Influence of COVID-19 on Manufacturing Industry and Corresponding Countermeasures from Supply Chain Perspective

Human activity's impact on urban vegetation in China during the COVID-19 lockdown: An atypical anthropogenic disturbance

The COVID-19 lockdown led to reduced industrial and transportation emissions in Chinese cities, improving air quality and affecting large-scale vegetation. This study examines changes in net primary productivity (NPP) across 283 prefecture-level cities in China (PCC) during the lockdown, focusing on aerosol optical depth (AOD), nighttime light (NTL), temperature, and precipitation. Results from spring 2020 show that 53.5% of cities experienced increased NPP, with greater gains in cities with high industrial and traffic activity due to reduced AOD. Structural equation modeling revealed that urban characteristics, particularly industrial levels, influenced NPP primarily through changes in AOD, with human activity shifts playing a larger role than climate factors. In cities with substantial NPP changes, human activity effects were especially pronounced. These findings highlight the complex interactions among urban characteristics, environmental changes, and vegetation responses, offering insights for ecological management and urban planning in the face of future disruptions.

Unveiling dynamics of urbanization, rural logistics, and carbon emissions: A study based on China's empirical data

In an era where global focus intensifies on sustainable development, in this study, I investigate the interplay between rapid urbanization, rural logistics evolution, and carbon dynamics in China. We aim to bridge the gap in existing literature by examining the tripartite relationship between these areas and their collective impact on sustainable development. I explore the dynamic interaction mechanisms between urban construction, rural logistics development, and carbon emissions, assessing their joint influence on sustainable development. A detailed analysis of demand dynamics and market mechanisms supporting urbanization, rural logistics development, and carbon emissions has been initiated, leading to the establishment of a theoretical framework. This framework adeptly captures the interdependencies and constraints among these variables, offering a mathematical and bioscientific perspective to understand their complex interactions. Furthermore, a sophisticated nonlinear model based on key quantitative indicators like urbanization level, rural logistics development, and carbon emissions has been incorporated. Considering the multivariate nature, uncertainty, and dynamism presented by the nonlinear model, genetic algorithms have been employed for the estimation of model parameters. Through rigorous empirical testing using data from China spanning the years 1991-2021, I not only validate the effectiveness of the model but also accurately the interactions between urbanization processes, rural logistics progression, and carbon emissions. The findings demonstrate that urban construction significantly drives rural logistics development and uncover a pronounced nonlinear relationship among urbanization, rural logistics development (with a significant pull effect of 4.2), and carbon emissions growth. This research highlights the subtle balance between rural-urban development and environmental management, providing theoretical backing for the creation of sustainable policy frameworks in rural contexts and setting a foundation for future research in this domain.

Effects of CEO water shortage experience and power intensity on corporate water performance - Evidence from China

Corporate water performance and sustainable development are currently vital focus areas for scholars. Therefore, this paper investigates the experience of Chief Executive Officers (CEOs) with water shortage influences corporate water performance by focusing on listed companies in water-intensive and high-water-risk industries in China between 2014 and 2019. This paper manually collected information relative to the cities and provinces where CEOs grew up to evaluate their early exposure to water shortages. Furthermore, this paper develops an evaluation scale, based on the Enterprise Water Conservation Evaluation Guide (GB/T 7119-2006), to compute the enterprise water management practices scores. These results will constitute the enterprise water performance evaluation score. Moreover, this paper focuses on CEOs who have experienced water resource shortages through a positive impact on the water resource performance of their companies. As for the findings, they demonstrate that CEOs who grew up in regions with higher water scarcity have a more pronounced positive effect on their water shortage experience through corporate water performance. Furthermore, CEO power intensity positively moderates the relationship between the CEO's water shortage experience and corporate water resource performance. Further investigation reveals generational differences in the impact of CEO water shortage experience on company water performance. CEOs, who grew up during periods with a higher incidence of droughts, demonstrate a more significant promoting effect on corporate water performance. To sum up, this study expands the understanding of factors influencing corporate water resource performance and deepens the knowledge of the early life experiences of CEOs.

How did COVID-19 affect logistics and supply chain processes? Immediate, short and medium-term evidence from some industrial fields of Italy

This paper provides empirical evidence on the impact of the Covid-19 pandemic on logistics and supply chain processes of five industrial sectors of Italy, namely food & beverage, machine manufacturing, metal mechanical industry, logistics & transport, and textile & fashion. A questionnaire survey, with 82 useful responses, was conducted to investigate various effects of Covid-19 on these businesses, such as the volumes handled and the service performance in the immediate-, short- and medium-term, the countermeasures implemented by companies and the future decision-making strategies. The period of analysis spans from January 2020 to June 2021. Results show that the impact of Covid-19 on volumes and service performance varied across the sectors: the food & beverage and logistics & transport were poorly affected by the pandemic and experienced a general increase in the demand and volumes, while mechanical or textile & fashion industries were mostly affected by a decrease in demand. The positive/negative impacts were particularly evident at the beginning of the pandemics, but, depending on the sector, the effects could cease quite quickly or last in the short-term. The countermeasures adopted against the Covid-19 emergency differ again across sectors; in general, industry fields that were particularly impacted by the pandemic emergency have applied more countermeasures. Typical strategies for risk management (e.g., the diversification in transport modes or the stock increase) turned out to be applied as immediate countermeasures or in plan for the future in few industries only. Differences across sectors were also observed about the sourcing strategies already in use, implemented to counteract the pandemics or expected to be maintained in time. Empirical outcomes offered are expected to help researchers gain a deep understanding of Covid-19 related phenomena, thus inspiring further research activities.

Graph Spatio-Temporal Networks for Manufacturing Sales Forecast and Prevention Policies in Pandemic Era

Worldwide manufacturing industries are significantly affected by COVID-19 pandemic because of their production characteristics with low-cost country sourcing, globalization, and inventory level. To analyze the correlated time series, spatial-temporal model becomes more attractive, and the graph convolution network (GCN) is also commonly used to provide more information to the nodes and its neighbors in the graph. Recently, attention-adjusted graph spatio-temporal network (AGSTN) was proposed to address the problem of pre-defined graph in GCN by combining multi-graph convolution and attention adjustment to learn spatial and temporal correlations over time. However, AGSTN may show potential problem with limited small non-sensor data; particularly, convergence issue. This study proposes several variants of AGSTN and applies them to non-sensor data. We suggest data augmentation and regularization techniques such as edge selection, time series decomposition, prevention policies to improve AGSTN. An empirical study of worldwide manufacturing industries in pandemic era was conducted to validate the proposed variants. The results show that the proposed variants significantly improve the prediction performance at least around 20% on mean squared error (MSE) and convergence problem.

Impact of COVID-19 (2020–2022) on Cotton and Garments Market of Bangladesh: A Small Country Case

Bangladesh imports roughly 98% of cotton from abroad to produce fabric or yarn (USDA 2020. Cotton and Products Update. Bangladesh. Also available at https://apps.fas.usda.gov/newgainapi/api/Report/DownloadReportByFileName?fileName=Cotton%20and%20Products%20Update_Dhaka_Bangladesh_11-30-2020). The production of textiles in Bangladesh depends on the price of raw material, the demand for garment products in the importing countries, smooth supply chain management, and the domestic supply of cheap garment laborers. The global pandemic of COVID-19 disrupted the supply chain of almost all physical goods and services, including textiles. It caused the price of textiles to fall due to a drop in worldwide demand, and increased the marginal cost of textile production due to supply chain interruptions. This paper shows how the decline in the demand for garments, coupled with an increase in cost, shrinks the producer welfare of textile manufacturing and garment exports of the small producing country, Bangladesh.

Effects of COVID-19 outbreak in pricing and collaboration of a health-social dual-channel supply chain

The coronavirus pandemic has affected most aspects of product supply and consumer behaviors and led to transformations in the supply chain. The COVID-19 pandemic and the requirements to reduce its prevalence have led many people to shop online and encouraged many manufacturers to sell their products online. In this study, a manufacturer, who intends to possess an online sales channel, and a retailer, who has an in-person sales channel, are considered. Then, pricing strategies and collaboration mechanisms between them in the health-social dual-channel supply chain are investigated. This study is developed in three models, including centralized, decentralized, and collaborated under Stackelberg game, whereas the optimal price of products in each channel, level of implementation of health and safety protocols in retailers, advertising level, and status of online shopping performance are obtained for improving customer trust. Moreover, the demand is represented as a function of selling prices of products in online and in-person shops, compliance level of health protocols, level of online shopping performance, and advertising in health during the COVID-19 pandemic. Although the centralized model provides more profit for the manufacturer, the collaborated model provides the highest profit for the retailer. Thus, since the supply chain profit of centralized and collaborated models is close, the collaboration model is the best option for members in this situation. Sensitivity analysis is finally performed to evaluate the impact of key parameters, and then according to obtained results, some management insights are suggested for the dual-channel supply chain during the COVID-19 pandemic.

Intelligent manufacturing eco-system: A post COVID-19 recovery and growth opportunity for manufacturing industry in Sub-Saharan countries

The lagging behind intelligent technologies and the COVID-19 pandemic together have impacted the emerging economy particularly the manufacturing sector in sub-Saharan countries. This paper systematically discusses intelligent manufacturing technologies with an aim to map out their importance and industrial applicability and to show their significance to contain COVID-19 pandemic. Intelligent Manufacturing Systems (IMS) is then adapted as a post COVID-19 recovery and growth opportunity to ensemble to production processes of manufacturing industry in the sub-Saharan countries. Proposition of a Triple Helix Collaboration Eco-system that delineate a recursive contribution of Government(s), academia, and industry accompanies the IMS adoption. The intention is to shape the existing industrial challenges through networking in the area of intelligence technologies. While proposing the Eco-system, a post COVID-19 recovery and growth opportunity and intra-Africa scientific collaborations are taken into account.

Innovation in manufacturing SMEs during the COVID-19 pandemic: How does environmental dynamism reinforce employee proactive behavior?

In a turbulent environment such as during the COVID-19 pandemic crisis, employee proactive behavior is imperative for innovation initiatives in small- and medium-sized enterprises (SMEs). We ask whether and how turbulent environments motivate employees to proactively engage in innovative behavior. This study argues that employees' perceptions of environmental dynamism reinforce employee proactive innovation behavior. Using a sample comprising 262 innovative employees from 40 manufacturing SMEs in Taiwan, this study tests a moderated-mediation model in which environmental dynamism is expected to increase the indirect effect of creative self-efficacy on employee innovative behavior through knowledge acquisition. The results confirm the mediating role of knowledge acquisition and the positive moderating effect of environmental dynamism. This study sheds light on the issue of employee proactive behavior in response to changing environments.

An integrated Industry 4.0-Sustainable Lean Six Sigma framework to improve supply chain performance: a decision support study from COVID-19 lessons

Purpose

The COVID-19 pandemic era has severely hampered the economy over the globe. However, the manufacturing organizations across all the countries have struggled heavily, as they were among the least who worked on online mode. The organizations are adopting various innovative quality methodologies to improve their performance. In this regard, they are adopting the Sustainable Lean Six Sigma (SLSS) concept and Industry 4.0 technologies to develop products at a faster rate. The use of Industry 4.0 technologies may reduce material movement and supply chain disruptions with the help of smart intelligent systems. There is a strong synergy between SLSS and Industry 4.0 technologies, resulting in an integrated approach for adoption. This study aims to develop a framework that practitioners can use to adopt Industry 4.0-SLSS practices effectively.

Design/methodology/approach

This study portrays 31 Industry 4.0-SLSS practices and 22 performance metrics identified through a literature review to improve the manufacturing supply chain performance. To compute the weights of these practices, the Robust Best–Worst Method (RBWM) is used. The Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method is used to rank performance metrics.

Findings

According to the RBWM results, “Process Development Practices (PDP)” are first among the major criteria, followed by “Organizational Management Practices (OMP)” at second, “Technology Adoption Practices (TAP)” at third, “Strategy Management Practices (SMP)” at fourth and “Executive Management Practices (EMP)” at fifth, whereas the PF-CoCoSo method resulted in the performance metric “On time product delivery” ranking first.

Research limitations/implications

The identified practices have the potential to significantly improve the performance of the manufacturing supply chain. Practices that encourage a sustainable manufacturing supply chain and the usage of emerging technology will benefit organizational effectiveness. Managers can assess performance using prioritized performance metrics.

Originality/value

During the COVID-19 pandemic era, this is one of the unique attempts to provide a framework to improve the manufacturing supply chain performance. This study integrates and identifies Industry 4.0-SLSS practices and performance metrics for enhancing overall performance.

Digitalization and entrepreneurial firms' resilience to pandemic crises: Evidence from COVID-19 and the German Mittelstand

While stressing the relevance of context, the organizational resilience literature has so far not extensively examined resilience in times of healthcare crises such as the ongoing COVID-19 pandemic. The Parasite Stress Theory of Values suggests that such pandemic crises have detrimental impacts on entrepreneurial activity due to social distancing and its effects on interaction, collaboration, and innovation. However, alternatives to personal contact now available thanks to digitalization, have not yet been examined. We expect entrepreneurial firms with more digitalized business models to show higher resilience to pandemic crises, especially those highly affected by globalization and more for non-family businesses than for family businesses. Based on a survey of German Mittelstand firms in the midst of the crisis induced by COVID-19, our findings broadly support our expectations and thus help qualify the Parasite Stress Theory of Values and contribute to a better understanding of organizational resilience in times of pandemic crises.

Two years of COVID-19 pandemic: Understanding the role of knowledge-based supply chains towards resilience through bibliometric and network analyses

Coronavirus disease (COVID-19) catastrophically disrupted most of the global supply chains (SC). Knowledge-based SC can cope with the pandemic disruptions by the efficient use of data, information, knowledge, human intelligence and emerging technologies. This article aims to critically analyse the SC research during the two years of COVID-19 pandemic to understand the role of knowledge-based supply chain towards SC resilience. A review of the 281 shortlisted articles is presented, along with bibliometric and network analyses in order to create an intellectual map of the domain and to identify the emerging knowledge themes. Bibliometric analysis reveals that the knowledge focus during this short span has migrated from COVID-19 pandemic to SC risk management and finally to risk mitigation strategies. The network analysis identifies five emerging knowledge themes, namely impact of COVID-19 on SC; SC risk mitigation and resilience; supply chain viability; sustainable SC strategies; and food SC. This review also elucidates the strategies to mitigate COVID-19 disruptions for incorporating resilience in SC. Future research directions for a knowledge-based sustainable-leagile-resilient (S-leagilient) supply chain have also been propounded.

Demand and Supply Disruptions During the Covid-19 Crisis on Firm Productivity

This paper explores the supply chain (SC) disruption impacts to the performance outcomes of a semiconductor company during the Covid-19 pandemic and proposes appropriate risk mitigation strategies to overcome the crisis. The research uses a single case study methodology and 24 SC employees from Belgium and Germany who take part in the survey. To measure the effect of SC disruptions to the firm's financial performance, some quarterly financial statement data are used from 2018 to 2021. The regression analysis results show that there is no significant impact of SC disruptions to the firm's productivity and non-financial performance. The paired samples t-test suggests that there is no significant change in the firm's financial performance before and during Covid-19 either due to the market's political and economic stability or the semiconductor company develops effective SC risk management strategies.

Remain or return? An empirical study of influencing factors on the return of Chinese international students during the COVID-19 pandemic

Background

COVID-19 is now a global public health crisis with unprecedented political, economic, and social consequences affecting nations across the world. It also has a profound impact on the mobility of international students. When the COVID-19 was under control in China, and it was spreading dramatically in the United Kingdom, Chinese international students studying in the United Kingdom have been caught in a double bind over whether to return home or not.

Objective

This study aims to explore the factors that influenced Chinese international students' choices of return during the COVID-19 pandemic when the COVID-19 was under control in China, while it was spreading dramatically in the United Kingdom.

Methods

Taking Chinese international students studying in the United Kingdom as an empirical case, this study used qualitative and quantitative research methods to explore the factors that influenced their choices of return. Based on the Rational Choice Theory and qualitative analysis of text data, this paper constructed the influencing factors model of returning to China. On this basis, we developed a questionnaire and collected data from 1,333 students in late April and early May 2020. Binary Logistic Regression with 95% CI for odds ratio (OR) was used to identify significant factors.

Results

The reserve of epidemic prevention supplies (OR = 0.712), transportation expenses (OR = 0.618), and quarantine expenses (OR = 0.702) negatively affected the return choice of overseas students. The supply of daily necessities (OR = 1.495), the anti-epidemic policy of the United Kingdom (OR = 1.684), and the demand for job hunting after graduation (OR = 1.661) had positive effects.

Conclusion

The institutional rationality had the biggest promoting effect, replaced development rationality, and became the most important factor for overseas students to return to China during the COVID-19 pandemic. Economic rationality, which has a significant negative effect, is the biggest obstacle to returning home. These conclusions have policy implications for governments' response to the COVID-19 epidemic and improvement of the quality of services for overseas students.

The role of Industry 4.0 technologies on performance measurement systems of supply chains during global pandemics: an interval-valued intuitionistic hesitant fuzzy approach

Purpose

This paper aims to investigate Supply Chain (SC) Performance Measurement Systems (PMSs) (SCPMSs) that are suitable and applicable to evaluate SC performance during unexpected events such as global pandemics. Furthermore, the contribution of Industry 4.0 Disruptive Technologies (IDTs) to implement SCPMSs during such Black Swan events is investigated in this study.

Design/methodology/approach

The research methodology is based upon a novel qualitative and quantitative mixed-method. A Systematic Literature Review (SLR) was initially employed to identify two complete lists of SCPMSs and IDTs. Then, a novel Interval-Valued Intuitionistic Hesitant-Fuzzy (IVIHF)-Delphi method was firstly developed in this paper to screen the extracted SCPMSs. Afterward, the Propriety, Economic, Acceptable, Resource, Legal (PEARL) indicator of the Hanlon method was innovatively applied to prioritize the identified IDTs for each finalized SCPMS.

Findings

Two high-score SCPMSs including the SC operations reference (SCOR) model and sustainable SCPMS were recommended to improve measuring the performance of the pharmaceutical SC of emerging economies such as Iran in which the societal, biological and economic issues were undeniable, particularly during unexpected events. Employing nine IDTs such as simulation, big data analytics, cloud technologies, etc., would facilitate implementing sustainable SCPMS from distinct perspectives.

Originality/value

This is one of the first papers to provide in-depth insights into determining the priority of contribution of IDTs in applying different SCPMSs during global pandemics. Proposing a novel multi-layer mixed-methodology involving SLR, IVIHF-Delphi, and the PEARL indicator of the Hanlon method is another originality offered by this paper.

Gender Differences in Enterprise Performance During the COVID-19 Crisis: Do Public Policy Responses Matter?

The COVID-19 crisis has introduced unique tradeoffs between health and economic risk, leading to a “life vs. livelihoods conundrum.” This study contributes to research on adversity and entrepreneurship by examining the implications of the pandemic for gender differences in enterprise performance. We further consider how public policy responses in the domains of public health and economic support moderate the potential gendered effects of the pandemic. Data analysis of more than 20,000 enterprises across 38 countries shows that women-owned enterprises were more adversely affected by the pandemic, and that stronger public health policy responses helped reduce the observed gap in performance.

Impact of the COVID-19 pandemic on accredited conformity assessment bodies: insights from a multinational study

The COVID-19 pandemic posed new and manifold challenges to organizations and their operations worldwide. Conformity assessment bodies (CABs), such as testing or medical laboratories, certification, and inspection bodies, were also affected by the associated disruptions. Their role in this crisis is highly relevant, as CABs are essential pillars of the quality infrastructure: their activities ensure that products and services meet requirements as defined in standards and regulations, thereby contributing to their safety and reliability. The question arises of how CABs and their operations were affected by the pandemic and how they responded. To this end, we present the results of an international survey of 986 CABs of all types in Germany, the UK, Italy, and New Zealand. Overall, CABs reported, on average, a reduction in demand for their services during the pandemic, facing restrictions in all countries. In addition, the pandemic had an overall negative impact on the CABs' investment and innovation activities. However, investments in digital infrastructure were increased as a countermeasure, with CABs reporting a higher need for digitalization. The paper highlights and discusses results from in-depth analyses relevant to policymakers and industry alike.

Towards the Next Decade of Industrie 4.0 – Current State in Research and Adoption and Promising Development Paths from a German Perspective

Considering the first ten years of Industrie 4.0 in Germany—the digital transformation of industry towards the goal of increased manufacturing productivity and mass customization—significant progress has been achieved. However, future efforts are required. This review first evaluates the status quo of implementation and research in Germany and finds that large-scale companies have proceeded faster than small- and middle-sized enterprises. Currently, regardless of their size, companies have in common a shortage of qualified specialists, coupled with a lack of adequate base technologies for Industrie 4.0 and an insufficient digital mindset. The creation of platform-based digital business models is particularly lagging behind, despite high research interest. This review subsequently identifies three research-driven fields of action that are particularly important for the future of Industrie 4.0: (1) resilience of value networks in the strategic area of sovereignty, (2) Open-Source as a driver for the strategic area of interoperability, and (3) the strategic combination of digitalization and sustainability as a basis for sustainable business models in the strategic area of sustainability.

Artificial Intelligence and Firm Performance: Does Machine Intelligence Shield Firms from Risks?

We estimate and compare the impact of the coronavirus pandemic (COVID-19) on the performance of Artificial Intelligence (AI) and conventional listed firms using stock market indices. The single-group and multiple-group Interrupted Time-Series Analyses (ITSA) with panel data were used with four interventions: when the news of COVID-19 spread and the pandemic entered the first, second, third, and fourth months (24 February 2020, 23 March 2020, 20 April 2020, and 18 May 2020, respectively). The results show that the negative impact of COVID-19 on the AI stock market was less severe than on the conventional stock market in the first month of the pandemic. The performance of the AI stock market recovered quicker than the conventional stock market when the pandemic went into its third month. The results suggest that the AI stocks were more resilient than conventional stocks when the financial market was exposed to uncertainty caused by the COVID-19 pandemic. The deployment of AI in firms serves as a resilient, crucial driver for sustainable performance in challenging environments. Observing the performance of AI-adopted firms is an interesting direction for technical and fundamental analysts. Investors and portfolio managers should consider an AI market index to minimize risk or invest in stocks of AI-adopted listed firms to maximize excess returns.

A Behavior-Simulated Spherical Fuzzy Extension of the Integrated Multi-Criteria Decision-Making Approach

Since its inception in 1965, fuzzy sets have been developed for many years and are widely used in multi-criteria decision making (MCDM) problems. Recently, spherical fuzzy sets (SFS), one of the most recent fuzzy sets, have been applied to extend and reinforce MCDM methods. To contribute to this development, the aim of this study is to propose a novel SFS extension of the integrated MCDM method that takes into account the psychological behavior of decision makers. In the proposed approach, the evaluation criteria are first weighted by the spherical fuzzy Decision-Making Trial and Evaluation Laboratory (SF DEMATEL) method based on symmetrical linguistic comparison matrices. Another notable advantage of this process is determining the interrelationship between the evaluation criteria. In the next stage, the spherical fuzzy Interactive Multi-Criteria Decision-Making method in the Monte Carlo simulation environment (SF TODIM’MC) was applied to evaluate the alternatives. This method allows the process of evaluating alternatives to be performed continuously with different psychological behavioral parameters, which are considered as asymmetric information. As a result, the influence of the decision maker’s psychological behavior on the evaluation results is analyzed comprehensively. The robustness of the proposed approaches is verified through their application to prioritizing post-COVID-19 operational strategies in the Vietnam logistics sector. Numerical results have provided a cause-and-effect relationship between the negative effects of the pandemic and their weights. Furthermore, the results of prioritizing the operational strategies in the simulated environment provide rankings corresponding to different levels of risk aversion. Based on the results, the proposed spherical fuzzy approach is promising for expert-based decision-making problems under psycho-behavioral influence.

Investigating the relationship between digital technologies, supply chain integration and firm resilience in the context of COVID-19

The outbreak of the COVID-19 pandemic has significantly augmented the complexity of information, adding to the challenges that firms face in effectively processing and grasping accurate information. As a result, the production uncertainty of firms has been seriously intensified during the pandemic, disrupting the normal operation of firms and their supply chains. Digital technologies serve as salient tools that help firms to process and analyse information, consequently enhancing firm resilience in the face of supply chain disruptions. This study aims to examine how digital technologies affect firm resilience in the context of COVID-19 through the lens of information processing theory and a large-scale survey conducted among Chinese manufacturers. Specifically, our study evaluates the mediating effect of supply chain integration (internal integration, customer integration and supplier integration) and the moderating effect of information complexity. The results show that supply chain integration plays a mediating role in the effect of digital technologies on firm resilience, and the mediation effect is particularly significant for customer integration. Furthermore, digital technologies have a stronger impact on firm resilience when information complexity is high. The findings advance our understanding and recognition of the resilience implications of digital technologies and provide important managerial implications for improving firm resilience in the context of COVID-19.

Managing supply chains during the Covid-19 crisis: synthesis of academic and practitioner visions and recommendations for the future

Purpose

The Covid-19 pandemic has created an environment of high uncertainty and caused major disruptions in supply chains. The new normal that has emerged during the pandemic is leading to a need to identify new solutions to improve supply chain crisis management in the future. Practitioners require adapted recommendations for solutions to implement. These recommendations are laid out in this paper.

Design/methodology/approach

A combination of a systematic literature review (SLR), qualitative semi-structured interviews and a questionnaire survey of supply chain practitioners is applied. The interviews provide insights into supply chain practitioners' views of their approaches and, together with the solutions proposed in the literature, provide future recommendations for action for supply chain managers.

Findings

During the pandemic, companies experienced disruptions in supply, production and demand, as well as interruptions in transportation and distribution. The majority of the solutions proposed in the literature, coincide with the opinions of practitioners. These include collaborative risk management, real-time monitoring and information sharing, supply network management, scenario planning and “what-if” simulations.

Research limitations/implications

Although the number of interviews conducted and questionnaires completed is limited, they still serve to supplement the SLR with important practical insights and recommendations.

Originality/value

This paper presents a review of recent academic literature focusing on the impact of Covid-19 on supply chains and the existing solutions to mitigate that impact and manage future crises. It has been expanded to include industry perspectives and experiences. The findings of this study present recommended practices and strategies for better managing supply chains during a crisis.

Analysis of the COVID-19 pandemic’s impacts on manufacturing: a systematic literature review and future research agenda

The COVID-19 pandemic has affected manufacturing companies and necessitated adaptations of firms’ operations. Despite the increasing interest in this subject, a scarcity of systematic analysis can be observed. The present study systematically reviews the existing research on the COVID-19 pandemic concerning the manufacturing industry. This paper aims to highlight the main impacts of the COVID-19 pandemic on the manufacturing sector from the operations management perspective, the practical adaptation actions, and future research opportunities. Open research questions and directions for further investigation are articulated and triangulated across organisational, process and technology perspectives.

Innovations in freight transport: a systematic literature evaluation and COVID implications

Purpose

This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed by researchers to study innovations and their implications in this industry. It analyses the role of transport and the impact of innovations during crises, such as COVID-19.

Design/methodology/approach

Qualitative and quantitative analysis of the innovations in freight transport unravels the pre-requisites of such endeavours in achieving a resilient and sustainable transport network that effectively and efficiently operates during a crisis. The authors performed keyword co-occurrence network (KCON) analysis and research focus parallelship network (RFPN) analysis using BibExcel and Gephi to determine the major resulting research streams in freight transport.

Findings

The RFPN identified five emerging themes: transport operations, technological innovation, transport economics, transport policy and resilience and disaster management. Optimisation and simulation techniques, and more recently, artificial intelligence and machine learning (ML) approaches, have been used to model and solve freight transport problems. Automation innovations have also penetrated freight and supply chains. Information and communication technology (ICT)-based innovations have also been found to be effective in building resilient supply chains.

Research limitations/implications

Given the growth of e-commerce during COVID-19 and the resulting logistics demand, along with the need for transporting food and medical emergency products, the role of automation, optimisation, monitoring systems and risk management in the transport industry has become more salient. Transport companies need to improve their operational efficiency using innovative technologies and data science for informed decision-making.

Originality/value

This paper advises researchers and practitioners involved in freight transport and innovation about main directions and gaps in the field through an integrated approach for evaluating research undertaken in the area. This paper also highlights the role of crisis, e.g. COVID-19, and its impacts on freight transport. Major contributions of this paper are as follows: (1) a qualitative and quantitative, systematic and effective assessment of the literature on freight transport through a network analysis of keywords supplemented by a review of the text of 148 papers; (2) unravelling major research areas; (3) identifying innovations in freight transport and their classification as technological and non-technological and (4) investigating the impact of crises and disruptions in freight transport.

Changes in the Innovation- and Marketing-Habits of Family SMEs in the Foodstuffs Industry, Caused by the Coronavirus Pandemic in Hungary

The economic specialties caused by the global coronavirus pandemic completely changed everyday life regarding certain sectors. For the small and medium enterprises, processing during the pandemic held several significant challenges, such as: cost-efficient operations, hardship of keeping employees, efficient management of innovation and various corporate activities, keeping the customers, etc. Many enterprises saw severe damages indirectly from the coronavirus pandemic, as society itself had its habits significantly changed, thereby necessitating changes in strategy for small and medium enterprises, most notably for local service providers and producers that have no delivery service. In order to solve the issue at hand, several governments tried applying a variety of solutions—mostly by financing the enterprises in question. The goal of the authors is to understand the current operation of innovation initiatives that small and medium enterprises have post-COVID-19, and to obtain a clear view on changes in marketing habits. Furthermore, the analysis concentrates on the following: the state of family SMEs dealing in foodstuffs, and how to create a future view for such members of the sector by identifying best practices. Using data collected during 2020 and 2021, and employing descriptive statistics and a conjoint analysis, the authors wished to see how the coronavirus pandemic affected SMEs, detect the changes in their marketing and innovation policy due to the pandemic, and help them create core business strategy via consumer feedback. Authors found that SMEs had to innovate by 2021 beyond their 2019 expectations, and that customers had partially validated their endeavors through their answers.

Decision-making framework for a resilient sustainable production system during COVID-19: An evidence-based research

This work presents a decision-making framework for integrating resilience and sustainability in managing production systems during COVID-19. An operationalization scheme manifested via a case study at a manufacturer in the food production sector supports the proposed framework. The focus is laid on the tactical and operational decisions within the production system. Through the discussion of the introduced changes to mitigate risks emanating from COVID-19, a set of findings related to the deployment of digital solutions, new dimensions of sustainability and resilience, the introduction of new workforce scheduling rules, the importance of alignment and coordination across supply chain members, and the approach of risk management are identified. This work contributes to a better understanding of the decision-making process during the pandemic and to building up knowledge for the management of resilient and sustainable production systems.

Shipping and Transportation Traffic of Medical and Non-Medical Goods Before and During COVID-19 in Oman

The transportation and logistics services have been severely disrupted starting from February 2020 due to precautionary measures of partial and complete lockdown taken by a number of countries to control the spread of COVID-19. The study aims to investigate the changes in the shipping and transportation traffic of medical and non-medical goods during and before the start of COVID-19 pandemic in Oman. The research question that will be addressed here is “Is there any significant difference in the volume of shipping and transportation traffic of medical and non-medical goods before and during COVID-19 in Oman?” The study applies the Wilcoxon Signed Rank Test and Friedman’s two way ANOVA on the data collected from 61 companies operating in Oman. The study found that the shipping and transportation traffic of both medical and non-medical goods decreased by 6.5% and 25.6% respectively during COVID-19. The higher percentage of decrease is noticeable in non-medical goods than the medical.

SMEs in Covid-19 Crisis and Combating Strategies: A Systematic Literature Review (SLR) and A Case from Emerging Economy☆

The paper intends to understand the research trends in “Covid-19 and SME” through a Systematic Literature Review (SLR) and extract themes to explore the most affected areas of SMEs during the Covid-19 pandemic. Subsequently, the study attempts to know the struggles of SME during Covid-19 crisis in a developing country . Furthermore, the study provides a critical dynamic resilience strategy framework to manage the SMEs in the crisis period. The authors extracted data from Scopus and Web of science to conduct a Systematic Literature Review (SLR), Extracted data from both databases were merged using R programming get the same tag in R programming. The study adopts a bibliometric analysis to present the research corpus in the domain of “Covid-19 and SMEs”. The cluster method of R programming has been used to usher the significantly affected areas of SMEs. Based on the cluster theme, an open-ended questionnaire was developed and used to interview 23 SMEs in Bangladesh for the case study. NVIVO-13.00 was used to extract the topic from the transcriptions of the interviews. The study reveals that Cash flow shortages and Supply Chain Disruptions are the critical constraints of SMEs. On the contrary, Digital transformation has gained momentum during this crisis. Enterprises that made the best use of digital platforms through technology, digital marketing, and innovations secured the peak of success and profitability. The study also recommends a critical dynamic, resilient strategy model to adopt in the "new normal" for successful navigation of SME business in the future. The study is the first of its kind that integrates SLR and a case study on the hurdles of SME owners during the Covid 19 crisis. Thus, it helps advance the understanding of the subject matter and enables the formulation of resilient strategies by policymakers and SME owners to navigate the business in any potential crisis in the future. The study has significant methodological contribution as it presents how to merge both Scopus and web of science data to conduct bibliometric analysis through R programming. Besides, it also contributes to using R’s clustering method to extract themes for “SME and Covid -19” domain. Finally, the study presents an overview of SMEs in crisis such as Covid-19 and a case study of a rising economy and its response measures. The Case study has been designed to concentrate on Bangladesh’s SME owners and practical implications potentially limited to Emerging Asian Economies.

Resilience in the supply chain management: understanding critical aspects and how digital technologies can contribute to Brazilian companies in the COVID-19 context

Purpose

The present study aims to identify the most critical elements of resilience in the management of supply chains of Brazilian companies and, in the sequence, debate possible digital technologies mentioned by literature to enhance them.

Design/methodology/approach

To identify the most critical elements, the information provided by qualified academics was used. Data analysis was performed through Cronbach’s alpha coefficient, hierarchical cluster analysis and Fuzzy TOPSIS approach.

Findings

Comparatively, the results pointed out three elements of resilience as the most critical in managing supply chains. They are the decision-making (understood as the definitions from the layout of the chain’s operations network to the choice of warehouse locations, distribution centres and manufacturing facilities), human resources (understood as management for human resources development and knowledge management through training) and security (understood as issues related to information technology for data security). For each of them, bibliographic research was performed to identify technologies that enhance these elements of supply chain management resilience.

Originality/value

The results presented here can significantly contribute to the expansion of debates associated with resilience in managing supply chains of Brazilian companies and directing researchers in the area.

Accelerated Aging Effect on Mechanical Properties of Common 3D-Printing Polymers

In outdoor environments, the action of the Sun through its ultraviolet radiation has a degrading effect on most materials, with polymers being among those affected. In the past few years, 3D printing has seen an increased usage in fabricating parts for functional applications, including parts destined for outdoor use. This paper analyzes the effect of accelerated aging through prolonged exposure to UV-B on the mechanical properties of parts 3D printed from the commonly used polymers polylactic acid (PLA) and polyethylene terephthalate–glycol (PETG). Samples 3D printed from these materials went through a dry 24 h UV-B exposure aging treatment and were then tested against a control group for changes in mechanical properties. Both the tensile and compressive strengths were determined, as well as changes in material creep characteristics. After irradiation, PLA and PETG parts saw significant decreases in both tensile strength (PLA: −5.3%; PETG: −36%) and compression strength (PLA: −6.3%; PETG: −38.3%). Part stiffness did not change significantly following the UV-B exposure and creep behavior was closely connected to the decrease in mechanical properties. A scanning electron microscopy (SEM) fractographic analysis was carried out to better understand the failure mechanism and material structural changes in tensile loaded, accelerated aged parts.

How is COVID-19 altering the manufacturing landscape? A literature review of imminent challenges and management interventions

Disruption from the COVID-19 pandemic has caused major upheavals for manufacturing, and has severe implications for production networks, and the demand and supply chains underpinning manufacturing operations. This paper is the first of its kind to pull together research on both-the pandemic-related challenges and the management interventions in a manufacturing context. This systematic literature review reveals the frailty of supply chains and production networks in withstanding the pressures of lockdowns and other safety protocols, including product and workforce shortages. These, altogether, have led to closed facilities, reduced capacities, increased costs, and severe economic uncertainty for manufacturing businesses. In managing these challenges and stabilising their operations, manufacturers are urgently intervening by-investing in digital technologies, undertaking resource redistribution and repurposing, regionalizing and localizing, servitizing, and targeting policies that can help them survive in this altered economy. Based on holistic analysis of these challenges and interventions, this review proposes an extensive research agenda for future studies to pursue.

A post-pandemic sustainable scenario: What actions can be pursued to increase the raw materials availability?

On January 30, 2020, COVID-19 outbreak, detected for the first time in Wuhan (China), was declared by WHO a Public Health Emergency. In a strongly connected world, the consequent slowdown of the Chinese economy contributed to disrupt the global supply chains of several products. In a post-pandemic scenario, the expected rapid increase in demand of critical raw materials (associated with the transition to more green energy sources), coupled with the problems that some mining activities are relegated only in certain countries and regions, must be considered in a sustainable perspective. This work analyses the literature about (critical) raw materials and COVID-19, not only to present the impact of the pandemic on their supply, but also to propose some actions that should be pursued in a post-pandemic renaissance scenario, to increase raw materials availability, with great attention to most critical ones, in the frame of circular economy principles. The post-pandemic possibilities are evaluated and suitable actions are suggested to secure the raw materials availability for the foreseen increase of investments in crucial and strategic sectors, in accord with the UN Sustainable Development Goals (SDGs). The proposed actions can be summarized as policy, strategy, economy, and technology activities.

The impact of artificial intelligence and digital style on industry and energy post-COVID-19 pandemic

The SARS-CoV-2 virus caused crises in social, economic, and energy areas and medical life worldwide throughout 2020. This crisis had many direct and indirect effects on all areas of society. In the meantime, the digital and artificial intelligence industry can be used as a professional assistant to manage and control the outbreak of the virus. The present article's objective is to investigate the effects of COVID-19 on each of the various fields of medicine, industry, and energy. What sets this article apart is studying the impact of artificial intelligence and digital style on reducing the damage of this fatal virus. Energy and related industries are of the areas affected by the SARS-CoV-2 virus. The most exciting approach in this article is to encourage countries with economies based on non-renewable energy to develop solar and wind energies. Renewable energies can operate well in the event of another phenomenon such as COVID-19 and reduce the virus's destructive effects and lead to economic prosperity.

An agent-based model for supply chain recovery in the wake of the COVID-19 pandemic

The current COVID-19 pandemic has hugely disrupted supply chains (SCs) in different sectors globally. The global demand for many essential items (e.g., facemasks, food products) has been phenomenal, resulting in supply failure. SCs could not keep up with the shortage of raw materials, and manufacturing firms could not ramp up their production capacity to meet these unparalleled demand levels. This study aimed to examine a set of congruent strategies and recovery plans to minimize the cost and maximize the availability of essential items to respond to global SC disruptions. We used facemask SCs as an example and simulated the current state of its supply and demand using the agent-based modeling method. We proposed two main recovery strategies relevant to building emergency supply and extra manufacturing capacity to mitigate SC disruptions. Our findings revealed that minimizing the risk response time and maximizing the production capacity helped essential item manufacturers meet consumers' skyrocketing demands and timely supply to consumers, reducing financial shocks to firms. Our study suggested that delayed implementation of the proposed recovery strategies could lead to supply, demand, and financial shocks for essential item manufacturers. This study scrutinized strategies to mitigate the demand-supply crisis of essential items. It further proposed congruent strategies and recovery plans to alleviate the problem in the exceptional disruptive event caused by COVID-19.

Surveying the impact of the coronavirus (COVID-19) on the poultry supply chain: A mixed methods study

The coronavirus pandemic (COVID-19) has affected all supply chains through severe disruption of logistics activities, production, and markets. This study aimed to survey the impact of the coronavirus on the poultry supply chain using an exploratory sequential mixed design. We first addressed those stages of the poultry supply chain disrupted in an ongoing pandemic, and then elaborated particular disturbances associated with each stage. This study was based on data collected from Iranian poultry industry owners and experts who had sufficient experience in agricultural supply chains as well. As the qualitative phase, the content analysis was conducted to identify the impacts of the coronavirus on the poultry supply chain. The results and conclusions that emerged from the qualitative phase were refined and weighted by the Fuzzy Delphi Method (FDM) and the Fuzzy Analytic Hierarchy Process (FAHP) respectively, in the quantitative phase. The results suggested that the pandemic has further affected the input supply as a stage in the poultry supply chain. This is probably because of the fact that the poultry industry is heavily dependent on inputs' flow. In addition, supply chain governance was seriously impaired due to the persistence of the pandemic. The coronavirus pandemic has significantly affected the stages that are most reliant on transportation. Finally, we found that a part of the disruptions that occur in the downstream of the supply chain is due to the epidemic's direct adverse effects, and another part is due to indirect consequences received from the upstream. Our findings and implications can be useful in decision-making procedures during ongoing epidemics.

Impact of COVID19 on Operational Activities of Manufacturing Organizations—A Case Study and Industry 4.0-Based Survive-Stabilise-Sustainability (3S) Framework

The SARS-CoV-2 pandemic is spreading rapidly and threatening lives all over the globe. Due to the pandemic, economies all over the world are in deep distress due to disruption in work and operations across all sectors. The present case study was performed for a private Indian manufacturing company that has been affected to a great extent due to this pandemic, as India has the second highest number of SARS-CoV-2 cases after the USA. The deeply troubled company’s current predicament is very complex, as various factors are responsible for the crisis. In order to restore the company back to normal functioning, these factors were studied and evaluated. A diagnostic survey was conducted to obtain data about current working conditions of company. Data from the survey were analyzed qualitatively and quantitatively to identify and evaluate the disruptive factors. Based on this analysis, problems in operational activities were identified and appropriate improvement actions (best practices) were proposed. Furthermore, the proposed improvement actions were assessed from a sustainability perspective to check their feasibility. The best practices framework was generalized to a three-step continuous improvement framework oriented around preparedness for future pandemic-like disruptions. The proposed framework may constitute an indication and set of best practices for consideration by other manufacturing companies that find themselves in a similar situation to the analyzed case study.

A COVID-19 Supply Chain Management Strategy Based on Variable Production under Uncertain Environment Conditions

The management of a controllable production in the manufacturing system is essential to achieve viable advantages, particularly during emergency conditions. Disasters, either man-made or natural, affect production and supply chains negatively with perilous effects. On the other hand, flexibility and resilience to manage the perpetuated risks in a manufacturing system are vital for achieving a controllable production rate. Still, these performances are strongly dependent on the multi-criteria decision making in the working environment with the policies launched during the crisis. Undoubtedly, health stability in a society generates ripple effects in the supply chain due to high demand fluctuation, likewise due to the Coronavirus disease-2019 (COVID-19) pandemic. Incorporation of dependent demand factors to manage the risk from uncertainty during this pandemic has been a challenge to achieve a viable profit for the supply chain partners. A non-linear supply chain management model is developed with a controllable production rate to provide an economic benefit to the manufacturing firm in terms of the optimized total cost of production and to deal with the different situations under variable demand. The costs in the model are set as fuzzy to cope up with the uncertain conditions created by lasting pandemic. A numerical experiment is performed by utilizing the data set of the multi-stage manufacturing firm. The optimal results provide support for the industrial managers based on the proactive plan by the optimal utilization of the resources and controllable production rate to cope with the emergencies in a pandemic.