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Due to the importance of quality to customers, this study considers criteria of quality and profit and optimizes both in a multi-echelon cold chain of perishable agricultural products whose quality immediately begins to deteriorate after harvest. The two objectives of the proposed cold chain are to maximize profit and quality. Since postharvest quality loss in the supply chain depends on various decisions and factors, in addition to strategic decisions, the authors consider the temperature setting in refrigerated facilities and transportation vehicles due to the unfixed shelf life of the products which is related to the temperature found by Arrhenius formula.

The authors use bi-objective mixed-integer nonlinear programming to design a four-echelon supply chain. The authors integrate the supply chain echelons to detect the sources and factors of quality loss. The four echelons include supply, processing, storage and customer. The decisions, including facility location, assigning nodes of each echelon to corresponding nodes from the adjacent echelon, allocation of vehicles to transport the products from farms to wholesalers, processing selection, and temperature setting in refrigerated facilities, are made in an integrated way. Model verification and validation in the case study are done based on three perishable herbal plants.

The model obtains a 29% profit against a total cost of 71 and 93% of original quality of the crops is maintained, indicating a 7% quality loss. The final quality of 93% is the result of making a US$6m investment in the supply chain, including the procurement of high-quality raw materials; facility establishment; high-speed, high-capacity vehicles; location assignment; processing selection and refrigeration equipment in the storage and transportation systems, helping to maximize both the final quality of the products and the total profit.

The proposed supply chain model should help managers with modeling decisions, especially when it comes to cold chains for agricultural products. The model yields these results – optimal location-allocation decisions for the facilities to minimize distances between the network nodes, which save time and maintain the majority of the products’ original quality; choosing the most appropriate processing method, which reduces the perishability rate; providing high-capacity, high-speed vehicles in the logistics system, which minimizes transportation costs and maximizes the quality; and setting the right temperature in the refrigerated facilities, which mitigates the postharvest decay reaction rate of the products.

Comparison of the results of the present research with those of the traditional chain (obtained through experts) shows that since the designed chain increases the profit as well as the final quality, it has benefits for the main chain stakeholders, which are customers of agricultural products. This study model is expected to have a positive impact on the environment by placing strong emphasis on quality and preventing excessive waste generation and air pollution by imposing a financial penalty on extra demand production.

Since profit and quality of the final product are two important factors in all cultures and communities, the proposed supply chain model can be used in any food industry around the world. Applying the proposed model induces growth in local industries and promotes the culture of prioritizing quality in societies.

To the best of the authors’ knowledge, this is the first research on a bi-objective four-echelon (supply, processing, storage and customer) postharvest supply chain for agricultural products including that integrates transportation logistics and considers the deterioration rate of products as a time-dependent variable at different levels of decision-making.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

The aim of this paper is to provide a review of state-of-the-art literature on information sharing in the context of African perishable agri-food supply chains (AFSCs). In doing so, the authors hope to stimulate further research and advance both theory and practice on African perishable AFSCs, which is a relevant, but under-investigated context.

The authors’ systematic literature review covers a period of 21 years (2000–2021). After providing the bibliometric and methodological insights related to this sample of literature, the authors provide a detailed analysis and discussion of the key aspects of information sharing in African perishable AFSCs, based on a review framework grounded in the information sharing literature.

The authors’ review revealed that information sharing in African AFSCs is still in its nascent stage. Findings are based on four themes of (1) why share information (mainly to gain market access), (2) what information is shared (price and market information) (3) how it is shared (still traditional communication, with limited adoption of digital technologies?) and (4) antecedents, drivers and barriers (technology adoption and socio-economic background of Africans).

This paper outlines a research agenda for advancing the theory on information sharing in AFSCs. Furthermore, the review highlights the importance of context, supply chain structure, relationships, product characteristics and culture in studying AFSCs.

A review on information sharing in African perishable AFSCs does not appear to exist in operations and supply chain management (O&SCM) and agribusiness journals.

Ineffective management inventory of medical products such as blood and vaccines can create severe repercussions for hospitals, clinics or medical enterprises, such as surgery delays and postponements. Inventory sharing is a form of horizontal collaboration that can provide solutions to key actors of the healthcare supply chain (HSC), yet no prior study reviewed this topic.

This study conducts a systematic literature review of thirty-nine inventory-sharing studies in the context of HSCs published from 2012 until early 2022. The descriptive and thematic analyses include chronological distribution, geographical location, comparison between developed/developing regions, stakeholder and incident analysis.

Thematic analysis classified inventory sharing among five product supply chains (blood, medical supplies, medicines, vaccines and generic medical products). Benefits include shortage reduction, cost minimisation, and wastage mitigation. Barriers include (1) IT infrastructure, (2) social systems, (3) cost and (4) supply chain operations. Perishable inventory policies include Fresher-First (FF), Last-Expire-First-Out (LEFO), First-In-First-Out (FIFO) and First-Expire-First-Out (FEFO). The analysis also showed differences between developed and developing countries. The study identifies several future research opportunities that include (1) product utilisation rate, (2) cost reductions, (3) shortage mitigation and (4) waste reduction.

No prior study has systematically reviewed inventory sharing in HSCs to reveal benefits, barriers, patterns and gaps in the current literature. It makes five propositions and develops a research model to guide future research. The study concludes with theoretical and managerial implications.

Cold supply chain technology is critical for extending the shelf life of perishable leafy green vegetables. This study aims to investigate the concept of managing leafy green products using cold supply chain technology and visualise the findings.

Using expert interviews and data visualisation approaches, this study examines how organisations deal with the complexity of cold supply chain processes and networks. Thematic data analysis was conducted. Two types of software were used to accomplish the research objectives. The first software used AntConc version 3.5.8 with word frequency (N-gram) analysis, whereas the second software, VOSViewer offered co-occurrence network visualisation and cluster analysis.

The findings show that the appropriate design of cold chain technology is critical in ensuring the freshness and quality of leafy green vegetables. The primary goal of managing the complexity of the cold supply chain is to achieve product freshness and energy efficiency. Regardless of the importance of energy efficiency, cold supply chains require warehouse management solutions for transportation and storage.

This study found that proper design and selection of appropriate technology in the cold supply chain have driven the companies to improve the firms’ competitive advantage while delivering the best quality of perishable leafy green food products. In addition, the freshness, quality, safety, and health of leafy green vegetables will be determined by the company’s capacity to handle long-distance transportation and select the appropriate distribution channels and storage. Warehouse management system technology was found to be secondary compared to cold chain technology, although distribution and warehousing practices are critical for supply chain performance.

This study has established the conceptual indicators based on best practices and outcomes for the cold supply chain. This study argued that cold supply chain management and performance should be monitored independently. Furthermore, the theory of technological adoption can be expanded to include product nature as a driver. Finally, this study has established cold chain best practices based on a perishable supply chain perspective. The findings of this study can promote healthy foods to solve zero hunger and achieve sustainable development goals. Although this study demonstrates that technology improves supply chain practises, cold storage and logistics benefit the most from technological advancements. In contrast, non-cold supply chains benefit from technology-driven improvements in performance.

Natural disasters cause serious operational risks and disruptions, which further impact the food supply in and around the disaster-impacted area. Resilient functions in the supply chain are required to absorb the impact of resultant disruptions in perishable food supply chains (FSC). The present study identifies specific resilient functions to overcome the problems created by natural disasters in the FSC context.

The quality function deployment (QFD) method is utilized for identifying these relations. Further, fuzzy term sets and the analytical hierarchy process (AHP) are used to prioritize the identified problems. The results obtained are employed to construct a QFD matrix with the solutions, followed by the technique for order of preference by similarity to the ideal solution (TOPSIS) on the house of quality (HOQ) matrix between the identified problems and functions.

The results from the study reflect that the shortage of employees in affected areas is the major problem caused by a natural disaster, followed by the food movement problem. The results from the analysis matrix conclude that information sharing should be kept at the highest priority by policymakers to build and increase resilient functions and sustainable crisis management in a perishable FSC network.

The study suggests practical implications for managing a FSC crisis during a natural disaster. The unique contribution of this research lies in finding the correlation and importance ranking among different resilience functions, which is crucial for managing a FSC crisis during a natural disaster.

The coronavirus disease (COVID-19) pandemic continues to impact economic systems, with devastating consequences on livelihoods. Anecdotal evidence has predicted the adverse effects of COVID-19 on the livelihood of food system actors. Uganda experienced two lockdowns in March 2020 and June 2021 with varying government containment measures. During the first lockdown, fresh food market vending was deemed essential to meet urban food demand, and was consequently exempted from a total shutdown despite the ban on public and private transport. Thus, this study sought to examine the effect of COVID-19 containment measures on fresh food market vending businesses in Uganda.

Using primary data collected from fresh food market vendors, this study applied a pooled time-series estimation to examine the effect of the first lockdown COVID-19 containment measures on fresh food vendors' welfare.

The study revealed that COVID-19 had a significant negative impact on the income of fresh food vendors, with female vendors being the most affected. COVID-19 containment measures reduced the diversity of buyers, individual customers and the number of commodities traded in causing a greater impact on vendors' income.

The unavailability of data for vendors who did not return to the market at the time of data collection limits the scope of the study. Additionally, the absence of data for the second lockdown limited the analysis to only March 2020 lockdown period.

The empirical analysis highlights how vulnerabilities of different gender categories could be exacerbated by crises. The study provides empirical evidence of various market distortions caused by the COVID-19 pandemic and the disproportionate impact on women and men market vendors which calls for the need to integrate women's perspectives in future planning for market systems as well as advocating for gender-sensitive recovery responses.

Due to the recent disruptions caused by COVID-19, global supply chains are stress tested. The affected supply chains have interfered with market tonnage prices for the yield of perishable products like mangoes that are highly dependent on their quality. This research, through empirical findings, thus determines and comprehends the factors influencing mango quality (size).

A framework is developed for finding the potential factors of quality building on the previous literature and studies on the available topic. The data collection included face-to-face interviews comprising 240 farmers, hired managers and preharvest contractors in India's Jangaon, Rangareddy and Yadadri Bhuvanagiri districts of Telangana state. The data analysis is done using multiple regression, and the outcomes form the basis of the design of the experiments model.

The empirical insights support that the quality of mango is affected by factors such as the number of picking cycles, the cost of fertilizer, the variety of fertilizers used, the variety of pesticides used and pesticide application frequency. The direct implications are the benefit to farmers in improving mango quality and maximizing profit per yield cycle.

To the best of the authors’ knowledge, the first research that has specifically focused on holistically improving the quality(size) of mangoes.

The findings contribute to the perishable supply chain literature, specifically to the mango study, to comprehensively showcase the factors impacting the quality of mangoes and provide guidance to farmers regarding orchard practices.

This study aims to discover the key performance indicators (KPIs) of the agricultural cold supply chain (ACSC) and analyze their consequences on the performance of ACSC within the bounds of Indian topography.

The KPIs have been explored based on the literature review both in global and Indian context and domain expert's opinions. The interdependency characteristics and cause–effect relationship among the KPIs have been analyzed using a fuzzy decision-making trial and evaluation laboratory (f-DEMATEL) approach.

The findings extracted from the empirical assessment of the problem find strong compliance with the notions of theoretical model assessment. The results highlight that the cost of product waste and operating and performance costs are the two most important performance indicators of an Indian ACSC. Furthermore, governmental policies and regulations and the effectiveness of cold chain (CC) equipment also have a high degree of influencing characteristics on ACSC performance.

To connect the study with practicalities, the assessment of the KPIs is allied with real-time practices by clustering the beliefs of Indian professionals. Therefore, the decision-making behavior of the experts might be influenced by geographical constraints. However, the key findings provide advantages to the ACSC players, a bright hope for future food security and a significant profit for farmers.

The presented paper encompasses various aspects of the ACSC, including theoretical and empirical perspectives exercised to contemplate the system dynamics, which inculcates the essence of the associated practicalities. Thus, this study has various practical contributions relevant to managerial and societal perspectives.

Short food supply chains have the potential to facilitate the transition to more sustainable food systems. Related distribution processes, however, can be challenging for smallholder and family farmers. To extend the market reach of farmers without the need for extensive investments, crowd logistics (CL) can be used. The purpose of this paper is to explore the benefits and trade-offs of implementing CL platforms in short food supply chains (SFSCs).

A decision support system (DSS) based on agent-based and discrete event simulation (DES) modelling is developed, which closely approximates the behaviour of customers and distribution processes at outlets. Different scenarios are explored to evaluate the potential of CL in rural and urban settings using the example of regions from Bavaria, Germany.

Results show that CL can be used to increase the reach of farmers in SFSCs at the cost of minor food quality losses. Moreover, a difference between urban and rural settings is noted: An urban scenario requires less investment in the driver base, whereas the rural scenario shows a higher potential to increase market reach.

Platform-based food delivery services are still mostly unexplored in the context of SFSCs. This research shows that platform services such as CL can be used to support local agriculture and facilitate the distribution of perishable food items, introducing a simulation-based DSS and providing detailed results on various application settings; this research serves as a steppingstone to facilitate successful real-world implementations and encourage further research.