Research Report: Innovation among Businesses Across the Agri-Food Supply Chain during COVID-19

Innovation contributes critically to business recovery following major crises. Traditionally, business innovation is characterized by a series of choices and actions over time. During COVID-19, however, businesses throughout the agri-food supply chain were forced to innovate rapidly due to sudden unforeseen policy changes. To understand innovation induced by COVID-19, we analyze 297 usable responses from a survey of agri-food supply chain businesses in two distinct study regions (California and the two-state region of Minnesota-Wisconsin). Results indicate that larger agri-food businesses managed by younger owner-operators were more likely to innovate and adapt during the COVID-19 crisis. © 2023, Food Distribution Research Society. All rights reserved.

Industry 4.0 and Beyond: A Review of the Literature on the Challenges and Barriers Facing the Agri-Food Supply Chain

In recent years, the Industry 4.0 concept has gained considerable attention from professionals, researchers and decision makers. For its part, the COVID-19 pandemic has highlighted the importance of managing the agri-food supply chain to ensure the food that the population needs. Industry 4.0 and its extensions can address the needs of the agri-food supply chain by bringing new features such as security, transparency and traceability in line with sustainable development goals. This study aims to systematically analyze the literature to address the challenges and barriers against the application of industry 4.0 and its related technologies in the management of an agri-food supply chain. Currently, despite the large number of publications, there is no clear agreement on what Industry 4.0 is, and even less its extensions. The next revolution that includes new technologies and improves several existing technologies brings additional conceptual and practical complexity. Consequently, in this work we first determine the main components of I 4.0 and their extensions by studying the literature, and then, in the second step, define the agri-food supply chain on which I 4.0 technologies are applied. Two well-known databases-Web of Science and Scopus-were chosen to extract data for the systematic review of the literature. For the final evaluation, we identified 24 of 100 reviewed publications. The results provide an exhaustive analysis of the different I 4.0 technologies and their extensions that are applied in regards to the agri-food supply chain. In addition, we find 15 challenges that are classified into five major themes in the agri-food supply chain: technical, operational, financial, social and infrastructure. The four most important challenges identified are technological architecture, security and privacy, big data management and IoT (internet)-based infrastructure. Only a few articles addressed sustainability, which reaffirms and demonstrates a considerable gap in terms of the sustainable agri-food supply chain, with waste management being the one that has attracted the most attention. This review provides a roadmap for academics and practitioners alike, showing the gaps and facilitating the identification of I 4.0 technologies that can help address the challenges facing the efficient management of an agri-food supply chain.

Robust optimization and strategic analysis for agri-food supply chain under pandemic crisis: Case study from an emerging economy.

Pandemic crises like the coronavirus disease 2019 (COVID-19) have severely influenced companies working in the Agri-food industry in different countries. Some companies could overcome this crisis by their elite managers, while many experienced massive financial losses due to a lack of the appropriate strategic planning. On the other hand, governments sought to provide food security to the people during the pandemic crisis, putting extreme pressure on companies operating in this field. Therefore, the aim of this study is to develop a model of the canned food supply chain under uncertain conditions in order to analyze it strategically during the COVID-19 pandemic. The problem uncertainty is addressed using robust optimization, and also the necessity of using a robust optimization approach compared to the nominal approach to the problem is indicated. Finally, to face the COVID-19 pandemic, after determining the strategies for the canned food supply chain, by solving a multi-criteria decision-making (MCDM) problem, the best strategy is specified considering the criteria of the company under study and its equivalent values are presented ​​as optimal values of a mathematical model of canned food supply chain network. The results demonstrated that "expanding the export of canned food to neighboring countries with economic justification" was the best strategy for the company under study during the COVID-19 pandemic. According to the quantitative results, implementing this strategy reduced by 8.03% supply chain costs and increased by 3.65% the human resources employed. Finally, the utilization of available vehicle capacity was 96%, and the utilization of available production throughput was 75.8% when using this strategy.

Challenges Facing Artificial Intelligence Adoption during COVID-19 Pandemic: An Investigation into the Agriculture and Agri-Food Supply Chain in India

The coronavirus (COVID-19) pandemic has witnessed a significant loss for farming in India due to restrictions on movement, limited social interactions and labor shortage. In this scenario, Artificial Intelligence (AI) could act as a catalyst for helping the farmers to continue with their farming. This study undertakes an analysis of the applications and benefits of AI in agri-food supply chain, while highlights the challenges facing the adoption of AI. Data were obtained from 543 farmers in Odisha (India) through a survey, and then interpreted using "Interpretive Structural Modelling (ISM)”;MICMAC;and "Step-Wise-Assessment and Ratio-Analysis (SWARA)”. Response time and accuracy level;lack of standardization;availability of support for big data;big data support;implementation costs;flexibility;lack of contextual awareness;job-losses;affordability issues;shortage of infrastructure;unwillingness of farmers;and AI safety-related issues are some challenges facing the AI adoption in agri-food supply chain. Implications were drawn for farmers and policy makers.

Dynamic capabilities in the "new normal”: a study of organizational flexibility, integration and agility in the Peruvian coffee supply chain

Purpose: Considering the unprecedented supply chain disruptions due to the COVID-19 pandemic, especially in the agri-food sector, the possession of dynamic capabilities (DCs) – particularly, the need for higher agility – seems to be the key to survival in highly uncertain environments. This study aims to use the dynamic capability view (DCV) theory to analyze how three key supply chain capabilities – organizational flexibility, integration and agility – should be combined to obtain the desired supply chain performance. Design/methodology/approach: The authors designed a conceptual model in which the relationships between these three key capabilities and supply chain performance were hypothesized. The model was first tested through partial least square regression using survey data collected from 98 members of the Peruvian coffee supply chain. A fuzzy-set qualitative comparative analysis (fsQCA) was conducted to uncover how DCs could be combined in successful supply chain configurations. Findings: The authors show that organizational flexibility is a driver of higher agility in agri-food supply chains, together with external and internal supply chain integration, that have a direct impact on agility, which positively affects supply chain performance. Higher levels of supply chain agility are necessary but insufficient to guarantee high performance, as sufficiency is reached when both integration (internal and/or external) and agility are present. Originality/value: This study represents a pioneering attempt to apply the DCV theory to agri-food supply chains – characterized by many sources of uncertainty. All the DCs are included within the same model and the joint use of PLS regression and fsQCA provides evidence about the relationships between DCs and how they can empower agri-food supply to obtain the desired performance. © 2021, Emerald Publishing Limited.

Policy responses of the COVID-19 pandemic in the Philippines: Impacts on the profitability of the agri-food supply chain

The Philippines experienced many challenges brought about by the COVID-19 pandemic. In 2020, the country experienced a decline in economic growth. The agri-food sector's micro, small and medium enterprises (MSME) are amongst the country's most vulnerable. This study analyses the various policy constraints and enablers related to food manufacturing as well as the distribution in the agri-food supply chain. This study applied a mixed methods approach. Interviews with 30 agri-food enterprise owners and key officers were conducted and concept mapping was applied using Leximancer software. Key themes emerged including introduction of new products, increased online selling activity, limited supply of inputs and packaging materials, increased cost of production and delivery, and availability of government assistance. A subsequent survey (n=125) for the food manufacturers, logistics operators, traders, wholesalers, and retailers was also implemented. The effect of policy measures on enterprises' profitability was assessed using ordered probit regression. The results suggest that the likelihood of reporting profitability after the pandemic increases when the owner or key officer is male, the business is operating under a partnership, enterprises suspended their operations at some point during the pandemic, enterprises implemented health and safety protocols for their employees, there is no oversupply of employees during the lockdown period, and enterprises increased operation work hours during lockdown. The study also highlighted that manufacturing and distribution of food during the pandemic should be unhampered. However, MSMEs in the agri-food chain experienced delays and increases in prices of raw materials despite clear policy guidelines. Interregional trade was affected due to varying localised policies on health protocols and lockdowns. These policy constraints generally affected the profitability of the enterprises.

Risk and resilience in agri-food supply chain SMEs in the pandemic era: a cross-country study

The sustainable and resilient agri-food systems are essential to ensure food security and nutrition for a rapidly growing world population. While the unprecedented COVID-19 outbreak has undoubtedly disrupted numerous businesses, small- and medium-sized enterprises (SMEs) of agri-food supply chains (AFSCs) wereseen more vulnerable to disruptions due to their unique operational challenges. This research explores how SMEs of AFSCs across developing and developed contexts were disrupted by COVID-19 inflicted risks and what useful measures were embraced to cultivate supply chain resilience (SCRE). A qualitative research method, with 24 semi-structured interviews including two developing (Pakistan and Tanzania) and a developed (Australia) country, was employed. The cross-country analysis unveils a noticeable difference in risk and SCRE profiles between developing and developed contexts. We devisea systematic account of COVID-19 inflicted risks and related SCRE strategies to survive and thrive amid the current pandemic and similar future crises. Multiple perspectives from different contextswould assistpractitioners and policymakers to learn the key lessons, enhancing resilience of agri-food SMEs. This is among the few studies exploring risk and SCRE in SMEs of AFSCs across developing and developed contexts, benchmarking robust strategies applied by some leading firms. Our proposed conceptual framework offers a roadmap to building more resilient agri-food SMEs. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Modelling Internet of things (IoT)-driven global sustainability in multi-tier agri-food supply chain under natural epidemic outbreaks.

Epidemic outbreak (COVID-19, SARS-CoV-2) is an exceptional scenario of agri-food supply chain (AFSC) risk at the globalised level which is characterised by logistics' network breakdown (ripple effects), demand mismatch (uncertainty), and sustainable issues. Thus, the aim of this research is the modelling of the sustainable based multi-tier system for AFSC, which is managed through the different emerging application of Internet of things (IoT) technology. Different IoT technologies, viz., Blockchain, robotics, Big data analysis, and cloud computing, have developed a competitive AFSC at the global level. Competitive AFSC needs cautious incorporation of multi-tiers suppliers, specifically during dealing with globalised sustainability issues. Firms have been advancing towards their multi suppliers for driving social, environments and economical practices. This paper also studies the interrelationship of 14 enablers and their cause and effect magnitude as contributing to IoT-based food secure model. The methodology used in the paper is interpretative structural modelling (ISM) for establishing interrelationship among the enablers and Fuzzy-Decision-Making Trial and Evaluation Laboratory (F-DEMATEL) to provide the magnitude of the cause-effect strength of the hierarchical framework. This paper also provides some theoretical contribution supported by information processing theory (IPT) and dynamic capability theory (DCT). This paper may guide the organisation's managers in their strategic planning based on enabler's classification into cause and effect groups. This paper may also encourage the mangers for implementing IoT technologies in AFSC.