Impact Of Supply Chain Disruptions Research Articles

Firm disruption orientation and supply chain resilience: understanding mechanisms to mitigate disruption impact

PurposeThis study aims to investigate the interplay between a proactive attitude towards disruptions – supply chain disruption orientation – and supply chain resilience, increasing our understanding of their influence on reducing the impact of supply chain disruptions within the B2B context.Design/methodology/approachAs unexpected disruptions are closely related to a dynamic and changing perception of the environment, this research is framed under the dynamic capabilities lens, consistent with existing resilience literature. The authors used partial least squares-path modeling (PLS-PM) to empirically test the proposed research model using survey data from 216 firms.FindingsResults show that a proactive approach to disruptions alone is insufficient in mitigating their negative impact. Instead, a firm’s disruption orientation plays a crucial role in boosting its resilience, which acts as a mediator, reducing the impact of disruptions.Originality/valueThis paper sheds light on the mechanisms by which firms can mitigate the effects of supply chain disruptions and offers insights into how certain capabilities are needed so that firms’ attitudes can effectively impact firm performance. This research thus suggests that dynamic capabilities, traditionally perceived as being enabled by other elements, act themselves as enablers. Consequently, they have the potential to translate strategic orientation or attitudes into tangible effects on performance, enriching our understanding of how firms combine their internal attitudes and capabilities to achieve sustained competitive advantage.

Supply chain driven herding behavior during COVID-19: evidence of interdependence from India

Purpose This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior. Design/methodology/approach Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors. Findings The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory. Originality/value The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.

Extreme risk spillovers between US and Chinese agricultural futures markets in crises: A dependence-switching copula-CoVaR model.

The linkages between the US and China, the world's two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.

The Role of Industry 4.0 Technologies in Mitigating Supply Chain Disruption: Empirical Evidence From the Australian Food Processing Industry

Supply chain disruption refers to a breakdown, often caused by an unforeseen incident or risk, in a supply chain's production or distribution process. Contemporary supply chains are globalized, complex, and extended, exhibiting an increased vulnerability to a multitude of risks and disruptions. However, the current trend of real-time data exchange through smart technologies, also known as industry 4.0, provides significant opportunities to reshape the conventional business operations and effectively cope with unanticipated supply chain breakdowns. Yet, limited attention has been paid to the role played by industry 4.0 technologies in mitigating supply chain risks and any resulting disruptions. By bringing together these inter-related yet often separate concepts, we devise a novel model that addresses this knowledge gap. In this article, we empirically test our model on a sample of 302 responses received from senior managers of the Australian food processing industry. We found that supply–demand mismatch, process risks, and transportation risks are currently the major sources of supply chain disruptions. Specifically, supply–demand mismatch appears to be the most severe and attention seeking risk, followed by process and transportation risks. We also reveal that industry 4.0 technologies significantly mitigate supply–demand mismatch and process risks and any resulting supply chain disruptions. Contrary to our expectations, however, the impact of industry 4.0 technologies on transportation risks is found to be positive but nonsignificant. This is the first empirical article to assess the extent to which the three critical supply chain risks may undermine firm performance and to explore the moderating effect of industry 4.0 technologies. We draw managers’ attention to the detrimental impact of supply chain disruptions and the significance of industry 4.0 technologies in dealing with adversities.

The impact of supply chain disruptions on the opportunity costs of road transport companies in Poland. A case study

The mission of many businesses around the world is to strive for continuous growth in their operations, thereby increasing their operability and profits generated. There are at least several ways to do this - from increasing the scope of a company's operations to looking for weak links within the company, thus optimising the costs incurred. It so happens, however, that it is not internal conditions that shape the business entity, but external influences over which one does not always have control. It then remains to adapt to the new reality and, as far as possible, reduce its negative impact. The aim of the study was to analyse the disruptions created within supply chains and their impact on the transport company. The problem discussed referred to the issue of opportunity cost - in particular the cost of lost opportunities and benefits, in order to then propose changes and actions to reduce the adverse effects from external influences. Based on the research conducted, it can be concluded that disruptions in supply chains affect companies' opportunity costs (1). By identifying and analysing disruptions, several options for minimising opportunity costs can be identified (2). Considering the disruptions in supply chains under the impact of the global crises, the following are cited as the most relevant: disruptions related to on-time delivery, limited opportunities to hire new drivers and opportunities to acquire a new set of vehicles (3). These disruptions prevented the surveyed entity from expanding its operations and thus impacted on its opportunity costs.

The impact of supply chain disruptions on business expectations during the pandemic

Utilizing the Federal Reserve Bank of Atlanta’s Business Inflation Expectations (BIE) survey, which has been continuously collecting subjective probability distributions over own-firm future unit costs since October 2011, we document two facts about firms’ marginal cost expectations and risk during the COVID-19 pandemic. First, in the early months of the pandemic, firms, on net, saw COVID-19 largely as a demand shock and lowered their one-year ahead expectations. However, as the pandemic wore on, firms’ one-year ahead unit cost expectations rose sharply alongside their views on supply chain and operating capacity disruptions. Second, the balance of unit cost risks shifted sharply over the course of the pandemic and by the end of 2022, upside risks had sharply outweighed perceived downside risks over the year ahead. We find that both positive demand shocks (e.g. large order backlogs) and negative supply shocks (e.g. long supplier delivery times and labor shortages) have contributed to elevated short-term unit cost expectations and risk. Specifically, supply shocks accounted for roughly 40% of the increase in manufacturers’ and nearly one-third of service-providers’ unit cost expectations.

Supply chain risk and resilience in startups, SMEs, and large enterprises: a systematic review and directions for research

PurposeThis systematic literature review analyzes the academic literature to understand SC risk and resilience across different organizational sizes and industries. The academic literature has well discussed the causes of supply chain (SC) risk events, the impact of SC disruptions, and associated plans for SC resilience. However, the literature remains fragmented on the role of two fundamental elements in achieving SC resilience: the firm's size and the firm's industry as firms' contingent factors. Therefore, it is important to investigate and highlight SC resilience differences by size and industry type to establish more resilient firms.Design/methodology/approachBuilding upon the contingent resource-based view of the firm, the authors posit that organizational factors such as size and industry sector have important roles in developing organizational resilience capabilities. This systematic literature review and analysis is based on the structural and systematic analysis of high-ranked peer-reviewed journal papers from January 2000 to June 2021 collected through three global scientific databases (i.e. ProQuest, ScienceDirect, and Google Scholar) using relevant keywords.FindingsThis systematic literature review of 230 high-quality articles shows that SC risk events can be categorized into demand, supply, organizational, operational, environmental, and network/control risk events. This study suggests that the SC resilience plans developed by startups, small and mdium-sized enterprises (SMEs), and large organizations are not necessarily the same as those of large enterprises. While collaboration and networking and risk management are the most crucial resilience capabilities for all firms, applying lean and quality management principles and utilizing information technology are more crucial for SMEs. For large firms, knowledge management and contingency planning are more important.Originality/valueThis study provides a comprehensive review of the literature on SC resilience plans across different organizational sizes and industries, offering new insights into the nature and dynamics of startups', SMEs', and large enterprises' SC resilience in different industries. The study highlights the need for further investigation of SC risk and resilience for startups, SMEs, and different industries on a more detailed level using empirical data. This study’s findings have important implications for researchers and practitioners and guide the development of effective SC resilience strategies for different types of firms.

Analyzing the Impact of Supply Chain Disruptions on Inflation: A Comparative Study across Time and Countries

Analyzing the Impact of Supply Chain Disruptions on Inflation: A Comparative Study across Time and Countries

Limiting the impact of supply chain disruptions in the face of distributional uncertainty in demand

Service‐level requirements play a crucial role in eliminating stock‐outs in a production pipeline. However, delivering a specific service level can become an unattainable goal given the various uncertainties influencing both the production pipeline and customer demand and causing the manufacturer to adapt the initial strategy in response to disruptions. Such deviations from optimality frequently result in unexpected (and potentially very high) costs and are complex to manage. On the one hand, the manufacturer can use a robust or distributionally robust approach to prepare for the worst‐case disruption, ensuring that the realized cost will be lower than the estimated cost with high probability. On the other hand, this solution may lead to overly conservative production schedules. In this article, we take a different approach and develop a bilevel stochastic optimization model with chance constraints, which allows us to make the production more predictable in the event of disruptions by driving costs and optimal schedules closer to the benchmark for each scenario considered. We introduce doubly probabilistic service‐level requirements to account for two interdependent layers of uncertainty, that is, production disruptions and distributional uncertainties in customer demand. This allows us to make high‐quality production decisions with only a limited understanding of the demand pattern. Approximating the problem for a numerical solution, we guarantee tight optimality gaps for high service levels and propose an efficient solution scheme, combining robust scenario reduction with a customized Benders decomposition procedure. In the managerial section, we use the Omega× Swatch MoonSwatches example to demonstrate that a desirable doubly probabilistic service level can be attained for disruptions with a drop in demand. In the case of disruptions followed by a peak in demand, one can tighten the optimality gaps if the service level is reduced.

The missing link in disruption management research: coping

The COVID-19 pandemic made it clear that the impact of supply chain disruptions on different organizations may vary widely. Even if different levels of capabilities (agility, adaptability, etc.) may have contributed to the differential in outcomes, organizations need to learn how to harness their capabilities effectively in the face of disruptions. Although there is vast literature on supply chain disruption management, risk management, and resilience, we are not aware of any theory that comprehensively explains the decision-making process for managing disruptions. We argue that coping theory can explain how organizations may channelize resources based on two stages of appraisal to handle long- and short-term disruptions. Borrowing from psychology, we adapt coping theory to disruption management for any organization in any industry. In this paper, we demonstrate how supply chain coping strategies may explain outcomes of several organizations from different industries during the COVID-19 pandemic. We argue that organizations may sustain and even thrive if they adopt the right coping strategies in their context. We present our thesis using the following three themes: (1) We first identify potential demand trajectories organizations may follow during and after the pandemic, (2) We explain how coping strategies adopted by organizations may impact these trajectories, and (3) We present a framework to help the decision makers understand potential positive impact the coping strategies may bring to their organizations in future crises.

Impact of supply chain disruptions during the COVID-19 pandemic to micro, small and medium enterprises in Davao Region, Philippines

PurposeThis paper aims to investigate the impact of supply chain disruptions on the operations and sales performance of micro, small and medium enterprises (MSMEs) and the adoption of “green” technology during the COVID-19 pandemic in Davao Region, Philippines.Design/methodology/approachA business impact survey was conducted among 113 MSMEs in Davao Region through the Regional Inclusive Innovation Center participated by the industry, government and the academe from October–December 2020. The impact of supply chain disruptions on the status of business operations was determined using ordered logit regression, while the impact on sales performance during the lockdown and new normal periods were modeled using logit regression. The technology upgrading plans of the MSMEs, including the adoption of “green” technology, were also determined.FindingsThis study found that the extent of disruption in processing the goods and services resulted in a negative impact on business operations, and the disruption of the availability of raw materials negatively affected the sales performance during the lockdown period. Moreover, around 20%–33% of MSMEs experiencing heavy supply chain disruptions had a plan to upgrade their business processes by adopting “green” technology.Research limitations/implicationsMSMEs need to establish strategic collaboration among the different stakeholders through public, private, non-government institutions and academe collaboration to enhance the capabilities of MSMEs in handling supply chain disruptions and pursuing technology upgrading.Originality/valueThis paper is among the early studies of the impact of COVID-19 to supply chains in the Philippines focusing on the MSMEs.

The impact of supply chain disruptions on stock market returns during COVID-19

PurposeHow has COVID-19 impacted meat processors' stock returns? The authors evaluate the effects of supply chain disruptions (e.g. lockdowns and COVID-19 incidences among workers) on stock market prices of meat processors during the COVID-19 pandemic.Design/methodology/approachThis study uses an event study approach to examine the disruptions from COVID-19 through events such as plant shutdowns, the pandemic announcement, lockdown dates and the first case of COVID-19 outbreaks in meat processing plants. The dataset includes S&P 500, Google Trends, financial beta and data collected for 14 US publicly traded meat processing companies.FindingsResults show that nationwide events (e.g. announcement of the pandemic) had no statistically significant impact on average abnormal returns of meat processing companies. Individually, however, firms experienced negative abnormal returns. COVID-19-related events in individual meat processing companies had a temporary negative abnormal return in the days prior to the event.Originality/valueThis study has two main contributions. First, the authors estimate the effect of COVID-19 on the returns of meat processors. Second, the authors use Google Trends to estimate the expected stock markets returns of meat processing companies. This study provides insight to investors on the behavior of industry returns from events such as outbreaks that affect human health.

A Case Study of Carbon Emissions from Logistic Activities During Supply Chain Disruptions

Supply chain disruptions have significant negative effects on logistics operations, in which recovery actions could in turn affect the environment if certain green precautions are not undertaken. The objective of this research is to assess the effect of disruption on carbon emissions from logistics activities in the supply chain. A case study was carried out in this study to identify the factors of supply chain disruptions that affect logistics operations, and investigate the impact of the disruptions on the environment. Data collection using the Fuel Monitor application and real disruption data from a selected company were used to quantify the carbon emissions during disruption and non-disruption scenarios. Analysis of the study found that carbon emissions during disruption events increased to approximately 18 – 20 % as compared to normal operations. This is due to the increase in travelling distance in order to fulfill customer backorders during the disruption occurrence. The carbon emission amount was slightly higher when using fuel consumption as reference data in comparison to distance travelled, as fuel consumption takes into account the driving behaviour and efficiency of the truck engines. This study is useful for analyzing the impact of supply chain disruptions on the environment, particularly from the post-disruption recovery decisions.

A supply chain disruption recovery strategy considering product change under COVID-19

A recent global outbreak of Corona Virus Disease 2019 (COVID-19) has led to massive supply chain disruption, resulting in difficulties for manufacturers on recovering their supply chains in a short term. This paper presents a supply chain disruption recovery strategy with the motivation of changing the original product type to cope with that. In order to maximize the total profit from product changes, a mixed integer linear programming (MILP) model is developed with combining emergency procurement on the supply side and product changes by the manufacturer as well as backorder price compensation on the demand side. The model uses a heuristic algorithm based on ILOG CPLEX toolbox. Experimental results show that the proposed disruption recovery strategy can effectively reduce the profit loss of manufacturer due to late delivery and order cancellation. It is observed that the impact of supply chain disruptions is reduced. The proposed model can offer a potentially useful tool to help the manufacturers decide on the optimal recovery strategy whenever the supply chain system experiences a sudden massive disruption.

Teaching supply chain risk management in the COVID‐19 Age: A review and classroom exercise

The COVID‐19 pandemic has undoubtedly affected every corner of the world in 2020. It has also emphasized the importance of managing supply chain risk and developing an agile supply chain. Supply chain management instructors will likely want to introduce risk management concepts and strategies into their courses to raise their students' sensitivity to the impact of supply chain disruptions. Unfortunately there is currently a dearth of coverage of supply chain disruptions and risk management in the major supply chain management text books as well as in the broader library of supply chain management pedagogical research publications. To help to close this gap in the literature for instructors, we have developed a reading and set of related discussion questions and exercises that detail the causes of the shortage in toilet paper during the pandemic and short‐ and long‐term strategies to make the supply chain more resilient in the future. By focusing on a disruption students likely experienced first‐hand, they can develop a more nuanced understanding of the complexity and interconnectedness of supply chain functions in providing products and services to customers.

The impact of supply chain disruption on the closed-loop supply chain configuration profit: a study of sourcing policies

A closed-loop supply chain configuration (CLSCC) encompasses the decisions related to the optimal selection of options at each stage of a closed-loop supply chain (CLSC) for the introduction and reconstruction of new products. The extant literature ignores the impact of supply chain disruptions on CLSCC. An attempt is made to fill this gap in this study. Thus, an integrated multi-sourcing CLSCC optimisation model for new and reconstructed products is developed. The optimisation model presented is a mixed-integer nonlinear programming (MINLP) model. Based on a real-world case study of an auto-parts manufacturer in India presented, a comprehensive set of computational experiments, scenario analyses are conducted. The key finding/observation that resulted from our computational experiments is that multi-sourcing generates higher net present value of total profit compared to single sourcing under the risk of supply chain disruption. Several other observations and managerial insights are drawn from computational experiments, and scenario analyses. Firms interested in configuring their CLSC under the risk of supply chain disruption may use the study's outcomes to understand the profit impact of various CLSCC parameters, individually and in combination.

An examination of the impact of flexibility and agility on mitigating supply chain disruptions

This paper examines the effect of flexibility and agility on improving supply chain responsiveness. We examine a supply chain with multiple sites, multiple transportation channels, and multiple product planning, over multiple periods, under supply risk and demand risk. Using a numerical example, we determine the relationship between three objective functions related to responsiveness, risk, and the cost of new and seasonal products, then discuss the impact of flexibility and agility on mitigating supply chain disruptions. To show a trade-off among objective functions in our numerical example, we solve the multi-objective mixed integer programming (MOMIP) model using three multi-objective optimization methods: the weighted goal programming (WGP) method, the augmented ε-constraint (AUGMECON) method, and the non-dominated sorting genetic algorithm (NSGA-Ⅱ). Our findings help decision makers with these two tasks: anticipate how much improvement in flexibility and agility will lead to an improvement in responsiveness; and create an investment plan to minimize the negative impact of supply chain disruptions by an examination of the trade-offs among responsiveness, risk, and cost. The results show that the NSGA-Ⅱ method outperforms the AUGMECON method in several metric indexes: the spacing metric, the diversity metric, and simple additive weighting.

An analysis of stock market impact from supply chain disruptions in Japan

PurposeThe purpose of this paper is to explore the stock market impact of supply chain disruptions for public companies in Japan. The impact in the USA and Japan are also compared.Design/methodology/approachUsing event study on a data set comprising of disruptions announced by Japanese and US companies during year 2000-2013, the authors measure the stock price reaction to supply chain disruptions.FindingsThe study finds that the Japanese companies, in an 11-day window around disruption announcement, witness an average abnormal return of −0.61 percent, which is statistically significant. In comparison to the USA, this stock decline is qualitatively smaller, yet statistically indifferent. The abnormal return is found significant in the two days before disruption announcement. However, a follow-up study with a refined data set (where the event date is the earlier of the announcement or disruption date) does not find any significant abnormal return prior to the event date. This difference from US market suggests the possibility of insider trading. Factors such as book-to-market ratio, industry type, and market capitalization did not affect the stock decline.Research limitations/implicationsThe research is limited to a data set from Japan and the USA. Further generalization of findings may need studies focused on other countries.Practical implicationsThe results are of interest for supply chain managers. The results should also help global investors in making investment decisions.Originality/valueMost supply chain disruptions management research is focused on companies in western countries. The paper is the first to test the impact of supply chain disruptions in Japan.

The economic impact of supply chain disruptions from the Great East-Japan earthquake

The Great East-Japan Earthquake of March 11th, 2011 had a serious negative economic impact on the Japanese economy. The earthquake substantially reduced production not only in regions directly hit by the earthquake but also in other parts of Japan through supply chain disruptions. We examine the economic impact of the supply chain disruptions immediately following the earthquake using a unique interregional input-output table combining two different regional IO tables, the JIP database, and other regional statistics. To conduct our analysis, we modify the forward linkage methodology to take into account the bottleneck effect in the intermediate input of manufacturing production. Our estimates show that the production losses caused by the supply chain disruptions would amount to at least 0.35% of the country’s GDP. We also analyzed how establishing multiple supply chains would work to mitigate the damage of potential natural disasters in the future. However, as multiple supply chains may lose production efficiency at the firm level, we would require policies that provide incentives to firms that diversify supply chains.

An assessment of supply chain disruption mitigation strategies

We assess the effectiveness of incorporating three types of redundancy practices (pre-positioning inventory, backup suppliers, and protected suppliers) into a firm’s supply chain that is exposed to ttwo types of risk: supply risk and environmental risk. Supply risk disrupts an individual supplier, while environmental risk makes a number of suppliers in a given region unavailable. An additional factor is supplier interdependence, where a disruption in one supplier may also disrupt other active suppliers. Utilizing the concept of a decision tree to capture different disruption scenarios, we develop a two-stage mixed-integer programming (two-stage MIP) model as a General Model to address the problem of supplier selection and order allocation under supplier dependencies and risk of disruptions. In the General Model, multi-sourcing is the only supplier strategy that the firm implements. Then we develop three separate extensions of the General Model, one for each of the three redundancy practices, and evaluate the expected supply chain cost of each extended model. We quantitatively show how adding redundancy to the supply chain in different forms, along with contingency plans, can help firms mitigate the impact of supply chain disruptions. The findings suggest that all three strategies reduce costs and risks compared to the General Model. An analysis of reliability, risks, dependence, and costs is conducted on each strategy to provide insights into supplier selection, demand allocation, and capability development in a supply chain under supply chain risks. Finally, we show that regionalizing a supply chain is an effective way to mitigate the negative impacts of environmental disruptions on the supply chain.