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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.

Despite the growing interest in blockchain technology (BCT) applications in the agri-food industry, evidence of their economic and strategic implications remains scarce. This study aims to contribute to filling this gap by jointly investigating how BCT adoption affects transactional relationships, and how it contributes to the firm’s strategic resources.

An explanatory case study is conducted based on a theoretical framework grounded on transaction cost economics and the resource-based-dynamic capabilities view. Six BCT implementations by agri-food firms are studied. Data were collected through semi-structured interviews and analysed using thematic analysis.

Findings reveal that BCT benefits depend on how companies integrate technology across their supply chains. In fact, the results suggest that overall transaction efficiency within the supply chain is enhanced only for those firms prioritising stakeholder engagement during technology implementation and leveraging existing trust relationships with economic agents. Moreover, the results suggest that BCT is not yet perceived as a strategic resource, but rather that it has the potential to enhance firms’ operational-adaptive, absorptive and innovative capabilities. When all supply chain actors clearly understand blockchain’s functionality and value, the development of these capabilities becomes more pronounced.

The study identifies two BCT adoption configurations. One primarily focuses on enhancing supply chain efficiency and transparency (dynamic BCT), while the other uses BCT mainly for marketing purposes (static BCT). These configurations lead to varied possibilities for leveraging BCT’s potential advantages. Furthermore, they show how a mismatch between a strategic approach and its chosen configuration could work against any positive impact and lead to disillusionment with the BCT. Thus, managers should assess carefully the impact of such different configuration choices on performance.

To the best of the authors’ knowledge, this is the first study to attempt to analyse the economic implications of adopting BCT in the food sector from both a firm and supply chain perspective. Additionally, it shows how interpreting these impacts is contingent on the diverse modalities for embedding BCT into existing supply chains.

Food quality and safety issues have always been imperative topics discussed by people. The anti-tampering of blockchain technology and the transparency of information make it possible to improve food traceability and safety quality. How to effectively apply blockchain traceability technology to food safety has great research significance for improving food safety and consumer quality trust.

The paper aims to analyze the differences in product quality levels and market participants’ profits before and after the use of blockchain-driven traceability technology in the food agricultural product supply chain (SC) in the dynamic game frameworks of supplier-led and retailer-led modes, respectively, and explores the willingness, social welfare and consumer surplus of each member of the agricultural product SC to participate in the blockchain. Besides, We investigate the SC performance improvement with the mechanism of central centralized decision-making and revenue-sharing contract, compared to the SC performance in dynamic games.

The results are obtained as follow: The adoption of blockchain traceability technology can help improve the quality of food agricultural products, consumer surplus and social welfare, but the application and popularization of technology is hindered by traceability technology installment costs. Compared with the supplier leadership model, retailer-led food quality level, customer surplus and social welfare are higher.

How to effectively apply blockchain traceability technology to food safety has great research significance for improving food safety and consumer quality trust.

Food quality and safety issues have always been hot topics discussed by people. The anti-tampering of blockchain technology and the transparency of information make it possible to improve food traceability and safety quality.

The research results enrich the theories related to food safety and quality, and provide a valuable reference for food enterprises involved in the decision-making exploration of blockchain technology.

Based on the characteristics of blockchain technology, the demand function is adjusted and the product loss risk of channel members is transferred through a Stackelberg game SC composed of agricultural products suppliers and retailers.

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  We introduce two features of blockchain: quality trust and product information tracking.

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  The willingness of each member of the supply chain to use blockchain for product traceability was explored.

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  The overall traceability effect of the retailer-led blockchain is better than that of the manufacturer-led blockchain.

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  The cost of blockchain technology is a barrier to its adoption.

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  Blockchain brings higher consumer surplus and social welfare.

We introduce two features of blockchain: quality trust and product information tracking.

The willingness of each member of the supply chain to use blockchain for product traceability was explored.

The overall traceability effect of the retailer-led blockchain is better than that of the manufacturer-led blockchain.

The cost of blockchain technology is a barrier to its adoption.

Blockchain brings higher consumer surplus and social welfare.

The complexity of citizenship behavior in organizations has long been a focus of research. Traditional methodologies have been predominantly used to address this complexity. This paper aims to tackle the problem using a cutting-edge technological tool: business process mining. The objective is to enhance citizenship behaviors by leveraging primary data collected from 326 white-collar employees in the Indian service industry.

The study focuses on two main processes: training and creativity, with the ultimate goal of fostering organizational citizenship behavior (OCB), both in its overall manifestation (OCB-O) and its individual components (OCB-I). Seven different machine learning algorithms were used: artificial neural, behavior, prediction network, linear discriminant classifier, K-nearest neighbor, support vector machine, extreme gradient boosting (XGBoost), random forest and naive Bayes. The approach involved mining the most effective path for predicting the outcome and automating the entire process to enhance efficiency and sustainability.

The study successfully predicted the OCB-O construct, demonstrating the effectiveness of the approach. An optimized path for prediction was identified, highlighting the potential for automation to streamline the process and improve accuracy. These findings suggest that leveraging automation can facilitate the prediction of behavioral constructs, enabling the customization of policies for future employees.

The findings have significant implications for organizations aiming to enhance citizenship behaviors among their employees. By leveraging advanced technological tools such as business process mining and machine learning algorithms, companies can develop more effective strategies for fostering desirable behaviors. Furthermore, the automation of these processes offers the potential to streamline operations, reduce manual effort and improve predictive accuracy.

This study contributes to the existing literature by offering a novel approach to addressing the complexity of citizenship behavior in organizations. By combining business process mining with machine learning techniques, a unique perspective is provided on how technological advancements can be leveraged to enhance organizational outcomes. Moreover, the findings underscore the value of automation in refining existing processes and developing models applicable to future employees, thus improving overall organizational efficiency and effectiveness.

The purpose of this study is to present a methodical procedure on how to prepare event logs and analyse them through process mining, statistics and visualisations. The aim is to derive roots and patterns of quality deviations and non-conforming finished products as well as best practice facilitating employee training in the food processing industry. Thereby, a key focus is on recognising tacit knowledge hidden in event logs to improve quality processes.

This study applied process mining to detect root causes of quality deviations in operational process of food production. In addition, a data-ecosystem was developed which illustrates a continuous improvement feedback loop and serves as a role model for other applications in the food processing industry. The approach was applied to a real-case study in the processed cheese industry.

The findings revealed practical and conceptional contributions which can be used to continuously improve quality management (QM) in food processing. Thereby, the developed data-ecosystem supports production and QM in the decision-making processes. The findings of the analysis are a valuable basis to enhance operational processes, aiming to prevent quality deviations and non-conforming finished products.

Process mining is still rarely used in the food industry. Thereby, the proposed method helps to identify tacit knowledge in the food processing industry, which was shown by the framework for the preparation of event logs and the data ecosystem.

Since previous literature provides fragmented and conflicting results about the use of digital data for product innovation, the article aims to comprehensively explore and shed light on how agri-food firms utilise external and internal digital data sources when dealing with different product innovations, such as incremental, architecture and radical innovation.

This paper adopts an exploratory multiple-case study and a theory-building process, focussing on the agri-food industry. We collected primary and secondary data from eight manufacturing companies.

The findings of this research show an empirical framework of six agri-food firms’ digital data utilisation behaviours: the supervisor, the passive supervisor, the developer, the passive developer, the pathfinder and the conjunction behaviour. These digital data utilisation behaviours vary according to a combination of data sources, such as internal data related to inside phenomenon measures (e.g. data generated by sensors installed in the production plan) or external data (e.g., market trends, overall sector sales), and innovation purposes.

This article offers guiding principles that assist agri-food companies when utilising internal and external digital data sources for specific product innovation outcomes such as incremental, architectural and radical innovation.

The significance of external and internal data sources in stimulating product innovation has garnered substantial attention within academic discussions, highlighting the critical importance of analysing digital data for driving such innovation. Nonetheless, the predominant approach is to study a single innovation outcome through the lens of digital technology. In contrast, our study stands out by adopting a fundamental perspective on data sources, enabling a more nuanced explanation of the overall product innovation outcomes within the agri-food sector.

This study draws on the conservation of resources logic to theorize the role of firm resilience in explaining variations in entrepreneurial well-being under varying conditions of supply chain disruption and dependency ratio.

The study uses ex-post survey data from 373 women entrepreneurs in diverse agricultural supply chains in Ghana, a sub-Saharan African country. Moderated regression analysis is employed to test the research hypotheses.

The results indicate that firm resilience has both positive and negative relationships with economic and subjective well-being, depending on the level of supply chain disruption and dependency ratio women entrepreneurs face. Notably, the findings suggest that firm resilience contributes more to economic and subjective well-being of women entrepreneurs when dependency ratio is low and supply chain disruption is high.

The study integrates firm resilience research and entrepreneurial well-being literature to provide new insights into theorizing and analyzing the benefit of firm resilience for women entrepreneurs’ well-being.

This study aims to investigate the integration of blockchain technology into the food supply chain within the restaurant industry. It focuses on how blockchain can be applied to enhance transparency and trust in tracking food sources, ultimately impacting customer satisfaction.

A service design workshop (Study 1) and three between-subjects experiments (Studies 2–4) were conducted.

Results indicate that blockchain adoption significantly improves traceability and trust in the food supply chain. This improvement in turn enhances customer satisfaction through perceived improvements in food safety, quality and naturalness. This study also notes that the effects of blockchain technology vary depending on the type of restaurant (casual or fine dining) and its location (tourist destinations or residential areas).

The findings offer practical insights for restaurant owners, technology developers and policymakers. Emphasizing the benefits of blockchain adoption, this study guides decision-making regarding technology investments for enhancing customer service and satisfaction in the hospitality sector.

This research contributes novel insights to the field of technology innovation in the hospitality industry. It extends the understanding of signaling theory by exploring how blockchain technology can serve as a tool for signal transmission in restaurant food supply chains.

Small farmers in India are collectivized and legalized as Farmer Producer Companies (FPCs) to progress in agri-food value chains as small agribusiness enterprises. FPCs are dependent on timely information for their sustainability and profitability. Mobile apps are a cost-effective form of information and communication technology. Hence, the purpose of this study is to explore the major determinants of mobile apps adoption by FPCs.

Quantitative and qualitative data are collected by administering a semi-structured questionnaire and conducting in-depth interviews with board members of 115 FPCs, with a total membership of 30,405 farmers operating in 14 districts of the state of Kerala, India. The logit model is used for quantitative analysis, while dialog mapping is used for qualitative analysis, based on an integrated technology acceptance model and technology organization environment framework.

Logistic regression results evidence that amongst FPC characteristics, while company size and age are significantly impacting apps adoption, there is no significant association between board size, education level, multiple commodities business or export intention of companies on apps adoption. Digital literacy and technical hands-on training for FPC board members are quintessential to facilitate mobile apps adoption.

The findings are pertinent to policymakers to earmark funds for technical handholding and digital upskilling of FPCs. The need for developing comprehensive, location-centric, farmer-friendly apps by agritech companies is evidenced.

To the best of the authors’ knowledge, this is a pioneering work in the domain of mobile apps adoption from a farmers’ agribusiness enterprise perspective in an emerging market economy using a mixed-methods approach.

The aim of this research is to elucidate the correlation between open innovation, digital strategies and networking in enhancing agricultural enterprises within the new perspective of Agrifood 5.0. As such, it contributes to making businesses more competitive, especially in the Italian agricultural sector, where small and medium-sized enterprises are highly fragmented. Numerous studies have asserted that the competitiveness of actors operating within a specific territory is closely linked to local identity and image enhancement. Agricultural organizations are undergoing a profound transformation, with technological assets emerging as catalysts for new synergies. Advanced technologies such as robotics, the Internet of Things (IoT) and automation (AI) are emerging as differentiating elements capable of further advancing the agricultural sector, transitioning it from Agrifood 4.0 to Agrifood 5.0. The empirical analysis of the research shows a positive correlation between a collaborative attitude and a propensity for innovation. Indeed, the data demonstrated that digital strategies and open innovation positively influence competitiveness in agricultural SMEs.

The methodology employed in this study is mixed, incorporating both qualitative and quantitative approaches. The quantitative aspect involves analysis of the dataset from the Italian Statistical Institute (ISTAT) through logistic regression, while the qualitative component entails analysis of semi-structured interviews conducted with a sample of 174 agricultural cooperatives in southern Italian regions (Campania). This approach allows for a comprehensive understanding of the research topic, capturing both numerical trends and nuanced insights from interviews.

After analyzing the data from the 7th General Census of Agriculture conducted by ISTAT, a clear understanding of the sector has emerged, revealing several potential research avenues. It is evident that innovation in the agricultural sector is often driven by the largest and best-capitalized production entities, primarily located in Italy. Conversely, smaller agricultural entities can benefit from networking as new technological assets act as catalysts for new synergies, innovation and competitiveness.

Enhancing the relational contribution within the network and humanizing a fragmented sector are crucial elements for promoting open innovation. Network structuring facilitates the transmission of managerial knowledge, contributing to an overall increase in the intellectual and relational capital of the agricultural sector. These factors, combined with open innovation, enhance the competitiveness of individual firms and elevate the brand of the entire sector, creating a conducive environment for transitioning toward Agrifood 5.0. This transition is characterized by increased interconnection, continuous innovation and overall prosperity. Specific studies on this topic are lacking in Italy, particularly in the southern regions. Therefore, this contribution focuses on investigating the Campania region.

The novelty of this study lies in its investigation of the relationship between agricultural enterprises and innovation in the context of enterprises networking strategies (i.e. associationism and/or cooperation), promoting competitiveness. The limitations of this study are related to the dimension of the sample selected and its relationship with other productive sectors.