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We explore the supply chain problem of a downstream durable goods monopolist, who chooses one of the following trading modes: an exclusive supply chain with an incumbent supplier or an open supply chain, allowing the monopolist to trade with a new efficient entrant in the future. The expected retail price reduction in the future dampens the profitability of the original firms. An efficient entrant's entry magnifies such a price reduction, causing a further reduction of original firms' joint profits. In equilibrium, the downstream monopolist chooses the exclusive supply chain to escape further price reductions, although it expects efficient entry.

The modern day food industries are part of a complex agri-food supply chain, where food production has become efficient, yet potentially vulnerable to supply chain risks. The COVID-19 pandemic is a testament to that end. This article measures and identifies the U.S. food manufacturing industries' vulnerability to upstream industries and labor occupations by (i) calculating a food industry's diversification of intermediate input purchases across upstream industries, (ii) quantifying the relative exposure of food manufacturing in a given industry and location to upstream input suppliers and labor occupations, and (iii) estimating each food industry's gross output elasticity of inputs. Among our results, we find the evidence that the animal processing industry's output is relatively vulnerable to production labor which is consistent with the observed disruptions to the meat packing sector during COVID19, which were largely caused by labor issues. Our results may help academics and practitioners to understand food industries' vulnerabilities to upstream industries and labor occupations.

Urban restaurants are increasingly putting local food on the menu. How do farm-to-restaurant relations fit into the local food movement, and how can these collaborations be supported by food policies and programmes of urban governments? Through a qualitative case study in the city-region of Groningen (The Netherlands), this article explores the values urban restaurants, local food suppliers and urban governments attribute to local food, the trust and barriers these actors experience in their collaborations, and their views on the municipality's preliminary plans for a local food hub. In line with the concepts of reflexive localism and values-based territorial food networks, and taking into account the perspectives, benefits, pitfalls and conditions uncovered in this study, a farm-to-restaurant-oriented food hub would need to (1) embrace the complex and relational nature of place, (2) foster reciprocal and practical partnerships, (3) negotiate reflexive and values-based goals and (4) broker between and unburden the involved parties.

International audience; This research examines the similarities between port traffic structure and economic structure of French port cities. Based on the combination of Automated Identification System (AIS) data and employment data, it performs complementary analyses of the mutual specialization between ports and cities. Main results show that while larger cities handle more diversified traffic, the cross-specialization is blurred by the complexity of trade networks and supply chains. We then propose a novel methodology whereby the spatial unit of analysis is enlarged according to the type and volume of port traffic.

In early 2020, apparel brands and retailers cancelled US$40 billion worth of orders, with critical consequences for suppliers and workers. Their actions illustrate the power asymmetries in global supply chains and the unequal distribution of costs during crises. This article explores these dynamics through original survey data, supplier questionnaires, stakeholder interviews, a time-line analysis and trade data analysis. Findings point to certain limits of buyer power, reflected in the effective collaboration between suppliers and worker rights advocates in the "#PayUp" campaign. Yet buyers retain the power to squeeze suppliers with adverse impacts on workers, thus leading to calls for binding agreements.

As supply chain channels physical, financial, and information flows as well as associated risks, a firm’s supply chain information should be helpful in understanding and predicting its credit risks. Credit ratings as an approximate but important measure of corporate credit risks have been widely used by investors, creditors, and supply chain partners in their decision-making. This paper studies the role of supply chain information in predicting companies’ credit ratings. Using firm-level supplier-customer linkages and corporate credit rating data, we develop a machine learning framework with gradient boosted decision tree to examine whether and what supply chain features can significantly improve the prediction accuracy of credit ratings, and what types of supply chain links have higher information content that positively affects the predictability of the supply chain features. We construct a firm’s supply chain variables from its supplier and customer portfolios to be used in the machine learning models. We show that incorporating supply chain features can improve prediction accuracy over the benchmark credit rating model using only the focal firm’s features. Moreover, the informativeness of supply chain links in focal credit risk prediction depends on the focal firm’s industry sector, the relationship strength of such links, and the switching costs. Finally, we develop a focal credit rating prediction model with a high accuracy level using supply chain factors solely, which can potentially be applied to predict credit risks of small and medium-sized enterprises (SMEs) and private firms with no public financial information, as long as their supply chain information is available.

BACKGROUND Extensive research shows that replacing animal protein with plant-based protein in the diet would strongly alleviate the environmental impact of the food system. However, much less attention has been given to the socio-economic considerations of dietary transitions. This study analyses the socio-economic performance of innovative legume-based food prototypes, developed in the Protein2Food research project, and conventional animal-based products (chicken meat and dairy milk). We implement a social life cycle assessment (sLCA) to quantify and compare their potential socio-economic impacts along the entire life cycle. RESULTS Findings from this analysis show that legume-based prototypes and their respective animal-based counterparts have, overall, a comparable socio-economic performance. Looking at the disaggregated life cycle stages, socio-economic hotspots (points of most negative impacts) were mainly identified at the production stage in legume-based products. Farm-level net margin and profitability are low when compared with their animal equivalents. However, at the processing stage, there are socio-economic gains for plant-based products regarding lower unemployment rates. Finally, at the consumption stage, there are mixed results. Plant-based products show worse protein affordability but better nutritional contents (lower saturated fat and cholesterol) than their animal counterparts. CONCLUSIONS To improve socio-economic performance of legume-based foods, greater emphasis should be placed upon developing improved processing technologies and supply chains. This would broaden the supply of sustainable protein-rich food options and make these products more economically attractive. The research illustrates that policies should be targeted to the different stages of the food value chain to optimize the development of innovative plant-based foods. © 2021 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The COVID-19 pandemic has put unprecedented stress on agricultural food. Therefore, the goal of this study is to analyze the effect of the COVID-19 outbreak on agricultural food and provide policy recommendations based on SWOT analysis to minimize risks. Data from the Food and Agriculture Organization and the Pakistan Bureau of Statistics were used for this study with a thorough literature review containing policy documents and scientific magazines in the related sector. There is enough evidence to demonstrate that the COVID-19 pandemic has had a massive influence on agricultural food supply, largely impacting food demand as well as food insecurity. The study uses SWOT analysis to identify the highest-priority policies that may remediate the current issues. Key strategies include developing new online resources such as digitized trade and providing a digital platform to strengthen the buyer?supplier collaboration and lower the risk of food wastage and insecurity. The government should invest in technology that contributes to the sustainable flow of agricultural products along the supply chain to prevent food crises during the pandemic.

The COVID-19 pandemic showed how vulnerable workers in global supply chains are to adverse human rights impacts. Protecting such workers must be a primary policy goal in the efforts to “build back better” from the crisis, and businesses conducting human rights due diligence (HRDD) is a primary means to do so. In Europe, there is a fast-moving trend towards legislatively mandating HRDD and there is potential for similar movement in the United States. Whether HRDD will significantly improve human rights conditions, however, is an open question. Based on our experience with corporate compliance programs, it is clear that the management and oversight of HRDD is an essential factor in ensuring meaningful implementation, as opposed to corporations focusing on form over substance. This article identifies those key internal governance issues and provides advice on how best to ensure effective implementation. This article argues that for most corporations, the day-to-day management of HRDD best fits with the compliance function—not the legal function—and this new role could be part of the next step in the evolution of the compliance function. This article also discusses the role of the board of directors and how HRDD combined with recent developments in the law of fiduciary duties can push directors to engage in more rigorous oversight. In addition, this article discusses the types of information that are essential for supporting the management and oversight of HRDD.

The 2013 Rana Plaza disaster highlighted the failure of labour regulation in global garment value chains. Eight years on, in the midst of the COVID-19 pandemic, what changes have occurred in labour regulation and with what consequences for workers? Using the concept of a labour governance system (LGS), the authors show that, despite improvements in building and worker safety regulation, the garment LGS remains weak and wages, working hours and the treatment of workers show little improvement. The pandemic appears to have exacerbated these deficiencies but it may also offer an opportunity to strengthen the LGS along lines proposed in this article.

With over half a trillion dollars in trade credit flowing between firms in the United States, it is critically important for managers to understand how the trade credit that their firm receives and provides affect its value. Trade credit is a strategic investment in supply chain relationships that allows the recipient to make payment later rather than at the time of the sale. A firm provides trade credit to its downstream business customers and also receives trade credit from its upstream suppliers. Although research has shown that provided trade credit builds a firm’s shareholder value, it has not examined what effect, if any, received trade credit has on the firm’s value. As a result, one might assume that received trade credit affects firm value in the same manner as provided trade credit. We argue otherwise and show that received trade credit and provided trade credit have differential effects on firm value. Received trade credit has a negative direct effect and a positive indirect effect (through profit), whereas provided trade credit has a positive direct effect and a negative indirect effect. The difference in direct effects hinges on the disparate nature of dependence in the supply chain. Provided trade credit increases customers’ dependence on the firm, building the firm’s value. In contrast, received trade credit increases the firm’s dependence on its suppliers, destroying the firm’s value. Empirical results using a sample of 2804 firms from 1986 to 2017 provide robust support for the hypotheses. They show that managers risk overestimating the value of a 1 SD increase in received (provided) trade credit by $284.74 ($74.95) million, on average, if they do not consider both the direct and indirect effects it has on their firm’s value.

Contract farming is becoming increasingly important in developing countries, to coordinate transactions along agricultural supply chains. In this paper, we examine the diet and nutrition implication of engaging in contract farming among smallholder farmers in Ghana. Previous studies have analyzed the effects of contract farming on farm production and household income. However, little is known about the effects of contract farming on household and individual nutrition. We know of no study that has analyzed the effects of contract farming on household and individual dietary diversity, as well as on anthropometric measures. Our study further contributes to the existing literature by investigating differences in effects across different types of contracts, which has largely been neglected. Results show that producing oil palm under contract has implications for household and individual nutrition. However, the effect depends on the type of contract. Resource-providing contracts lead to higher dietary diversity at the household level, as well as for female household members. Our findings also reveal that children in households with resource providing contracts have a higher height-for-age z-score (HAZ) and weight-for-age z-score (WAZ), suggesting positive long-term nutritional benefits for small children aged 2-6 years. The effects of marketing contracts are less clear. The results indicate positive effects on women’s dietary diversity and on the child’s weight-for-age z-score. Additionally, we find positive nutrition effects if the contracted farmer is female.

The quality of such processed agrifood products as dehydrated apple is related to the quality and variety offresh harvested products and connected with wastage reduction throughout the agrifood supply chain. Forthis purpose, cold-storage management is important to avoid or mitigate the quality decay of fresh prod-ucts stored in refrigerated systems. This paper explores the benefits of a two-stage stochastic programmingmodel for product quality through the selection of producers and the management of cold storage to miti-gate deterioration and guarantee the maintenance of quality. A case study with real data from an agribusinesscompany is presented in the case study to illustrate and assess the suitability of the stochastic approach. Un-certainty regarding the conversion rate of fresh apples into the final dehydrated product and the purchasecost of the apples in the system are represented through scenarios generated from historical data. Recourseactions include the purchase of additional fruit and renting of additional cold stores to meet the demand.Based on the different scenarios, the value of the stochastic solution shows that modeling and solving theproposed stochastic model minimizes costs by an average of around 6.4%. In addition, the expected valueof perfect information demonstrates that using a proactive strategy could reduce costs by up to 9%. Theseresults ensure the applicability of this model in practice before and during the harvesting season for planningand replanning as uncertainty is revealed under a rolling horizon. The authors wish to acknowledge Marcos Oliva-Fernández for his valuable comments and sugges-tions and CYTED program for supporting the thematic network BigDSS-Agro (P515RT0123).D.Sc. Marcela González-Araya would like thank to FONDECYT Project 1191764 (Chile) forits financial support and D.Sc. Wladimir Soto-Silva would like to thank MEC Project 80180022(Chile). Moreover, this work was supported by the Ministerio de Economía y Competitividad un-der contract TIN2017-84553-C2-2-R and the Ministerio de Ciencia e Innovación under contractPID2020-113614RB-C22. Jordi Mateo and Francesc Solsona are members of the research group2017-SGR363 and Lluís M. Plà of 2017-SGR01193, funded by the Generalitat de Catalunya.Also, this research was partly supported by the European Union FEDER (CAPAP-H5 networkTIN2014-53522-REDT).

Guanxi, which literally means interpersonal relationship or social connections, plays an important role in achieving business success in China. This study investigates the effect of interpersonal relationship on trust and trustworthiness in four regions in China. Eighty pairs of close friends participated in the experiment: 20 pairs from Beijing, 20 pairs from Guangdong, 20 pairs from Shanghai, and 20 pairs from Chongqing. A cooperation experiment based on a two-tier simulated supply chain was conducted, in which the participant who played as a supplier solicited demand forecast information from the participant who played as a retailer to plan production. Participants were instructed to perform two tasks: one with a "friend" counterpart and one with a "stranger" counterpart. The results demonstrated regional differences in the effects of interpersonal relationship on trust and trustworthiness: the effect of interpersonal relationship was greater in Guangdong than in the other regions. Additionally, a quantified classification of trustworthiness-trust was proposed by clustering analysis. The type of self-protective trustworthiness and altruistic trust occupied an overwhelming majority in each region, followed by the type of altruistic trustworthiness and self-protective trust, the type of altruistic trustworthiness and altruistic trust, and the type of self-protective trustworthiness and self-protective trust. Regional differences in the distribution proportions in the four types were discovered.

The international nature of supply chains has led to the rise of private authority in regulating the environmental and social impacts of production, which companies frequently address through corporate social responsibility (CSR) in the form of private governance (PG). Despite its claim to establish “global” rules, PG usually has national origins, and multiple efforts to address the same issue from different national perspectives frequently coexist. Numerous studies have explored the impact of national business systems on companies' domestic CSR practices, yet little is known about what factors shape CSR practices like PG internationally. Therefore, this study seeks to understand how differing domestic contexts shape approaches to CSR in the form of PG in host countries. I explore this empirically through the comparative case study of competing PG initiatives in the post‐Rana Plaza Bangladesh garment industry, uniquely conceived to govern companies' practices rather than certify products. It combines empirical findings with the comparative CSR literature to hypothesize about ideal types of PG organizing in US and European contexts. It extends the analysis to also account for other influential factors, such as stakeholder pressure, thus demonstrating how institutional and agentic factors amalgamate to shape firms' choices. By explicating linkages between international PG and its domestic context, as well as between the comparative CSR and PG literature studies, this study extends our understanding of how and why international PG practices and preferences vary for firms originating from different environments.

The COVID-19 pandemic and associated public health and social distancing mandates caused unprecedented shifts and disruptions for local and regional food systems (LRFS). The pandemic also brought new and heightened attention to the structure and resiliency of US food systems, and LRFS appeared to be positioned to significantly increase the scope and scale of their market reach as a result. Researchers from three universities collaborated with staff from the U.S. Department of Agriculture's Agricultural Marketing Service to recruit leaders from sixteen key coalitions within the U.S. LRFS sector to frame an adaptive, community-driven set of applied research activities to understand important themes, learn from effective responses and gain insights into how local and regional supply chains may change post-pandemic. In this paper, we summarise urgent and emergent strategies and innovations from LRFS captured in a fall 2020 consumer survey, with additional insights on how the survey was framed and interpreted, considering synthesis of collaborative discussions and project team interactions. We conclude the article with a set of research, policy and technical assistance priorities that were identified and validated by this LRFS network.

The COVID 19 crisis and geopolitical ruptures of recent years have highlighted the importance of operations and supply chain management (OSCM) to firms and society. How do OSCM executives make decisions under uncertainty, and how do they balance the competing needs of various stakeholders? The behavioral agency model (BAM), which has been widely used in the management literature, focuses on the executive as the unit of analysis, like the behavioral science research in which it is embedded;by contrast, much of the supply chain risk management research has examined risk at the level of the firm. We review BAM literature and its core constructs, refine its original predictions, identify OSCM executive decision contexts that could take advantage of BAM, and highlight research opportunities using BAM. We aim to provide a platform for further risk research applying BAM in the domain of OSCM executive decision-making.

We analyze the effects of uncertainty and anticipation shocks associated with the 2016 Brexit vote as a treatment on trade between the UK and 14 EU and 14 non-EU trading partners, using the Synthetic Control Method (SCM). After controlling for exchange rate and GDP changes, UK exports to both groups of countries fell below those of the ‘synthetic Britain’, with much of the shortfall developing over the year prior to the referendum, following the 2015 Conservative general election win. The results indicate that UK exports to EU countries may have lost nearly 25% by early 2018, due to the Brexit shock, somewhat more than those to non-EU countries. Imports from the EU and non-EU countries also declined a little, although there is tentative evidence that UK consumers may have been avoiding countries with PTAs with the EU, and possibly turning towards the Commonwealth. Overall, the results confirm that policy uncertainty has a major effect upon trade, and that uncertainty about supply chain costs is a potential explanation for at least some of the shortfall.

Critical infrastructure networks, such as transportation and supply chains, are becoming increasingly interdependent. As the operability of network nodes relies on the operability of connected nodes, network disruptions have the potential to spread across entire networks, having catastrophic consequences in the realms of physical network performance and also economic performance. While risk-informed physical network models and economic models have been well-studied in the literature, there is limited study of how physical features of network performance interact with sector-specific economic performance, particularly as these physical networks recover from disruptions of varying durations. In this article, we create a generalizable framework for integrating Functional Dependency Network Analysis (FDNA) and Dynamic Inoperability Input-Output Models (DIIM), to assess the extent to which disruptions to critical infrastructure could degrade its functionality over a period of time. We demonstrate the framework using disruptive scenarios for a critical transportation network in Virginia, USA. We consider scenarios involving: (a) mild case that is relatively more frequent such as recurring traffic conditions; (b) moderate case involving an incident with a multihour delay, and (c) severe case that is relatively less frequent such as evacuation after a major hurricane. The results will be useful for network managers, policymakers, and stakeholders who are seeking to invest in risk mitigation for network functionality and economic activity.

Internet of things (IoT) plays a significant role in offering a wide range of benefits to the healthcare supply chain. It improves the quality of patient care, reduces the cost of medical procedures, maintaining flawless operations and supports clinical decisions. Despite strong policy interest and vast potential benefits of IoT in the healthcare supply chain, the actual adoption rate is relatively low and it's in the nascent stage in developing countries like India. The objective of this paper is to identify and analyze the potential barriers which would restrain the healthcare industry from adopting IoT. Based on the review of the literature and brainstorming with experts from industry and academia, 14 barriers were identified for IoT adoption. The contextual relationship between the identified barriers was developed using interpretive structural modeling and the obtained results were used as input to fuzzy MICMAC analysis to determine the driving and dependence power of the IoT adoption barriers. From the result, Legal and regulatory standards, Lack of IT Infrastructure are major barriers influencing the adoption of IoT in the healthcare supply chain. The findings will support the decision-makers to understand the contextual relationship between the IoT adoption barriers in the Indian healthcare supply chain.

We consider a sequential decision model over multi-tier supply chain networks and show that in particular, for series parallel networks, there is a unique equilibrium. We provide a linear time algorithm to compute the equilibrium and study the impact and invariant of the network structure to the total trade flow and social welfare.