Guest editorial: Post-COVID-19 sustainable supply chain management in emerging markets

Since the early 2000s, emerging markets have become the heart of global supply chains hosting a large volume of industrial productions. The second article looked into the barriers to attaining sustainability in supply chain of the Bangladeshi pharmaceutical sector and developed a hierarchical structure of those barriers using interpretive structural modeling and MICMAC analysis. The eleventh article explored a new way to assess suppliers' suitability by considering pseudo-resilience factors to achieve SSC in the post-COVID-19 era using an analytical hierarchy process and R. It also provided a case study of three smartphone processor suppliers (Jessin et al., 2023).

Antecedents of digital supply chains for a circular economy: a sustainability perspective

PurposeA digital supply chain (DSC) positively enhances circular economy (CE) practices. However, what factors and conditions lead to the implementation of DSC for transitioning toward CE is not yet clear. Therefore, this study aims at identifying and subsequently analyzing the antecedents of DSC for CE.Design/methodology/approachThe study identifies major antecedents of DSC for CE to achieve sustainability objectives through literature review and expert opinions. In this study, 19 potential antecedents of DSCs for CE are established from the literature and suggestions from industry professionals. A trapezoidal fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is applied quantitatively to investigate the antecedents identified.FindingsConducted in the context of Indian automobile manufacturing industry, the findings of the study reflect that advanced information sharing arrangement, effective government policies for DSC and CE implementation and digitalizing the supply chains are the top three potential antecedents of DSC for a CE.Originality/valueIn the existing literature, few studies are specific to investigating the DSC and CE paradigm. The present study will help organizations develop a practical and integrated strategic approach that will foster DSC through improved knowledge of CE.

Sustaining circular economy practices in supply chains during a global disruption

PurposeCircular economy (CE) practices are critical to achieving sustainable development goals. However, the recent global disruption caused by the COVID-19 pandemic has significantly impacted sustainable practices. The literature shows a significant research gap in analyzing factors that sustain CE practices in supply chains during a global disruption. This study fills the research gap by developing a mix-method approach to analyze factors for sustaining CE practices during a global disruption.Design/methodology/approachTo fulfill the objectives of this study, the list of factors that sustain CE practices was first identified by conducting a literature review and finalized through an expert opinion survey. The survey finalized 18 different factors for sustaining CE practices. The finalized factors were further analyzed using the grey decision-making trial and evaluation laboratory (DEMATEL) method. The quantitative analysis confirmed the priority of the factors and their cause-and-effect relationships.FindingsThe results revealed that continued stakeholder pressure, retention of CE and sustainability culture, continued implementation of cleaner technology, feedback system and ongoing CE training for resilience issues are the top five factors that sustain CE practices during a global disruption. The study also revealed ten factors as belonging to the cause group and eight to the effect group.Originality/valueThis study contributes to the literature by exploring factors for sustaining CE practices during a global disruption. Moreover, the study's findings are important in real-life situations, as decision-makers can use the findings to formulate strategies for sustaining CE practices during future global disruptions.

A recovery planning model for online business operations under the COVID-19 outbreak

This study analytically develops a new recovery planning optimisation model for managing the impacts of the recent COVID-19 outbreak for online business operations. Firstly, a mathematical model for the ideal plan is designed and then extended to generate a recovery plan in a finite planning horizon that maximises total profit. Recovery plans are generated considering two scenarios, namely the dynamic and uncertain situations. For the dynamic situation, a realistic system with time-dependent and dynamic demand, supply, and warehouse capacity for investigating the impacts of the COVID-19 outbreak is developed using several measures, such as collaborating with emergency suppliers, increasing warehouse capacity, and considering back-orders and lost sales to form recovery strategies. For the uncertain situation, demand, supply, and warehouse capacities are considered as uncertain variables. Further, an innovative solution approach using an adapted differential evolution technique, which is capable of (i) generating long-term recovery plans and (ii) solving both small- and large-scale problems, is developed. The results are illustrated using numerical analyses and simulation experiments. A sensitivity analysis is also conducted. In practice, the proposed optimisation model will assist the decision-makers of online business operations facing the COVID-19 outbreak to decide the optimal recovery plans.

Operational challenges during a pandemic: an investigation in the electronics industry

PurposeThe recent coronavirus disease 2019 (COVID-19) pandemic poses numerous challenges to supply chains. This pandemic is quite unique when compared to previous epidemic disruptions and has had a severe impact on supply chains. As a result, the operational challenges (OCs) caused by COVID-19 are still unknown among practitioners and academics. It is critical to comprehensively document current OCs so that firms can plan and implement strategies to overcome them. Consequently, this study systematically identifies and ranks COVID-19-related OCs.Design/methodology/approachThis study uses an integrated methodology combining expert interviews and the best-worst method (BWM) to analyze the results. The data have been collected from the electronics industry of Bangladesh, an emerging economy. This study also conducts a sensitivity analysis to check the robustness of the results.FindingsThe results reveal 23 COVID-19-related OCs under five categories: sourcing, production and inventory management, demand management and distribution, return management and after-sales service, and supply chain-wide challenges. The quantitative investigation reveals that overstock in finished goods inventory, low end-customer demands, order cancellations from dealers and retailers, high inventory holding costs and lack of transportation are the top five OCs.Practical implicationsThe findings will help practitioners to understand the OCs and allow them to prepare for future major disruptions and formulate long-term strategies for operations during and after the COVID-19 pandemic.Originality/valueThis study contributes to the literature on supply chain complexity and challenges by considering a major pandemic outbreak. Moreover, the study also contributes to the knowledge on emerging economies, which have been largely neglected in the current literature.

Strategic drivers to overcome the impacts of the COVID-19 pandemic: implications for ensuring resilience in supply chains

The recent coronavirus (COVID-19) pandemic has affected the manufacturing industry's entire supply chain system. It is important to investigate the strategic drivers to deal with the impacts of COVID-19 in the manufacturing industry. Accordingly, this study aims to identify the strategic drivers to overcome the impacts of the COVID-19 pandemic and improve the resiliency of the Bangladeshi footwear industry, an emerging economy. The strategic drivers are identified after reviewing research papers, reports, blogs, and discussions on social media platforms. The main drivers and their respective sub-drivers are finalized by discussing with domain experts. To offer strategic plans for building resiliency, it is crucial to know the importance of the main drivers and sub-drivers;therefore, the best–worst method is applied to determine the priority importance of the strategic drivers. The findings indicate that the top five drivers to defeat the impacts of COVID-19 are "high capability of reconfigurability,” "enhance the relationship with suppliers,” "develop health protocols to continue manufacturing,” "government support through incentives, subsidy, tax rebate, etc.,” and "set a policy to stable material supply”. Based on the findings, this study also provides practical implications with proposed research themes for policymakers and operations managers towards mitigating the impacts of the COVID-19 pandemic. The study's contribution is unique and important for the footwear supply chain as the research on COVID-19 in the context of resiliency focusing on the footwear supply chain is non-existent.

Benchmarking sustainable E-commerce enterprises based on evolving customer expectations amidst COVID-19 pandemic.

The 2019 coronavirus disease (COVID-19) pandemic has seriously impacted the performance of all types of businesses. It has given a tremendous structural boost to e-commerce enterprises by forcing customers to online shopping over visiting physical stores. Moreover, customer expectations of the digital and operational capabilities of e-commerce firms are also increasing globally. Thus, it has become crucial for an e-commerce enterprise to reassess and realign its business practices to meet evolving customer needs and remain sustainable. This paper presents a comprehensive performance evaluation framework for e-commerce enterprises based on evolving customer expectations due to the COVID-19 pandemic. The framework comprises seven primary criteria, which are further divided into 25 sub-criteria, including two sustainability factors, namely, environmental sustainability and carbon emissions. The evaluation approach is then practically demonstrated by analyzing the case of three Indian e-commerce firms. The results are obtained using a multi-criteria decision-making (MCDM) method, namely, Fuzzy VIKOR, to capture the fuzziness of the inherent decision-making problem. Further, numerical analysis is conducted to evaluate and rank various e-commerce enterprises based on customer expectations and satisfaction benchmarks. The findings explain the most important criteria and sub-criteria for e-commerce businesses to ensure customer expectations along with their economic and environmental sustainability.

An integrated framework for digitalization of humanitarian supply chains in post COVID-19 era

Digital Supply Chains (DSCs) are transforming industries across various domains. Digitalization can improve coordination, increase data collection and retention capacities, enhance funding mechanisms, and improve operational performance and resource utilization. However, DSC adoption is constrained by lack of funding, operational complexities, infrastructure issues, etc. Thus, the need emerges to explore the digitalization process in the Humanitarian Supply Chain (HSC) and provide a comprehensive solution that can ease the adoption of DSC. In this study, a framework is created to facilitate the digitalization process of HSC in post COVID-19 era. Nineteen related drivers are identified with the potential to digitalize the HSC. The drivers are identified via a literature review and finalized with the assistance of industry experts. A Principal Component Analysis is performed to obtain the most relevant drivers from the identified list. A Kappa analysis is adopted to perfect the priority map of the digitalization drivers based on developing consensus between the experts. Further, the neutrosophic DEMATEL methodology is adopted to prioritize the potential drivers and find their dependency on each other. The results indicate that the most influential drivers fall under the operational and technological categories. However, the social drivers have the potential to play a significant role in HSC digitalization. In addition, the study presents strategies for enhancing funds collection and data management using emerging technologies. These strategies can assist HSC decision-makers in formulating relevant policies and strategic interventions.

Modeling the artificial intelligence-based imperatives of industry 5.0 towards resilient supply chains: A post-COVID-19 pandemic perspective.

The recent COVID-19 pandemic has significantly affected emerging economies' global supply chains (SCs) by disrupting their manufacturing activities. To ensure business survivability during the current and post-COVID-19 era, it is crucial to adopt artificial intelligence (AI) technologies to renovate traditional manufacturing activities. The fifth industrial revolution, Industry 5.0 (I5.0), and artificial intelligence (AI) offer the overwhelming potential to build an inclusive digital future by ensuring supply chain (SC) resiliency and sustainability. Accordingly, this research aims to identify, assess, and prioritize the AI-based imperatives of I5.0 to improve SC resiliency. An integrated and intelligent approach consisting of Pareto analysis, the Bayesian approach, and the Best-Worst Method (BWM) was developed to fulfill the objectives. Based on the literature review and expert opinions, nine AI-based imperatives were identified and analyzed using Bayesian-BWM to evaluate their potential applicability. The findings reveal that real-time tracking of SC activities using the Internet of Things (IoT) is the most crucial AI-based imperative to improving a manufacturing SC's survivability. The research insights can assist industry leaders, practitioners, and relevant stakeholders in dealing with the impacts of large-scale SC disruptions in the post-COVID-19 era.

Assessing strategies to mitigate the impacts of a pandemic in apparel supply chains

The COVID-19 pandemic has taught global businesses that a pandemic can put business dynamics in unforeseeable turbulence. The disruptions created by the pandemic in the apparel industry exposed the vulnerabilities of apparel supply chains (SCs). To recover the supply chain impacts (SCIs) during an unprecedented event such as the COVID-19 pandemic, apparel SCs need a robust framework that can identify, measure, and mitigate the severity of SCIs by assessing effective mitigation strategies. This study identifies 12 critical SCIs in apparel SCs during a pandemic and 17 mitigation strategies. To assess SCIs and mitigation strategies, a modified grey-based bi-level analytical network process (ANP) is proposed to deal with the complex relationship between the SCIs and mitigation strategies. A real-life case study is conducted from an apparel supply chain for validation purposes. The findings suggest that policymakers in apparel SCs should prioritize implementing government policies and financial aid to deal with increased material and operational costs, the sudden surge in the unemployment rate, cancellation of orders and delayed payment, and increased transportation costs during a pandemic. This study also contributes to the literature by providing a robust decision-making framework for practitioners to deal with the complexity of SCs during future pandemics.

Modeling a sustainable vaccine supply chain for a healthcare system.

This study develops a vaccine supply chain (VSC) to ensure sustainable distribution during a global crisis in a developing economy. In this study, a multi-objective mixed-integer programming (MIP) model is formulated to develop the VSC, ensuring the entire network's economic performance. This is achieved by minimizing the overall cost of vaccine distribution and ensuring environmental and social sustainability by minimizing greenhouse gas (GHG) emissions and maximizing job opportunities in the entire network. The shelf-life of vaccines and the uncertainty associated with demand and supply chain (SC) parameters are also considered in this study to ensure the robustness of the model. To solve the model, two recently developed metaheuristics-namely, the multi-objective social engineering optimizer (MOSEO) and multi-objective feasibility enhanced particle swarm optimization (MOFEPSO) methods-are used, and their results are compared. Further, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model has been integrated into the optimization model to determine the best solution from a set of non-dominated solutions (NDSs) that prioritize environmental sustainability. The results are analyzed in the context of the Bangladeshi coronavirus disease (COVID-19) vaccine distribution systems. Numerical illustrations reveal that the MOSEO-TOPSIS model performs substantially better in designing the network than the MOFEPSO-TOPSIS model. Furthermore, the solution from MOSEO results in achieving better environmental sustainability than MOFEPSO with the same resources. Results also reflect that the proposed MOSEO-TOPSIS can help policymakers establish a VSC during a global crisis with enhanced economic, environmental, and social sustainability within the healthcare system.

Strategic drivers to overcome the impacts of the COVID-19 pandemic: implications for ensuring resilience in supply chains

The recent coronavirus (COVID-19) pandemic has affected the manufacturing industry’s entire supply chain system. It is important to investigate the strategic drivers to deal with the impacts of COVID-19 in the manufacturing industry. Accordingly, this study aims to identify the strategic drivers to overcome the impacts of the COVID-19 pandemic and improve the resiliency of the Bangladeshi footwear industry, an emerging economy. The strategic drivers are identified after reviewing research papers, reports, blogs, and discussions on social media platforms. The main drivers and their respective sub-drivers are finalized by discussing with domain experts. To offer strategic plans for building resiliency, it is crucial to know the importance of the main drivers and sub-drivers;therefore, the best–worst method is applied to determine the priority importance of the strategic drivers. The findings indicate that the top five drivers to defeat the impacts of COVID-19 are “high capability of reconfigurability,” “enhance the relationship with suppliers,” “develop health protocols to continue manufacturing,” “government support through incentives, subsidy, tax rebate, etc.,” and “set a policy to stable material supply”. Based on the findings, this study also provides practical implications with proposed research themes for policymakers and operations managers towards mitigating the impacts of the COVID-19 pandemic. The study’s contribution is unique and important for the footwear supply chain as the research on COVID-19 in the context of resiliency focusing on the footwear supply chain is non-existent.

A mathematical model for managing the multi-dimensional impacts of the COVID-19 pandemic in supply chain of a high-demand item.

The COVID-19 pandemic has wreaked havoc across supply chain (SC) operations worldwide. Specifically, decisions on the recovery planning are subject to multi-dimensional uncertainty stemming from singular and correlated disruptions in demand, supply, and production capacities. This is a new and understudied research area. In this study, we examine, SC recovery for high-demand items (e.g., hand sanitizer and face masks). We first developed a stochastic mathematical model to optimise recovery for a three-stage SC exposed to the multi-dimensional impacts of COVID-19 pandemic. This allows to generalize a novel problem setting with simultaneous demand, supply, and capacity uncertainty in a multi-stage SC recovery context. We then developed a chance-constrained programming approach and present in this article a new and enhanced multi-operator differential evolution variant-based solution approach to solve our model. With the optimisation, we sought to understand the impact of different recovery strategies on SC profitability as well as identify optimal recovery plans. Through extensive numerical experiments, we demonstrated capability towards efficiently solving both small- and large-scale SC recovery problems. We tested, evaluated, and analyzed different recovery strategies, scenarios, and problem scales to validate our approach. Ultimately, the study provides a useful tool to optimise reactive adaptation strategies related to how and when SC recovery operations should be deployed during a pandemic. This study contributes to literature through development of a unique problem setting with multi-dimensional uncertainty impacts for SC recovery, as well as an efficient solution approach for solution of both small- and large-scale SC recovery problems. Relevant decision-makers can use the findings of this research to select the most efficient SC recovery plan under pandemic conditions and to determine the timing of its deployment.

Sustainable Assessment in Supply Chain and Infrastructure Management

Assessing sustainability in supply chain and infrastructure management is important for any organization in the competitive business environment or public domain. Public buildings such as higher education institutions are responsible for a substantial portion of energy consumption and anthropogenic greenhouse gas (GHG) emissions. Roukouni et al. (contribution twelve) developed truck platooning and multi-sided digital platforms games for barge transportation, both improving the sustainability of hinterland transportation. Besides these studies, Özdemir et al. (contribution thirteen) assessed the efficiency of the operations strategy matrix in the healthcare system amid COVID-19.

Enablers for resilience and pandemic preparedness in food supply chain

The recent COVID-19 pandemic has caused enormous disruptions to supply chain (SCs). Border restrictions forced countless businesses to close either permanently or temporarily. However, the food industry is an essential sector that needs to be operational during a pandemic. Although the food industry has proactively worked towards fulfilling human needs, the food supply chain (FSC) faced numerous challenges, forcing SC managers to rethink their business strategy to cater to consumer demands effectively. In a pandemic situation, manufacturing operations need to repurpose and adapt to produce different high-demand products. Resilience initiatives help fight disruption phases in an uncertain environment by building capacity to resist and recover to a better position. This study identifies 14 key enablers to develop a resilient FSC and reveals the most significant enablers in India. We used a hybrid Delphi-interpretive structural modeling (ISM) and Fuzzy decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) methodology to achieve these goals. The Delphi technique identified essential enablers, while the ISM analyzed the interrelationship among enablers and level of importance in a hierarchical structural model. Finally, the Fuzzy-DEMATEL categorized the enablers into the cause-effect group. This study helps SC decision-makers recognize the enablers and the contextual and causal relationships to improve resilience initiatives. It also helps them repurpose their manufacturing operations and shift to other highly required and high-demand production.

Guest editorial

[...]the consequences of the COVID-19 pandemic may go beyond the merely economic performance and affect supply chain viability (Ivanov, 2020b), posing the questions of supply chain resiliency, sustainability, recovery and reconfigurability (Paul et al., 2021a, b;Cheramin et al., 2021). [...]this special issue published seven articles in the area of sustainable recovery in supply chains. The second article explored 13 critical sustainable recovery measures for transportation systems and found that efficient traffic management, sustainability-focused policies, sensitization of stakeholders, financial support and adoption of 4 R practices are important for a sustainable recovery in freight transportation systems (Dwivedi et al., 2021).

Supply chain viability in the context of COVID-19 pandemic in small and medium-sized enterprises: implications for sustainable development goals

PurposeThe recent outbreak of the coronavirus disease 2019 (COVID-19) pandemic has severely disrupted the operations of global supply chains (SCs) providing an opportunity for decision-makers to rethink and tune their existing strategies. To tackle the impacts caused by such a pandemic, this study aims to examine the contextual relations among the factors influencing supply chain viability (SCV) for achieving long-term Sustainable Development Goals (SDGs).Design/methodology/approachA decision-aid approach by integrating Pareto analysis, grey theory and total interpretive structural modeling (TISM) has been propounded. The proposed approach examines contextual relations among the factors for SCV for small and medium-sized enterprises (SMEs) in an emerging economy. This study contributes to theory, methodology and practice by exploring a new research problem in the context of the SCV and COVID-19 pandemic and by developing a new decision-aid approach.FindingsThe findings reveal that the creation of SC digital twin and transformation of SCs to supply networks would help the policymakers to deal with the “new normal.” Also, SC crowdfunding and policy development for health protocols are critical driving factors influencing SCV.Originality/valueThis research work is perhaps one of few initial attempts to advance the theoretical and practical understanding of SCV and to achieve SDGs in industries following a pandemic risk.

Supply chain recovery challenges in the wake of COVID-19 pandemic.

The COVID-19 pandemic has revealed the fragility of global supply chains arising from raw material scarcity, production and transportation disruption, and social distancing. Firms need to carefully anticipate the difficulties during recovery and formulate appropriate strategies to ensure the survival of their businesses and supply chains. To enhance awareness of the issues, this research aims to identify and model recovery challenges in the context of the Bangladeshi ready-made garment industry. A Delphi-based grey decision-making trial and evaluation laboratory (DEMATEL) methodology was used to analyze the data. While the Delphi method helped identify the major supply chain recovery challenges from the impacts of the COVID-19 pandemic, the grey DEMATEL approach helped categorize the causal relationships among these challenges. Of the 23 recovery challenges finalized, 12 are causal challenges. The study's findings can assist decision-makers in developing strategic policies to overcome the recovery challenges in the post-COVID-19 era.