A Data-Driven Topic Modeling Analysis of Blockchain in Food Supply Chain Traceability

Abstract

Blockchain technology plays a critical role in strengthening traceability in food supply chains (FSCs), particularly in relation to transparency, authenticity, food safety, and sustainability. This study conducts a systematic review of 518 journal articles retrieved from Scopus and Web of Science and applies latent Dirichlet allocation (LDA) topic modeling to identify dominant research trends. The analysis reveals eight key themes, including blockchain adoption enablers and challenges, consumer perceptions, supply chain traceability systems, sustainability, and food safety applications. The findings highlight significant growth in academic interest and demonstrate how blockchain improves visibility and efficiency across supply chain actors. The review offers theoretical insights into blockchain’s interdisciplinary role in FSC traceability and provides practical guidance for farmers, food industries, policymakers, and technology developers, while outlining future research opportunities.

1. Introduction

Global food supply chains (FSCs) have undergone significant transformation under the influence of globalization, which has intensified cross-border exchanges of both products and information [1,2,3]. Traditionally, FSCs are characterized by strong vertical integration and coordination, pursuing efficiency by reducing transaction, operational, and marketing costs, while simultaneously meeting consumer expectations regarding food quality and safety [4,5]. Consequently, the demand for greater transparency, reliable information flows, and robust traceability systems that monitor agricultural products from production to retail has considerably increased [6,7,8]. The urgency of these requirements has been accentuated by major international food scandals, including the horsemeat case in Europe and the melamine contamination in China [9,10]. In response, regulatory frameworks now mandate the traceability of each component within food products [11]. Furthermore, consumers’ persistent demand for agricultural goods across seasons has amplified the need for detailed information on safety, quality, authenticity, provenance, and traceability, thereby accelerating the adoption of advanced technologies within FSCs [12,13,14]. For example, Rejeb et al. [15] argue that RFID technology has been applied to improve visibility and traceability, reduce waste, and enhance overall operational efficiency. Similarly, scholars note that cloud computing has become a crucial enabler that offers both retailers and consumers access to food-related data storage and retrieval [16,17,18]. Beyond storage, cloud platforms facilitate communication along the agricultural supply chain and enable timely updates and essential guidance [19].

Despite the technological progress in FSCs, persistent challenges remain. These include continuous monitoring of FSCs, accurate prediction of product shelf life, fragmented data management, and the lack of both transparency and interoperability [7,20]. In this context, blockchain has been widely recognized by both researchers and practitioners as a potentially transformative solution. The ability to offer higher visibility and traceability makes blockchain a viable option for addressing structural inefficiencies associated with centrally managed systems, potentially reshaping supply chain processes and policies towards more transparent and efficiently managed FSCs [21,22].

From a conceptual standpoint, blockchain is defined as “a digital, decentralized, and distributed ledger, chronologically logging transactions to create permanent, tamper-proof records” (p. 574) [23]. Rejeb et al. [24] note that blockchain is best understood as a convergence of multiple technologies, tools, and practices designed for specific applications. While initially linked to cryptocurrencies [25,26], blockchain has since attracted increasing attention in logistics and supply chain management due to its ability to secure transaction immutability, enhance transparency, and foster trust among stakeholders [27]. Considering that research on blockchain in FSC traceability is still in its early stages, further exploration is necessary to realize its potential. The inherent complexity of FSCs generates new health and safety concerns that require the development of sustainable food ecosystems [28,29].

Several concrete applications illustrate the potential of blockchain technology in the food industry. For example, Dubai’s “Food Watch” program leverages blockchain alongside other digital technologies to strengthen food safety. By digitizing roles and processes, the platform provides nutritional and safety information for products offered by over 20,000 food enterprises [30]. Similarly, collaborations between IBM, Walmart, and Tsinghua University have demonstrated blockchain’s capacity to improve food safety and traceability within Chinese supply chains [31]. In another instance, the Chinese retailer Jindong partnered with Kerchin, a beef producer from Inner Mongolia, to implement a blockchain-based traceability system. This initiative integrates diverse forms of digital product data, such as farm origin, batch numbers, processing details, expiration dates, storage conditions, and shipping records. Consumers can retrieve this information, including the animal’s breed, weight, diet, and farm location, simply by scanning a QR code on the packaging [18]. Collectively, these projects point to the accelerating adoption of blockchain in the food sector as a means of promoting transparency, enhancing accountability, and boosting consumer trust in global FSCs.

Although blockchain applications in FSCs have attracted considerable scholarly attention, important gaps remain. As such, existing reviews mainly focus on specific aspects such as sustainability, transparency, or transaction efficiency, rather than providing a holistic overview of the field [32,33]. Consequently, this narrow scope risks neglecting cross-cutting linkages across different blockchain applications in agri-food systems and limits the understanding of broader implications for traceability, safety, and governance. To address this gap, the present study introduces three guiding research questions: (1) What major research themes characterize the literature on blockchain-enabled food supply chain traceability? (2) How have these themes evolved in terms of focus, intensity, and scholarly direction? (3) Which areas remain underexplored, signaling opportunities for future research and practical application? These questions operationalize the analytical approach and are examined through LDA-based topic modeling. Moreover, a stronger critical evaluation of previous literature reviews is incorporated in the next section to highlight existing limitations in scope and methodological depth, thereby reinforcing the need for a comprehensive, data-driven synthesis.

In this article, we provide an overview of the current state of research on blockchain-enabled food supply chain traceability, outline the methodological procedures used in our LDA-based topic modeling approach, present the resulting thematic structure, and discuss the implications of these findings for both theory and practice. The paper is organized as follows: Section 2 reviews the state of the field; Section 3 describes the research method; Section 4 presents the results; Section 5 offers a detailed discussion of the identified topics; and Section 6 concludes with key insights and future research directions.

2. State of the Field

In academia, the introduction of blockchain into FSCs has stimulated a growing body of reviews that examine its potential, limitations, and future pathways. In summary, existing studies converge on blockchain’s value in enhancing transparency, traceability, and trust, while also highlighting persistent barriers such as scalability, regulatory gaps, and limited stakeholder understanding. Several systematic reviews emphasize structured approaches for blockchain adoption. For example, Vu et al. [32] analyze 69 studies and identify drivers, barriers, and opportunities for blockchain implementation in FSCs. Similarly, Rana et al. [34] focus on sustainability and show how blockchain can support environmentally and socially responsible practices, while uncovering challenges such as privacy and scalability. Antonucci et al. [35] point out that blockchain technology can increase transparency and reduce transaction costs. However, blockchain’s early stage of maturity and inherent complexity are problematic for the widespread adoption of the technology. Duan et al. [36] stress benefits for traceability and recall efficiency, but highlight shortcomings in regulation and technical knowledge. Complementing these perspectives, Pandey et al. [37] opine that blockchain plays a critical role in fostering trust among stakeholders, whereas Li et al. [38] synthesize evidence from 74 studies to demonstrate its capacity to combat fraud and enhance food safety. Zhao et al. [33] identify six critical challenges in agri-food value chains, while Rejeb et al. [30] provide an overarching account of both benefits and obstacles, calling for deeper research in this evolving domain.

More recent reviews expand the scope. For instance, Chiaraluce et al. [39] examine high-value chains such as wine and olive oil, sectors prone to fraud. The authors argue that blockchain can strengthen profitability and sustainability, though research remains fragmented. Katsikouli et al. [40] analyze Small and Medium Enterprises (SMEs) in Denmark and show that blockchain can improve authenticity documentation, fair trade, and cost efficiency, but the lack of standards can hinder large-scale adoption. Finally, Ellahi et al. [18] review 60 frameworks and confirm blockchain’s established role in traceability and security while identifying underexplored areas such as food donation, redistribution, supply chain financing, and animal welfare.

To date, systematic literature reviews and bibliometric analyses have been the dominant approaches. Although they provide valuable insights, both methods have notable shortcomings. For instance, bibliometric studies often rely heavily on citation-based indicators, which alone do not capture the thematic richness or emerging research frontiers [41]. Likewise, systematic reviews typically draw from a limited body of literature and reflect subjective interpretations, potentially overlooking novel or niche areas [42]. To address these limitations, this study employs latent Dirichlet allocation (LDA) [43]. By applying topic modeling, it offers a systematic and quantitative mapping of the research landscape and identifies dominant themes as well as underexplored opportunities. In doing so, the study complements existing review methods and provides a more comprehensive understanding of blockchain in FSC traceability, informing both academic inquiry and practical applications [30].

3. Research Method

This study adopts the LDA method, which represents a hierarchical Bayesian model originally introduced by Blei et al. [44]. Conceptually, LDA is widely recognized as a probabilistic machine learning framework designed for latent topic modeling. This modeling approach is valued for its effectiveness in analyzing large collections of textual data by identifying and categorizing recurring themes [45]. Fundamentally, the model assumes that documents are mixtures of hidden topics, with each topic defined by a specific probability distribution over a set of terms [46]. When the number of topics (“K”) is predetermined and the documents are expressed through a fixed vocabulary, the algorithm generates K topics, each represented as a multinomial distribution of words. These topics emerge from clusters of associated keywords and enable researchers to infer thematic connections through inductive reasoning [47].

This research is designed as a data-driven systematic review that employs quantitative content analysis using machine learning techniques [48]. It is exploratory in nature, follows an inductive analytical logic, and relies on computational text mining to uncover latent thematic structures within a large corpus of scientific publications [49]. By combining systematic literature review principles with LDA-based topic modeling, the study provides an objective, reproducible, and scalable approach to mapping research trends [50].

In this study, the choice of LDA is motivated by its proven ability to provide reproducible and objective insights from extensive datasets [51]. The analysis was carried out using statistical and programming environments such as R 4.5.2 and Python 3.14.0, which supported tasks ranging from data preprocessing to topic extraction and visualization. These tools also facilitated natural language processing (NLP) procedures and ensured rigorous treatment of the corpus. Finally, to illustrate the overall procedure, Figure 1 offers a schematic representation of the review process and summarizes the main stages: data preparation, topic extraction with LDA, and thematic interpretation.

3.1. Selection of Publications

In this study, journal articles addressing blockchain applications in FSC traceability were chosen as the unit of analysis. Because full-length articles are often lengthy, heterogeneous, and computationally demanding, applying LDA directly to entire texts was deemed impractical. To maintain consistency across studies and ensure efficient thematic extraction, abstracts were selected for analysis because they concisely summarize the core objectives, methods, and results of each publication [52]. In addition to practical and computational considerations, analyzing abstracts ensures thematic comparability across documents, reduces variation in writing style and structure, and minimizes distortion caused by extensive methodological or contextual sections present in full texts. This approach aligns with recommendations from prior topic-modeling studies that emphasize the suitability of abstracts for extracting high-level research themes [43]. This choice was based on practical, computational, and comparative advantages rather than a methodological limitation of LDA, as the model can also be applied to full texts [53]. Nonetheless, we acknowledge that using abstracts may omit finer conceptual nuances that appear only in full articles.

Following previous studies [49,54], the analysis was restricted to abstracts, which concisely summarize a study’s objectives, methods, and findings. Abstracts are therefore well suited for detecting central themes and emerging research directions [55]. This approach avoids the noise of non-essential details, such as citations or appendices, and enables a more efficient thematic analysis. Moreover, this choice facilitates replicability and reduces the computational burden associated with processing long, complex documents, which can lead to sparse matrices that negatively affect LDA performance.

To compile the dataset, two major academic databases, Scopus and Web of Science, were employed. Both are widely used in bibliometric research for their comprehensive coverage and reliable indexing of peer-reviewed publications [42,56]. A systematic search was carried out on 9 July 2025 using the following query:

(“blockchain*” OR “block chain*” OR “block-chain*”) AND (“traceability” OR “traceabl*” ) AND (“food*” OR “agricultur*” OR “agri-food*” OR “agro-food*” OR “milk” OR “dairy” OR “meat” OR “poultry” OR “egg*” OR “grain*” OR “seafood*” OR “fish*” OR “aquaculture” OR “beverage*” OR “oil*”) AND (“supply chain*” OR “value chain*” OR “food system*” OR “food chain*”)

The search initially retrieved over one thousand records. A rigorous screening process was then applied, including the removal of duplicates and exclusion of irrelevant entries. Ultimately, 518 journal articles were retained for the final analysis. This carefully curated dataset forms a robust foundation for applying LDA topic modeling. By systematically analyzing abstracts from these studies, the research aims to map prevailing themes, uncover emerging trends, and highlight underexplored dimensions of blockchain-enabled FSC traceability.

3.2. Corpus Preparation

Before applying the LDA model for unsupervised analysis, the collected texts were subjected to a comprehensive preprocessing stage. The process began with a rigorous cleaning of the dataset, during which elements such as special characters, punctuation, newline markers, and web addresses were removed [57]. This step was necessary to standardize the textual input and eliminate extraneous noise. Following this, the data were further refined using Gensim 4.3.3, which represents an open-source Python library well suited for large-scale text processing [58]. A key function of Gensim is the removal of stopwords or common terms such as adverbs, adjectives, or auxiliary verbs that occur frequently but add little analytical value. To further enhance accuracy, the default stopword list was expanded with additional context-irrelevant terms, including “study,” “article,” “period,” and “findings,” which were unlikely to contribute meaningfully to the identification of dominant themes. After this refinement, the text was tokenized, converting sentences into lists of discrete words. Each token was then assigned a unique identifier (ID) within the Gensim library to facilitate systematic tracking of word frequency and distribution across the corpus. Through this multi-step preprocessing, the dataset was carefully standardized, filtered, and structured to ensure that it was both computationally manageable and optimally prepared for the extraction of latent themes and patterns during topic modeling. The LDA model was configured using standard parameters recommended in the literature, including α = 0.1, β = 0.01, 1000 iterations, and a symmetric Dirichlet prior, ensuring model stability and allowing full replication of results.

3.3. Topic Modeling and Selection of Optimal Number of Topics

Constructing a reliable vocabulary represents a fundamental step in preparing the LDA model to extract meaningful topics from the dataset [59]. The process began with the creation of a vectorized bag-of-words representation using Gensim’s id2word functionality, which organizes the text into a structured format suitable for subsequent analysis. For the implementation of topic modeling, the study employed the Mallet software package, which is well known for its efficiency in document classification, clustering, and topic modeling [47]. Mallet is also advantageous when working with relatively small datasets, making it an appropriate tool for this investigation.

A critical stage in the modeling process involved determining the optimal number of topics. To achieve this, multiple LDA models were generated in Mallet, each configured with a different number of topics. The performance of these models was then evaluated using coherence scores, which measure the degree of semantic similarity among the words that compose a topic. Higher coherence scores indicate stronger thematic consistency and, consequently, greater interpretability. Figure 2 displays the distribution of coherence scores across the tested models. The results show that an eight-topic model achieved the most balanced outcome, with a mean coherence score of 0.4265. Importantly, increasing the number of topics beyond this threshold did not lead to any notable improvement in coherence.

Table 1. Coherence scores for LDA models with varying topic numbers (Own elaboration).

Number of Topics	Coherence Score
2	0.378835968
4	0.34465636
6	0.327121952
8	0.426552658
10	0.384988602
12	0.386371258
14	0.370418075
16	0.35633771
18	0.372183515

further summarizes the coherence scores obtained and confirms that eight topics offered the best compromise between clarity and semantic cohesion. Accordingly, this configuration was selected for detailed analysis and interpretation in the following sections.

3.4. LDA Model Framework and Topic Extraction

As a generative probabilistic framework, the LDA model was employed to uncover latent topics within the corpus by conceptualizing each document as a combination of underlying themes. Each topic, in turn, is represented by a cluster of words that collectively define its semantic meaning [44]. The structure of the LDA model is illustrated in Figure 3. In this representation, rectangular plates indicate repeated processes: the outer plate covers the entire document collection, while the inner plate shows the iterative assignment of topics to words within individual documents. Words identified in the text are denoted as w, which are linked to topic distributions represented by z. The parameter β describes the probability distribution of words across topics, while θ indicates how topics are distributed within each document. Finally, α reflects the overall distribution of topics across the corpus.

Using this framework, the model identified eight dominant themes frequently discussed in the context of blockchain applications for FSC traceability. The analysis quantified the prevalence of each topic across documents and pinpointed the most relevant publications within each theme. To ensure accuracy, semantic coherence scores were applied to assess the degree of relatedness among keywords associated with each topic [54]. Two researchers then used an inductive approach to assign publications to topics, thereby refining the classification. The outputs of the LDA model were further validated with complementary Python tools 3.14.0. The PyLDAvis library was applied to visualize the ten most representative words for each topic, while Matplotlib was used to display the distribution of topics across the dataset. This multi-step procedure ensured that the extracted topics were semantically coherent and practically meaningful, offering a comprehensive overview of the thematic landscape in blockchain-based FSC research.

3.5. Bibliometric Analysis of Blockchain Research in FSC Traceability

A bibliometric analysis was undertaken on the collected body of scientific literature to examine the influence of academic journals and the overall impact of research within the field of blockchain applications in FSC traceability. Following the approach proposed by Aria and Cuccurullo [60], the analysis was carried out using the bibliometrix R package 4.5.2, which is designed to identify and visualize linkages among publications. This tool facilitates a deeper understanding of scholarly networks and thematic clusters by revealing patterns of collaboration and knowledge dissemination.

The bibliometric assessment was guided by two overarching objectives: performance evaluation and science mapping [61]. Performance analysis focuses on measuring the contributions of individual researchers, institutions, and journals, thereby offering insights into their effectiveness and influence within the domain [52,58]. In contrast, science mapping aims to capture the intellectual structure of the field and trace its development, knowledge flows, and emerging thematic trends. By combining these two perspectives, the analysis not only identifies the productivity and impact of key actors but also provides a holistic view of how the field is evolving. Therefore, this integrated approach enables both an evaluation of scholarly performance and a mapping of the thematic and conceptual landscape surrounding blockchain-enabled FSC traceability.

4. Results

4.1. Descriptive Statistics

The present study explores the rapid growth and scholarly impact of blockchain applications in FSC traceability (

Table 2. Main information about the selected sample (Own elaboration).

Description	Results
Timespan	2018:2025
Sources (Journals)	265
Documents	518
Annual growth rate %	61.58
Document average age	1.99
Average citations per doc	44.66
Average citations per year per doc	9.94
References	14,199
Document types
Article	424
Review	94
Document contents
Keywords plus (ID)	1668
Author’s keywords (DE)	1169
Authors
Authors	1820
Author Appearances	2106
Authors of single-authored docs	14
Authors collaboration
Single-authored docs	14
Documents per author	0.285
Co-Authors per doc	4.07
International co-authorships %	0.330

). The dataset spans the period from 2018 to 2025 and comprises 518 documents, published across 265 journals. Of these, 424 are research articles and 94 are reviews, reflecting a diverse yet academically rigorous body of work. The field demonstrates a remarkable annual growth rate of 61.58%, which signals accelerated interest and expanded research activity in recent years. With an average of 44.66 citations per document, equivalent to 9.94 citations per year, the literature exhibits strong academic visibility and influence, positioning blockchain-enabled FSC research as a highly impactful area of inquiry. In addition, the average document age of 1.99 years indicates that the field is relatively young and rapidly evolving, with new contributions consistently shaping its trajectory. In terms of authorship, 1731 scholars have contributed to the literature, with a total of 2107 author appearances. Although the field includes only 14 single-authored documents, collaboration remains a defining feature, as reflected in an average of 4.07 co-authors per publication. Interestingly, only 0.33% of the publications in the dataset feature international co-authorship, suggesting that blockchain-FSC traceability research remains predominantly conducted within national or regional contexts. Overall, these findings underline the dynamism of the field and illustrate both its scholarly significance and its growing role in advancing transparency, safety, and sustainability in global food systems.

Figure 4 illustrates the yearly progression of publications on blockchain applications in FSC traceability. In this field, research activity began modestly in 2018 with only four articles, but the number of studies has expanded consistently in subsequent years. A marked acceleration is observed from 2020 onward, when publications rose from 35 in 2020 to 81 in 2022. The upward trajectory reached its peak in 2024 with 136 articles, reflecting the highest annual output recorded. Although a slight decrease is observed in 2025 (115 articles), the overall trend clearly demonstrates sustained scholarly momentum. The rapid growth, with a compound annual increase of 61.58%, signals that blockchain-FSC traceability has emerged as a prominent research domain [18,22]. The surge in publications during 2023 and 2024, in particular, coincides with heightened global interest in digital technologies for food safety, transparency, and sustainability [62,63]. This increase reflects both technological advances and the pressing demand for traceability solutions to address challenges such as food fraud, supply chain inefficiencies, and consumer trust [64,65,66]. The consistent rise in scholarly contributions demonstrates that scholars consider blockchain a transformative tool for reshaping agri-food supply chains and supporting more resilient and transparent food systems [30].

Figure 5 presents the leading academic journals contributing to research on blockchain applications in FSC traceability. Sustainability leads the field with 29 publications, underlining its strong emphasis on sustainable practices and innovations in agri-food systems. Close behind, IEEE Access accounts for 28 studies, with the journal’s focus is on digital technologies and their role in advancing transparency and efficiency within supply chains. The journal Foods contributes 18 publications and covers research that highlights the growing significance of blockchain technology in food safety, quality, and provenance. The British Food Journal, Journal of Cleaner Production, and Trends in Food Science and Technology each publish nine studies. These journals reinforce the multidisciplinary interest in blockchain across food systems, sustainability, and technological innovation. Overall, the journal-wise distribution demonstrates that blockchain-FSC traceability research is not confined to a single domain but spans a variety of academic fields. As such, technology-focused outlets emphasize its digital infrastructure, while food and sustainability journals showcase the practical implications of blockchains for ensuring trust, authenticity, and resource efficiency. The prominence of well-established journals in this list underscores the academic recognition and validation of blockchain as a promising tool in global food systems.

4.2. Latent Dirichlet Allocation

The central objective of this study was to design and evaluate an LDA model to uncover prevailing themes in the application of blockchain technology to FSC traceability. The analysis produced eight distinct topics, each associated with specific keywords and weighted contributions from the dataset. Through inductive reasoning, these topics were interpreted as representing critical research directions and ongoing debates in the field (

Table 3. Topics identified through LDA modeling (Own elaboration).

Topic	Keywords	Label
1	0.025*”retailer” + 0.023*”fresh” + 0.016*”BCT” + 0.014*”supplier” + 0.014*”product” + 0.012*”cost” + 0.012*”chain” + 0.011*”investment” + 0.011*”profit” + 0.011*”subsidy” + 0.010*”supply” + 0.009*”strategy” + 0.009*”sharing” + 0.008*”member” + 0.008*”decision”	Retailer strategies in blockchain-enabled FSCs
2	0.042*”food” + 0.026*”BCT” + 0.015*”chain” + 0.015*”traceability” + 0.013*”supply” + 0.011*”technology” + 0.011*”sustainability” + 0.010*”system” + 0.010*”agrifood” + 0.009*”safety” + 0.008*”sector” + 0.007*”analysis” + 0.007*”challenge” + 0.007*”application” + 0.006*”research”	Blockchain for food safety and sustainability
3	0.023*”BCT” + 0.013*”chain” + 0.012*”supply” + 0.008*”traceability” + 0.007*”enablers” + 0.007*”data” + 0.007*”information” + 0.006*”industry” + 0.006*”consumer” + 0.006*”transparency” + 0.005*”ASC” + 0.004*”management” + 0.004*”organic” + 0.004*”product” + 0.004*”seafood”	Enablers of blockchain adoption in FSCs
4	0.008*”consumer” + 0.006*”batch” + 0.006*”signature manager” + 0.006*”meat” + 0.006*”video” + 0.006*”different” + 0.005*”use” + 0.005*”short” + 0.004*”tag” + 0.003*”agro” + 0.003*”ingredient” + 0.003*”towards” + 0.003*”item” + 0.003*”storytelling” + 0.003*”halal”	Blockchain and consumer perceptions
5	0.039*”BCT” + 0.020*”food” + 0.019*”adoption” + 0.019*”chain” + 0.018*”supply” + 0.016*”consumer” + 0.016*”traceability” + 0.015*”trust” + 0.013*”barrier” + 0.009*”intention” + 0.008*”organic” + 0.007*”transparency” + 0.007*”perceived” + 0.007*”technology” + 0.006*”framework”	Blockchain adoption challenges
6	0.008*”framework” + 0.007*”traceability” + 0.006*”technology” + 0.006*”supply” + 0.005*”chain” + 0.005*”greenhouse” + 0.005*”sea trace pricing” + 0.005*”provenance” + 0.004*”fish” + 0.004*”seafood” + 0.004*”fruit” + 0.004*”dining” + 0.004*”energy” + 0.003*”video” + 0.003*”surveillance”	Blockchain frameworks for sustainable food systems
7	0.038*”BCT” + 0.036*”chain” + 0.034*”supply” + 0.027*”food” + 0.018*”traceability” + 0.012*”technology” + 0.009*”data” + 0.009*”agrifood” + 0.008*”system” + 0.008*”transparency” + 0.007*”safety” + 0.007*”quality” + 0.006*”challenge” + 0.006*”product” + 0.006*”application”	Blockchain for agri-food safety and transparency
8	0.028*”chain” + 0.026*”BCT” + 0.025*”traceability” + 0.025*”system” + 0.022*”food” + 0.021*”supply” + 0.021*”product” + 0.018*”data” + 0.010*”information” + 0.008*”based” + 0.008*”quality” + 0.008*”consumer” + 0.007*”agricultural” + 0.006*”safety” + 0.006*”process”)]	Blockchain traceability systems in FSCs

).

To ensure the thematic boundaries of the topics were robust and to address possible concerns about redundancy, an intertopic distance map (Figure 6) was generated. The visualization largely confirms that the model achieved a meaningful separation across themes. Nevertheless, a degree of conceptual overlap is evident between Topic 7 (Blockchain for agri-food safety and transparency) and Topic 2 (Blockchain for food safety and sustainability). This overlap is logical because both emphasize blockchain’s potential to strengthen food safety systems, though Topic 7 does so with a stronger focus on transparency in agrifood systems, while Topic 2 highlights sustainability imperatives alongside safety outcomes.

When ranked by importance, the topics reveal a hierarchy of research interest: Topic 7 emerges as the most influential, followed closely by Topic 8 (Blockchain traceability systems in FSCs) and Topic 2. Together, these form the thematic core of the literature and confirm that blockchain technology has the potential to enhance safety, transparency, and system-level traceability. Topic 5 (Blockchain adoption challenges) and Topic 3 (Enablers of blockchain adoption in FSCs) reflect an important secondary cluster that concentrates on barriers, drivers, and organizational dynamics determining whether blockchain solutions can scale effectively. In contrast, Topics 1, 6, and 4 address more specialized aspects, that is, retailer strategies, blockchain frameworks for sustainable food systems, and consumer perceptions, respectively. Taken as a whole, the identified topics illustrate the breadth of ways blockchain is reshaping FSC traceability. From strengthening transparency and food safety (Topics 7 and 2), to building robust technical traceability systems (Topic 8), and addressing adoption dynamics at both organizational and consumer levels (Topics 3, 4, and 5), the literature highlights a consensus among scholars that blockchain technology represents a transformative tool in the food sector [29,67]. The intertopic distance map (Figure 6) underscores that despite some conceptual proximity between themes, the model successfully distinguishes between them and offers a comprehensive yet structured perspective. In short, this analysis demonstrates that blockchain research in FSC traceability is driven by two converging priorities: addressing food safety and transparency concerns, and developing robust technical and organizational systems for adoption. In particular, the prominence of Topics 7 and 8 indicates that blockchain’s core value lies in its capacity to restore trust, ensure product authenticity, and safeguard sustainability in increasingly complex global food chains [6,9,68].

The analysis of topic frequency across the corpus of selected publications shows a clear distribution of research attention within the field of blockchain-enabled FSC traceability. Each of the eight identified topics is represented by at least 20 scientific articles, indicating their consistent relevance in academic discourse. Among them, Topic 7 (Blockchain for agri-food safety and transparency) emerges as the most influential, with 304 publications (58.69% mean contribution). This reflects the central role of blockchain technology in safeguarding food quality, improving safety standards, and fostering consumer trust [13,69]. Closely following, Topic 8 (Blockchain traceability systems in FSCs) accounts for 250 articles (48.26%) and covers research associated with the importance of system-level implementations for enhancing product provenance and ensuring end-to-end transparency in food supply networks [70,71,72]. While these two themes dominate the landscape, Topic 2 (Blockchain for food safety and sustainability) also stands out with 170 studies (32.82%), underscoring the technology’s contribution to sustainable practices and resilience in agri-food systems. By contrast, Topic 5 (Blockchain adoption challenges), although addressed in 118 publications (22.78%), revolves around organizational and strategic barriers that hinder widespread implementation. As a result, this reveals an ongoing concern in bridging the gap between blockchain’s potential and its practical adoption. Similarly, Topic 3 (Enablers of blockchain adoption in FSCs) with 75 contributions (14.48%) provides valuable insights into the conditions that foster effective integration, particularly regarding technological readiness and institutional support [73,74].

On the other hand, Topic 1 (Retailer strategies in blockchain-enabled FSCs) and Topic 6 (Blockchain frameworks for sustainable food systems), with 57 (11%) and 26 (5.02%) publications, respectively, represent more specialized areas that often address operational practices or framework development for sustainable and ethical supply chain models. Finally, Topic 4 (Blockchain and consumer perceptions), with only 20 publications (3.86%), appears less frequently explored. This suggests that consumer-oriented perspectives remain an underdeveloped yet promising field of inquiry. Altogether, the examination reveals a median of 96.5 publications per topic and an average of 127.5, reflecting a diverse research agenda that spans both technological and socio-economic aspects of blockchain applications in FSCs. The prominence of Topics 7 and 8 confirms that safety, transparency, and traceability form the backbone of current blockchain research in FSCs. Meanwhile, the relatively modest attention to consumer behavior and governance frameworks suggests that scholars need to focus on these important avenues for future exploration. Ultimately, these findings validate the robustness of the topic modeling process and demonstrate the multidimensional nature of blockchain research in FSCs, ranging from technical systems to adoption dynamics and sustainability considerations (Figure 7).

The distribution of topics across journals was examined by combining bibliometric insights with the outputs of the LDA model.

Table 4. Leading academic journals contributing to each research topic (Own elaboration).

Topic 1	Topic 2	Topic 3	Topic 4
Computers and Industrial Engineering	Sustainability	IEEE Access	Foods
Sustainability	Trends in Food Science and Technology	Sustainability	IEEE Access
Food Control	IEEE Access	Trends in Food Science and Technology	Sensors
IEEE Access	British Food Journal	British Food Journal	Agriculture
Electronics	Foods	Journal of Cleaner Production	Frontiers in Sustainable Food Systems
Topic 5	Topic 6	Topic 7	Topic 8
British Food Journal	Sustainability	Sustainability	IEEE Access
Sustainability	Journal of Industrial Information Integration	IEEE Access	Foods
Sustainable Futures	British Food Journal	Foods	Sustainability
Agriculture	Agriculture	Journal of Cleaner Production	International Journal of Advanced Computer Science and Applications
International Journal of Mathematical, Engineering and Management Sciences	Journal of Cleaner Production	Food Control	Electronics

summarizes the five most relevant journals associated with each topic. Across all themes, Sustainability and IEEE Access emerge as recurring outlets that play a vital role in shaping the scholarly debate on blockchain and FSC traceability. Their broad scope allows them to host contributions that address both technical advancements and socio-economic implications of blockchain adoption.

In Topic 1 (Retailer strategies in blockchain-enabled FSCs), journals such as Computers and Industrial Engineering and Food Control appear prominently to reflect a focus on operational efficiency and compliance frameworks within blockchain-mediated retail systems. Similarly, Topic 2 (Blockchain for food safety and sustainability) is strongly represented in Sustainability, Trends in Food Science and Technology, and British Food Journal. This indicates a convergence of technological solutions with broader sustainability debates, linking blockchain applications to food integrity and sustainable supply practices. For Topic 3 (Enablers of blockchain adoption in FSCs), IEEE Access and Trends in Food Science and Technology stand out, alongside Journal of Cleaner Production. This finding stresses the interdisciplinary nature of research that integrates technological, managerial, and environmental perspectives. In Topic 4 (Blockchain and consumer perceptions), Foods and Frontiers in Sustainable Food Systems dominate. Articles published in these journals point to a growing emphasis on consumer trust, product authenticity, and the influence of blockchain-enabled traceability on purchasing behavior. Turning to Topic 5 (blockchain adoption challenges), outlets like British Food Journal and Sustainable Futures focus on structural and organizational barriers, while Agriculture reflects the practical realities of implementation in farming contexts. Topic 6 (blockchain frameworks for sustainable food systems) draws contributions from Journal of Industrial Information Integration and Journal of Cleaner Production, both of which showcase the design and testing of blockchain-based frameworks that strengthen system sustainability.

The strongest presence is observed in Topic 7 (Blockchain for agri-food safety and transparency), where Sustainability, IEEE Access, and Food Control lead the discussion, reflecting the urgent priority of transparency and quality assurance in food chains. Lastly, Topic 8 (blockchain traceability systems in FSCs) finds consistent coverage in IEEE Access, Foods, and International Journal of Advanced Computer Science and Applications. The topic illustrates the technological and applied dimensions of blockchain system design and deployment. In sum, the results reveal both breadth and specialization. Certain journals, such as Sustainability and IEEE Access, serve as central hubs for multidisciplinary research. Others like Food Control or Journal of Cleaner Production offer more focused contributions aligned with food safety or sustainability frameworks. This variation demonstrates the diverse yet interconnected landscape of blockchain research in FSC traceability, where technical, organizational, and consumer-oriented dimensions are addressed across complementary publication venues.

5. Discussion of Topics

5.1. Retailer Strategies in Blockchain-Enabled FSCs

Figure 8 illustrates retailer strategies in blockchain-enabled FSCs, as identified through our review analysis. Topic 1 has been thoroughly examined with regard to blockchain applications in FSCs, with numerous studies analyzing how technology can enhance transparency, efficiency, and resilience. For example, Liu et al. [75] investigated sales mode selection in fresh food supply chains and showed that blockchain-enabled traceability and freshness significantly influence whether e-commerce platforms adopt reselling or agency selling. This study explains the role of blockchain in driving competitive strategies, raising product quality, and improving overall supply chain profits. In a similar vein, Shi et al. [29] explored blockchain adoption as a means to strengthen resilience in the post-pandemic era. Their game-theoretic analysis demonstrated that blockchain enhances inspection accuracy and sourcing transparency, allowing retailers to mitigate risks when dealing with risky versus safe suppliers. The authors demonstrate the potential of blockchain to foster all-win outcomes across retailers, suppliers, consumers, and the broader supply chain.

A study conducted by Li et al. [76] examined pricing decisions in a three-level agricultural supply chain and revealed that blockchain traceability can increase profits and stabilize pricing strategies. However, their findings also indicated that excessive costs may intensify double marginalization effects, thereby constraining supply chain efficiency. Xing and Miao [77] advanced this area by analyzing investment decisions in blockchain for fresh food supply chains. They concluded that blockchain mitigates supplier misreporting of freshness and, when paired with cost-sharing and revenue-sharing contracts, aligns incentives and improves coordination. Therefore, blockchain can restore trust while promoting Pareto-efficient outcomes for all members of the supply chain. In addition, Liao et al. [78] investigated the role of governmental strategies in blockchain-enabled supply chains during the post-pandemic era. According to the authors, demand for traceability stimulates higher levels of traceability adoption and anti-pandemic efforts. Interestingly, while subsidies and anti-pandemic strategies are most effective when combined, relying solely on subsidies may, under certain conditions, discourage investment in blockchain-based traceability. Thus, this finding underscores the complex interplay between policy instruments and technological adoption in food systems.

The findings from Topic 1 highlight the diverse factors that shape the effectiveness and adoption of blockchain in FSCs, including cost structures, consumer preferences, competitive dynamics, and governmental policies. To enhance future research in this field, scholars might consider examining the integration of blockchain with complementary technologies such as the Internet of Things (IoT), artificial intelligence (AI), or federated learning to optimize data traceability, security, and decision-making in real time. Furthermore, research could explore regional, cultural, and product-specific differences in blockchain adoption, while also assessing consumer perceptions of trust and willingness to pay for blockchain-enabled traceability. Another promising direction is the evaluation of smallholder farmers’ access to blockchain systems, particularly regarding affordability and scalability. Future research should not only refine economic and operational models for retailers but also expand into consumer behavior, policy frameworks, inclusivity, and technological integration. This will create a holistic understanding of blockchain’s transformative role in food supply chains.

Table A1. Future research agenda: Retailer strategies in blockchain-enabled FSCs (Own elaboration).

Research Area	Key Questions	Suggested Methodologies
Cost–benefit optimization & scalability	How can retailers balance blockchain costs with efficiency gains? What models reduce double marginalization?	Game theory, optimization models, case studies
Integration with complementary technologies	How can blockchain be integrated with IoT, AI, or federated learning for real-time decision-making?	Simulation, digital twin modeling, system architecture design
Consumer-centric perspectives	How do consumers perceive blockchain-enabled transparency? Are they willing to pay more for traceability?	Surveys, conjoint analysis, behavioral experiments
Retailer strategy & competition	How does blockchain adoption affect retailer competition, pricing, and sales modes? Are there first-mover advantages?	Analytical modeling, agent-based simulation, competitive benchmarking
Policy & governance interactions	How do subsidies, regulations, and policies influence retailer adoption of blockchain? What governance models ensure fairness?	Policy analysis, comparative case studies, multi-stakeholder interviews
Inclusion & equity	How can smallholder farmers and SMEs access blockchain FSCs affordably? Does blockchain risk widening digital divides?	Field studies, participatory research, mixed-method approaches
Resilience & risk management	How does blockchain improve resilience against disruptions (pandemics, climate shocks, fraud)?	Risk modeling, scenario analysis, longitudinal studies

(see Appendix A) summarizes the future research agenda in Topic 1. Ultimately, addressing these knowledge gaps will provide a more comprehensive understanding of blockchain’s transformative role in fostering transparency, safety, and sustainability in food supply chains.

5.2. Blockchain for Food Safety and Sustainability

The second topic has emerged as a central theme in recent scholarship, examining how blockchain can enhance transparency, traceability, and sustainable practices in food systems. For instance, Gupta and Shankar [79] investigated India’s Public Distribution System, a key national food safety net, and proposed a blockchain-enabled traceability framework. The authors argued that blockchain can significantly improve transparency and operational efficiency, thereby reducing food insecurity and providing valuable insights for policymakers.

In a different geographical context, Vorwerk and Rexroth [80] explored the role of blockchain in strengthening food safety across Europe, particularly in response to past food scandals and outbreaks such as EHEC. Their analysis highlights how blockchain can accelerate traceability, exemplified by Walmart’s mango case, where the time needed to track product origins fell from seven days to just 2.2 s. Consequently, blockchain can improve accuracy and responsiveness during food safety crises. Building on this perspective, Rossi et al. [81] provided a comprehensive review of agri-food traceability systems and integrated regulatory requirements with technological innovations. Blockchain, alongside other emerging tools such as AI and IoT, can improve authenticity, safety, and sustainability in products like wine, garlic, and coffee. These technologies not only strengthen consumer trust but also advance public health and sustainable food production.

Furthermore, Zhang et al. [82] examined the combined use of blockchain and IoT (BlockIoT) for sustainable food management. As per the authors, this integration can reduce food waste, enhance transparency, and lower costs across supply chains, thereby contributing to all three pillars of sustainability: social, environmental, and economic. Nevertheless, technical and adoption challenges may hinder widespread implementation. Finally, Baladraf and Marimin [83] conducted a bibliometric study on blockchain adoption in the food cold chain and identified three key areas of impact: improving traceability and reducing waste, enhancing competitiveness, and increasing consumer confidence in food safety. In cold chains, blockchain adoption is rapidly expanding, though further research is needed to address issues such as storage, transportation, and carbon emissions.

Taken together, the studies pertaining to Topic 2 offer insights into how blockchain can promote food safety, sustainability, and consumer trust across diverse food supply chains. Nonetheless, future research should deepen empirical testing of blockchain applications in real-world contexts, examine cross-sector adoption barriers, and evaluate the integration of blockchain with complementary technologies such as cloud computing, augmented reality, and digital twins. Addressing these gaps will be essential for realizing blockchain’s full potential in building resilient, safe, and sustainable food systems.

Table A2. Future research agenda: Blockchain for food safety and sustainability (Own elaboration).

Research Area	Key Questions	Suggested Methodologies
Food safety & crisis response	How can blockchain accelerate food recalls and improve accuracy during crises? What are best practices for integrating blockchain into national food safety systems?	Case studies (e.g., Walmart, EU), simulation of outbreak scenarios, policy analysis
Sustainability & waste reduction	How effective is blockchain (alone or with IoT/AI) in reducing food waste and carbon emissions? How does it support the triple bottom line (economic, social, environmental)?	Life Cycle Assessment (LCA), empirical field studies, system dynamics modeling
Technology integration	How can blockchain be combined with IoT, cloud computing, AR, and digital twins for end-to-end traceability? What technical barriers limit integration?	Pilot projects, architecture design, interoperability testing
Consumer trust & behavior	How does blockchain-enabled traceability influence consumer trust, purchasing behavior, and willingness to pay for safe/sustainable products?	Surveys, experiments, conjoint analysis
Cross-sector & regional adoption	What adoption challenges exist in different regions (e.g., developing vs. developed economies)? How do cross-sector collaborations (agriculture, logistics, retail, regulators) shape outcomes?	Comparative studies, cross-country case analysis, stakeholder interviews
Cold chain & perishables	How does blockchain adoption affect traceability, waste reduction, and emissions in cold chains? What are the implications for food safety and competitiveness?	Empirical studies in perishable supply chains, optimization modeling, bibliometric analysis
Governance & policy implications	How should policymakers regulate and incentivize blockchain for food safety and sustainability? What governance models ensure accountability, transparency, and interoperability?	Policy evaluation, scenario analysis, Delphi studies with experts

(see Appendix A) provides an overview of the main questions and suggested methodologies for advancing research related to Topic 2.

5.3. Enablers of Blockchain Adoption in FSCs

The third topic covers the enabling conditions and drivers that support blockchain adoption in FSCs, with research discussing consumer preferences, circularity, institutional dynamics, and technological integration. For instance, Petrontino et al. [84] explored Italian consumers’ willingness to pay for pasta products tracked with blockchain and labeled with sustainable attributes. Their discrete choice experiment showed that consumers were prepared to pay a premium for blockchain-enabled labels that guaranteed food safety, environmental sustainability, and social responsibility. As a result, the adoption of blockchain in FSC traceability not only protects consumers from fraud but also creates economic incentives for producers to adopt sustainable practices. In a similar vein, Sharma et al. [85] examined blockchain adoption as a driver of circularity in agricultural supply chains. Using an integrated ISM-DEMATEL framework, ten key enablers were identified, with traceability emerging as the most prominent. The study further introduced a 12Rs framework to promote circular practices and demonstrated that blockchain adoption is closely linked to sustainability outcomes when supported by seamless information flow and distributed ledger technologies.

At the same time, Thompson and Rust [86] examined how blockchain adoption faces resistance in the Australian seafood industry. Their interviews revealed that entrenched power structures, particularly the dominance of wholesalers, created reluctance among smaller actors to adopt blockchain despite recognizing its benefits for transparency. Blockchain implementation depends on overcoming institutional and cultural barriers and will only gain traction if influential actors perceive value in its use. Complementing this, Zulkarnain [87] analyzed blockchain-based systems for tracking fish species and conservation status. Combined with AI, blockchain is demonstrated to address pressing challenges such as overfishing, counterfeit products, and poor handling practices, while supporting sustainable fisheries management. However, challenges around data privacy and interoperability remain persistent, stressing the need for further innovation. Finally, Tokkozhina et al. [88] studied blockchain adoption in a multi-tier frozen fish supply chain in Portugal. Their mixed-method study found that while blockchain improved traceability and consumer trust, it did not eliminate the reliance on pre-existing trust relationships between supply chain actors, since data input remained dependent on human accuracy. Interestingly, their survey revealed that even when consumers were not highly interested in traceability, they were more likely to purchase products that offered transparent blockchain-based information.

In summary, the studies related to Topic 3 reveal that blockchain adoption in FSCs is driven by a mix of consumer demand, sustainability goals, and technological enablers, but its success also depends on overcoming socio-cultural and institutional barriers. Future research should further examine how blockchain can be integrated with complementary technologies such as IoT and AI to strengthen interoperability, while also addressing adoption resistance among powerful supply chain actors. Exploring these areas will be critical for scaling blockchain adoption and ensuring that its benefits for traceability, transparency, and sustainability are fully realized.

Table A3. Future research agenda: Enablers of blockchain adoption in FSCs (Own elaboration).

Research Area	Key Questions	Suggested Methodologies
Consumer demand & willingness to pay	How do consumer preferences for blockchain-enabled traceability vary across regions, demographics, and product categories? To what extent are consumers willing to pay a premium for food safety and sustainability?	Discrete choice experiments, surveys, cross-country consumer studies
Sustainability & circular economy	How can blockchain strengthen circular practices (e.g., 12Rs framework) in FSCs? What role does blockchain play in driving sustainable sourcing and reducing waste?	ISM-DEMATEL modeling, system dynamics, case studies
Institutional & cultural barriers	How do entrenched power structures (e.g., wholesalers, distributors) influence blockchain adoption? What strategies can overcome resistance among dominant actors?	Qualitative interviews, institutional analysis, stakeholder mapping
Technological integration & interoperability	How can blockchain be effectively integrated with AI, IoT, and other digital tools to enhance traceability and sustainability? How can interoperability and data privacy challenges be addressed?	Pilot projects, architecture testing, technical benchmarking
Trust & data reliability	To what extent can blockchain reduce reliance on pre-existing trust relationships? How can human data input errors be minimized to ensure blockchain integrity?	Mixed-method studies, experiments with automated data capture, blockchain–IoT integration
Conservation & resource management	How can blockchain, when combined with AI/IoT, improve fisheries management, prevent overfishing, and combat counterfeit seafood?	Empirical field research, fisheries modeling, conservation-focused pilots
Scaling & adoption dynamics	What conditions (policy, cost-sharing, ecosystem collaboration) are necessary to scale blockchain adoption in FSCs? How can smaller actors be incentivized to adopt blockchain despite power imbalances?	Comparative case studies, adoption modeling, policy evaluation

(see Appendix A) provides the future research agenda for Topic 3.

5.4. Blockchain and Consumer Perceptions

The fourth topic centers on how consumers perceive and respond to blockchain-enabled FSCs, particularly regarding trust, willingness to pay, and purchase intentions. For example, Cao et al. [89] analyzed the role of short video storytelling in shaping Chinese consumers’ attitudes toward blockchain-credentialed Australian beef. Their experimental study revealed that videos enhanced consumer perceptions of quality, labeling, and traceability trust. However, there is limited or even negative effects on willingness to pay, suggesting that communication strategies must carefully align consumer expectations with blockchain’s value propositions. In a similar vein, Vázquez Meléndez et al. [90] explored Australian consumers’ willingness to pay for blockchain-certified food products and found that consumers positively valued blockchain’s capacity to ensure provenance and ethical production. Notably, women were more likely to pay a premium for transparency and labeling verification, which highlights gender differences in attitudes toward food authenticity and sustainability.

Martinelli and De Canio [91] further investigated whether blockchain affects consumer purchase intentions. The results of the study suggested that consumer knowledge of blockchain remains limited, with only a minority demonstrating awareness. Nevertheless, perceived usefulness, ease of use, and the assurance of authenticity significantly influenced attitudes and intentions to adopt blockchain-enabled traceability systems. Consequently, there is a need to develop consumer education and user-friendly solutions in order to foster blockchain adoption in FSC traceability. Complementing this, Ellahi et al. [92] looked at the integrity challenges in the halal meat supply chain and assessed how Industry 4.0 technologies, including blockchain, could address fraud, contamination, and traceability issues. Alongside AI, AR, and digital twins, blockchain can improve transparency and compliance. Several research gaps were identified, particularly regarding emerging technologies like intelligent packaging and 3D-printed halal meat. Finally, Li et al. [93] studied consumer adoption of blockchain traceability systems by integrating the Technology Acceptance Model with Technology Readiness. Survey results from Chinese supermarket consumers indicated that perceived ease of use and usefulness were strong predictors of adoption attitudes and intentions. Moreover, positive traits such as optimism and innovativeness strengthened adoption likelihood, while negative traits such as discomfort had little impact. Thus, blockchain adoption in food retail depends not only on technological design but also on consumer readiness and mindset.

Collectively, the findings across these studies reveal that consumer perceptions of blockchain hinge on factors such as trust, communication strategies, perceived benefits, and technological readiness. To advance this line of inquiry, future research could investigate cross-cultural variations in consumer attitudes, assess long-term willingness to pay for blockchain-certified products, and explore the combination of blockchain with other emerging technologies can further enhance consumer trust. Additionally, greater attention should be given to smallholder contexts and marginalized consumer groups to ensure that blockchain-enabled traceability contributes to transparency and inclusive and sustainable food systems.

Table A4. Future Research Agenda: Blockchain and Consumer Perceptions (Own elaboration).

Research Area	Key Questions	Suggested Methodologies
Trust & communication strategies	How do communication tools (e.g., short videos, storytelling, labeling) shape consumer trust in blockchain-enabled FSCs? What strategies reduce the gap between expectations and actual willingness to pay?	Experimental studies, consumer behavior surveys, content analysis
Willingness to pay & gender/cultural differences	How do gender, cultural, and demographic factors influence willingness to pay for blockchain-certified products? Do these differences persist across product types (e.g., beef, halal meat, coffee)?	Discrete choice experiments, cross-cultural comparative studies, segmentation analysis
Consumer knowledge & education	How does consumer awareness of blockchain affect adoption? What role do education campaigns and user-friendly designs play in shaping perceptions?	Technology Acceptance Model (TAM), field experiments, longitudinal consumer surveys
Technology readiness & adoption	How do individual traits (optimism, innovativeness, discomfort) influence adoption intentions? How do blockchain-enabled FSCs align with Technology Readiness?	TAM-TRI integration, structural equation modeling, large-scale surveys
Integration with emerging technologies	How can blockchain combined with AI, AR, digital twins, or intelligent packaging improve consumer trust and product authenticity?	Pilot projects, experimental trials, technology adoption case studies
Ethical & religious food systems	How does blockchain adoption affect consumer trust in halal, kosher, or other religious/ethical food supply chains?	Qualitative case studies, focus groups, mixed-method research
Inclusivity & marginalized groups	How do smallholder farmers and marginalized consumer groups perceive blockchain-enabled traceability? Does blockchain improve inclusivity and access to safe, sustainable food?	Field studies, participatory research, surveys in low-income markets

(see Appendix A) summarizes the future research agenda for Topic 4.

5.5. Blockchain Adoption Challenges

Topic 5 addresses the obstacles and limitations hindering blockchain adoption in FSCs, as well as the strategies proposed to overcome them. For instance, Lahane et al. [94] evaluated the barriers to implementing Industry 4.0 technologies, including blockchain, in sustainable FSCs in India. Using a hybrid evaluation framework, the findings of the authors revealed that organizational, strategic, and social barriers pose the greatest challenges. More specifically, poor managerial perception of digitization and unwillingness to adopt new technologies were identified as the most critical impediments. To address these barriers, top management commitment, combined with government support in the form of subsidies and tax relief, is necessary to enable successful blockchain integration. In a similar vein, Liu et al. [95] explored blockchain adoption intentions in agricultural supply chains through the Technology–Organization–Environment and Diffusion of Innovation frameworks. In light of the findings, technological, organizational, and environmental contexts all significantly affect adoption. Interestingly, although perceived cost was not found to directly reduce adoption intentions, it did moderate the influence of organizational factors. Hence, this highlights the importance of cost-effectiveness and internal advocacy in driving technology acceptance.

Expanding on consumer perspectives, Duong [96] assessed how cultural values shape organic food consumption in Vietnam and whether blockchain-enabled traceability influences this behavior. Drawing on the findings, collectivism, uncertainty avoidance, and long-term orientation positively affected consumer attitudes toward organic food, while masculinity exerted a negative influence. Blockchain traceability further strengthened consumers’ sense of control, thereby enhancing their purchase intentions and behaviors. In related work, Duong et al. [97] analyzed how blockchain-enabled traceability impacts organic food purchase intentions through the lens of transparency and trust. The authors proved that blockchain improves information transparency, which in turn boosts purchase intentions, while trust acted as a crucial moderator in strengthening this effect. Similarly, Ta and Duong [98] emphasized that blockchain-driven transparency enhances both personal and system trust, which jointly mediate consumer purchase behavior. However, an imbalance between these forms of trust could weaken consumer willingness to adopt blockchain-based products.

In a nutshell, the findings from the analysis of Topic 5 demonstrate that blockchain adoption in FSCs is shaped by a combination of organizational readiness, cost considerations, cultural values, and consumer trust. Future research could benefit from exploring how adoption barriers vary across regions and industries, while also examining the role of collaborative ecosystems, such as partnerships between governments, industry actors, and consumers, in overcoming resistance. Moreover, more empirical studies are needed to assess how blockchain trust-building mechanisms interact with affordability and accessibility, particularly in smallholder and resource-constrained contexts.

Table A5. Future research agenda: Blockchain adoption challenges in FSCs (Own elaboration).

Research Area	Key Questions	Suggested Methodologies
Organizational & managerial readiness	How do managerial perceptions, digital literacy, and top management commitment influence adoption success? What strategies can build internal advocacy for blockchain?	Surveys with managers, organizational readiness assessments, case studies
Cost & economic feasibility	How do costs (implementation, maintenance, training) interact with organizational factors to shape adoption? What financing models (subsidies, cost-sharing, tax relief) lower barriers?	Economic modeling, cost–benefit analysis, policy simulations
Technological & environmental contexts	How do blockchain adoption challenges differ across industries (e.g., seafood vs. fresh produce)? What environmental or infrastructural factors (e.g., digital infrastructure) hinder scaling?	Comparative case studies, Technology–Organization–Environment (TOE) framework applications
Cultural & social influences	How do cultural values (e.g., collectivism, uncertainty avoidance) affect consumer and organizational adoption? Do cultural differences shape trust-building in blockchain-enabled FSCs?	Cross-cultural surveys, cultural dimension analysis (e.g., Hofstede), structural equation modeling
Consumer trust dynamics	How do personal trust and system trust interact in shaping adoption? What happens when trust dimensions are imbalanced?	Experimental studies, trust mediation models, longitudinal consumer research
Collaborative ecosystem approaches	How can partnerships among governments, retailers, suppliers, and consumers help overcome adoption resistance? What governance frameworks enable inclusive blockchain ecosystems?	Stakeholder analysis, ecosystem mapping, Delphi studies with experts
Smallholder & resource-constrained contexts	How can blockchain adoption be made affordable and accessible for smallholders and SMEs? What scalable solutions address inequality in adoption?	Field experiments, participatory research, pilot projects in developing regions

(see Appendix A) presents the proposed future research directions for Topic 5.

5.6. Blockchain Frameworks for Sustainable Food Systems

The sixth topic centers on blockchain-based frameworks designed to strengthen transparency, efficiency, and sustainability in food systems. In this context, Rani et al. [99] introduced the Sea-Trace-Pricing framework, which is a permissioned blockchain solution to address challenges in the seafood supply chain, such as pricing volatility, fraud, and limited traceability. The proposed model integrates real-time factors like demand, quality, and seasonality to enable dynamic pricing, while also employing Hyperledger Fabric for secure transactions and IPFS for decentralized data storage. The evaluation showed that STP can process transactions with high efficiency and low latency, while also providing resilience against cyberattacks. Consequently, blockchain technology can significantly enhance market efficiency, consumer trust, and traceability in seafood distribution. In another study, John and Mishra [100] proposed a three-layer blockchain-enabled model for the tuna supply chain that integrates green technologies, fish waste utilization, and seaweed bioplastic packaging. Investing in these innovations reduced emissions and waste management costs by up to 95%, while blockchain ensured full traceability and prevented illegal or unsustainable tuna from entering the market. This integrated approach illustrated how blockchain can work alongside eco-innovations to foster both profitability and environmental responsibility.

Addressing agricultural production, Rizwan et al. [101] developed a blockchain-based greenhouse management framework that optimizes energy use and improves fruit traceability. Using IoT sensors, fuzzy logic, and the Firefly algorithm, the system minimizes energy consumption by 38% while enabling transparent product tracking through QR codes. The implementation of blockchain in this system links operational efficiency with consumer trust in greenhouse-grown produce. Building on the theme of security, Sheriff and Aravindhar [102] advanced a quantum-resilient blockchain framework that integrates federated AI, quantum-inspired reinforcement learning, and lattice-based cryptography. The suggested system achieved high accuracy in anomaly detection, fast processing speeds, and protection against quantum-level cyber threats, while maintaining energy efficiency suitable for IoT devices. This study points to the potential of blockchain frameworks to future-proof FSCs against emerging risks while ensuring reliable traceability. Finally, Le et al. [7] examined blockchain adoption in Vietnam’s fine dining sector, where consumer demand for provenance and authenticity is rapidly growing. Through case studies with chefs and restaurateurs, blockchain-based traceability was proven to improve sustainability storytelling, strengthen consumer trust, and reinforce cultural authenticity.

Collectively, the content of the studies associated with Topic 6 reveals the diverse ways blockchain frameworks are being deployed across food systems, from fisheries and agriculture to premium dining. Scholars have made efforts in this aspect and highlighted the dual promise of blockchain: improving operational efficiency while fostering consumer trust and sustainability. Future research should investigate how such frameworks can be scaled across different cultural and economic settings, while also addressing energy costs, interoperability, and inclusion of small-scale producers. In doing so, blockchain can be positioned as a cornerstone for resilient and sustainable food systems worldwide.

Table A6. Future research agenda: Blockchain frameworks for sustainable food systems (Own elaboration).

Research Area	Key Questions	Suggested Methodologies
Framework design & operational efficiency	How can blockchain frameworks optimize operational efficiency (e.g., pricing, energy use, resource allocation) across diverse FSCs? What models ensure resilience against fraud and volatility?	Simulation modeling, optimization algorithms, IoT integration studies
Integration with eco-innovations	How can blockchain be combined with green technologies (e.g., waste utilization, bioplastics, energy-efficient systems) to promote sustainability?	Case studies, LCA (Life Cycle Assessment), comparative environmental impact analysis
Security & quantum-resilience	How can blockchain frameworks protect against emerging cybersecurity threats, including quantum-level attacks? What cryptographic approaches are most effective for FSC applications?	Security modeling, federated AI simulations, cryptography experiments
Consumer trust & market applications	How do blockchain frameworks enhance transparency, provenance, and authenticity in consumer-facing contexts (e.g., fine dining, seafood, greenhouse produce)?	Field experiments, consumer surveys, case studies with restaurants and retailers
Scalability & interoperability	How can blockchain frameworks be scaled across diverse cultural, economic, and geographic settings? How can interoperability between different blockchain systems be achieved?	Pilot implementations, multi-stakeholder workshops, interoperability testing
Inclusion of small-scale producers	How can smallholders and SMEs participate in blockchain frameworks without prohibitive costs? What incentives or cooperative models support inclusive adoption?	Participatory action research, pilot projects, cost–benefit analysis for SMEs
Energy efficiency & sustainability metrics	How can energy consumption of blockchain operations be minimized while maintaining transparency and security? How do blockchain frameworks contribute to measurable sustainability outcomes?	Energy modeling, IoT-enabled monitoring, sustainability performance assessment

(see Appendix A) encapsulates the agenda for future research concerning Topic 6.

5.7. Blockchain for Agri-Food Safety and Transparency

The seventh topic groups articles that explained how blockchain can increase safety, trust, and efficiency across FSCs. For example, Kumar et al. [103] proposed a conceptual framework for developing countries to explain the role of blockchain in reducing waste, bridging demand–supply gaps, and ensuring transparency. Although earlier blockchain versions face challenges in complex systems, the adoption of blockchain 4.0 could significantly improve governance, minimize inefficiencies, and integrate marginalized producers into the formal economy. Likewise, Sakthivel et al. [104] designed a blockchain-based architecture to improve transparency and trust in precision agriculture. By combining blockchain with IoT, the proposed model incorporates secure registration, authentication, and optimized data management. Experimental validation on the Hyperledger network confirmed its efficiency in transaction speed and scalability, showing blockchain’s potential to meet the growing demands of modern agriculture.

In addition, Armas et al. [105] examined the Philippine onion industry, where smallholder farmers face challenges related to fraud and insufficient traceability. The findings revealed that stakeholders’ are not satisfied with current practices, paving the way for blockchain to strengthen trust through decentralization and immutability. However, the potential of the technology is undermined by various barriers such as scalability and regulatory compliance, stressing the need for collective action among governments, technology providers, and producers. Khanna et al. [106] shifted attention to India’s dairy sector to reduce food fraud and contamination. A blockchain-enabled supply chain platform was proposed for products like milk, cheese, and butter, integrating QR codes, IoT, and smart contracts. Beyond traceability, the model aims to safeguard nutritional quality, prevent adulteration, and improve the socio-economic viability of dairy farming, offering benefits across social, operational, and sustainability dimensions.

Finally, Ghag and Shedage [107] addressed inefficiencies in foodservice supply chains and transparency gaps that affect distribution, sourcing, and safety. Using a multi-criteria decision-making approach, the authors revealed how blockchain can reduce post-harvest losses, ensure ethical sourcing, and enhance compliance with food safety standards. The integration of IoT sensors and smart contracts further strengthens coordination, minimizes fraud, and builds consumer confidence. Taken together, all the findings discussed above confirm the importance of blockchain in fostering transparency and safety across agri-food systems. They also reveal that while its potential is widely recognized, addressing barriers such as scalability, regulatory alignment, and stakeholder engagement remains essential for realizing blockchain’s full benefits.

Table A7. Future research agenda: Blockchain for agri-food safety and transparency (Own elaboration).

Research Area	Key Questions	Suggested Methodologies
Traceability & transparency	How can blockchain ensure end-to-end traceability across complex agri-food supply chains? What mechanisms enhance transparency for consumers and regulators?	Case studies, process mapping, blockchain simulation
Integration with IoT & smart contracts	How can blockchain combined with IoT sensors and smart contracts optimize safety, coordination, and efficiency? What technological architectures are most effective?	Pilot projects, experimental validation, Hyperledger-based prototypes
Food safety & quality assurance	How can blockchain prevent adulteration, contamination, and fraud in dairy, horticulture, and other agri-food sectors?	Risk assessment, quality control studies, field trials
Scalability & regulatory compliance	What scalability challenges limit adoption in developing countries or smallholder systems? How can regulatory compliance be ensured while maintaining efficiency?	Multi-criteria decision-making, policy analysis, stakeholder interviews
Socio-economic & inclusive outcomes	How does blockchain adoption affect smallholders’ socio-economic viability and market access? How can marginalized producers be integrated into formal agri-food systems?	Field studies, participatory research, impact assessment
Operational efficiency & waste reduction	How can blockchain reduce post-harvest losses, improve distribution, and bridge demand–supply gaps?	Simulation modeling, optimization studies, supply chain analytics
Consumer trust & ethical sourcing	How can blockchain increase consumer confidence in ethical and safe sourcing practices? How can transparency influence purchasing behavior?	Consumer surveys, experimental studies, conjoint analysis

(see Appendix A) delineates the future research agenda within the scope of Topic 7.

5.8. Blockchain Traceability Systems in FSCs

The final topic engages with the study of blockchain-enabled traceability systems, which are increasingly designed to improve transparency, safety, and trust within FSCs. For example, Susanty et al. [108] created a halal traceability framework for chicken meat products in Indonesia. Their web-based application, underpinned by distributed ledgers, smart contracts, and consensus mechanisms, enables consumers to confirm halal certification through QR code scans. Nevertheless, the system still operates with manual consensus and lacks integrated mapping and product visuals. Even so, it offers a valuable foundation for ensuring halal integrity and strengthening consumer trust. Similarly, Ahuja et al. [109] introduced SeedChain, which represents a blockchain-driven model intended to revolutionize seed distribution. By minting non-fungible tokens for approved seeds, the system records their origin and ownership, allowing farmers to avoid counterfeit supplies. Moreover, smart contracts facilitate transparent auctions for seed transportation and prevent monopolistic control. Deployed on Ethereum, the model proved both viable and more transparent than conventional seed supply mechanisms. Hameed et al. [110], in contrast, pursued a formalized systems approach and developed a blockchain- and IoT-based food supply chain model using wireless sensors and finite automata. Importantly, the proposed system automates payments via smart contracts and enhances decision-making when contract violations occur, thereby reducing reliance on centralized authorities.

By comparison, Wang et al. [111] emphasized decentralization through the integration of blockchain with RFID technology. The authors suggested a system that embeds blockchain structures directly into RFID tags to store and transmit product data during shipment, storage, and stocking. This framework is implemented on Hyperledger Fabric to ensure data integrity and scalability, offering a simplified solution for industrial traceability. Finally, Zhang et al. [112] addressed the grain supply chain, which is especially complex and prone to safety issues. A blockchain-based safety management system was proposed to combine multimode storage with chain integration, ensuring dynamic, tamper-proof tracking. Tested with real-world wheat-processing enterprises, the system significantly improved hazardous-material management, information sharing, and process reliability.

Looking ahead, future research could explore how blockchain traceability systems can be scaled across diverse agri-food sectors while ensuring affordability and interoperability. In addition, investigating the integration of blockchain with IoT and AI may enable real-time, automated monitoring of food safety and quality. Finally, greater attention should be given to regulatory frameworks and cross-border standards to ensure global harmonization of blockchain-based traceability solutions. Future research directions for Topic 8 are presented in

Table A8. Future research agenda: Blockchain traceability systems in FSCs (Own elaboration).

Research Area	Key Questions	Suggested Methodologies
System design & automation	How can blockchain-based traceability systems be automated for real-time monitoring and decision-making? What architectures (smart contracts, IoT integration, RFID) optimize efficiency?	Pilot implementations, system simulations, IoT/blockchain integration studies
Sector-specific applications	How can traceability systems be tailored for diverse sectors (halal meat, seeds, grains, etc.)? What features enhance sector-specific transparency and safety?	Case studies, field trials, comparative analysis
Decentralization & data integrity	How can decentralized blockchain structures reduce reliance on central authorities and ensure tamper-proof data? How effective are consensus mechanisms in multi-stakeholder FSCs?	Technical experiments, Hyperledger/Ethereum prototypes, simulation studies
Integration with IoT & AI	How can IoT sensors, AI algorithms, and blockchain work together to enable automated quality monitoring and predictive safety alerts?	IoT-enabled pilot projects, AI analytics integration, real-time monitoring studies
Scalability & interoperability	How can blockchain traceability systems be scaled across regions and supply chains while remaining affordable? What interoperability standards are needed for multi-platform adoption?	Multi-case implementation studies, interoperability testing, cost–benefit analysis
Regulatory & cross-border standards	How can regulatory frameworks support adoption and global harmonization of blockchain traceability? How can compliance be ensured across jurisdictions?	Policy analysis, comparative legal studies, expert Delphi panels
Consumer trust & engagement	How can blockchain traceability systems enhance consumer confidence and willingness to pay for verified products?	Consumer surveys, experimental studies, adoption behavior modeling

(see Appendix A).

6. Conclusions

This study employed LDA topic modeling to map the thematic structure of blockchain applications in FSC traceability, thereby providing a comprehensive overview of the field. The findings highlight the rapid growth of research activity in this domain, with a marked surge in publications over the last decade. The analysis identified eight major thematic areas that define the scholarly discourse: retailer strategies in blockchain-enabled FSCs, blockchain for food safety and sustainability, enablers of blockchain adoption, consumer perceptions, adoption challenges, blockchain frameworks for sustainable food systems, blockchain for agri-food safety and transparency, and blockchain traceability systems in FSCs. Among these, blockchain for food safety and sustainability emerged as one of the most extensively investigated themes, reflecting the global urgency to ensure secure, ethical, and environmentally responsible food systems. Conversely, research on blockchain frameworks for sustainable food systems and fine-grained traceability applications appears less developed. This suggests both the novelty of these areas and the technical and organizational challenges they entail.

When compared with similar LDA-driven studies in broader supply chain contexts—such as Rejeb’s [49] exploration of blockchain in general SCM, Nguyen’s [113] analysis of full-text blockchain studies, Madzík’s large-scale mapping of blockchain in sustainable supply chains [114], and Balcıoğlu’s bibliometric synthesis [115]—the present study provides a more focused and granular examination specifically within food supply chains. While prior studies identify wider thematic clusters across logistics, finance, and manufacturing, our review reveals how FSC-specific concerns (e.g., food safety, consumer trust, and agri-food transparency) drive a distinct set of research priorities. This comparative perspective underscores the unique characteristics of blockchain adoption in FSCs and highlights the value of domain-specific insights that cannot be fully captured in broader SCM-focused analyses.

6.1. Research Implications

The current study makes a significant contribution to the theoretical understanding of blockchain applications in FSC traceability. The findings reveal that blockchain research spans diverse disciplines, including supply chain management, information systems, food science, and sustainability studies. As a result, there is a need for integrative and interdisciplinary approaches. More specifically, this article advances supply chain management theory by clarifying how blockchain reshapes coordination mechanisms, trust formation, information governance, and transparency across food systems. The eight identified topics offer a theoretically grounded framework that maps the key components of blockchain’s role within FSCs, thereby supporting the development of a more coherent research agenda in blockchain-enabled supply chain management. Furthermore, the eight identified topics provide a structured overview of the existing research landscape and unearthed critical areas such as food safety, consumer perceptions, and adoption challenges, while also drawing attention to underexplored avenues like blockchain frameworks for sustainable food systems. The application of LDA-based topic modeling demonstrates the effectiveness of systematic literature analysis in uncovering thematic patterns and guiding future scholarly inquiry in this evolving domain.

From a practical perspective, this study offers valuable implications for stakeholders across the FSC. Farmers and producers can benefit from blockchain-enabled traceability systems that secure product authenticity and reduce vulnerability to fraud. Agribusinesses and retailers may leverage blockchain to enhance consumer trust, optimize logistics, and support sustainability-driven marketing strategies. Policymakers are encouraged to use these insights to design regulatory frameworks and incentive structures that foster blockchain adoption while addressing scalability, interoperability, and governance challenges. Finally, technology developers must prioritize creating cost-effective, user-friendly, and scalable blockchain platforms that can be adopted not only by large corporations but also by smallholder farmers to ensure inclusivity in global food system transformation.

6.2. Research Limitations

Although this study provides valuable insights into blockchain applications in FSC traceability, several limitations must be acknowledged. Despite the effectiveness of the LDA-based topic modeling approach in identifying overarching themes, this study may overlook nuanced connections and emerging intersections across related areas of research. Moreover, the analysis is limited to the selected dataset, which might not fully capture the breadth of global scholarship on blockchain adoption in diverse food systems, particularly in regions where empirical studies remain scarce.

Future research would benefit from expanding the dataset to include a wider range of case studies, industry reports, and gray literature to provide a more comprehensive perspective. In addition, examining the integration of blockchain with complementary technologies such as IoT, AI, or quantum-resistant cryptography could deepen our understanding of its evolving role in food traceability and sustainability. Finally, there is an opportunity in broadening the scope to cross-disciplinary studies, spanning agriculture, policy, and consumer behavior, to yield richer insights into how blockchain innovations address the interconnected challenges of food security, climate change, and supply chain resilience.