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The literature review shows research gaps into the food supply chain design. In that context, this paper deals with the design of a sustainable supply chain. A multi-objective mixed-integer linear programming model includes four decisions and three sustainable criteria (economic—total network costs—, environmental—carbon emissions—, and social—work conditions and societal development—). The model aims to determine the optimal location and capacity of processing and distribution facilities, to choose the suppliers from a set of potential candidates, to determine transportation modes between all the actors, and to define the quantity of product, in order to satisfy the demand of dairy products in a set of regions. The applicability of the model is tested in a realistic case in the dairy sector in the central region of Colombia. The results show the existent trade-offs between the three dimensions of sustainability. The unweighted balance results, giving more priority to the social dimension, which obtains the least deviation, affecting the environmental performance of the chain. The analysis carried out in this paper does help decision-makers that will have at hand a set of possible configurations to be chosen in order to comply with environmental and social regulations without neglecting economic performance. [ABSTRACT FROM AUTHOR]

Global warming, climate change, and social problems are the worst human-induced sustainability issues that economies across the globe have witnessed. Water pollution, greenhouse effect, poor working conditions, child labour and lack of coordination among channel partners have caused the considerable interruptions in the supply chain network. The purpose of the paper is to identify critical factors affecting behavioural and sustainable supply chain coordination and evaluate strategies for risk reduction in the supply chain coordination in the context of digitization. This study purposes a novel supply chain coordination framework which consists of four themes such as system, actor, objective and action on which the success or the failure of supply chain can be contingent. Our study integrates multi-criteria decision approach using Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to investigate factors that affected the behavioural and sustainable supply chain coordination in the context of digitization. The Fuzzy-AHP method qualified to hierarchically rank the factors based on the relative fuzzy weightage while Fuzzy-DEMATEL established the inter-relationships among the factors and classified them into cause and effect groups. The findings of our study identified the Environmental performance and decarbonization as the most significant factor and the speed to market as the least important factor in developing behavioural and sustainable supply chain coordination in the context of digitization. Our analysis from Fuzzy AHP-DEMATEL approach reveal that the social preferences (power balance, reciprocity, fairness) is a significant causal factor which can effectively abolish the issues plaguing behavioural and sustainable supply chain coordination in the context of digitization. The results from our study aim to facilitate decision makers in cultivating a sustainable supply chain framework that can boost trust among the channel partners environmental performance, social performance and channel efficiency of the supply chain, thereby ensuring sustainability and socio welfare of all the supply chain. [ABSTRACT FROM AUTHOR]

The coronavirus (COVID-19) outbreak shows that pandemics and epidemics can seriously wreak havoc on supply chains (SC) around the globe. Humanitarian logistics literature has extensively studied epidemic impacts; however, there exists a research gap in understanding of pandemic impacts in commercial SCs. To progress in this direction, we present a systematic analysis of the impacts of epidemic outbreaks on SCs guided by a structured literature review that collated a unique set of publications. The literature review findings suggest that influenza was the most visible epidemic outbreak reported, and that optimization of resource allocation and distribution emerged as the most popular topic. The streamlining of the literature helps us to reveal several new research tensions and novel categorizations/classifications. Most centrally, we propose a framework for operations and supply chain management at the times of COVID-19 pandemic spanning six perspectives, i.e., adaptation, digitalization, preparedness, recovery, ripple effect, and sustainability. Utilizing the outcomes of our analysis, we tease out a series of open research questions that would not be observed otherwise. Our study also emphasizes the need and offers directions to advance the literature on the impacts of the epidemic outbreaks on SCs framing a research agenda for scholars and practitioners working on this emerging research stream. [ABSTRACT FROM AUTHOR]

Research on the development of sustainable supply chain models is highly active nowadays. Merging the concept of supply chain management with sustainable development goals, leads to simultaneous consideration of all economic, environmental and social factors. This paper addresses the design of a sustainable closed-loop supply chain including suppliers, manufacturers, distribution centers, customer zones, and disposal centers considering the consumption of energy. In addition, the distribution centers play the roles of warehouse and collection centers. The problem involves three choices of remanufacturing, recycling, and disposing the returned items. The objectives are including the total profit, energy consumption and the number of created job opportunities. As far as we know, these objectives are rarely considered in a sustainable closed-loop supply chain model. The proposed model also responds to the customer demand and also addresses the real-life constraints for location, allocation and inventory decisions in a closed-loop supply chain framework. Another novelty of this research is to develop a set of efficient Lagrangian relaxation reformulations and fast heuristics for solving a real-world numerical example. The results have revealed that the obtained solution is feasible and the developed solution algorithm is highly efficient for solving supply chain models. Finally, a comprehensive discussion is provided to highlight our findings and managerial insights from our results. [ABSTRACT FROM AUTHOR]

The pandemic and a series of subsequent disruptive events fully exposed the vulnerability of supply chains. Research in the field of resilience in supply chain risk management has recorded significant interest across a wide range of academic disciplines. Therefore, there is a need to synthesize, categorize and explain existing and newly emerging research directions, which may represent relevant platforms for developing supply chain concepts in the future. This study addresses this need by providing a bibliometric review of published papers on resilience in supply chain risk management. By analyzing more than 2500 published papers through bibliometric and machine-learning-based methods, we identified ten topics related to risk and resilience of supply chains: Pandemic impacts of food supply chain; Practices for capability and performance; Supplier-related modeling and optimization; System security and critical infrastructure; Production changes; IT in manufacturing process; Sustainability in global economy; Management and business approach; Modeling and design of complex networks; Operational strategies for risk mitigation. By analyzing articles published since 2020, we also identified a change in the direction of research dedicated to supply chain risk and resilience; we identified three other topics that were not recognized as distinct topics prior to 2020—Operational management; strategy; Sustainable production. The results of this study help in understanding the change in the direction of research in the area of risk and resilience of supply chains and thus provide up-to-date information for further research in this dynamically developing area. [ABSTRACT FROM AUTHOR]

Digitalisation is expected to transform end-to-end supply chain operations by leveraging the technical capabilities of advanced technology applications. Notwithstanding the operations-wise merits associated with the implementation of digital technologies, individually, their combined effect has been overlooked owing to limited real-world evidence. In this regard, this research explores the joint implementation of Artificial Intelligence (AI) and Blockchain Technology (BCT) in supply chains for extending operations performance boundaries and fostering sustainable development and data monetisation. Specifically, this study empirically studied the tuna fish supply chain in Thailand to identify respective end-to-end operations, observe material and data-handling processes, and envision the implementation of AI and BCT. Therefore, we first mapped the business processes and the system-level interactions to understand the governing material, data, and information flows that could be facilitated through the combined implementation of AI and BCT in the respective supply chain. The mapping results illustrate the central role of AI and BCT in digital supply chains' management, while the associated sustainability and data monetisation impact depends on the parameters and objectives set by the involved system stakeholders. Afterwards, we proposed a unified framework that captures the key data elements that need to be digitally handled in AI and BCT enabled food supply chains for driving value delivery. Overall, the empirically-driven modelling approach is anticipated to support academics and practitioners' decision-making in studying and introducing digital interventions toward sustainability and data monetisation. [ABSTRACT FROM AUTHOR]

Big data analytics research in humanitarian supply chain management has gained popularity for its ability to manage risks. While big data analytics can predict future events, it can also concentrate on current events and support preparation for future events. Big data analytics-driven approaches in humanitarian supply chain management are complicated due to the presence of multiple barriers. The current study aims to identify the leading barriers; further categorize them and finally develop the contextual interrelationships using the Fuzzy Total Interpretive Structural Modeling (TISM) approach. Sustainable humanitarian supply chain management research is in nascent stage and therefore, Fuzzy TISM is used in this study for theory building purpose and answering three key questions-what, how and why. Fuzzy TISM shows some key transitive links which provides enhanced explanatory framework. The TISM model shows that the fifteen barriers achieved eight levels and decision-makers must aim to remove the foundational barriers to apply big data analytics in sustainable humanitarian supply chain management. Fuzzy TISM were synthesized to develop a conceptual model and this was statistically validated considering a sample of 108 responses from African based humanitarian organizations. Findings suggest that organizational focus is required on implementing modern management practices; second, more emphasis is required on infrastructure development and lastly, improvement is required on quality of information sharing as these variables can influence sustainable humanitarian supply chain management. Finally, the conclusions and future research directions were outlined which may help stakeholders in sustainable humanitarian supply chain management to eliminate the BDA barriers. [ABSTRACT FROM AUTHOR]

This study explores the operational characteristics of supply chain operations during disaster scenarios within Bangladesh and the profound impact of disruption risks due to poor operational effectiveness and structural dynamics within the supply chain network. Via the analysis of representative case studies and interviews with over 500 stakeholders, we identify and analyse the many structural and administrative complexities and subsequent disruption risks surrounding the utilisation of traditional supply chain infrastructures for emergency disaster scenarios. The findings illustrate the severe impact of poor demand estimation, inadequate selection of supply items, bureaucratic and extended chain of administration, poor central coordination among the participating organizations, absence of interoperability, poor infrastructure, and lack of information sharing. We propose a new emergency supply chain infrastructure to mitigate these threats offering contribution to the literature as well as support to disaster relief efforts within Bangladesh. [ABSTRACT FROM AUTHOR]