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Despite its crucial role in ensuring food safety, traceability remains underutilized by small and medium-sized enterprises (SMEs), a vital component of China’s agricultural supply chain, thereby compromising the integrity of the supply chain traceability system. Therefore, this study sets out to explore the factors influencing SMEs’ adoption of traceability systems and the impact of these factors on SMEs’ intent to adopt such systems. Furthermore, the study presents a model to deepen understanding of system adoption in SMEs and provides a simulation demonstrating the evolutionary trajectory of adoption behavior.

This study considers the pivotal aspects of system adoption in SMEs, aiming to identify the influential factors through a grounded theory-based case study. Concurrently, it seeks to develop a mathematical model for SMEs’ adoption patterns and simulate the evolution of SMEs’ adoption behaviors using the Q-learning algorithm.

The adoption of traceability among SMEs is significantly influenced by factors such as system attributes, SMEs’ capability endowment, environmental factors and policy support and control. However, aspects of the SMEs’ capability endowment, specifically their learning rate and decay rate, have minimal impact on the adoption process. Furthermore, group pressure can expedite the attainment of an equilibrium state, wherein all SMEs adopt the system.

This study fills the existing knowledge gap about the adoption of traceability by SMEs in China’s agricultural supply chain. This study represents the pioneer study that identifies the factors influencing SMEs’ adoption and examines the effects of these factors on their traceability adoption, employing a multi-methodological approach that incorporates grounded theory, mathematical modeling and the Q-learning algorithm.

The objective of this study is to improve the food supply chain performance taking into consideration the fundamental concepts of traceability by combining the current frameworks, its principles, its implications and the emerging technologies.

A narrative literature review of already existing empirical research on traceability systems was conducted resulting in 862 relevant papers. Following a step-by-step sampling process, the authors ended up with 46 final samples for the literature review.

The main findings of this study include the various descriptions of the architecture of traceability systems, the different sources enabling this practice, the common desirable attributes, and the enabling technologies for the deployment and implementation of traceability systems. Moreover, several technological solutions are presented, which are currently available for traceability systems, and finally, opportunities for future research are provided.

It provides an insight, which could affect the implementation process of traceability in the food supply chain and consequently the effective management of a food traceability system (FTS). Managers will be able to create a traceability system, which meets users' requirements, thus enhancing the value of products and food companies.

This study contributes to the food supply chain and the traceability systems literature by creating a holistic picture of where something has been and where it should go. It is a starting point for each food company to design and manage its traceability system more effectively.

The purpose of this study is to increase awareness of current supply chain (SC) security-related issues by providing an extensive analysis of existing SC security solutions and their limitations. The security of SCs has received increasing attention from researchers, due to the emerging risks associated with their distributed nature. The increase in risk in SCs comes from threats that are inherently similar regardless of the type of SC, thus, requiring similar defence mechanisms. Being able to identify the types of threats will help developers to build effective defences.

In this work, we provide an analysis of the threats, possible attacks and traceability solutions for SCs, and highlight outstanding problems. Through a comprehensive literature review (2015–2021), we analysed various SC security solutions, focussing on tracking solutions. In particular, we focus on three types of SCs: digital, food and pharmaceutical that are considered prime targets for cyberattacks. We introduce a systematic categorization of threats and discuss emerging solutions for prevention and mitigation.

Our study shows that the current traceability solutions for SC systems do not offer a broadened security analysis and fail to provide extensive protection against cyberattacks. Furthermore, global SCs face common challenges, as there are still unresolved issues, especially those related to the increasing SC complexity and interconnectivity, where cyberattacks are spread across suppliers.

This is the first time that a systematic categorization of general threats for SC is made based on an existing threat model for hardware SC.

This study aims to examine the blockchain landscape in supply chain management by drawing insights from academic and industry literature. It identifies the key drivers, categorizes the products involved and highlights the business values achieved by early adopters of blockchain technology within the supply chain domain. Additionally, it explores fingerprinting techniques to establish a robust connection between physical products and the blockchain ledger.

The authors combined the interpretive sensemaking systematic literature review to offer insights into how organizations interpreted their business challenges and adopted blockchain technology in their specific supply chain context; content analysis (using Leximancer automated text mining software) for concept mapping visualization, facilitating the identification of key themes, trends and relationships, and qualitative thematic analysis (NVivo) for data organization, coding and enhancing the depth and efficiency of analysis.

The findings highlight the transformative potential of blockchain technology and offer valuable insights into its implementation in optimizing supply chain operations. Furthermore, it emphasizes the importance of product provenance information to consumers, with blockchain technology offering certainty and increasing customer loyalty toward brands that prioritize transparency.

This research has several limitations that should be acknowledged. First, there is a possibility that some relevant investigations may have been missed or omitted, which could impact the findings. In addition, the limited availability of literature on blockchain adoption in supply chains may restrict the scope of the conclusions. The evolving nature of blockchain adoption in supply chains also poses a limitation. As the technology is in its infancy, the authors expect that a rapidly emerging body of literature will provide more extensive evidence-based general conclusions in the future. Another limitation is the lack of information contrasting academic and industry research, which could have provided more balanced insights into the technology’s advancement. The authors attributed this limitation to the narrow collaborations between academia and industry in the field of blockchain for supply chain management.

Practitioners recognize the potential of blockchain in addressing industry-specific challenges, such as ensuring transparency and data provenance. Understanding the benefits achieved by early adopters can serve as a starting point for companies considering blockchain adoption. Blockchain technology can verify product origin, enable truthful certifications and comply with established standards, reinforcing trust among stakeholders and customers. Thus, implementing blockchain solutions can enhance brand reputation and consumer confidence by ensuring product authenticity and quality. Based on the results, companies can align their strategies and initiatives with their needs and expectations.

In essence, the integration of blockchain technology within supply chain provenance initiatives not only influences economic aspects but also brings substantial social impacts by reinforcing consumer trust, encouraging sustainable and ethical practices, combating product counterfeiting, empowering stakeholders and contributing to a more responsible, transparent and progressive socioeconomic environment.

This study consolidates current knowledge on blockchain’s capacity and identifies the specific drivers and business values associated with early blockchain adoption in supply chain provenance. Furthermore, it underscores the critical role of product fingerprinting techniques in supporting blockchain for supply chain provenance, facilitating more robust and efficient supply chain operations.

Food insecurity is a major concern for developing economies. Operational inadequacies get introduced with unorganized interactions among stakeholders in the food supply chain, affecting social, economic, environmental and operational (SEEO) aspects of a nation. This study analyzes India's largest food safety net program, Public Distribution System (PDS) and develops a perception-based model, mapping the root causes (of food insecurity) with possible solutions. The novelty lies in leveraging blockchain in the implementation of food traceability system.

Soft system methodology (SSM) is used to identify and analyze problems in PDS, leveraging the learning and inquiry process. It relies on system thinking and action research to create a defendable and rational model, which helps in proposing recommendations for addressing the problem.

Blockchain-enabled food traceability system increases transparency, thus enabling the fulfillment of basic food necessities for beneficiaries.

The proposed model enables policymakers to build a profound understanding of existing operational issues and provides insightful recommendations for making informed decisions to deal with the grave issue of food insecurity.

Unlike previous studies, this research attempts to understand operational inefficiencies during interactions among stakeholders. It proposes a perception-based conceptual model for the final implementation at the ground level. It also reveals significance of three systems: a delivery system, an enabling system empowering delivery system and a criteria system to control and monitor processes. This study thus bridges an important gap in the literature by proposing a blockchain-driven traceability system, under the control of criteria system, through the integration of system-thinking and action-research approach.

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.

Firms are increasingly pressured to comply with mandatory supply chain transparency (SCT) regulations. Drawing on information processing theory (IPT), this study aims to show how blockchain technology can address information uncertainty and equivocality in assuring regulatory compliance in an interorganizational network (ION).

IPT is applied in a single case study of an ION in the mining industry that aimed to implement blockchain to address mandatory SCT regulations. The authors build on a rich proprietary data set consisting of interviews and substantial secondary material from actors along the supply chain.

The case shows that blockchain creates equality between actors, enables compliance and enhances efficiency in an ION, reducing information uncertainty and equivocality arising from conflict minerals regulation. The system promotes engagement and data sharing between parties while protecting commercial sensitive information. The lack of central authority prevents larger partners from taking control. The system provides mineral provenance and a regulation-compliant record. System cost analysis shows that the system is efficient as it is inexpensive relative to volumes and values of metals transacted. Issues were identified related to collecting richer human rights data for assurance and compliance with due diligence regulations.

The authors provide some of the first evidence in the operations and supply chain management literature of the specific architecture, costs and limitations of using blockchain for SCT. Using an IPT lens in an ION setting, the authors demonstrate how blockchain-based systems can address two key IPT challenges: environmental uncertainty and equivocality.

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 research examines the impact of governance structures within the Brazilian pork supply chain on the necessary controls for exportation. Specifically, the goal is to unravel the intricacies of this supply chain and decode its complexity.

Using transaction cost economics as a theoretical lens, we surveyed the main bodies responsible for the export and quality assurance sectors of Brazilian organizations that trade and export pork. Our sample comprises 53.5% of the country’s pork exporting companies during the period analyzed.

The presence of vertical and horizontal governance structures in the pork export chain stands out. While the vertical structure enables greater control due to command relations, there are trust and cooperation relations in the horizontal structure. This makes it possible to establish mechanisms to control health, quality, safety and traceability in both structures. We also identified each company’s characteristics: formation configuration (if the cooperative, publicly traded company, or other modality), capital stock, location, the average daily slaughter of pigs for export and sows per producer. We conclude that the organizations have concerns related to the food safety programs, as there are programs that seek transparency throughout the process in many supply chain stages.

Studies that relate the level of orientation to the export market with the occurrence or risk of corrupt and opportunistic behavior and the coordination mechanisms adopted may represent an interesting and important opportunity for studies.

This study helps to understand the complexity of the Brazilian pork supply chain.

The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.