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The demand for the cold chain logistics of agricultural products was investigated through demand forecasting; targeted suggestions and countermeasures are provided. This paper aims to discuss the aforementioned statement.

A Markov-optimised mean GM (1, 1) model is proposed to forecast the demand for the cold chain logistics of agricultural products. The mean GM (1, 1) model was used to forecast the demand trend, and the Markov chain model was used for optimisation. Considering Guangxi province as an example, the feasibility and effectiveness of the proposed method were verified, and relevant suggestions are made.

Compared with other models, the Markov-optimised mean GM (1, 1) model can more effectively forecast the demand for the cold chain logistics of agricultural products, is closer to the actual value and has better accuracy and minor error. It shows that the demand forecast can provide specific suggestions and theoretical support for the development of cold chain logistics.

This study evaluated the development trend of the cold chain logistics of agricultural products based on the research horizon of demand forecasting for cold chain logistics. A Markov-optimised mean GM (1, 1) model is proposed to overcome the problem of poor prediction for series with considerable fluctuation in the modelling process, and improve the prediction accuracy. It finds a breakthrough to promote the development of cold chain logistics through empirical analysis, and give relevant suggestions based on the obtained results.

Generic business process models for the supply chain do not cover the specific requirements of the cold chain catering to the needs of temperature-sensitive, perishable goods. The purpose of this paper is to draft a reference model specific to the cold chain.

Following an object-oriented modeling approach, conceptual elements that have been synthesized from a literature review are transferred into the static view (object model) of the reference model. In addition, the reference model’s dynamic properties representing the business process view are outlined.

While a few atomic process steps are sufficient to model the cold chain’s dynamic properties, the complexity of the cold chain lies in the object model. The classes of the object model are highly interrelated and cover four domains: perishable product, information technology, infrastructure/equipment and regulatory framework. This technical approach is more adequate to the complex nature of cold chains than typical business process models.

In the present draft status, the reference model is limited by the pure conceptual approach of this paper. As it is in the nature of things for a draft of a reference model, case studies to challenge the draft and a discourse of experts are required before detailed specifications can be added or any software implementation can be started. It is expected that the reference model is able to substantially support further research on cold chain design and optimization.

The cold chain reference model is intended to be a standard toolbox for planning and evaluating cold chains. By integrating the technical, information technology and regulatory objects behind the business processes, it allows to design and analyze cold chains from a more holistic perspective.

To the best knowledge of the author, this paper is the first to outline a reference model for the cold chain that goes beyond the business processes.

This paper aims to improve operational efficiency and minimize accident frequency in cold storage facilities through adopting an effective occupational safety and health program. The hidden knowledge can be extracted from the warehousing operations to create the comfortable and safe workplace environment.

A fuzzy association rule-based knowledge management system is developed by integrating fuzzy association rule mining (FARM) and rule-based expert system (RES). FARM is used to extract hidden knowledge from real operations to establish the relationship between safety measurement, personal constitution and key performance index measurement. The extracted knowledge is then stored and adopted in the RES to establish an effective occupational and safety program. Afterwards, a case study is conducted to validate the performance of the proposed system.

The results indicate that the aforementioned relationship can be built in the form of IF-THEN rules. An appropriate safety and health program can be developed and applied to all workers, so that they can follow instructions to prevent cold induced injuries and also improve the productivity.

Because of the increasing public consciousness of occupational safety and health, it is important for the workers in cold storage facilities where the ambient temperature is at/below 10°C. The proposed system can address the social problem and promote the importance of occupational safety and health in the society.

This study contributes to the knowledge management system for improving the occupational safety and operational efficiency in the cold storage facilities.

Most 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).

A 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.

Four 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.

The 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.

While 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.

The purpose of this paper is to determine compatibility groups of different fruits and vegetables that can be stored and transported together based upon their requirements for temperature, relative humidity, odour and ethylene production. Pre-cooling which is necessary to prepare the commodity for subsequent shipping and safe storage is also discussed.

The methodology used in this journal is an attempt to form clusters/groups of storing together 43 identified fruits and vegetables based on four important parameters, namely, temperature, relative humidity, odour and ethylene production. An agglomerative hierarchical clustering algorithm is used to build a cluster hierarchy that is commonly displayed as a tree diagram called dendrogram. The same is further analyzed using K-means clustering to find clusters of comparable spatial extent. The results obtained from the analytics are compared with the available data of grouping fruits and vegetables.

This study investigates the usefulness and efficacy of the proposed clustering approach for storage and transportation of different fruits and vegetables that will eventually save huge investment made in terms of developing infrastructure components and energy consumption. This will enable the investors to adopt it for using the space more effectively and also reducing food wastage.

Due to limited research and development (R&D) data pertaining to storage parameters of different fruits and vegetables on the basis of temperature, relative humidity, ethylene production/sensitivity, odour and pre-cooling, information from different available sources have been utilized. India needs to develop its own crop specific R&D data, since the conditions for soil, water and environment vary when compared to other countries. Due to the limited availability of the research data, various multi-criteria approaches used in other areas have been applied to this paper. Future studies might be interested in considering other relevant variables depending upon R&D and data availability.

With the increase in population, the demand for food is also increasing. To meet such growing demand and provide quality and nutritional food, it is important to have a clear methodology in terms of compatibility grouping for utilizing the available storage space for multi-commodity produce and during transportation. The methodology used shall enable the practitioners to understand the importance of temperature, humidity, odour and ethylene sensitivity for storage and transportation of perishables.

This approach shall be useful for decision making by farmers, Farmer Producer Organization, cold-storage owners, practicing managers, policy makers and researchers in the areas of cold-chain management and will provide an opportunity to use the available space in the cold storage for storing different fruits and vegetables, thereby facilitating optimum use of infrastructure and resources. This will enable the investors to utilize the space more effectively and also reduce food wastage. It shall also facilitate organizations to manage their logistic activities to gain competitive advantage.

The proposed model would help decision makers to resolve the issues related to the selection of storing different perishable commodities together. From the secondary research, not much research papers have been found where such a multi-criteria clustering approach has been applied for the storage of fruits and vegetables incorporating four important parameters relevant for storage and transportation.

Since last few years, cold chain management (CCM) has gained growing interest among practitioners, policymakers, researchers and academicians. The purpose of this paper is to provide a review focused on food cold chain management (FCCM) over the last 16 years to identify state of the art in the literature, highlight research gaps and define appropriate research questions (RQs) for future research.

The paper analyzes the content of 89 research articles published on the topic of food cold chain (FCC) from 2001 to 2016 within different journals. The Scopus and Web of Science databases were taken into consideration to shortlist research articles. Henceforth, the authors scrutinized the FCC industry to offer some effective strategies to tackle the chain complexities. The authors also draw interwoven between FCC infrastructure, integration, stakeholders’ interest, value addition, partners’ performance and overall food cold chain performance (FCCP) into a conceptual framework.

This paper identifies four research gaps in the literature of FCC concerning the most popular approaches used for the FCCP measurement, the performance measurement metrics, the factors which negatively affect the FCCP and the main sustainability issues in FCC.

This study identifies RQs which represent possible areas of investigation to improve the body of the FCCP evaluation and management. Furthermore, the FCC practitioners, food authorities and researchers might find this review useful, as it draws a clear picture of research in the respective domain.

Monitoring the real-time temperature, humidity, and physical position status of goods is vital in the cold chain. Diverse logistics technologies and systems have been adopted in the cold chain for monitoring perishable goods. However, these technologies and systems are independent from each other. Data and information in them are not integrated so that information control is not effective. The paper aims to discuss these issues.

By integrating Internet of Things and tracking technologies, this paper proposes an intelligent tracking system, which is designed to achieve effective and fast live monitoring of goods in the cold chain at the lowest cost and with the largest network capacity and simplest protocols.

Structure and information platform design mechanism are introduced. The key part of this system is a wireless sensor network built on Zigbee. Wireless sensors located in cold storages or refrigerated trucks are able to collect and transmit live data quickly and efficiently.

Users of the proposed system can easily monitor goods transported in cold chains. In addition, the system assigns specific servers to save historical data for inquiries.

An optimal temperature monitoring is a prerequisite for cold chain management and thus for the production and supply of high quality and safe products as well as for the reduction of waste and economic losses. The aim of this paper is to identify and compare already existing temperature monitoring solutions in operation and novel temperature monitoring solutions with a view to their use for optimal temperature monitoring in meat supply chains. A special focus is placed on the identification and specification of challenges by the implementation of temperature monitoring systems which allow an optimal control of the temperature conditions in meat supply chains, as required by the new European food law.

The paper is a literature review of existing and novel temperature monitoring systems and challenges faced by the practical implementation of monitoring systems which allow continuous control of the temperature conditions in meat supply chains. First, the relevant literature relating to these aspects was examined and second, expert knowledge was applied with system developers of temperature monitoring and information management systems, participants in the meat supply chains and researchers

In the article different intra‐ as well as inter‐organisational challenges relating to the practical implementation of optimal temperature monitoring solutions have been identified and described.

The paper provides a holistic perspective of temperature monitoring solutions in meat supply chains. The challenges met when implementing temperature monitoring solutions have not been widely discussed in the literature. The proposed solutions to the specified challenges make an important contribution to developing guidelines for the implementation of optimal temperature monitoring systems in meat supply chains, resulting in improvements in food quality and safety.

A poor performance of the cold supply chain (CSC) may increase the loss of quality and potency of perishables and temperature-sensitive products that deteriorate the financial and environmental aspects of the same. The purpose of the current research work is to identify the critical performance factors (criteria) and their co-factors (sub-criteria) that are responsible for the performance measurement of CSC and suggest the best possible solutions (alternatives) to improve the same.

To achieve the objective of the research, a hierarchical model has been developed and analyzed using Analytic Hierarchy Process (AHP)-Fuzzy TOPSIS as a hybrid approach to obtain the severity weights of the identified criteria and prioritization toward their relative importance for the best possible alternatives.

Analysis reveals that the criteria “energy consumption” comes out to be the most critical criteria, and alternative “application of passive cold devices” is the most effective solution for improving the performance of CSC. Higher energy consumption leads to a higher rate of greenhouse gas (GHG) emissions increasing the global warming phenomenon, high operational cost and degradation of natural energy resources. The Application of Passive Cold Devices (PCDs) utilizes solar energy to operate the refrigeration units reducing the energy consumption, environmental and operating cost of CSC.

The research work provides several insights into the critical issues related to the CSC and suggests significant findings that enable the management and decision-makers to adopt these practices for performance evaluation and improvement of the same. The key findings of the work, such as “application of passive cold devices” and “application of IoT in cold chain logistics”, facilitate an improved platform to improve the CSC performance and proposed several directions that will enhance the merit of future research.

The presented study consolidates the various perspectives associated with CSC performance, explores the most critical criteria and proposes the best suitable cold chain practices for organizational growth. The work also provides an analytical analysis with the essence of practicalities and sensitivity analysis to support the robustness of the results. By enriching the literature and quantitative analysis of the new proposed model, this paper forms vast managerial and research implications in the field of CSC.

Blood cold chain (BCC) represents a system for preserving the blood during its journey from the donor to the ultimate transfusion site. Existing BCCs have many drawbacks related to information transparency and information security. Secured and real-time information sharing in BCC can bring several benefits. The purpose of this paper is to summarise the issues in typical BCCs and to explore the scope of blockchain in the management of BCCs.

Issues in the existing BCCs are identified through a narrative review. To explain the potential of blockchain in mitigating these issues, a blockchain-based traceability solution is demonstrated with respect to a particular BCC scenario. The BCC management system discussed in this study makes use of the Ethereum blockchain’s smart contract feature and internet of things (IoT) technology. The smart contract is written in the solidity programming language and tested and validated using the Remix integrated development environment.

BCCs are concerned with several issues both from technical and non-technical perspectives. Blockchain technology is capable of troubleshooting the issues in the existing BCCs. Combining blockchain and IoT technology enables real-time information sharing among the entities. The demonstration presented in this work depicts how the blockchain-based smart contract can support operations in a typical BCC.

This paper explores the scope of blockchain in BCCs through a demonstration. To get insights into its technical and economical feasibilities, further investigations are needed.

Blockchain-based traceability system presented in this work can be adopted in BCCs to ensure the quality of blood or blood products. Blockchain-based smart contracts can aid the BCCs to achieve a proper balance between blood shortage and outdating.