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This paper aims to explore the underlying intention behind using blockchain technology (BLCT) in the agri-food supply chain (AFSC). This is achieved by using a conceptual framework based on technology acceptance models that considers various factors influencing user behavior toward implementing this technology in their practices.

The conceptual framework developed is empirically validated using structural equation modeling (SEM). A total of 258 respondents from agri-food domain in India were involved in this survey, and their responses were analyzed through SEM to validate our conceptual framework.

The findings state that food safety and security, traceability, transparency and cost highly influence the intention to use BLCT. Decision-makers of the AFSCs are more inclined to embrace BLCT if they perceive the usefulness of the technology as valuable and believe it will enhance their productivity.

This study contributes to the existing literature by providing thorough examination of the variables that influence the intention to adopt BLCT within the AFSC. The insights aim to benefit industry decision-makers, supply chain practitioners and policymakers in their decision-making processes regarding BLCT adoption in the AFSC.

This study investigates how decision-makers’ perceptions of BLCT influence their intention to use it in AFSCs, as well as the impact of the different underlying factors deemed valuable in the adoption process of this technology.

Production systems occupy geographically dispersed organizations with limited visibility and transparency. Such limitations create operational inefficiencies across the Supply Chain (SC). Recently, researchers have started exploring applications of Digital Twins Technology (DTT) to improve SC operations. In this context, there is a need to provide comprehensive theoretical knowledge and frameworks to help stakeholders understand the adoption of DTT. This study aims to fulfill the research gap by empirically investigating DTT readiness to enable transparency in SC.

A comprehensive literature survey was conducted to develop a theoretical model related to Supply Chain Transparency (SCT) and DTT readiness. Then, a questionnaire was developed based on the proposed theoretical model, and data was collected from Indian manufacturers. The data was analyzed using Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) to confirm the proposed relationships.

The findings from the study confirmed a positive relationship between DTT implementation and SCT. This study reported that data readiness, perceived values and benefits of DTT, and organizational readiness and leadership support influence DTT readiness and further lead to SCT.

This study contributes to the literature and knowledge by uniquely mapping and validating various interactions between DTT readiness and sustainable SC performance.

Managing supply chain risk is a crucial element in ensuring the long-term sustainability of any organization or industry. As such, identification of risks and deploying their mitigation strategies should be the focal point to sustain in the long run. The risks that are faced by food processing supply chains are gaining prominence, given more consumers requiring higher quality products while ensuring traceability. In essence, this research focuses on the supply chain risks and mitigation strategies in the spice industry of an emerging economy, Sri Lanka.

This paper integrates two popular multi-criteria decision-making (MCDM) techniques, such as the analytical hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess the supply chain risks and to derive their mitigation strategies for the spice industry.

Findings show that “inability to meet quality requirements” has been established as the most significant risk in the Sri Lankan spice industry. On the other hand, “vertical integration” (backward integration) has been discovered as the key mitigation strategy to ameliorate the effects of supply chain risks in this sector.

This study is exploratory, and more empirical data and statistical analyses are needed to further validate the outcomes of the study.

Despite being one of the largest trade exporters in Sri Lanka, the spice industry gets scant attention to the identification and mitigation of the risks. The authors explored the supply chain risks in the spice industry and then prioritized the suitable mitigation strategies using an integrated AHP-TOPSIS method.

The 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.

This 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.

The 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.

The 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.

This 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.

The purpose of this study is to investigate the barriers for implementing Lean Six Sigma (LSS) in small and medium-sized enterprises (SMEs) and present a framework that provides prioritized strategies to overcome the barriers.

The barriers and strategies are identified via a comprehensive literature review and validated by industry experts. The study uses the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS) to analyze the barriers and strategies for determining the prioritized list of strategies.

The findings reveal that there are sixteen barriers to LSS implementation in Indian SMEs. To overcome these barriers, this study reveals twelve strategies. The analysis shows that “effective management” is the most crucial strategy to overcome the barriers for implementing LSS in Indian SMEs.

This research guides SMEs practitioners to efficiently and effectively implement LSS, which, in turn, can enhance the performance of SMEs.

This study contributes to the literature by integrating the strategies with the barriers for implementing LSS in Indian SMEs. Besides, this study provides the prioritized list of strategies to overcome the barriers for implementing LSS in Indian SMEs.

The impacts of the novel coronavirus (COVID-19) outbreak continue to devastate supply chain operations. To attain a competitive advantage in the post-COVID-19 era, decision-makers should explore key supply chain strategies to move forward and ready their policies to be implemented when the crisis sufficiently subsides. This is a significant and practical decision-making issue for any supply chain; hence, the purpose of this study is to explore and analyse key supply chain strategies to ensure robustness and resilience in the post-COVID-19 era.

This study conducted an expert survey targeting practitioners and academics to explore key supply chain strategies as means of moving forward in the post-COVID-19 era. Further, the key strategies were quantitatively analysed by applying the best-worst method (BWM) to determine their priority importance in the context of the manufacturing sector.

The results revealed that supply chain resilience and sustainability practices could play a dominant role in this period. The findings of the study can assist supply chain decision-makers in their formulations of key strategies.

This is the first study to investigate key supply chain strategies for the post-COVID-19 era. This study will help practitioners paying attention to resilience and sustainability practices for managing the impacts of future large-scale disruptions.

A recent global pandemic, known as coronavirus disease 2019 (COVID-19), affects the manufacturing supply chains most significantly. This effect becomes more challenging for the manufacturers of high-demand and most essential items, such as toilet paper and hand sanitizer. In a pandemic situation, the demand of the essential products increases expressively; on the other hand, the supply of the raw materials decreases considerably with a constraint of production capacity. These dual disruptions impact the production process suddenly, and the process can collapse without immediate and necessary actions. To minimize the impacts of these dual disruptions, we aim to develop a recovery model for making a decision on the revised production plan.

In this paper, the authors use a mathematical modeling approach to develop a production recovery model for a high-demand and essential item during the COVID-19. The authors also analyze the properties of the recovery plan, and optimize the recovery plan to maximize the profit in the recovery window.

The authors analyze the results using a numerical example. The result shows that the developed recovery model is capable of revising the production plan in the situations of both demand and supply disruptions, and improves the profit for the manufacturers. The authors also discuss the managerial implications, including the roles of digital technologies in the recovery process.

This model, which is a novel contribution to the literature, will help decision-makers of high-demand and essential items to make an accurate and prompt decision in designing the revised production plan to recover during a pandemic, like COVID-19.

The recent pandemic caused by coronavirus disease 2019 (COVID-19) has significantly impacted the operational performances of pharmaceutical supply chains (SCs), especially in emerging economies that are critically vulnerable due to their inadequate resources. Finding the possible barriers that continue to impede the sustainable performance of SCs in the post-COVID-19 era has become essential. This study aims to investigate and analyze the barriers to achieving sustainability in the pharmaceutical SC of an emerging economy in a bid to help decision-makers recognize the most influential barriers.

To achieve the goals, two decision-making tools are integrated to analyze the most critical barriers: interpretive structural modeling (ISM) and the matrix of cross-impact multiplications applied to classification (MICMAC). In contrast to other multi-criteria decision-making (MCDM) approaches, ISM develops a hierarchical decision tool for decision-makers and cluster analysis of the barriers using the MICMAC method based on their driving and dependency powers.

The findings reveal that the major barriers are in a four-level hierarchical relationship where “Insufficient SC strategic plans to ensure agility during crisis” acts as the most critical barrier, followed by “Poor information structure among SC contributors,” and “Inadequate risk management policy under pandemic.” Finally, the MICMAC analysis validates the findings from the ISM approach.

This study provides meaningful insights into barriers to achieving sustainability in pharmaceutical SCs in the post-COVID-19 era. The study can help pharmaceutical SC practitioners to better understand what can go wrong in post-COVID-19, and develop actionable strategies to ensure sustainability and resilience in practitioners' SCs.