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Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a trade-off between financial and environmental aspects of these decisions, this paper aims to determine an optimal location, among candidate locations, of a new logistics center, its capacity, as well as optimal network flows for an existing distribution network, while concurrently minimizing the total logistics cost and gas emission. In addition, uncertainty in transportation and warehousing costs are considered.

The problem is formulated as a fuzzy multiobjective mathematical model. The effectiveness of this model is demonstrated using an industrial case study. The problem instance is a four-echelon distribution network with 22 products and a planning horizon of 20 periods. The model is solved by using the min–max and augmented ε-constraint methods with CPLEX as the solver. In addition to illustrating model’s applicability, the effect of choosing a new warehouse in the model is investigated through a scenario analysis.

For the applicability of the model, the results indicate that the augmented ε-constraint approach provides a set of Pareto solutions, which represents the ideal trade-off between the total logistics cost and gas emission. Through a case study problem instance, the augmented ε-constraint approach is recommended for similar network design problems. From a scenario analysis, when the operational cost of the new warehouse is within a specific fraction of the warehousing cost of third-party warehouses, the solution with the new warehouse outperforms that without the new warehouse with respective to financial and environmental objectives.

The proposed model is an effective decision support tool for management, who would like to assess the impact of network planning decisions on the performance of their supply chains with respect to both financial and environmental aspects under uncertainty.

Warehouse receipt-based financing (WRF), an innovative instrument with its structure embedded in the agricultural value chain can potentially address farmers' concerns about timely credit access and accessible remunerative markets. However, studies indicate farmers' exclusion from currently practiced WRF mechanisms across developing countries. Transaction cost and lack of assured remunerative markets post storage are the challenges thwarting farmers' participation. The study explores how these challenges can be addressed by analyzing a case study. The finding will help in coming up with a farmer-inclusive WRF mechanism.

The study uses a case study as an analysis tool. Primary data is gathered through farmers. Descriptive statistics and partial least squares (PLS) approach to structural equation modeling methodology has been adopted for empirical testing of the hypothesis of the study. The study uses SMART PLS 3.0 for analysis of data.

Single window offering of multiple value chain operations and technological intervention in physical handling substantially reduces transaction costs for farmers. Sustained farmers' participation in the case supports this finding. The presence of an assured market (PAM) is found to have a positive and significant relationship with WRF in the case of beneficiary farmers. The PAM is found to have a negative yet significant relationship with WRF in the case of nonbeneficiary farmers. Critical success factors of the entity KisanMitra stated in the case substantiates a farmer-inclusive WRF mechanism.

The study analyzes a case study of specific geography. However, similarities enlisted across developing countries in the introduction section provide a scope of generalization of findings across developing countries. The identified factors for a farmer-inclusive WRF mechanism will enable the governments, policymakers and development institutions to ascertain and align their WRF implementation measures to inculcate and upgrade these factors to the prospective WRF agents. Future studies can explore the replication of farmer-inclusive WRF mechanisms across other geographies. The studies also explores the role of technological interventions in further reducing the transaction cost and suitable policy modifications to encourage replication of the study in other geopgraphical context.

The study on WRF and the methodology adopted is first of its kind to identify factors for a farmer-inclusive WRF mechanism.

This study aims to analyse how the adoption of Industry 4.0 technologies can help different types of agri-food supply chains introduce and manage innovations in response to the challenges and opportunities that emerged following the COVID-19 pandemic.

A systematic literature review methodology was used to bring together the most relevant contributions from different disciplines and provide comprehensive results on the use of I4.0 technologies in the agri-food industry.

Four technological clusters are identified, which group together the I4.0 technologies based on the applications in the agri-food industry, the objectives and the advantages provided. In addition, three types of agri-food supply chains have been identified and their configuration and dynamics have been studied. Finally, the I4.0 technologies most suited for each type of supply chain have been identified, and suggestions on how to effectively introduce and manage innovations at different levels of the supply chain are provided.

The study highlights how the effective adoption of I4.0 technologies in the agri-food industry depends on the characteristics of the supply chains. Technologies can be used for different purposes and managers should carefully consider the objectives to be achieved and the synergies between technologies and supply chain dynamics.

This study aims to investigate the role of international price volatility and inventories on domestic market price dynamics in the case of agricultural commodities.

A structural model is employed to uncover relationships among commodity price, price volatility, inventories and convenience yield. Monthly producer price data along with annual data on trade, consumption, inventories and tariffs for 71 countries and 13 commodities covering 2010–2019 are assembled to estimate the model. With a first-stage Least Absolute Shrinkage and Selection Operator (LASSO) estimator to identify the best instrument set, a nonlinear approach is used to estimate the model.

Results show that international market information plays a critical role in domestic market price dynamics. International price volatility has a stronger effect on domestic prices than that of international inventories.

Current upheaval in commodity markets requires an understanding of how prices move together and inventories affect that movement. A country's internal price is not independent of the effects of global market events.

Although hypotheses exist that global market information (volatility and inventories) helps countries manage domestic commodity prices, there have been limited studies on this relationship, especially with a structured model and cross-country data.

The aim of this paper is to better understand European consumers' behaviour in relation to Short Food Supply Chains (SFSCs), so as to provide insights to support their development as part of a sustainable food system. Specifically, it aims to analyse consumer purchase patterns, motivations and perceived barriers and to identify patterns of behaviour amongst different consumer groups.

An online consumer survey was conducted in 12 European countries (n = 2,419). Quantitative data analysis, including principal component analysis (PCA) and cluster analysis, was undertaken using SPSS.

Four consumer clusters are named according to their behavioural stage in terms of SFSC engagement: Unaware Unengaged, Aware Unengaged, Motivationally Engaged and Executively Engaged. Unaware Unengaged and Aware Unengaged are in the non-engagement phase of behaviour. Motivationally Engaged are motivationally activated to engage in the behaviour but fail to do so consistently. Executively Engaged is the fully engaged cluster, being motivated to act and purchasing local food on a frequent basis. The results show an interesting interplay between motivations and barriers, i.e. higher scores for motivations and lower scores for barriers do not necessarily translate into higher purchase frequency.

The research gleans insights into the contextual factors that may inhibit SFSC purchases in different consumer segments. It offers practical implications for policymakers and others seeking to develop SFSCs as part of a sustainable food system.

The public distribution system (PDS) is an Indian food security system established to manage the distribution of food grains at affordable prices. As a result of the population explosion, the long-established PDS system finds it challenging to maintain operational efficiency, quality, trust and transparency. This paper explores the possibility of leveraging blockchain technology to overcome these operational hurdles.

Through a literature review and expert interactions, the present research identifies critical success factors in terms of enablers and barriers that influence the adoption of blockchain technology in PDS. Furthermore, we propose two independent interpretive structural models (ISM) and MICMAC to characterize these attributes.

The research identifies 15 distinct enablers and ten barriers that influence the diffusion of the latest technology in the sector at focus. The analyses disclose the interrelationships/dependencies among these enablers and between barriers, along with their individual driving power and dependence power.

The research showcases the importance of automating the system and illustrates how the features of blockchain technology can assist in augmenting stakeholder satisfaction levels. However, poor or nonexistent government regulations and patronage are found to be the major impediments to adoption. The research also delineates the cost implications of this barrier through its interrelationships with other barriers.

Interesting inferences are drawn from the models that offer actionable insights for the industry, government and technologists for improving PDS performance. Such interventions will ensure national food security through enhanced trust and transparency, which can further improve efficiency and effectiveness.

This paper examines how key actors in the UK food system (FS) understand the role of the local food sector in relation to FS resilience.

Discourse analysis was used to assess and compare the framings of the UK FS in 36 publications released during Covid-19 from alternative food networks (AFNs) actors and from other more mainstream FS actors, including the UK government.

The analysis shows that AFNs actors perceive the UK FS as not resilient and identify local FSs as a route towards greater resilience (“systemic” framing). In contrast, other food actors perceive the UK FS as already resilient, with the role of local food limited to specific functions within the existing system (“add-on” framing). The two groups converge on the importance of dynamic public procurement and local abattoir provision, but this convergence does not undermine the fundamental divergence in the understanding of the role of “the local” in resilient UK FSs. The local food sector’s messages appear to have gone largely unheard in mainstream policy.

The paper presents an analysis of public sector reports focused on the UK FS released during the Covid-19 pandemic years 2020–2021. The corpus inclusion criteria mean that publications during this period which focus on other food sector issues, such social injustices, climate change and health, were not included in the analysis, although they may have touched upon local food issues. The authors further recognise that Covid-19 had a longer lasting effect on FSs than the years 2020–2021, and that many other publications on FSs have been published since. The time span chosen targets the time at which FSs were most disrupted and therefore aims to capture emerging issues and solutions for the UK FS. The authors’ insights should be further validated through a more complete review of both public reports and academic papers covering a wider base of food-related issues and sectors as well as a broader timespan.

A comparison of how different FS actors understand the importance of local food, especially in relation to resilience, has not been undertaken to date. The findings raise important questions about the disconnect between AFN actors and other actors in the framing of resilience. Considering the need to ensure resilience of the UK FS, this study's findings raise important insights for UK food policy about the “local food blindspot” and for food movement actors wishing to progress their vision of transformative change.

The purpose of this study is to examine the relationship between the productive structure and the size of the informal economy in Latin American countries.

The study employs econometric techniques for panel data covering the period from 2002 to 2017 and considering 17 Latin American countries. The evidence presented is based on the informal economy data generated by Medina and Schneider (2018) who estimate the size of the informal economy using a structural equation model and the share of manufacturing in total employment as a measure of the size of the manufacturing sector. Also, the study addresses the possible endogeneity bias in the relationship studied and makes the conclusions more robust, thus avoiding spurious correlations that weaken the findings.

The results indicate that most industrialized Latin American countries are associated with a smaller size of the informal economy.

The findings have important policy implications, as they suggest that Latin American economies need to switch the structure of the economy toward more sophisticated productive structures if they want to reduce the size of the informal economy. Thus, more efforts should be deployed to policies to diversify and upgrade economies.

The study contributes to the literature on the informal economy by connecting the country’s productive structure and informality. Specifically, the results show that the productive structure of countries is a plausible explanation for the size of the informal economy.