Moreover, the study presents an analysis supported with examples of quantitative approaches which were used to model the SCs based on risk factors, their impacts, mitigation tactics’ costs and benefits and what-if scenarios for testing certain strategies (Das and Lashkari 2015 ). Optimization is the mathematical method most often used for this purpose (stochastic programing, mixed-integer programing, multi-objective programing) followed by simulation techniques (system dynamics, discrete-event simulation, agent-based model and Monte-Carlo simulations) that can handle more uncertainty and complexity. Statistical analysis, graph theory and game theory are also among the modeling methods that are distinguished in the papers of our review. Many models incorporate a function of cost to measure the impact of disruptions and provide a cost–benefit analysis of mitigation or resilience actions.

There is also an attempt to benefit, with regards to data promptness and accuracy, from the operability with new digital solutions (e.g. IOT, BDA, machine learning) to build real-time reconfigurable SC models based on the incurring disruption and knowledge that has been accumulated from past reactions. These trends call for new principles and models to support SCM and populate the future research agenda. Such promising methods for dynamic supply-chain models are Agent-based models, which are configurable distributed software components that continually realign goals and processes (Blackhurst et al. 2005 ). In the research agenda of SC disruptions and the ripple effect, notable is the call for the development of quantitative decision-making models coupled with the new digital technologies’ capabilities including blockchain contracts. Another area is the behavioral analysis of managers who interpret the automated generated knowledge and the importance of receiving training for tackling SC disruptions and increasing the level of preparedness. The study offers a long list of topics in the field that require immediate investigation from interested researchers. While the research dealing with disease outbreaks from the humanitarian logistics aspect provides a substantial body of knowledge, e.g. (Banomyong et al. 2019 ; Dubey et al. 2019a , b , c ), the literature on analyzing the impact of pandemics from a business point of view is still limited (Ivanov 2020a ) but growing fast. Therefore a special focus is required with regards to SC disruptions caused due to pandemics, such as COVID19. New and fast changing regulations for lockdowns, transport guidelines and employees’ working conditions call for urgent understanding and evaluation of their effect in the SCs and identification of appropriate ways to react and adapt with the minimum possible distraction.

Managerial implications

The review part of this study has also identified several interesting points with managerial applicability.

The literature brings up several recovery and resilient strategies and methods that firms choose to adopt either in isolation or in coordination with the other SC echelons. The aim should be to build resilience to reduce or avoid disruptions (Hosseini et al. 2019a ). Popular resilience strategies are redundancy building through safety stock, capacity reservations and multiple sourcing but more effective is considered the flexibility acquisition strategy through alternative suppliers, contingency plans and the adoption of ICT for information access, tracing, monitoring, warning, reporting and prediction of SC risk for fast response and rescheduling of operations (Centobelli et al. 2019 ). Moreover, information-sharing, collaborative communication with the other SC echelons, joint relationship efforts from the product/service design until its delivery and the reverse logistics flow and decision synchronization utilizing ICT capabilities (Nakano and Lau 2020 ) are all cost-effective ways for building resilience to SC disruptions and minimizing the occurrences and the duration of man-made disruptions.

Digital technologies have also played a crucial role, maybe the most important of all, in the improvement of SC performance enabling new capabilities of real-time reconfigurations and fast response and implementation of emergency plans in cases of disruptions. While the individual contributors (e.g. robots, sensors, RFID, agents, modular factories, etc.) are not new, they are becoming more approachable and companies more receptive to using them to stay competitive. More recent technologies, such as the IOT, augmented reality, Industry 4.0, 3D printing, BDA, artificial intelligence and blockchain are all examples of tools that are progressively changing the way SCs are organized. The level of accuracy, transparency, traceability and flexibility is immensely growing, transforming SCs to systems which continuously evolve and can be reconfigured on demand. Involvement of such technologies, which are often characterized as disruptive to the traditional SC model, have the potential to shrink SCs, and also produce better quality, reduce product development times, increase customized offerings to customers (Viswanadham 2018 ) and be more prepared for timely reactions to perturbations. Applicability studies of these technologies in the business environment are part of the future agenda. More importantly at the current situation of the rapid-spreading pandemic which has caused so many SC disruptions the whole business world is changing the business model by fast-tracking digital transformation to increase chances of survival.

Natural disasters and disease outbreaks consequences can be mitigated through resilient management of the relief SC operation. Development of trust between humanitarian organisations and other partners/stakeholders is necessary for coping with complex tasks during disaster relief and following standard code of ethics (Awasthy et al. 2019 ). Therefore, a focus on metrics and performance measurement such as delivery time, number of saved lives, the quantity of distributed relief items, and operations’ costs is essential in order to empower the effectiveness and long-term relationships of the humanitarian aids and relief SCs (Baharmand et al. 2019 ). Foremost, research emphasizes the development of flexible resiliency strategies with assisting technological solutions, such as BDA and AI technologies offering open-source imagery tools and analytic mapping tools in humanitarian logistics, for improving responsiveness through information and materials pipeline visibility and increased effectiveness of processes through better management of the scene (Griffith et al. 2019 ). Flexible networks with prompt rescheduling functions can achieve the required balance between speed and quality of the survival processes.

Conclusions

IT professionals continually develop new applications with big data capabilities to help stakeholders increase value (Galetsi et al. 2019 ), thus there are expectations for the allocation of higher budgets towards IT infrastructure and BDA experts (Galetsi et al. 2020 ). Investing in appropriate technology and quality information sharing helps with SC visibility, enhances trust and cooperation among SC partners and eventually leads to a more resilient SC (Dubey et al. 2019a , b , c ; Kamalahmadi and Mellat-Parast 2016 ) against disruptive events. This should be the focus of the top administration of each firm alone and in collaboration with the other echelons of their SC. Supply chains should embrace the TQM (total quality management) philosophy of prevention, as studies have shown that building resilience is less costly than recovering from problems (Jabbarzadeh et al. 2018 ). Yet, it is impossible to completely avoid disruption and attention should also be drawn to the recovery policies regardless of what caused the disruption. Therefore, human-driven adaptation first, followed by computer-driven adaptation, is needed to change SC plans, inventory policies and schedules to achieve the desired performance, which is the precondition of stability and robustness (Ivanov et al. 2013 ). As SCs become more global and complex, the impact of any disruption intensifies. The answer is building resilience by incorporating longer term partnerships, government policy that enables flexibility, an IT approach that fosters business continuity (Wright 2013 ) and a culture of readiness in contingency actions.

See Tables  3 , ​ ,4, 4 , ​ ,5, 5 , ​ ,6 6 .

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Contributor Information

K. Katsaliaki, Email: [email protected] .

P. Galetsi, Email: [email protected] .

S. Kumar, Email: ude.samohtts@ramuks .

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Supply Chain Resilience: A Decade of Evolvement

• First Online: 25 September 2022

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• Alexandra Anderluh 6 &
• Michael Herburger 7 , 8  

Part of the book series: Springer Series in Supply Chain Management ((SSSCM,volume 17))

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Supply chain resilience is a topic that has been gaining increasing importance over the last decade. During these few years, resilience in the field of supply chains has already undergone a change of understanding reaching from the ability of a supply chain to get back in the original state after a disruption via the ability to provide system functions in the face of shocks and stresses to the ability to persist, adapt or transform when facing a significant change. In addition, despite the short research period, numerous scientific publications tackling the resilience of supply chains can already be found. Therefore, we provide a classification of relevant papers found by a systematic literature review. The classification focuses on the type of disruption, the research methods used, and the sectors addressed. Furthermore, we point out research gaps that can serve as a basis for further research in supply chain resilience.

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Anderluh, A., Herburger, M. (2022). Supply Chain Resilience: A Decade of Evolvement. In: Kummer, S., Wakolbinger, T., Novoszel, L., Geske, A.M. (eds) Supply Chain Resilience. Springer Series in Supply Chain Management, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-030-95401-7_2

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Supply chains: To build resilience, manage proactively

No one would dispute that the COVID-19 pandemic created significant disruption to global supply chains. Nothing like this had happened in decades, and many operators relied on strategies that only partly addressed their challenges . Then came the Russian invasion of Ukraine, which has caused the greatest humanitarian crisis in Europe since the Second World War. Already, thousands of lives have been lost, and millions have been displaced—a tragedy with consequences that will unfold for years to come.

About the authors

This article is a collaborative effort by Knut Alicke , Cengiz Bayazit, Tim Beckhoff, Tacy Foster , and Mihir Mysore , representing views from McKinsey’s Operations and Risk Management practices.

The invasion compounded supply chain troubles in critical sectors, including agriculture, automotive, energy, and food. As the frequency and magnitude of the disruptions increased, applying ad hoc remedies to restore predictability to a system premised on ever-increasing cost optimization became more difficult. To restore the needed resilience , supply chain operators may need to consider a range of options, including structural reform.

So with good reason, the rapid decay of a decades-old model of supply chain reliability and efficiency is a key feature of CEO agendas. Over the course of a decade, companies may face disruptions that erase half a year’s profits or more . For companies in most sectors, a single prolonged shock to production could wipe out 30 to 50 percent of one year’s earnings before interest, taxes, and depreciation. Clogged ports, expensive cargo capacity, and emergency shipments became prevalent during the COVID-19 pandemic. Since then, the conflict in Ukraine has also contributed to product-line closures, transport delays, and spiraling input costs. These issues have contributed to large increases in commodity prices and a troublesome spike in inflation and in expectations for higher prices around the globe .

Yet these immediate effects are only part of the story. In fact, they may be overtaken in the long term by slower-moving but more permanent effects on supply chains occurring beneath the surface. Supply chain leaders could face challenges with short-term shocks while installing the building blocks of deeper structural reform. Nonetheless, structural reform may be the only way for leaders to restore the resilience that companies depend on from their supply chains, as is evident from several of the short- and longer-term implications of the disruptions.

Key export categories are suffering immediate supply shocks

Today, five categories of exports—agricultural products, chemicals, manufacturing, metals, and oil and gas—face three immediate challenges from the invasion of Ukraine:

• reduced production or shutdowns at many manufacturing plants
• lower purchases of goods sourced from Russia, because of economic sanctions or self-imposed sanctioning by companies
• logistics disruptions across air cargo, ports, road and rail, and shipping

These challenges have had an impact on product lines: for example, multiple automotive companies reduced production in Germany because wire-harness suppliers shut down. Transport delays and spiraling input costs have become more frequent. These immediate effects have spread across export sectors, but the impact appears to be highest for the automotive, chemicals, energy, food and agriculture, and travel and logistics sectors (exhibit). Some particular effects deserve to be highlighted.

First, since the conflict began, many companies have announced that they are exiting operations in Russia or refusing to carry Russian goods. This level of self-imposed sanctioning is creating several effects, including greater unpredictability, since disruptions are harder to track and estimate.

Second, while many business leaders worry about rising inflation, they are also concerned about the unavailability of critical supply chain inputs because such shortfalls can shut down products and revenues. These effects will likely have a larger impact on companies than inflation but are harder to gauge in many supply chains and can occur quickly.

Finally, many such effects are still rippling through supply chains, and their full impact may not become obvious for a few months. Some companies, for instance, have safety stocks for exported materials. As those stocks get depleted, disruptions may become more frequent.

These immediate effects are challenging. But leaders may also need to focus on the significant and long-lasting problems developing below the surface for supply chain operators.

The longer-term threat to demand and critical-materials volume

As we have seen during the war in Ukraine , supply chain operators face several emerging developments that could pose a larger, more long-lasting challenge in the medium term. For example, an increased focus, particularly in Europe, on securing food, energy, and other critical materials will probably have a lasting effect on demand supply chains. Stockpiling items may provide a temporary buffer, but eventually, a guaranteed source of supply—driving up costs—may be needed.

What’s more, lockdowns during the COVID-19 pandemic, which contributed to shifts in consumer spending from services to products, are partly responsible for the current supply chain challenge. As demand begins shifting back to services, demand for products may decline. That could ease some of the pressure—but also adds to the overall uncertainty.

Lastly, demand for suppliers with lower carbon footprints or greener alternatives to existing products could rise as a result of the March 2022 US Securities and Exchange Commission ruling on carbon disclosures 1 On March 21, 2022, the US Securities and Exchange Commission proposed rule changes that would require registrants to include certain climate-related disclosures in their registration statements and periodic reports. This information would include greenhouse-gas emissions, a commonly used metric to assess a registrant’s exposure to climate risks. (among other announcements), as well as Europe’s continued focus on sustainability. Suppliers may have to shift their inventory management strategies in the coming years.

Taken together, such factors will be a durable underlying source of supply chain disruptions , which will evolve over time. As the impact of the conflict in Ukraine continues to develop, these problems may even get worse. Therefore, one consideration for business leaders is how to stabilize the immediate disruptions while building resilience against future ones.

Three steps to optimal resilience

Short-term solutions could work at a time when supply chains were more predictable than they are today. Preparing for long-term uncertainty and possible upheaval may encourage companies to build resilience into their supply chains. This process could evolve in three stages:

Firefighting

One potential response to supply chain problems is to focus on short-term, day-to-day actions, such as expedited delivery services to meet demand or speeding up production by purchasing components on an emergency basis. These tactics can help to some degree, particularly for identifying previously overlooked supply chain gaps. However, they don’t build resilience and aren’t fundamentally new, so overstretched suppliers may be reluctant to use them.

In such cases, CEOs could consider implementing cross-silo efforts that ensure an agile response to fast-moving events. They could also exhort teams and suppliers to not only adopt appropriate short-term measures but also stay the course for the more difficult long-term reforms, which begin during the second stage.

Integrating and streamlining operations

Designing an integrated nerve center.

• Nerve center organization: Outline the response, with clear owners and accountabilities.
• Decision authority: Clarify any changes in decision authority needed to guide response.

Operating cadence

• Weekly meeting calendar: Set up key meetings to ensure an integrated response and connections across multiple efforts.

Decision-enabling tools

• Situation report: Create a regular memo that details the current situation, how it may evolve, and the immediate decisions needed.
• Trigger-based actions: Proactively define strategic actions that may be needed as the situation evolves.
• Initiative tracking: Describe the status of cross-silo initiatives that are relevant to the effort.

Early warning system

• Situational awareness: Cover any relevant developments and broader economic and social factors.
• Supply chain disruption monitor: Serve as a single source of truth for supply chain disruptions, covering events from source to end market.
• Sanctions compliance monitoring: Track the latest sanctions and actions needed for compliance from suppliers, partners, and customers.
• Cybersecurity monitor: Ensure readiness for potential attacks and implement advanced threat detection.

Source: McKinsey Resilient Operations Center

In this stage, three actions can be critical to building resilient supply chains: creating a nerve center for the supply chain, simulating and planning for extreme disruptions, and reevaluating just-in-time strategies.

Create a nerve center to consolidate organizational responses. A cross-functional team for such a nerve center coordinates and manages proactive responses to issues that might range from caring for distressed colleagues to testing financial stability under a range of scenarios. The nerve center could be organized under four categories: people, operating cadence, decision-enabling tools, and an early-warning system, which could, for example, signal potential political developments or cyberthreats, as well as compliance or regulatory issues (see sidebar “Designing an integrated nerve center”).

Simulate and plan for extreme supply-and-demand disruptions. This second category of actions involves ordering components earlier than usual and allowing extra time for delivery; accounting for the higher cost of energy, materials, and transportation; and checking inventories of critical materials to reprioritize production should shortages seem inevitable. If logistics disruptions are likely, try to get capacity on alternative routes. Another tactic to avoid building up excess inventory is simulating the effects of regional demand shifts on production. Examine the risks in supplier networks, labor, manufacturing, and delivery to determine if any part of the value chain is exposed to internal or external disruptions. Set up controls to minimize their effects.

Reevaluate just-in-time inventory strategies. If a crisis on the scale of the pandemic occurs, the absence of a back stock of inventory or materials can seriously threaten supply chains. Many of today’s most pressing supply shortages (semiconductors, for example) occur in supplier subtiers where manufacturers have little visibility. To achieve transparency beyond the first tier, companies could work to identify suppliers from spending data, N-tier mapping, or both. Prioritize them by their importance to the business and assess their vulnerability. Some potential measures to mitigate risk include finding new suppliers, redesigning networks, resetting inventory targets, keeping safety stocks, and sourcing locally or regionally.

Achieving structural resilience

Creating long-term resilience in a high-tech supply chain: a case study.

After experiencing significant supply chain disruptions from COVID-19, a global telecom company focused on going beyond building up inventory. In its efforts to develop end-to-end supply chain resilience, two areas took priority: changing supplier contracts to ensure maximum agility and transparency, and reducing the share of components sourced from any single supplier. The company already had dual suppliers for components but decided to go a step further by adding a production model using two different designs for the same products. This dual-source, dual-design strategy would provide the highest level of protection against raw-material shortages.

The next step was to evaluate the R&D outlay for the designs and to balance it with lower inventory-holding costs. The company conducted a pilot to test this approach and assess its feasibility for other products. It also drew up a sales model based on its exposure to the risks of the dual-design, dual-sourcing effort. In this way, the company developed the flexibility to expand its supplier base if necessary and to increase its sales volumes and gross margins.

CEOs and other top executives may focus on quick responses during a crisis but may also need to consider the difficult concern of building longer-term resilience. Transparency may be hard to attain. Diversifying the supplier base, though critical for resilience, is expensive. And the cost of keeping safety stocks on hand may be hard to justify if they are not used in several years. These issues are real and can make the task of building resilience in supply chains feel like wading through molasses, but leaders may have to continue to focus on them. (See sidebar “Creating long-term resilience in a high-tech supply chain: A case study,” to learn how one global telecom maker structured a strategy to protect itself from shortages of raw materials.)

Some ideas and proven techniques can help with the difficult work of building long-term supply chain resilience, such as the following:

Construct a ‘digital twin’ of the most critical parts of a supply chain. A digital twin is a virtual replica of a business’s operation that allows companies to simulate how a product, process, or service will perform before it is implemented in the real world. If building a digital twin isn’t feasible, two models could be constructed: one to estimate the current flow of Ukrainian or Russian commodities and materials that may be going into an organization’s products, and the other to show where a product originates in the value chain. This approach can help organizations pinpoint hidden suppliers or materials flows and expose previously invisible interdependencies.

Create and test ‘what if’ scenarios. Suppose you want to find out what would happen if the shift from rail to sea transport reduced the supply of vessels by 25 percent. One technique you may want to consider is building several what-if scenarios that can be tested quickly and then prioritizing and mitigating the parts of the supply chain that fail most often. It may seem daunting to create a large number of scenarios nearly continuously, at varying levels of detail and impact, but that is critical for this technique to provide insights. The vulnerabilities it reveals may make a big difference, but leaders shouldn’t expect any one scenario to play out.

Increase data sharing with suppliers. To minimize risk when sharing data, businesses could consider terms that require the disclosure of data under specific conditions. Even if data sharing is restricted, companies may be able to have clean teams share data with a third-party firm that analyzes the supply chain for weaknesses and provides recommendations.

Consider ringfencing a small part of the supply chain team. Charge this subgroup solely with building long-term resilience, not resolving day-to-day supply chain issues.

Tackling the medium-term challenge

One option to help mitigate longer-term, more permanent damage from supply chain disruptions is to maintain a strategic priority on customers. There are several reasons for this.

One option to help mitigate longer-term, more permanent damage from supply chain disruptions is to maintain a strategic priority on customers.

First, e-commerce, by itself, doesn’t necessarily promote positive outcomes. Our research shows that many retailers whose online sales increased during the COVID-19 pandemic also experienced pressure on supply chains and high fulfillment costs that eroded profitability. One avenue for success in e-commerce is capturing high-value demand at an acceptable margin , depending on product and business model.

Second, the global economy may slow down in the coming year. The United States, for example, is posting strong growth and job creation numbers, but indicators of slackening demand have appeared. Prices in several sectors are spiraling quickly. The US Federal Reserve has raised interest rates to curb rising inflation. 2 Scott Horsley, “The Fed raises interest rates by the most in over 20 years to fight inflation,” NPR, May 4, 2022. In the eurozone, many observers suggest that a recession may be possible, 3 John Kemp, “Global recession risks rise after Russia invades Ukraine,” Reuters, March 6, 2022. linked to several factors including the ongoing impact of the conflict in Ukraine.

Third, past economic downturns suggest that customers tend to stick with companies that stay closest to their core offerings. During the recession of 2008–09, for example, one company closed a number of stores but increased its investment in those that stayed open, catering especially to its core segment. By contrast, its competitor sought to use the recession to enter a segment that was not part of its historical core. The company that stayed with its core customers emerged from the downturn far stronger than its competitor and grew significantly in the postrecession years.

CEOs recognize that none of these actions come without costs and that it may be hard to count on visions of long-term resilience to pay for the investments required to achieve it. After the experience of the past two-plus years, chief executives may need to define the circumstances in which they think consumers would pay a premium to ensure the availability of goods. They could also consider exploring whether suppliers will accept discounts to help ensure demand for their products and absorb the costs through more productive operations. Perhaps the hardest task for CEOs could be convincing investors to accept resilience as the new table stakes and to change their view of expected risk-adjusted returns.

Knut Alicke is a partner in McKinsey’s Stuttgart office, Cengiz Bayazit is a partner in the Stamford office, Tim Beckhoff is a manager of solution delivery in the Munich office, Tacy Foster is a partner in the Charlotte office, and Mihir Mysore is a partner in the Houston office.

The authors wish to thank Edward Barriball and Yogesh Malik for their contributions to this article.

This article was edited by Rama Ramaswami, a senior editor in the Stamford office.

Russia’s invasion of Ukraine in February 2022 is having deep human, social, and economic impact across countries and sectors. The implications of the invasion are rapidly evolving and are inherently uncertain.

As a result, this document, and the data and analysis it sets out, should be treated as a best-efforts perspective at a specific point in time, which seeks to help inform discussion and decisions taken by leaders of relevant organizations. The document does not set out economic or geopolitical forecasts and should not be treated as doing so. It also does not provide legal analysis, including but not limited to legal advice on sanctions or export control issues.

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Supply Chain Management Thesis Topics- Top 30 Ideas

One of the most frequently asked question from SCMDOJO followers is, I am doing Supply Chain Management Masters from  Europe ,  UK  or  USA  and I need some Master Thesis ideas in Supply Chain?

Key academic research areas in SCM are offering robust and implementable supply chain management thesis that are transforming worldwide trends. The increasing strength of global Supply Chain Management (SCM) is one functional area that shows several students are seeking a good start, especially in solving significant problems in the form of  Masters  and  PhD thesis .

Nevertheless, with the changing trends in the industry, some students are likely to struggle with the early stages of academic writing. A significant reason for this problem is usually down to a lack of ideas or facing new topics with low research activity.

Old Industries and New Industries

The recent pattern shifts in academia, from the traditional research approach to other conventional methods, is taking a more student-centred view. Most of the supply chain management thesis is crafted by students, including dissertation, topic creation, research, and more with help of their supervisors.

With new industries, like Amazon and Apple, transforming old concepts with technological disruption, there are new trends to look out for to help narrow your supply chain management thesis.

The  7 Powerful Supply Chain Trends  (I also dubbed “Supply Chain 7.0”) have the potential to become a powerful influence over time. These trends, including Augmented reality (AR), Big Data, Gamification of the supply chain, moving supply chain to “Cloud,” and Internet of Things (IoT) – Industry 4.0. Also, Artificial Intelligence (AI) and machine learning in supply chain alongside 3D Printing are now needed to support the product life cycle.

Forbes also highlights the key  2020 Supply Chain Technology Trends  that are receiving lots of buzz in Supply Chain Management. In this regard, students seeking top-notch research areas for supply chain management thesis can consider new trends to help create adequate research content.

30  Supply Chain Management Thesis Topics for 2020

On these premises, any supply chain management thesis should be comprehensive. There several topics and areas to consider, and below are 30 Supply Chain Management Thesis Topics for 2020 that students can do research on towards an excellent postgraduate study in SCM.

Digital Transformation

• Digital Transformation Key Attributes; Challenges; enablers & Success Factors
• Smart Government Initiatives: How Governments are Driving Digital Change
• Digital Leadership linking to Virtual Teams or Self Organised Teams (Agile PM)
• COVID 19 impacted the implementation of Digital Transformation?
• Cross-functional collaboration in the decision-making process.
• The value of data and interdependencies in decision-making.
• Machine learning techniques in supply chain management

Sustainable Project Management (SPM)

• Can apply the SPM model or any of its dimensions to any type of project
• Can Blockchain help with Sustainable Project Management?
• Factors affecting the application of an efficient supply management system.

IoT- Industry 4.0 and Big Data

• Application of IoT in Logistics – Challenges; enablers & Success Factors
• The practicability of intertwined supply networks with IoT.
• Implementation of IoT in 3PL/4PL Industry – Challenges; enablers & Success Factors
• Big data and impact in DDMRP
• Evaluation of technology use in modern supply chain management.
• The extension of supply chain resilience through Industry 4.0
• The Impact of Industry 4.0 on supply chain management.
• Implementation of E-logistics in Supply Chain Operations.

Operations and Supply Chain Management

• Risk Evaluation and Management involved in a supply chain
• Partnerships Perspective in Supply Chain Management
• Assessing Supply Chain Risk Management Capabilities
• Implementation of Green Supply Chain Management Practices
• Supply Chain Management Practices and Supply Chain Performance Effectiveness
• The Impact of Supply Chain Management Practices on the Overall Performance of the org
• The Influence of Environmental Management Practices and Supply Chain Integration on Technological Innovation Performance
• The Relationship between Total Quality Management Practices and their Effects on Firm Performance
• Level of Commitment to Top Management regarding the TQM Implementation
• Impact of Mobility Solutions (transportation / latest technologies) on logistics.
• Study on the roles of supply chain management in corporate outsourcing.
• Evaluating strategies for cost reduction in SCM relating to exports and imports.

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The supply chain systems of today are more likely to see massive changes technologically in the coming years. Some selected supply chain management thesis topics may face limited data or access to real-time data in making proper research and forecast, including seasonality and trends. So, due diligence is necessary to ensure you not only pick an exciting supply chain management thesis, but you also have sufficient access to data, studies, and materials useful in such an area. The impact of these trends alongside technological advancement in the selected areas would certainly help your thesis stand out and unique.

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About Dr. Muddassir Ahmed

Dr. Muddassir Ahmed is a global speaker, blogger and supply chain industry, expert. Dr Muddassir Ahmed has received a PhD in Management Science from Lancaster University Management school. Muddassir is a Six Sigma black belt and has founded scmdojo.com with the intention to enable supply chain professionals and supply chain teams to solve the problems they face in their jobs & business.

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About Zaragoza Logistics Center

Zaragoza Logistics Center is a research and educational institute affiliated to the  Massachusetts Institute of Technology  and the  University of Zaragoza .  Core research areas  in logistics and supply chain management at Zaragoza Logistics Center (ZLC) strive to be actionable and applied so that people and organizations can make decisions and take action.

Zaragoza Academic Partnership (ZAP)

The Zaragoza Academic Partnership (ZAP) Program  allows companies to sponsor ZLC students’ thesis projects for both masters  ZLOG , ZLOGb and MDSC . It is an initiative to enhance applied research and bring industry-academia relationships closer together in the field of supply chain management. Each year students are required to complete thesis projects and many of them work with our partner companies on challenging and innovative research projects through the ZAP Program.

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The resilience, diversity and security of supply chains has long been fundamental to the prosperity of the United States. By following these three key principles, the nation has built a world-class, agile, and globally competitive manufacturing base, backed by solid systems, trusted critical infrastructure, and reliable transportation. This foundation has allowed the country’s public health and national security systems to prosper.

Each of these industries have benefitted from innovative automation and digitalization capabilities that have come from using RFID to connect to the Internet of Things. At least 80 billion items have been tagged with RAIN RFID in the U.S., with the data from these tags serving to enhance supply chain resilience through digital transformation in countless critical sectors. Furthermore, this figure looks set to continue its rapid growth with the inclusion of RAIN RFID readers in mobile handsets enabling a new wave of innovation.

RAIN RFID technology is therefore fundamental for key industries in modern society to continue functioning. However, a current petition under consideration by the Federal Communication Commission (FCC) risks undermining the use of UHF RFID and other “Part 15” devices in the U.S. across all use cases, leaving the country’s supply chain resilience, diversity and security in peril.

What is The Impact of The Petition?

NextNav , a 3D geolocation service provider, has filed a petition with the FCC to realign the 902-928 MHz band to expand the power level, bandwidth and priority of its licenses, which would allow the company to further push its Position, Navigation and Timing (PNT) services. However, to do so would require significant receiver blocking, cross modulation and Out Of Band (OOB) emissions, which would have a profound impact on the countless Part 15 devices operating within the band.

The power levels that NextNav proposes using would cause such notable interference that it would render RAIN RFID operation impossible. All those that rely on RAIN RFID devices in the U.S.—across many critical applications in a broad range of industries—would be in danger of being blocked, with this disruption resulting in significant negative socio-economic outcomes.

Three of the most notable use cases that would be negatively impacted are as follows:

• Retail: Over 40 billion tagged items are deployed in the U.S. retail sector alone. These deliver unparalleled end-to-end operational efficiencies, helping track deliveries, automate inventory, enable online business models, prevent counterfeiting and improve profitability.
• Healthcare: U.S. hospitals spend an average of $11.9 million on medical and surgical supplies each year. RAIN RFID plays a fundamental role in elevating patient safety by helping track and monitor these materials, as well as supporting staff and patient workflow, automating replenishment and billing, authenticating quality and tracking sterilization processes.
• National Defense: Virtually all military assets can be tracked, managed and monitored seamlessly with RFID. This engenders seamless military supply chains, especially for assets in transit to be deployed, while providing on-demand data on both traceability and inspection requirements.

Beyond these three industries, countless additional sectors depend on UHF RFID. Aerospace, the automotive industry, the energy and utility sectors, transportation, farming and the logistical chains of a host of different industries depend on the technology; all of which face significant disruption should the 902-928 MHz band be reallocated to serve the interests of NextNav.

What Actions Are Being Taken?

The RAIN Alliance Radio Regulations Advisory Committee (RRAC) is thoroughly investigating and analyzing the potential devastating impact that this petition could have. Comprised of leading RAIN RFID experts from throughout the RAIN Alliance membership, the committee has alerted fellow industry organizations of the threat this petition poses and drafted a comprehensive position paper in collaboration with AIM which outlines these concerns in detail.

Your Voice Matters

The most important consideration is how this proposed amendment would impact those who currently rely on the 902-928 MHz band and the benefits of UHF RFID. That’s why the FCC wants to hear from you.

Every voice has a profound impact. The Wireless Telecommunications Bureau and Office of Engineering and Technology are seeking comment on the petition through the FCC to inform their decision on next steps. It is vital that the FCC consider the full scope of the adverse effects that the proposed changes would have on US critical infrastructure.

The Power of Community

At times like this, organizations like the RAIN Alliance are exemplars of the power of community. It is this strong community that we once again build on as we seek to protect the interests of industries who have built their critical supply chain infrastructure on the 902-928 MHz band, using RAIN RFID technology.

Uniting the UHF RFID community allows the RAIN Alliance to continue its core work of enabling businesses and consumers to identify, authenticate, locate and connect billions of devices to the IoT. We continue to push for the increased availability of the global harmonized UHF frequency band, and we champion RAIN RFID as a data carrier for the emerging EU Digital Product Passport legislation.

These activities can only be done collaboratively, using the Power of Community to align interests, ensure all voices are heard, and benefit from the collective wisdom and knowledge of the brightest minds in our industry.

We look forward to continuing to work with our membership and our partners to foster market adoption of this powerful technology. Together we are stronger.

Related stories:

Impinj ceo: rain rfid industry must oppose proposed changes to 900 mhz frequency band.

• FCC Considers NextNav Petition for UHF Band

About the Author: Aileen Ryan - President & Chief Executive Officer, RAIN Alliance

Aileen Ryan’s executive career spans software and hardware engineering, strategy and commercial operations with a variety of technology firms and industry associations including Siemens, TM Forum, Huawei and Motorola. She joined the RAIN Alliance in October 2022 from a senior position at Siemens, having played a pivotal role in the strategic acquisition of UltraSoC Technologies where she was Chief Strategy and Chief Operating Officer. She also spent a decade at the TM Forum, a global industry association, in various roles including Chief Operating Officer where she led the growth and transformation of the organization including restructuring, re-skilling, and re-designing its portfolio of services. She is widely recognized as a leader in the global communications industry and was named by Silicon Republic as one of the top 25 Irish leaders in the Sci-Tech world, and by IT Security Guru and KPMG as one of the most inspiring women in cyber security in 2021. She holds an M.B.A., an M.Sc. in Computer Science, and a Bachelor’s degree in Electrical Engineering and has completed advanced executive business studies at the University of Cambridge and the Stanford University Graduate School of Business.

Posted in: Expert Views

Tagged with: Aileen Ryan , FCC , Federal Communications Commission , healthcare , military , National Defense , NextNav , PNT , Position Navigation and Timing , Radio Regulations Advisory Committee , Rain Alliance , RAIN RFID , Retail , RRAC , UHF RFID

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Rethinking hard tag removal: how rfid technologies are complementary to eas hard tags, top benefits of implementing smart parking solutions in cities, rfid applications set to boom: poised to become the next trillion-dollar industry.

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Is Your Organizational Transformation Veering Off Course?

• Andrew White,
• Adam Canwell,
• Michael Smets

Lessons on navigating turning points from surveys of 846 senior leaders and 840 employees involved in transformation programs.

Nearly all transformation efforts face significant challenges that can derail the whole program. These can range from exogenous shocks, such as inflation, supply-chain disruption, or political events; operating-model issues, such as the need to change technology, governance, or ways of working; or human dynamics, such as employee confidence in or ownership of the change. How can leaders identify these turning points — and get things back on track? New research, based on surveys of more than 1,600 leaders and employees involved in transformations, suggests that changes in a team’s emotional energy — their collective mood, vibe, and intensity of emotions — often signals that there’s an issue. Organizations that successfully navigate these turning points look for shifts in the team’s emotional energy, dig into the underlying issues at play, and quickly take action to create the conditions where teams can thrive.

There comes a moment in almost every organizational transformation — even the successful ones — when the program goes off course and leaders need to intervene. As researchers who study transformations , we are often approached by C-suite executives, who ask questions like: What do I do when things go wrong? How can I detect when things may be going off track? Is there a way to use these pivotal moments to my advantage?

• Andrew White is a senior fellow in management practice at Saïd Business School, University of Oxford, where he directs the advanced management and leadership program and conducts research into leadership and transformation. He is also a coach for CEOs and their senior teams.
• AC Adam Canwell is head of EY’s global leadership consulting practice. Adam has published extensively on leadership and strategic change. Adam has sold and delivered transformation programs across multiple industries in both the UK and Australia, working with FTSE 100 (or their equivalent) organizations .
• Michael Smets is a professor of management at Saïd Business School, University of Oxford. His work focuses on leadership, transformation, and institutional change.

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Michigan Journal of Economics

Chained Together: Global Supply Chains & the Pandemic

Written by Tarini Sathe

The global Coronavirus outbreak highlighted many problems with various systems and institutions on different scales; one of the biggest problems it exposed was the weakness of supply chains across global industries. A supply chain is a network of entities or stakeholders involved in the production process of a good; the chain begins with the producers of raw materials and only ends upon delivery to the consumer. Optimizing supply chains ensures greater efficiency at lower costs, which is crucial for firms to stay competitive (Hayes, 2023). The shutdown of the world disrupted the flow of production at every level—creating massive supply shocks—with recovery still ongoing. However, it has also provided opportunities for firms to rebuild and strengthen their supply chains. Therefore, it is important to look at how the pandemic affected supply chains globally, the weaknesses it exposed and how they are recovering three years post-Covid. 

When countries went into lockdown, only essential industries (pharmaceutical, etc.) remained functional while the majority of other industries temporarily shut. This disrupted and slowed the rate of production at all levels of the supply chain (Yadav, 2023). Manufacturing industries with in-person labor dealt with illnesses, Covid distancing and testing protocols, and lack of public transport—all of which caused worker shortages, resulted in less productivity, and a reduced ability to complete orders on time. Moreover, closed airspaces and ports hampered shipping efficiency (Yadav, 2023), and with longer routes or alternate transportation being used, delivery time and costs went up—further delaying the production and delivery of the finished goods.  

Some of the most affected entities were firms part of global value chains (GVCs)—ones that both import material and export their manufactured product. GVC firms were affected by shipping and international trade issues more so than firms that simply imported or exported (Lebastard et al., 2023). In addition to actual production hurdles, they faced shortages and higher costs to import required (raw) materials, as well as weaker foreign demand for their product and shipping challenges. Lebastard et al. (2023) did a study—with results analyzed on the World Economic Forum— on all the French firms trading internationally to understand the links between supply chains and exporting activity during the pandemic, and further looked at the trends of GVC firms versus non-GVC firms. In order to better understand supply chain and export patterns with context to Covid developments, they looked at three time periods: February to April 2020, the beginning of lockdowns and abrupt production halts; May to August 2020, which was a period of some recovery; and September 2020 to the end of 2021, when supply chain disruptions intensified (Lebastard et al., 2023). Their findings show that “participation in GVCs increased firm vulnerability to the pandemic,” (Lebastard et al., 2023); GVC firms were at greater risk of facing losses, had little cash flow and much-delayed production and delivery timelines. Being doubly affected by international supply shocks, which resulted in this vicious cycle of delays, ensured that it took much longer for GVC firms to get back on track with production. While there was some recovery in the second period, the third period and intensification of Covid and disruptions had a “relatively greater impact” on the exports of GVC firms (Lebastard et al., 2023). In fact, it took until after December 2021 for GVC firms to regain their January 2020 nominal export levels, whereas non-GVC firms had a much quicker recovery—nominal exports reached January 2020 levels by March 2021, and exceeded pre-pandemic export levels by September 2021 (Lebastard et al., 2023). The graph below depicts the same; for all exporting firms in France that have been categorized as GVC or non-GVC firms, their export performance over the time periods in the study has been graphed. 

Another issue that the study touches upon is how affected a firm was by supply chain disruption depending on how downstream or upstream the GVC firm was in the supply chain—downstream being tiers that involve the movement of the finished product. It found that downstream GVC firms were more heavily affected than upstream ones  (Lebastard et al., 2023), and therefore continued the cycle of creating more (intense) supply shocks. This goes hand-in-hand with a supply chain weakness exposed to firms during this time—not fully understanding every tier of their supply chain and therefore not foreseeing their own production challenges. While firms analyze their sourcing statistics, not many look beyond the first tier to ensure that sources are diversified. However, it is the second and third tiers of the chain coming from regions that firms have actually moved away from—for good reason—that disruptions are rooted in (LaRocco, 2023).  Tiers two, three, and lower tend to be located in economically weaker regions—for cost benefits, access to specific resources, etc.—which were majorly affected by Covid and struggled to rebound, thus affecting the production capabilities of firms with otherwise stronger sources of supply. As a result, firms have had to reevaluate their production flows and partnerships—identifying inefficiencies and unnecessary complexities and prioritizing collaboration and transparency with the end goal of a streamlined production process from start to finish (Vitasek, 2023). The silver lining, though, is that these reevaluations have and will continue to enable firms to better optimize cost and efficiency, thus providing consumers with better goods, all the while having facilitated a smooth supply chain experience. 

Not only have firms had to reevaluate the complexities of their supply chains, the pandemic has also shown them how putting (almost) all your eggs in one basket leaves you with very few options in times of crisis. Firms had relied massively on China for manufacturing and during the pandemic, with China’s ‘Zero Covid’ policy and shutdowns, supply logistics, deliveries, etc. got knocked out of whack—leaving them in the lurch. Zac Rogers, an assistant professor of operations and supply chain management at Colorado State University, said, “In 2019, we had basically all of our chips in on one hand… things are built in East Asia, come… through the ports in Southern California, they get… distribute[d] to the East Coast,” (Wallace, 2023). He also said that “companies are embracing different paths for the supply chain, whether it be in Vietnam, Bangladesh, Central America, or domestically,” (Wallace, 2023) because even though they cannot cut off China completely, the need of the hour is to diversify production sources in order to be more resilient. The Lebastard et al. study also indicated that diversified supply networks (looking at core imported inputs) of firms served to buffer the impact of supply shocks more so than firms without such networks. Additionally, firms diversifying their supply chains means that they are no longer as vulnerable, and potential future shocks can be better absorbed—particularly ones that are China-centric. In Rogers’ words, Covid was a “trigger” to exposing the state of global supply chains (Wallace, 2023), and this has been an opportunity to strengthen them and make them more resilient to future shocks. 

Over the last three years, supply chain activity has begun to recover, although there are still ongoing disruptions at various tiers of their production processes. The pandemic has ensured that firms look inward and evaluate their practices in order to become more efficient and resilient. In fact, a McKinsey report states that “future supply chains will need to be much more dynamic—and be able to predict, prepare, and respond to rapidly evolving demand and a continually changing product…” (Vitasek, 2023). Ultimately, despite the devastation of the pandemic and the havoc it wreaked on global production and supply chains, firms and industries must use it as an opportunity to become more resilient and revolutionize their partnerships to suit the dynamic nature of current consumer demand. 

Works Cited

Hayes, A. (2023). The Supply Chain: From Raw Materials to Order Fulfillment. Investopedia . https://www.investopedia.com/terms/s/supplychain.asp#toc-what-is-a-supply-chain

LaRocco, L. A. (2023, January 27). Another Covid Surge in China Is the Global Supply Chain’s Biggest Fear, but It May Be Overstated. CNBC . https://www.cnbc.com/2023/01/27/another-covid-surge-in-china-is-the-global-supply-chains-biggest-fear.html

Lebastard, L., Matani, M., & Serafini, R. (2023, March 30). Understanding the impact of COVID-19 supply disruptions on exporters in global value chains . World Economic Forum. https://www.weforum.org/agenda/2023/03/understanding-the-impact-of-covid-19-supply-disruptions-on-exporters-in-global-value-chains/ 

Vitasek, K. (2023, June 15). How Strategic Partnerships Simplify Post-Pandemic Supply Chains. Forbes . https://www.forbes.com/sites/katevitasek/2023/06/15/how-strategic-partnerships-simplify-post-pandemic-supply-chains/?sh=624c643a2a24

Wallace, A. (2023, January 16). Covid broke supply chains. Now on the mend, can they withstand another shock? CNN Business. https://www.cnn.com/2023/01/16/economy/supply-chain-outlook-2023/index.html

Yadav, S. (2023, July 11). Supply Chain Management in a Post-Covid World. Forbes . https://www.forbes.com/sites/forbesbusinesscouncil/2023/07/11/supply-chain-management-in-a-post-covid-world/?sh=792c987c5462

Economic Resilience through Sustainable Urbanization in Southeast Asia

MIT-VNU Joint Workshop on Global Supply Chain Reallocation and Vietnam’s Sustainable Urbanization

The MIT Center for Real Estate’s Asia Real Estate Initiative (AREI) sponsored a workshop jointly organized by the MIT Sustainable Urbanization Lab and Vietnam National University International School (VNU-IS) in Hanoi, Vietnam, on July 17, 2024. 

Titled “Rising with Global Supply Chain Reallocation: On Vietnam’s Sustainable Urbanization,” the workshop explored various aspects of sustainable urbanization, economic development, and global integration, focusing on experiences from China and their potential applications to Vietnam. The program brought together experts from institutions in the US, Vietnam, and China to share insights on urban development, industrial production, cross-border dynamics, sustainable planning, and emerging economic sectors. Prof. Siqi Zheng, Faculty Director of the MIT Center for Real Estate, and two AREI researchers, Assoc. Prof. Wen-Chi Liao from the National University of Singapore Business School, and Dr. Li Hou from Harvard University Graduate School of Design, participated in the workshop.

The workshop featured a mix of presentations, panel discussions, and roundtables, offering opportunities for in-depth exploration of topics and collaborative dialogue. Siqi Zheng delivered a keynote speech on “Industrial Parks in China: Economic Engine, Misallocation Cost, and the Role of Transportation Infrastructure.” Wen-Chi Liao presented key findings from the collaborative paper “Tariff Wall Jumping at the China-Vietnam Border,” co-authored with Matthew E. Kahn and Siqi Zheng. Dr. Dong Chung from VNU-IS examined the “survivability” of the Vietnamese manufacturing industry in the global value chain, advocating support for domestic and non-state-owned businesses to enhance their survival prospects. Laurent El Ghaoui, Professor, Vice Provost of Research, and Dean of the College of Engineering and Computer Science at VinUniversity, discussed the semiconductor industry’s future and labor force education in Vietnam. He also participated in panel discussions on bridging research with policy-making and industrial practices, alongside Siqi Zheng and other participants. Xueli Liu and Li Hou evaluated the planning efforts and impacts on the high-speed rail new towns in China, while Dr. Xiaoyi Wen from Tongji University, China, presented recent territorial planning and infrastructure construction schemes in the China-Vietnam border region.

Through the joint workshop, participants gained valuable insights into the latest research and practical applications in sustainable urbanization, economic development, and global integration, with a specific focus on the challenges and opportunities facing Vietnam in light of China’s experiences and emerging global trends. This AREI-sponsored event aimed to foster knowledge exchange, encourage international collaboration, and contribute to developing sustainable urban policies and practices in the Southeast Asia region. It also addressed the pressing need for skilled workforce development in high-tech industries, the complexities of managing rapid urban growth in major metropolitan areas like Hanoi, and strategies for enhancing economic resilience through global integration.

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Please note you do not have access to teaching notes, turning the ordinary into the extraordinary: using dynamic knowledge management to improve innovation and supply chain resilience.

Strategic Direction

ISSN : 0258-0543

Article publication date: 16 August 2024

Issue publication date: 29 August 2024

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

Design/methodology/approach

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

This paper identified that dynamic knowledge management can improve both innovation and supply chain resilience.

Originality/value

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

• Supply chain resilience
• Dynamic knowledge management

(2024), "Turning the ordinary into the extraordinary: Using dynamic knowledge management to improve innovation and supply chain resilience", Strategic Direction , Vol. 40 No. 7, pp. 7-9. https://doi.org/10.1108/SD-07-2024-0127

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