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This paper aims at understanding how companies in the agri-food are reconfiguring their competitive strategies to face the coronavirus disease 2019 (COVID-19) pandemic. Literature has focused mainly on the effect of the pandemic on the supply chain or in its value chain but little has been said on the competitive strategies adopted to overcome the challenges posed by COVID-19 pandemic.

The study was conducted on Italian companies operating in the agri-food industry from May to September 2020, following a mixed method approach. First, a focus group with experts in competitive strategy and agri-food industry has been organized to identify the most important challenges that companies are facing. Second, through a structured questionnaire, data from 123 companies operating in the agri-food industry were gathered and analyzed with K-means clustering method.

Four clusters of companies were identified, each implementing different strategies to face the COVID-19 pandemic: “the cost fanatics”, “the brand focused”, “the sales centered” and “the strategists”. Furthermore, it was possible to identify new trends in competitive strategies to increase the added value that the Italian agri-food industry can provide to the customer.

The paper answers to the need for an investigation of the competitive strategies that agri-food companies have put in place to face the COVID-19 pandemic; moreover, it provides insights on how companies are adapting themselves to this rapidly changing environment. From a managerial point of view, it gives practitioners and managers useful insights on the different strategies that companies are undertaking to maintain a competitive advantage.

Scholarly literature on entrepreneurial activities in the agri-food sector has flourished over the years in several different ways. This study uses the metaphor of an orchard to describe how this stream of literature has evolved from its initial “seeds” to the rich and diversified “fruits” of current debate. It is now time to harvest and catalogue these “fruits”. This study aims to map out and systematise the current stock of knowledge on agri-food entrepreneurship, so as to identify gaps and thus “plant” new seeds for the future of the “orchard”.

To identify thematic clusters, this study used a bibliometric analysis coupled with a systematic literature review performed over a dataset of 108 peer-reviewed articles.

The results revealed six thematic clusters related to agri-food entrepreneurship: ecosystems, formal and informal institutions; contextual entrepreneurial practices; community and stakeholders’ engagement; barriers and opportunities; entrepreneurial orientation; and sustainable entrepreneurship. After investigating each of them, this study created a framework to highlight future avenues through which the topic could be further developed.

To the best of the authors’ knowledge, this study is the first of its kind to systematise, analyse and critically interpret the literature concerned with agri-food entrepreneurship.

The purpose of this study is to propose a halal cluster concept to better organise production and trade of halal food.

This paper builds further on previous work published in the Journal of Islamic Marketing on halal food supply chains and value chains. A cluster analysis is conducted on the Malaysia and Dubai halal cluster to provide a better understanding of their halal cluster models and sustainability.

Food production and trade has been described as the weak link in the halal value chain. To guarantee availability of and access to halal food, a new paradigm is required in better organising the production and trade of halal food through halal clusters. A halal cluster model is proposed based on five pillars, namely, Muslim consumer, education and research, halal integrity network, halal supply chain and enablers.

This conceptual paper proposes a halal cluster model to scale up the production of halal food for the world. However, more empirical research on halal purchasing, halal network development, halal trade and halal parks is needed to support the development of these halal clusters.

To better address today’s issues in the halal industries (ingredients, certification, logistics, etc.), there are evident benefits of producing in strong halal clusters, hereby providing easy access to halal ingredients and access to attractive Muslim markets.

As halal is going through an evolution, towards a halal supply chain and value chain, new business models are required. It is the first study investigating halal clusters.

This paper aims to provide an overview of the application of blockchain to agri-food supply chains, including key issues and trends. It examines the state of the art and conceptual structure of the field and proposes an agenda to guide future research.

This article performs a bibliometric analysis using VOSviewer software on a sample of 205 articles from the WoS database to identify research trend topics.

The number of publications in this area has increased since 2020, which shows a growing research interest. The research hotspots are related to the integration of blockchain technology in the agri-food supply chain for traceability, coordination between all actors involved, transparency of operations and improvement of food safety. Furthermore, this is linked to sustainability and the achievement of the sustainable development gtoals (SDGs), while addressing key challenges in the implementation of blockchain-based technologies in the agri-food supply chain.

The application of blockchain in the agri-food supply chain may consider four key aspects. Firstly, the implementation of blockchain can improve the traceability of food products. Secondly, this technology supports sustainability issues and could avoid disruptions in the agri-food supply chain. Third, blockchain improves food quality and safety control throughout the supply chain. Fourthly, the findings show that regulation is needed to improve trust between stakeholders.

The paper provides a comprehensive overview of the blockchain phenomenon in the agri-food supply chain by optimising the search criteria. Moreover, it serves to bridge to future research by identifying gaps in the field.

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 analyses the literature on artificial intelligence (AI) and its implications for the agri-food sector. This research aims to identify the current research streams, main methodologies used, findings and results delivered, gaps and future research directions.

This study relies on 69 published contributions in the field of AI in the agri-food sector. It begins with a bibliographic coupling to map and identify the current research streams and proceeds with a systematic literature review to examine the main topics and examine the main contributions.

Six clusters were identified: (1) AI adoption and benefits, (2) AI for efficiency and productivity, (3) AI for logistics and supply chain management, (4) AI for supporting decision making process for firms and consumers, (5) AI for risk mitigation and (6) AI marketing aspects. Then, the authors propose an interpretive framework composed of three main dimensions: (1) the two sides of AI: the “hard” side concerns the technology development and application while the “soft” side regards stakeholders' acceptance of the latter; (2) level of analysis: firm and inter-firm; (3) the impact of AI on value chain activities in the agri-food sector.

This study provides interpretive insights into the extant literature on AI in the agri-food sector, paving the way for future research and inspiring practitioners of different AI approaches in a traditionally low-tech sector.

The purpose of this study is to disentangle the drivers of adoption of procurement strategies in situations where small agri-food firms deal with constrained organizational choices. More specifically, the authors investigate the role of transaction costs, capabilities and networks in the definition of feasible “make-or-buy” choices in emerging wine regions.

This article analyzes a unique dataset of small wineries from five US states: Illinois, Michigan, Missouri, New York and Vermont. The reported results derive from both a hurdle model (i.e. a probit model and a truncated regression model) and a tobit model.

The results suggest the importance of trust as a replacement for formal governance structures whenever small firms deal with highly constrained sets of organizational choices. On the other hand, the level of dependence on a limited mix of winegrape varieties and the perception that these varieties are fundamental in building legitimacy help to explain higher rates of vertical integration.

This study is important because it sheds light on organizational constraints that affect millions of farmers across the globe. The study of “make-or-buy” decisions in agri-food supply chains has mostly relied on the implicit assumption that all organizational choices are available to every firm. Nevertheless, limited capabilities and the participation in low-density networks may constrain the ability of a firm to adopt a governance mechanism. Stated organizational preferences and actual organizational choices may thus differ.

This paper aims to analyse how local agri-food systems (LAFS), compared to other production models, can offer innovative responses to the important environmental challenges facing food production under the twin transition. These responses are more conducive to community inclusion and local development.

The paper combines territorial development, clusters and industrial districts literature with studies on agri-food industry environmental problems and twin transition technologies to develop an agri-food systems typology. This typology is based on a territorial approach to environmental challenges of food production and serves to illustrate the ways in which LAFS can provide innovative responses to these challenges.

The study allows to visualise the differences between LAFS and other agri-food production models, showing how the operationalisation and implementation of digitisation occur at territorial level and how rural communities are involved in the process. The theoretical proposal emphasises not assuming that technology is inherently beneficial but ensuring that its implementation is inclusive and generates social value for the communities.

The paper aims to enrich future research by adopting a territorial perspective to study the twin transition challenges associated with food production systems.

Inquiring about the patterns of interaction within clusters can provide a valuable insight into the cooperation and competition strategies followed by firms. However, such internal patterns are difficult to identify using conventional methods. This study aims to apply a social network analysis approach to identify and analyze different sub-groups of firms within a dairy cluster. These sub-groups seem to respond to different forms of productive organization, with different levels of territorial anchorage.

The authors study the dairy cluster in the south-west of Uruguay, where one of the country’s main industries is located. The authors use data from semi-structured interviews applied to managing directors of 40 dairy industrial firms. The authors analyze the collaboration network among firms and industry support organizations. Using a community detection algorithm, the authors identify strategic groups of firms and organizations within the network. The authors analyze information from the interviews to delve deeper into the strategies pursued by actors in each of these sub-groups.

The four groups identified by the algorithm respond to particular logics associated not only with collaborative behavior, but also with territorial distribution and competitive strategies pursued by firms. In particular, these communities show a positive association between the centrality of their nodes in the network, the size of their firms, their export orientation and their innovative capacity. These associations indicate the co-existence, within the cluster, of different local productive systems and other forms of productive organization.

The paper illustrates how different strategies of firms within a cluster can be understood using social network analysis. This approach is particularly interesting in agri-food clusters, where their wider dispersion in the territory often implies their firms following different collaborative and competitive strategies, and different levels of territorial anchorage.

Because the business model (BM) is a fairly new concept, research is lacking on business model innovation (BMI) in certain industry sectors. One such sector is the agri-food sector. Using a systematic literature review (SLR) of peer-reviewed journal articles published from 1990 to 2014, the purpose of this paper is to examine the where, when, and how of the use of BMs and BMI in the agri-food sector.

A web-based search was conducted to identify peer-reviewed journal articles that contained a combination of “BM” or “BMI” with agriculture-related and food-related terms (e.g. “agri-food sector”). After winnowing out irrelevant and duplicate articles, 505 articles were chosen for analysis.

Using categories, the paper analyses various data about the selected articles. The categories include research settings, units of analysis, methodologies, and theories. Based on this analysis, the paper finds that these agri-food sector articles are primarily qualitative, empirical studies that focus on one or a few companies (i.e. case studies). The paper also finds that theory is not yet well-developed in the research on the agri-food sector.

SLRs of various concepts, theories, and models are common in many fields (e.g. information/software technology, healthcare, and organizational management). However, no such review is available for the agri-food sector, in particular in its use of BMs and BMI. This paper addresses that gap with its review of relevant articles published in more than 300 journals in recent years. Based on this review, the paper draws conclusions about BMI in the agri-food sector and offers suggestions for future research.