A Review of Artificial Intelligence Applications in Cold Chain and Reverse Logistics

In recent years, sustainable supply chain management has gained increasing attention, and greenhouse gas (GHG) emissions throughout supply chains have been identified as one of the most important sustainability issues. This paper presents an investigation of the problem of transshipment among distribution centers (DCs) in a cold supply chain to achieve sustainable inventory cross-filling. Although transshipment is an effective tool for supply chain pooling, the possibility of increased GHG emissions raises environmental concerns. This study establishes a sustainable cold-chain logistics model that considers GHG emissions from DC storage and transshipment trucks. The new sustainable cold-chain model also reflects laden status and cargo weights of trucks for accurate emission assessment. An optimization model is also developed to minimize both GHG emissions and costs in the cold chain. Numerical simulations are conducted for diverse problem cases to examine important problem characteristics. The result analysis identifies that inventory service levels and demand variability have a strong impact on GHG emissions in transshipment; small p-values in the statistical analysis verify the significance of this effect. The different effects of demand variability and service levels on each emission source are also analyzed. The results demonstrate that transshipment among DCs can effectively reduce both GHG emissions and costs in cold supply chains. This study provides useful models and tools to assess GHG emissions and optimize decisions for the design and operation of transshipment. The proposed models will enable the assessment of sustainable alternatives and achieve sustainability objectives effectively for cold supply chains.

The global cold chain logistics market is witnessing a significant upswing, driven by the rising demand for perishable food products and increasing shipment volumes worldwide. Technological advancements are leading to a more intelligent and digitally enabled cold chain logistics system. However, the high loss rate of fresh agricultural products in China poses a significant threat to the country's food security. Therefore, it is imperative to explore innovative solutions, such as blockchain, to address the challenges of traditional cold chain logistics. In this paper, inspired by the prospect theory and evolutionary game theory, we propose an evolutionary game model to analyze the behavioral strategies of the tripartite of n-level cold chain participants, consumers, and government. Using MATLAB software, the numerical simulation of the game path of this tripartite theory is conducted, and the influence of variable parameters on the evolutionary process and outcomes of the system is analyzed. The results the following: (1) The development of an effective cold chain supply chain system can be divided into three stages, and blockchain technology plays a pivotal role in creating a seamless cold chain environment. The cost of blockchain adoption, government rewards, as well as penalties can significantly influence the behavioral choices of the three stakeholders. (2) The behavior of individual cold chain participants has a strong negative externality, which can impact the behavior of others. We also find that the larger the scale of the cold chain, the lower the probability of default by the participants. (3) The government's adoption of blockchain technology and the implementation of effective incentive policies can foster the successful development of the cold chain blockchain infrastructure. Our research contributes to the theoretical understanding of cold chain logistics decision making and policy creation for the tripartite stakeholders, including cold chain participants, consumers, and government. Our findings can serve as a valuable reference for scientific decision making and policy formulation to encourage the development of a robust cold chain supply chain system.

As a country where two-thirds of its territory consists of oceans, the fisheries sector is one of the government's main programs. Fisheries, which is also an agricultural subsector, has great potential in developing the country's economy, which is shown by the increasing number of fisheries production from year to year. The increase in the production of fishery products, both raw and processed materials, must be balanced with an effective and efficient distribution system method to ensure the quality of the fish remains in good condition. Good distribution management of fish products by controlling product temperatures that remain low throughout the distribution process is known as cold supply chain management. This requires cold supply chain management to be handled well because it has a controlling effect on fisheries logistics costs. Some of the facts above are the background for this research through analysis of the logistics cost structure, including the obstacles faced by the cold chain supply chain for caught fish and the cold chain business prospects and obstacles faced by this industry. Analysis of the distribution process also involves a review of the refrigerated transport fleet. The methodology used in this study is a mix method which begins with the development and distribution of questionnaires related to logistics operations and fishing costs. Next, data collection was carried out through interviews with fishermen, collectors and traders on the north and south coasts of Java Island.

PurposeMost of the extant literature on resilience builds on normative, conceptual or silo approaches, thereby lacking an integrative approach to cold chain logistics risks (CCLRs) and resilience. The purpose of this paper is to bridge the current research gap by developing a model, based on broad empirical evidence, of the interplay between CCLRs, resilience and firm performance (FP) in perishable product supply chains (PPSCs).Design/methodology/approachA mixed method approach is used with qualitative data from interviews and quantitative data from a survey across the supply chain. The analysis is framed by contingency theory and resource-based theory.FindingsFour significant sources of CCLRs and six resources used to build resilience are identified. Then, supply chain resilience (SCR) as a moderator of the negative relationship between CCLRs and FP is corroborated.Practical implicationsThe findings will help improve managerial understandings of critical sources of risks in cold chain logistics and resources indispensable to build resilience. The scope of the research is cold chain logistics for PPSCs, which has relevance to other cold supply chains as well.Originality/valueWhile some theoretical frameworks suggest resilience being a moderator in the negative relationship between cold chain risks and a firm’s performance, this study empirically tests this relationship using the survey across the entire supply chain. A new empirically and theoretically driven definition of SCR is also developed.

Food wastage is a critical issue as it adds to the problem of global food shortage. Cold supply chain, which helps preserve the freshness of postharvest fresh food from source until they are purchased by the consumers, can be an effective means to mitigate the problem. Owing to fragmented operation and lack of coordination, deficiency, abuse or fluctuation in temperature control along the cold chain is quite common. Absence of clear and consistent guidelines for material handling across the entire cold chain also leads to bruising, rotting, aging, and wilting of fruit and vegetables thereby increasing wastage. This study attempts to review thoroughly the extant literature on cold chain issues and supply chain collaboration with a view to developing a collaboration framework for cold chain underpinned by appropriate management theories. It is expected that collaboration among firms in a cold chain, if it proves successful, will help meet temperature specifications at every point in the chain thereby minimizing damage and ensuring quality of product. It will also enhance overall efficiency and responsiveness of the cold chain through optimization and lead time reduction. These improvements can significantly reduce wastage of fruit and vegetables delivered via cold chain and lessen the problem of global food shortage.

Purpose Digital technologies offer substantial opportunities for enhancing operational efficiency; however, their precise roles in managing cold chains – especially long-distance logistics – remain unclear. Cold chains are vulnerable to various risks that can jeopardize food safety and diminish the food supply. This study employs resource-based theory to investigate how technologies and capabilities can improve cold chain performance and overall organizational effectiveness. Design/methodology/approach Using the partial least square – structural equation model (PLS-SEM), the research analyzed responses from a survey of 243 multinational and local firms operating in South and Southeast Asia. Findings The findings suggest that, although many organizations utilize technologies for traceability and data analysis, their impact on cold chain performance is limited. Companies often face challenges in effectively integrating these technologies at both operational and tactical levels. Additionally, the study highlights inadequate technology adoption across the supply chain, leading to significant fragmentation in information exchange among partners. This fragmentation not only drives up operational costs but also results in poorly coordinated and disconnected cold chains, resulting in higher food loss and waste. Practical implications This research provides practical guidance for cold chain managers to prioritize the adoption of IoT and data analytics capabilities (DAC) for improved efficiency and risk mitigation. It highlights the need for standardized technologies and enhanced collaboration to meet global compliance and market access goals. Additionally, it offers policymakers actionable insights to improve food security and logistics performance through targeted technology implementation. Originality/value This research contributes to the growing body of knowledge on digital cold chains, offering valuable insights for policymakers and scholars. The results can inform national logistics strategies and encourage practitioners to enhance technology adoption by focusing on developing capabilities beyond simple investments. Such advancements could improve food security and study.

PurposeThere is a large number of perishable foodstuffs produced, stored, distributed and delivered daily around the world. Almost all except for root vegetables are sensitive products to temperature. Thus, adopting uninterrupted and appropriate logistics activities with predetermined range of temperature from production site until end-user is critical for ensuring required quality and safety. If a mistake is made during either transport or storage, it not only becomes risky for human health, but also generates huge food waste for the environment and negative economic impact for food providers. Therefore, this study aims to identify all potential factors affecting the cold chain performance in the food industry and to design a framework that includes these factors. This framework is also a roadmap for managers, food providers and logistics parties for sustainable cold chain management.Design/methodology/approachConsidering, tangible and intangible potential criteria, the ultimate goal of this study is to identify potential criteria affecting cold food chain performance and propose a conceptual framework including 12 main criteria. Next, the importance order of each criterion and the causal relationships between them are determined. In this study, this relationship among criteria is analyzed by using fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL) approach because of its ability to solve complex problems by ensuring causal relationship among factors, additionally to determine importance order. Finally, suggestions for administrative implications are presented.FindingsFuzzy DEMATEL was used to explain the causal link and importance order among identified drivers. The analysis shows that five criteria (C1, C3, C8, C9 and C12) belong to cause (influential) groups and remaining seven criteria belong to effect (influenced) groups. The highest influential criterion is staff (C8) and is followed by technical issues (C9) as the second most influential factor. Additionally, top three most important factors are traceability (C7), staff (C8) and cold transportation (C5). According to the numerical results of fuzzy DEMATEL implementations, suggestions for managerial implementations are presented.Practical implicationsThe main contribution of the study is to propose meaningful suggestions for managerial implications about sustainable cold chain in food industry for businesses and to examine causal relations between criteria and to rank criteria in descending importance order.Originality/valueTo the best of the authors’ knowledge, this is the first study that focuses on determining the potential criteria affecting cold supply chain performance both theoretically and empirically in the sustainability environment. What are the enablers that affect the cold food supply chain stages is the research question of this study.

Sustainability is becoming increasingly important as a topic in general supply chains and cold chains. This study addresses the critical need for an integrated and comprehensive approach to supply chain design that simultaneously maximizes cost efficiency and incorporates environmental sustainability, focusing specifically on cold chains. Prior research has identified a gap in existing studies, highlighting the absence of an overarching framework from the logistics providers’ perspective. Our novel mathematical programming model introduces a unique strategy that carefully balances environmental concerns and cost optimization, addressing the shortcomings found in previous works. By integrating variables related to distribution, transportation, and inventory management, the model aims to minimize overall expenses and environmental impact, specifically regarding energy consumption and carbon emissions. We formulate and solve the optimization problem through rigorous mathematical programming, offering a flexible solution applicable to various logistics scenarios. The results demonstrate a significant reduction in overall expenses and environmental effects, providing logistics providers with a powerful tool for informed decision-making and sustainable supply chain management. This research contributes to the evolving field of supply chain sustainability by presenting a practical and effective model for maximizing cost savings while promoting environmental responsibility. The study concludes with compelling statistics, revealing a noteworthy decrease in overall expenses by €25 128 146.73 (100.25%) and environmental impact by 17 359.39 (100.04%). The outcomes show a notable decrease in general expenses and environmental effects, giving logistics providers a strong instrument for wise choices and sustainable supply chain management.

PurposeThe purpose of this paper is to give an up-to-date and structured insight into the literature published during the past decade on sustainable green supply chain management. It also suggests trends for future research based on the research issues identified through systematic and comprehensive analysis of previous studies in the area of green and sustainable supply chain management.Design/methodology/approachA state-of-the-art literature review is carried out by systematically collecting the existing literature over a period of 10 years (2005-2014) and categorizing it on the basis of attributes such as stages in supply chain, methodology and the industries/sectors under consideration. The classification of literature is also done according to the geographic region and year of publication.FindingsThere has been an increased interest among researchers and practitioners in the area of sustainable green supply chain management in the past decade. A need for achieving sustainability through adoption of greener practices has been universally felt, owing to an increasing environmental and ecological complexity. The review reveals that there exists a need to address behavioural issues like human resource management and supply chain partner relationship management. Moreover, reverse logistics, closed-loop supply chain management and waste management are areas that need special focus to achieve environmental sustainability.Research limitations/implicationsThe current review focuses on research trends in the past 10 years only. Moreover, papers from only good quality, peer-reviewed journals are considered in the study.Originality/valueMost of the previous reviews have either focused on specific issues related to sustainable supply chains only or green supply chains. The present study collectively takes into consideration papers both from green supply chain management as well as from sustainable supply chain literature that have a prime focus on environmental sustainability.

The tuna agro-industrial cold supply chain faces complex challenges. The implementation of cold chains has economic, social, and environmental implications. Breaking the cold chain directly reduces tuna quality. To overcome these challenges, an effective and efficient cold chain management method that focuses on the aspects of risk, performance, value chain, and sustainability is required. This study aimed to analyze the methods used in cold chain management and develop an integrated framework to increase the effectiveness and efficiency of sustainable cold supply chain management in tuna agro-industries. This study uses a systematic literature review (SLR) approach. Scientific article search databases using Scopus, Google Scholar, and others in 2013-2023. The selection resulted in 86 articles for further studies. The results of this study show that there are still very few cold chain studies in the tuna agro-industry. Cold chain studies on risk, performance, and sustainability aspects are dominated by quantitative methods with the following percentages: 76%, 58%, and 92%, respectively. By contrast, studies on the value chain aspect are dominated by descriptive qualitative methods (89%). This study found that the tuna cold chain problem in Indonesia is a soft problem on the upstream side and a hard problem on the downstream side. These two properties are rarely considered in single cold chain studies. The properties of the soft and hard systems were studied using qualitative and quantitative methods, respectively. In future research, we will develop an integrated framework for tuna agro-industry cold chain management in terms of performance, risk, value chain, and sustainability by considering the soft and hard aspects of the cold chain from onboard the ship to the consumer.

PurposeThe purpose of the paper is to identify the multiple types of data that can be collected and analyzed by practitioners across the cold chain, the ICT infrastructure required to enable data capture and how to utilize the data for decision making in cold chain logistics.Design/methodology/approachContent analysis based literature review of 38 selected research articles, published between 2000 and 2016, was used to create an overview of data capture, technologies used for collection and sharing of data, and decision making that can be supported by the data, across the cold chain and for different types of perishable food products.FindingsThere is a need to understand how continuous monitoring of conditions such as temperature, humidity, and vibration can be translated to support real-time assessment of quality, determination of actual remaining shelf life of products and use of those for decision making in cold chains. Firms across the cold chain need to adopt appropriate technologies suited to the specific contexts to capture data across the cold chain. Analysis of such data over longer periods can also unearth patterns of product deterioration under different transportation conditions, which can lead to redesigning the transportation network to minimize quality loss or to take precautions to avoid the adverse transportation conditions.Research limitations/implicationsThe findings need to be validated through further empirical research and modeling. There are opportunities to identify all relevant parameters to capture product condition as well as transaction data across the cold chain processes for fish, meat and dairy products. Such data can then be used for supply chain (SC) planning and pricing products in the retail stores based on product conditions and traceability information. Addressing some of the above research gaps will call for multi-disciplinary research involving food science and engineering, information technologies, computer science and logistics and SC management scholars.Practical implicationsThe findings of this research can be beneficial for multiple players involved in the cold chain like food processing companies, logistics service providers, ports and wholesalers and retailers to understand how data can be effectively used for better decision making in cold chain and to invest in the specific technologies, which will suit the purpose. To ensure adoption of data analytics across the cold chain, it is also important to identify the player in the cold chain, which will drive and coordinate the effort.Originality/valueThis paper is one of the earliest to recognize the need for a comprehensive assessment for adoption and application of data analytics in cold chain management and provides directions for future research.

With the continuous improvement of people’s quality of life and tremendous changes in consumption concepts, people’s demand for fresh agricultural products is increasing, which has led to a huge gap in the supply of fresh agricultural products logistics. In recent years, frequent food quality and safety issues have attracted the attention of consumers and have been highly valued by the country, making enterprises deeply aware of the importance of the refrigeration supply chain. However, the traditional cold chain supply of agricultural products is far from being able to meet the strict quality requirements of food for consumers in terms of production, processing, storage, transportation and sales. Therefore, how to improve the efficiency of the product refrigeration supply chain, reduce logistics costs, and ensure product freshness and quality assurance has become the focus and difficulty of establishing a cold chain supply chain business. This article is based on the analysis and design of the intelligent cold chain logistics simulation model under the Internet of Things technology. Firstly, the literature research method is used to summarize the problems of the intelligent cold chain logistics under the Internet of Things technology and the advantages of the intelligent cold chain logistics under the Internet of Things technology. The feasibility of the intelligent cold chain logistics simulation model under the Internet of Things technology, and then through the analysis of the cold chain logistics process unit and organization, the modeling is carried out based on the analysis results.

Warehouses play a significant role in cold chains as they do for regular supply chains. Although their goals are the same for both cold chains and regular supply chains, the operations of cold warehouses are more sophisticated since the cost of operation is considerably higher due to energy consumption and obsolesce of products in substandard conditions. Recently, there has been an enormous interest in the cold food supply chain to reduce food waste occurring along the chain. Hence, efficient management of cold warehouses becomes an important issue in this direction. Design and operation requirements in a cold warehouse may be different from a traditional non-cold warehouse. In this paper, we aim to provide an overview of cold chain operations, mostly by focusing on cold warehouse operations. We provide some statistics from a cold chain, design, and technology requirements for cold warehouses as well as warehouse operations shaped according to that warehouse features. It is observed that there are quite different design parameters in cold storage.KeywordsWarehouse operationsCold supply chainCold warehouseTechnologies for cold chain

Collaboration in a supply chain continuously proves its role in increasing the performance of supply chains, which attracts the attention of both academia and practitioners, specifically, how to generate higher impacts of collaborative partnership on the performance of supply chains and measure them. In cold supply chains of agriculture and foods, the vital need for collaboration becomes even more significant to improve the performance. Therefore, this paper reviews relevant articles derived from the Web of Science and Scopus databases. Via the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), the research team classifies the types of collaborative partnership in cold agriculture and food supply chains, issues of the literature when analyzing collaboration impacts on the performance of CSCs of agriculture and foods, and finally, the opportunities for the future research to boost the collaboration practices in these cold chains. Following this sequence, 102 articles were eventually extracted for the systematic review to identify themes for not only addressing the review questions but also highlighting future research opportunities for both development of partnership integration and performance of the cold chains of agriculture and foods.

This study applies Actor-Network Theory (ANT), Resource-Based View (RBV), and Closed-Loop Supply Chain (CLSC) Theory to investigate the integration of Internet of Things (IoT) and blockchain technology for sustainable waste management in cold chain food supply chains. Using a case study of Company A, supported by datasets such as the Time-Temperature Data and the Google Cloud Blockchain Dataset, the research evaluates how IoT sensors and blockchain systems monitor waste and enhance operational efficiency across supply chain stages. Findings reveal that IoT-enabled real-time monitoring significantly reduces waste by addressing temperature deviations, while blockchain enhances traceability and accountability through immutable record-keeping and smart contracts. The combined application of these technologies demonstrates substantial waste reduction potential, particularly in transportation and distribution stages, aligning with sustainability objectives such as the UN Sustainable Development Goals. This research provides both theoretical and practical contributions to the adoption of digital tools in sustainable supply chain management.