Leveraging Milk-Traceability Technologies for Supply-Chain Performance: Evidence from Saudi Dairy Firms

Abstract

Growing concern over food safety and adulteration has thrust milk traceability technologies to the forefront of agrifood supply chains. This qualitative study explores the technological, organisational, and environmental (TOE) determinants of traceability technology adoption in Saudi Arabia’s dairy sector. In-depth semi-structured interviews with nine senior managers from small-, medium-, and large-scale dairy farms were analysed thematically in NVivo. Thematic analysis revealed that technological cost and compatibility played crucial role, while contrary to the prior literature, respondents downplayed technological complexity, arguing that training could offset it. Organisational culture and employee resistance were the primary inhibitors within dairy firms. Saudi Vision 2030, post COVID-19 consumer pressure and competitor pressure emerged as the dominant environmental factors. The findings offer insights for managers and policymakers on how to improve supply chain transparency, operational efficiency, product quality, and consumer trust while advancing several UN SDGs.

1. Introduction

The occurrence of diseases such as COVID-19, Salmonella, and bird flu highlight the importance of food quality and the role that traceability technology can play in ensuring safety, particularly in the food industry [1]. The sector has been under increasing pressure to improve food safety, particularly during and post COVID-19 pandemic that caused infectious diseases spreading through human interactions. However, empirical evidence on how and why firms decide to adopt these technologies particularly in dairy supply chains remains thin; thus, calling for context-rich studies to examine organisational realities [2]. Indeed, authors [3] suggest a proactive approach in implementing efficient traceability technologies early on to preserve food quality and safety for consumers. Parties engaged in the food supply chain need to adopt appropriate technologies to support product quality and increase operational efficiency [4].

Traceability has been defined in many ways [5,6,7,8,9], and there is no single common definition since they are context-specific [9,10]. Food traceability, for this study, is defined as the ability to trace the product through logistics processes from raw materials acquisition to production, processing, distribution, and retailing to preserve the quality, enhance safety, and gain customer trust [8].

Previous scholarly investigations have explored the assimilation of traceability technologies such as RFID tag (radio frequency identification), ERP (enterprise resource planning), and sensors like IoT (Internet of Things) in diverse settings, with a focus on the Chinese food supply chain [11], organisational elements influencing RFID adoption [12], implementation barriers to ERP systems [13], and the U.S. food industry’s adoption of IoT [14]. Others [15] investigated the trends of blockchain technology in agricultural supply chain and explored some of its adoption challenges. Some of these challenges are the lack of government regulations and lack of training and training platforms [15].

Upon reviewing the previous literature on food traceability technologies, the researcher is confronted with noticeable gaps, especially when considering the devastating consequence of the COVID-19 pandemic on global supply chains [16]. A critical analysis of these gaps underpins the novelty of this research and illuminates avenues for significant contributions to both academic and practical knowledge. Further, the lack of sector-specific studies (i.e., dairy industry) on Supply Chain Traceability in the dairy sector presents a clear research gap. Research focusing on the food and beverage industry is substantial [17,18], while most studies were on meat and meat products [2]; yet, the dairy sector with its unique operational complexities around its short shelf-life products is noticeably under-researched. The proposed research addresses this shortfall by investigating technology adoption strategies, thereby understanding this sector’s technology potential, and challenges facing the adoption of new technologies.

The objective of this study is to investigate the factors affecting the adoption of emerging traceability technologies within Saudi dairy firms by focusing on technological, organisational, and environmental framework. Further, it aims to explore how technology adoption is likely to enhance the overall supply chain performance.

The following research question guides the above objectives:

• RQ. How can Saudi dairy firms leverage traceability technologies and overcome traceability challenges to improve supply chain performance?

The sub-questions are:

• RQ1.1. What are the traceability challenges and barriers they face?
• RQ1.2. What factors determine the intention to adopt dairy traceability technologies in Saudi dairy firms?
• RQ1.3. How can food traceability technologies help improve the supply chain performance for dairy firms?

This research is drawn on the theoretical perspectives of Technology–Organisation–Environment (TOE) framework. This helped to identify key factors that could extend the suitability of the TOE framework in Dairy firm context. Following [19], this research is classified as theory elaboration rather than theory development and theory testing. This study has identified evidence in the interviews to support the traditional TOE factors in context of dairy firms, and it also attempted to explore new factors that could potentially extend the TOE theory.

The rest of the paper is organised as follows. Section 2 undertakes a literature review, offering a snapshot of technologies in Saudi dairy sector, followed by various traceability technologies available in general and the TOE dimensions affecting the adoption decision. Section 3 discusses the methodology of sampling and sampling frame, data collection, analysis, and findings. Section 4 presents a detailed discussion and the study implications, followed by Section 5 on conclusion and limitations.

2. Literature Review

The dairy supply chain comprises dairy farms, milk processing units, distribution centres/warehouses, retail stores, customers, and transporters for in-store and online operations. Wholesalers receive the dairy products from the manufacturers/milk processing units and sell them either directly to the market or the retailers. The retailers, supermarkets and hypermarkets receive milk and dairy products in bulk from manufacturers and stock them on shelves. The consumers can then pick the products from the shelves as per their preferences. The milk and milk products require extra refrigeration to protect them from spoilage. It implies that the stocking and sale of dairy products need extra care until they reach the customers. Traceability technologies play a vital role in tracking the food quality and safety along its supply chain.

2.1. Saudi Dairy Sector and Its Supply Chain

Dairy producers in Saudi Arabia, especially milk producers, have always been and continue to be the market leaders in the industry. The producers sell their products locally and within the Gulf region. The increasing population in these regions has contributed to the rising per capita milk consumption. Moreover, the high demand for nutrient-rich foods such as milk and other dairy products has rapidly driven the Saudi Arabian markets to grow. Milk is a rich source of Vitamin B12, potassium, magnesium, calcium, and proteins, all of which play a significant role in muscle growth, cognitive function, facilitating weight loss, and bone health [20]. These factors have further driven the country’s sale of milk and other dairy products.

The Saudi government also encourages new technologies and offers subsidies, which have played a part in the growth of the dairy sector. The country aims to be self-sustaining and produce all the milk and dairy products needed by the locals without importing. The development of the dairy sector has been very impactful and has resulted in a rise in the economy and reduced the levels of unemployment in the country. While the Saudi dairy sector has achieved a level of self-sufficiency with its legacy technologies, there remains a significant room for improvement, especially in integrating technologies across processing units, warehouses, transportation, and retailing within the dairy supply chain. The current localised technologies, while effective in their specific settings, fall short of the cohesive integration that Industry 4.0 promotes. The critical need is for technologies that not only perform tasks efficiently within a single location but also communicate seamlessly across the supply chain, ensuring a real-time flow of information for higher visibility. This integration is vital for keeping pace with the advancements encouraged by Industry 4.0, which is rapidly defining the future of industrial operations [21].

The integration of supply chain processes is essential in achieving efficient tracking, tracing, and visibility of products. This holistic approach ensures that each segment of the supply chain, from production to retail, is interconnected, allowing for real-time data sharing and decision-making [22]. In the context of the Saudi dairy industry, the current practice lacks this level of integration. As a result, there are missed opportunities in terms of operational efficiency, risk management, and meeting customer expectations for transparency. Implementing integrated systems would allow for better control over the supply chain, enhancing the quality and safety of dairy products and bolstering consumer trust.

2.2. Traceability Technologies

Traceability is a technology-aided system that allows tracking of products as they move along a supply chain [4]. The commonly used traceability technologies are the barcode, Radio Frequency Identification (RFID) tags, the Internet of Things (IoT), or sensors [23], as well as other emerging technologies like blockchain [24,25], and Artificial Intelligence [26]. It is crucial to have a clear and consistent method for recording and storing captured data, along with a robust system for sharing information between parties in a supply chain [5]. However, firms perceive real-time data sharing as a threat to their business [27]. This could be one of the reasons why the real-time decision-making through collaborative data sharing has not achieved its full potential despite its urgent need and benefits argued for years [28]. Nevertheless, adopting emerging technologies in traceability are expected to have a positive impact on supply chain performance [29].

In traceability technologies context, IoTs have been identified as catalyst for technological advancement, especially within the supply chain industry [30]. IoT facilitates interaction between intelligent objects with environment or with other computer devices. These objects, initially associated with RFID technology, have now expanded to include a vast array of embedded technologies (e.g., micro-chips) within physical entities [30]. RFID technology consists of identification tags that store information captured through radio waves by remote readers. It can be used in several food categories and food supply chains, demonstrating its versatility. For example, animals can be traced individually from birth to distribution; fresh fish can be traced from the fishing vessel to the port [31]. Authors [32] even suggest a traceability system of plants using radio frequency technologies. Yet, RFID is not frequently cited in the individual identification of final products/items due to its high cost. Instead, barcodes are considered more economical as retailers use them frequently and customers can easily read them through radio frequency (RF) guns [33]. Moreover, de vass et al. [30] state that RFID is not yet popular for individual items, although it is economical for cases or pallets of items. By connecting a RFID reader to the Wi-Fi-enabled Internet terminal, users can recognise, track, and control tag-attached objects globally in real time, as RFID is also considered as having a sensor mechanism similar to IoT. In fact, RFID is considered as the most predominant technology for sensing and communication protocols in the context of technological traceability systems [34].

Near Field Communication (NFC) is increasingly gaining attention for its potential to transform food traceability systems. As authors [35] claim, NFC technology serves as a conduit for short-range communication between electronic devices, thereby facilitating an intricate yet easily accessible information network spanning from producers to consumers. This advancement is particularly relevant given the increasing societal demand for transparency and accountability in food sourcing and quality assurance. NFC technology also fulfils contemporary industry prerequisites for wireless, passive, low-cost, and portable detection systems [36]. Nonetheless, the existing literature is yet to provide a substantive comparative analysis between NFC with RFID and Quick Response (QR) codes. Such a gap in the literature raises questions about the specific benefits and drawbacks of NFC, which could otherwise provide valuable insights for organisations deliberating on which technology to adopt for optimal traceability.

The wireless sensor network (WSN) is a group of linked sensor nodes used to track the weather [37]. Temperature, relative humidity, and levels of volatile compounds, among other environmental data, can be sensed by these sensors. Each node in the WSN consists of a microcontroller and an antenna for communication with other nodes [38]. The WSN records the real-time temperature and humidity in cold chains that store and distribute temperature-sensitive foods, such as vegetables, fresh fruits, meats, and other perishables [39]. WSN technology shows the promise for use in the food supply chain; however, it needs to be further developed to meet more complex and stringent security requirements.

Blockchain technology (BCT) operates as a distributed and decentralised system composed of time-stamped blocks linked via cryptographic hash [40,41,42,43]. Renowned for addressing fundamental problems related to trust, security, information transparency, and tampering prevention, BCT offers a promising approach to enhance trust mechanisms and resolve confidentiality and security issues within supply chains. While BCT is most widely used in the financial sector, its potential as a transformative driver is gradually being recognised by other industries as well [44]. The advent of international standards like ISO 22739:2020 and ISO 23257:2022 is testament to the growing efforts to facilitate BCT applications. Given the growing significance of real-time monitoring systems in food supply chain, BCT application in AFSCs is increasingly essential [45]. It enables the creation of a transparent, immutable, and reliable system, which in turn fosters real-time decision-making. In the context of digital food traceability systems, Internet of Things (IoT) tools such as RFID are already being utilised, while BCT is emerging as a potentially efficacious solution [40,45,46]. Additionally, the potential impacts of BCT-based traceability systems in FSCs remain unexplored [47].

In the case of food traceability where many technologies are available, each technology has its own set of advantages and challenges. However, the focus of this literature review was deliberately narrowed down to some key technologies—IoT, RFID, NFC, WSN, and Blockchain—due to their frequent mention and utilisation in the food supply chain literature and real-life applications. These technologies are at the forefront of innovation in food traceability, offering a combination of robustness, scalability, and real-time data capture capabilities that are critical for modern supply chain management. Furthermore, they have demonstrated their potential in enhancing transparency, safety, and efficiency of products flowing from farm to fork, thus making the case highly relevant for in-depth investigation.

Table 1. Food Traceability Technologies.

Technologies	Purpose	Example	Features and Observations
Near Field Communication (NFC)	Identification	[35]	No line-of-sight needed. Enhanced data capacity compared to barcodes. Supports wireless data transitions.
Barcode	Identification	[48]	Cost-effective alternative to RFID. Quick and consistent readings. Needs direct visibility for scanning.
Radio Frequency Identification (RFID)	Identification	[11]	No direct visibility required. Extended read ranges with high precision. Offers increased data retention capabilities. Efficient, but at a higher cost.
Blockchain	Data Integration	[49]	Decentralised data structure. Reduces potential for data tampering.
Internet of Things (IoT)	Data Integration	[30]	Networked device connectivity. Enables automated data collection and smart controls.
Wireless Sensor Network (WSN)	Data Integration	[50]	Facilitates “one-up one-down” traceability. Requires specific data formatting like EDIFACT or XML.

Note: technologies were selected because they dominate current agrifood traceability discourse; other niche tools (e.g., QR variant codes, hyperspectral imaging) fell outside this review’s scope.

presents a brief list of traceability technologies applicable to the food sector.

In fact, the key health risks associated with milk and dairy products can be divided into three categories: first, biological risk (i.e., toxigenic fungi, bacteria, and viruses); second, chemical risk (i.e., toxins, food additives, pesticide residues, presence of veterinary drugs such as antibiotics, deworming, and antimicrobials in the dairy product); and third, physical risk (i.e., shards of glass, insect fragments, stones, and hair). However, studies reveal that food-borne illness outbreak linked to milk and dairy products are mainly due to bacteria (e.g., Salmonella spp., E-coli, Clostridium spp, Listeria), rather than chemical contaminants [51]. Therefore, traceability is believed to prevent these problems since it helps in the recall of unsafe food if required by keeping track of food in the entire supply chain. The more information you have, the better and faster it would be to detect the affected food, reduce consumer risk, and save money and time.

2.3. Technological, Organisational, and Environmental (TOE) Dimensions

Research has applied many theories that underpin the technology adoption research. The commonly used frameworks are Technology Acceptance Model (TAM), Theory of Reasoned Action (TRA), Technology–Organisation–environment (TOE) framework, and Innovation Diffusion Theory (IDT). The last two frameworks are used to explain technology adoption from the perspective of organisational use [52,53,54]. Although, IDT takes technological and organisational factors into account, it does not include environmental factors, such as competitor pressure or government policy [53,54]. Therefore, this study employs the TOE framework, proposed by [55], to explore the adoption of new technologies based on technological, organisational, and environmental factors within an organisation [52,56]. It is adopted for exploring factors affecting the decision on traceability technologies adoption in logistics and supply chain [56]. TOE is more widely used in the technology adoption literature than other adoption frameworks, e.g., the IDT and the TRA [57].

The literature outlined in

Table 2. TOE factors used in existing literature on technology.

Sl. No	Authors	Study Focus	Technological Factors	Organisational Factors	Environmental Factors
1	[21]	Industry 4.0 Technology	Compatibility, cost	Top management support, employee capability	Competitive pressure
2	[58]	Blockchain technology	Complexity, relative advantage compatibility, trust, and scalability.	Organisations’ IT resources, top management support, size, financial resources	Competitive pressure, trading partner pressure, government policy and regulations, inter-organisational trust
3	[59]	Artificial intelligence and robotics	Internal and External IT expertise, relative advantage, complexity.	Market position, financial justification, resistance by employees	Customer readiness, and expectation, competition, legal issues
4	[60]	Blockchain technology	Infrastructural facility, complexity, availability of specific blockchain tools perceived benefits, privacy, compatibility, security	Presence of training facilities, top management support, firm size, capability of human resources, perceived costs, organisational culture	Government policies, competitive pressure, institutional-based trust, market turbulence, stakeholder pressure
5	[61]	Computer-assisted audit tools and techniques (CAATTs)	n/a	Firm size, top management commitment, employee IT competency	Complexity of clients’ accounting information systems, level of support of professional accounting bodies
6	[62]	Blockchain technology	n/a	Top management support, organisational readiness, organisation size	n/a.
7	[63]	Cloud computing	Compatibility, relative advantage, complexity, ease of use, trialability, technology integration	Firm size	Competitive intensity, regulatory support
8	[64]	Big data analytics	Complexity, compatibility, IT assets.	Top management support, organisation data environment, perceived costs	External pressure, industry type
9	[57]	Enterprise resource planning (ERP) software	Technical know-how, compatibility, value, security, technology infrastructure	demographic composition, size, scope of business operations, subjective norms	Competitive pressure, external support, trading partners’ readiness

shows the dominant factors influencing the adoption of various advanced technologies within the context of the TOE framework. The studies reviewed a range of technologies, from Industry 4.0 to blockchain and cloud computing, highlighting key technological factors like compatibility and complexity. Organisational factors such as top management support and environmental factors like competitive pressure are consistently noted as influential.

2.3.1. Technological Factors

The technological context focuses on internal and external technologies that are beneficial for organisations. The advantages of external emerging technologies over the internal legacy systems play a crucial role in adoption decisions. As various technologies emerge from the range of technologies under the Industry 4.0 era (e.g., artificial intelligence, robotics, blockchain, 3D printing, Internet of Things, and digital twins), as well as the knowledge of the importance of socio-technical factors under Industry 5.0 (e.g., workers’ experience, physical capacity and limitations, postural ergonomic risks, noise and vibration exposure, and workers’ boredom) [65], firms have the options to choose and adopt the right technologies as they deem fit. The technological features such as relative advantage, compatibility, and complexity are critical in new technologies adoption decisions [52].

Rogers [66] describes relative advantage as the extent to which a technological factor is regarded as offering superior benefits to organisations. Authors [67] demonstrate that food tracing systems using technologies have improved operational efficiency in organisations. Adoption of food traceability technology can significantly contribute to the sustainability and transparency of traceability management [42,68,69]. Some food traceability technologies offer users the ability to access and approve documents from anywhere in the world, provided they have access to computers and Internet [70]. Users do not need to own a computer for cloud computing services. Shared resources is another advantage for companies offered by cloud systems, which enables employees to access resources in the cloud from any location, saving businesses time and money (Jain & Bhardwaj, 2010) [70]. With the relative advantage of emerging technologies, it is likely that the technologies will be adapted into the organisations.

Rogers [66] defines compatibility as the extent to which an innovation aligns with the values, previous experiences, and technological requirements of prospective adopters. Later, [71] defines it as the degree to which technology is considered compatible with the current values, past experiences, and requirements of potential users. Perceived compatibility considers whether an organisation and its employees’ current values, behavioural habits, and experiences are reconcilable with emerging technologies and/or innovation [52,71,72,73]. It has been suggested that the more compliant a foreign technology is with the current technology, the greater the trust in mastering the new technology and the more positive the attitude will be [52,74].

Complexity is the perceived level of difficulty in learning and using a system [52,75]. The more complicated the technology, the less likely it is for a successful application. When a type of technology is considered complex for a company to adopt, upper management decides whether to ignore it or to adopt it later. Thus, the complexity of food traceability technologies has a negative relationship with its adoption [11]. Generally, it is quite similar to the ease of use. However, numerous studies treat it as a different and independent factor [76,77].

2.3.2. Organisational Factors

The organisational context refers to the firm’s structure, as well as the resources and intra-firm communications [78]. In this research, organisational culture, top management support, and training and education are included as organisational variables. Organisational culture plays a critical role since cultural and social norms have a strong impact on technology adoption in the organisations within the Arab world. Thus, technology adoption is not only difficult but also risky for Saudi organisations [79]. Saudi Arabia’s culture is tightly bound by Islamic belief and norms, which is supported by the government of Saudi Arabia [80,81]. To improve the technological adoption in Saudi Arabia, it is important to better understand the cultural factors to investigate the reason behind the slow process of technology adoption [81]. Some studies have explored environmental and behavioural factors while others investigated the logistics, legislation, and technology infrastructure [82,83]. However, a very few research has focused on understanding and identifying the cultural factors related to technology adoption in the form of traceability. As a result, focusing on organisational culture and its effect on technology adoption in Saudi Arabia is both important and timely.

Culture wields a significant impact on technology adoption, specifically in developing countries such as those with Arab histories [84]. Abunadi [85] states that individuals carry cultural biases, beliefs, and values that affect their perceptions of what new technologies may offer and their acceptance decision. Moreover, the results of [86] suggest that attitude and subjective norms significantly affect the intention of adopters. The incompatibility of any technology with cultural practices, values, and traditions is considered as one of the main factors in rejecting the decision of new technology adoption.

While technological attributes form the bedrock of adoption, organisational factors, specifically the role of top management support, play a critical role [58,87]. Low et al. [88], in the cloud computing context, emphasise on an organisation’s readiness and the broader scope of business operations. Authors [52] highlighted the significant influence of top management in driving technological change within organisations. Salwani et al. [89] argue that the perceptions and awareness of top management about the usefulness of technology create substantial value for organisations. This value is manifested through a long-term vision, enhancement of resources, and fostering an ideal organisational environment, which includes higher evaluation of employee self-efficacy and support in overcoming obstacles and employee resistance [90,91,92]. Additionally, the impact of top management support is often intertwined with organisational culture, as argued by [93]. In integrating these findings, this research aims to explore how top management support within Saudi organisations, shaped by the unique cultural and strategic landscape of Saudisation, influences the adoption of technology.

Training is defined as how an organisation teaches its workers to use a tool in terms of quantity and quality [94]. Since food traceability technologies can be too complex, employees need to be trained and educated before implementing these tools. It decreases employee stress levels and anxiety about the technology, increases motivation, and provides improved understanding about the technological benefits for employee tasks. In addition, training reduces ambiguity and assists employees in understanding successful use in future [52], which improves overall ease of use and usefulness.

2.3.3. Environmental Factors

A variety of external factors may influence organisational decisions on technology adoption. These factors include, but are not limited to, broader socio-economic crisis such as the adverse impact of the COVID-19 pandemic [95], consumer pressure [96,97], competitive pressure [52,98], and regulatory/government policy [99,100].

The socio-economic crisis, such as the COVID-19 pandemic, adds another layer of complexity, magnifying the need for more robust and transparent supply chain systems. As organisations were not prepared for such a low-frequency but high-impact crisis [101], food supply chain safety, among others, was the first urgent problem under consideration, requiring safety measures for the entire food supply chain (from farm to fork) [95]. In fact, advanced and more appropriate digital traceability technologies are largely argued for in an emerging public health crisis [102]. Traceability technologies such as blockchain, artificial intelligence (AI), and sensor technology (e.g., Internet of Things) would allow direct tracing and tracking of goods from farm to fork. By combining advanced traceability technologies with new analytical and smart technologies such as remote or virtual inspections, data streams could help minimise the time required to respond to foodborne outbreaks [103].

In parallel, consumer pressure for transparency, investigated by [96,97], supports organisations to revisit and possibly upgrade their traditional supply chain traceability technologies. Consumer pressure, particularly in areas concerning food safety and traceability, has increasingly become a primary catalyst in shaping business strategies. The consumer preferences are not only rapidly evolving [96] but also exerting a profound influence on organisational decision-making processes. This offers an understanding of how consumer-driven demands can spur technological innovation and adoption, especially in sectors where transparency and safety are paramount.

The urgency of ensuring food supply chain safety, particularly in the context of farm-to-fork traceability, was brought to the forefront by [95]. This concern was further amplified by increasing consumer demand for information about the traceability of food products, spurred by concerns over food quality, safety, and environmental considerations, as illustrated in many prior studies [96,97,104,105]. They increasingly request information about the source and ingredients of their food products due to the COVID-19 pandemic [106]. Hence, the food industry is facing challenges in tracking and tracing the food products through production, processing, and distribution [96]. Therefore, food traceability systems can reduce consumer information asymmetry and food safety risks [107,108,109].

The ability of organisations to maintain competitiveness is intrinsically linked to their adoption of new technologies, which in turn is influenced by competitive pressures and support from trading partners. Authors [52] noted the interdependence between competitive pressure, regulatory support, and the adoption of new technologies. This perspective is further supported by [98,110], who identified competitive advantage, regulatory support, and competitive pressure as key determinants in the adoption of new technology.

Moreover, government policy is a critical factor, acting both as an enabler and a regulatory framework within which businesses operate [60]. Policies can dictate the pace and nature of technological adoption, either by encouraging innovation through incentives or by imposing restrictions that necessitate adaptation. Understanding the interplay between policy and technology adoption sheds light on how regulatory environments shape and sometimes even redefine technological trajectories. Regulatory aspects, as highlighted by [58,59], either facilitate or hinder the technology adoption, depending on their alignment with the technology’s objectives and capabilities.

On 15 July 2017, the Strategic Management Committee in Saudi Arabia, approved the delivery plan for the National Industrial Development and Logistics Programme (NIDLP) [111]. The programme is mandated to transform the Kingdom of Saudi Arabia into a leading industrial powerhouse and a global logistics hub in promising growth sectors, including the food sector, focusing on automation and transformation toward Industry 4.0 [112], which is consistent with Saudi Vision 2030 and emphasises on new technologies, requiring massive investments in technology to ensure its success [113]. Hence, Saudi companies have been under pressure to adopt and implement new technologies to meet government requirements. The TOE framework has been further elaborated through semi-structured interviews with the participants from dairy firms in Saudi Arabia. Details of the data collection and analysis are presented in the Methodology Section.

3. Methodology

3.1. Sampling and Data Collection

The Kingdom of Saudi Arabia (KSA)’s dairy sector is highly competitive, where few local companies cater to the country’s high demand for milk and milk products. As of the year 2020, data obtained from the head of the National Committee for Fresh Dairy Producers at the Council of Saudi Chambers revealed the presence of 12 national dairy firms operating within the KSA. The major players include Almarai Company, Sadafco (Saudia Dairy & Foodstuff Company), NADEC (National Agriculture Development Company), and ASD (Al Safi Danone Company). Remarkably, these four firms accounted for a substantial 89% market share within the dairy industry [114]. This data served as a basis for identifying the population of dairy firms for this research. The whole population has been treated as the sample for the study because of the small number.

Using a variety of data collection methods, such as semi-structured interviews, the literature reviews, and dairy firms’ websites, a comprehensive understanding of traceability technology adoption in each individual Saudi dairy firm was sought. This approach offers a deep dive into each firm’s unique context while offering flexibility to draw comparisons across the firms. Interviews offer first-hand insights into the experiences and perceptions of dairy industry managers [115]. To facilitate access to key participants within these dairy companies, the head of the National Committee for Dairy Producers at the Council of Saudi Chambers was contacted. The potential participants were then contacted using email, WhatsApp, LinkedIn, and phone calls. All 12 dairy companies were formally invited to participate voluntarily in this research to ensure a comprehensive representation of the industry. Ultimately, nine senior production and distribution managers from nine small to large dairy firms agreed to participate. All nine interviewees held managerial positions and played integral roles in making strategic decisions about the technology adoption within their respective organisations.

Table 3. Sample demographic data.

Code	Work Exp.	Job Title	Firm Size	First Adopted FTT
A	32	Head of quality	Large	2002
B	14	Supply chain manager	Large	2011
C	21	Senior director of manufacturing	Large	2010
D	19	Head of Production	Large	2013
E	26	Supply chain manager	Medium	2019
F	21	The CEO	Medium	Not yet—adopted
G	20	Supply chain manager	Medium	2014
H	17	Plant manager	Small	Not yet—adopted
J	18	Manufacturing Manager	Small	Not yet—adopted

shows the interviewees’ work experience, job title, firm size, and the year of adoption of food traceability technology (FTT). A medium firm (F) and two small firms (H, J) have yet to adopt traceability technologies because of the technological complexities and resource constraint for undertaking training.

This study used semi-structured interview questionnaire with flexibility to ask questions linked to the research context [116]. Semi-structured interviews allow flexibility for the interviewee’s spontaneous speech and narratives, while also providing structure to obtain the interviewee’s insights in a systematic way [117,118]. It enables the researcher to ask “how” and “why” questions while exploring information that had not been expected.

Following the TOE framework underpinning this research, the open-ended questions aimed to investigate the factors that affect the adoption of food traceability technologies based on technology, organisation, and environment perspectives. The questionnaire had 33 questions under five sections which focused on general information about the respondents and traceability technologies adoption in dairy supply chain. Section 1 focused on interviewees’ demographic background along with key information about the dairy firms. Section 2 was about the technological factors that affected the company’s adoption decision. Participants were asked to reflect on the traceability technologies employed in their supply chain, their future adoption plans and how these technologies influence the performance of the supply chain. In Section 3, the participants were asked about the organisational culture if it supports adoption, and how top management thinks about the traceability technologies adoption. In Section 4, the role of environmental factors such as socio-economic crisis, consumer pressure, competitive pressure, and government policy in adoption decisions were explored. The supervisory team and a couple of industry professionals were engaged in pre-testing the questionnaire where they were asked to verify their relevance and clarity/ambiguity.

3.2. Data Analysis

This research adopted thematic analysis to ensure comprehensive and accurate exploration. Utilising the capabilities of the NVivo 12 Pro qualitative software, thematic analysis was meticulously executed using the interview transcripts. NVivo served as an invaluable ally, enhancing the precision, depth, and systematic approach to theme generation. The TOE theoretical framework and the literature were the basis of pattern recognition within the data [119].

The theme generation followed the following steps:

Data import and familiarisation: All interview transcripts were systematically imported into NVivo.

Coding process: Using NVivo’s robust coding functionalities, segments of the primary data were methodically coded. This entailed segmenting the data and assigning labels to denote what each fragment represents contextually.

Theme identification: Potential themes were discerned employing NVivo’s querying capabilities. This step congregated the coded data by mutual ideas or conceptual similarities.

Theme refinement: A thorough review and refinement process was undertaken within NVivo. Certain themes were amalgamated, some were bifurcated, while others, lacking substantive support, were omitted.

Theme definition: Post refinement, each theme was precisely defined within the context of the research.

Integration with initial themes: Leveraging NVivo’s comparison tools, the themes emerging from the interview data were seamlessly integrated with the initial themes rooted in the TOE framework. This ensured a comprehensive theme set rooted both in the literature and empirical data.

3.3. Findings

The sample included nine dairy firms of the total 12 in Saudi dairy industry. The four of them are large firms (>500 employees, as classified in Nitaqat), and three were medium size (>50 and <499), the rest two were small size (>10 and <49) [120]. The participants have worked for their company for a minimum of 7 years to a maximum of twenty-six years.

Table 4. Participants’ demographics.

Code	Age	Gender	Citizenship	Job Role	Experience (Years)	Firm Size	Location	Traceability Technologies Adopted
P1	52	Male	Non-citizen	Head of quality	32	Large	Riyadh	2002
P2	37	Male	Citizen	Supply chain manager	14	Large	Alahsa	2011
P3	46	Male	Citizen	Senior director of manufacturing	21	Large	Riyadh	2010
P4	45	Male	Citizen	Head of production	19	Large	Jeddah	2013
P5	50	Male	Non-citizen	Supply chain manager	26	Medium	Alahsa	2019
P6	46	Male	Citizen	The CEO	21	Medium	Alqassim	Not yet—adopted
P7	47	Male	Non-citizen	Supply chain manager	20	Medium	Alahsa	2014
P8	43	Male	Non-citizen	Plant manager	17	Small	Alqassim	Not yet—adopted
P9	41	Male	Citizen	Manufacturing manager	18	Small	Jeddah	Not yet—adopted

shows the profiles of each participant. The participants’ identity is decoded for anonymity and coded as P1 to P9.

Table 5. Thematic frequency analysis (in percent) in the Saudi dairy industry (P1 to P9 are not appearing in order).

Themes	P2	P9	P5	P3	P4	P6	P8	P7	P1
Technology adoption	21.06	12.06	10.96	13.67	9.1	7.97	7.19	8.39	9.6
Environment	29.53	13.32	12.68	16.85	8.99	2.73	4.65	4.98	6.26
Competitors	4.25	20.4	15.01	27.2	3.4	4.82	8.22	5.67	11.05
Consumer pressure	62.59	4.07	9.63	3.33	16.3	0	0	4.07	0
Consumer Awareness	62.59	4.07	9.63	3.33	16.3	0	0	4.07	0
Government Support	24.04	11.86	16.67	10.26	8.97	11.54	8.01	4.49	4.17
Mandatory SFDA	17.49	4.96	12.29	23.4	28.84	5.91	0	0	7.09
Vision 2030	50	0	0	23.08	0	21.37	0	0	5.56
Future challenges	12.96	14.2	5.86	13.27	7.41	27.47	6.17	3.4	9.26
Organisation	10.33	13.09	8.01	20.84	14.87	7.39	14.16	4.81	6.5
Organisational culture	0	0	11.11	64.05	11.11	0	13.73	0	0
Saudisation-OC	10.99	10.64	17.38	10.28	12.77	7.8	11.35	5.32	13.48
Top Management support	16.25	19.11	9.29	14.11	7.5	9.11	13.39	0.71	10.54
Training and development	18.29	7.62	4	10.86	20.57	6.1	15.43	9.52	7.62
Technology factors	22.07	10.71	11.72	12.29	8.07	7.93	6.25	10.57	10.4
Compatibility	16.26	21.54	10.16	0	9.35	3.66	26.02	8.54	4.47
Complexity	9.12	20.85	14.33	9.12	11.73	14.66	15.31	4.89	0
Employees’ resistance	14.94	20.12	17.84	19.09	7.88	5.19	7.88	7.05	0
Future technology	23.62	20.09	7.95	9.05	8.39	16.56	5.52	6.62	2.21
Technology advantages	32.28	2.11	13.18	14.76	10.41	5.67	4.61	3.69	13.31
SC performance	9.33	18.48	23.43	5.71	7.62	12.57	8.95	6.48	7.43
Current traceability technologies	20.51	5.9	9.2	10.32	6.59	6.96	3.92	18.46	18.15
Traceability technologies adoption motivation	33.8	7.18	16.2	17.13	3.94	5.09	8.33	3.7	4.63
COVID-19	21.73	8.25	14.08	10.26	9.96	12.37	5.23	2.31	15.79

encapsulates the prevalence of specific themes derived from the interviews with industry participants, labelled P1 through P9. The frequencies, expressed as percentages, reflect the extent to which each theme was referenced by participants, offering insights into areas such as technology adoption, environmental considerations, competitive pressures, and the impact of COVID-19. This data, organised through NVivo’s analytic capabilities, provide a quantitative look at the qualitative data, aiding in understanding the focal concerns and priorities within the industry’s current discourse.

Table 6. Extended overview of themes and subthemes of traceability technology. [Interviewees’ codes are indicated within bracket].

TOE Factors	Main Theme	Subtheme 1	Subtheme 2	Subtheme 3	Subtheme 4
Technology	Existence of traceability technologies in Saudi dairy sector (p1,p2,p3,p4,p5,p8)	-	-	-	-
Technology and organisation	Traceability technology adoption challenges and barriers (p1,p2, p3, p6, p8,p9)	Employee’s resistance (P2,P6,P3)	Compatibility considerations (P2,P4,P6,P7)	Complexity in the adoption process (P6,P1,P7,P2,P3)	-
Organisation	Role of organisational culture and top management support in the adoption process (p2,p3,p6)	Role of organisational culture(P2, P6)	Role of pop management support (P3,P2,P6)	-	-
Technology and organisation	Impact of food traceability technologies on supply chain performance (p1,p2,p3,p4,p5,p6,p7, p8,p9)	Efficiency: cost, profit, time, effort (P1,P2,P3,P5, P7,P8)	Flexibility (P5)	Food quality (P1,P2,P5)	Transparency, information availability, and accuracy(P7)
Environment	Impact of COVID-19 and post-COVID-19 period on technology investment (p1,p2,p3,p5,p7,p8)	-	-	-	-
Environment	Impact of consumer pressure on food traceability technology adoption (p1,p2,p3,p9)	Consumer awareness (P2)	-	-	-
Environment	Influence of competitor pressure (p1,p2,p3,p4,p5,p6, p7,p8,p8)	-	-	-	-
Environment, technology	Role of government policy in influencing FTT adoption (P1,P2,P3,P4,P7,P8)	Vision 2030 initiative (P1,P2,P3)	Technology investment (P1,P4,P7,P8)	-	-
Organisation	Importance of employee training in technology adoption (P1,P2,P4)	-	-	-	-
Environment	Workforce localisation initiative (Saudisation) (P1,P2P6,P9)	-	-	-	-

presents the main themes and subthemes pertinent to the adoption of traceability technology within the Saudi Dairy Industry. It offers a structured overview of the TOE factors influencing technology adoption, ranging from internal organisational dynamics to external market pressures. Each main theme is meticulously broken down into its constituent subthemes, painting a comprehensive picture of the various elements at play. This framework not only guides the analysis of qualitative data but also shapes the discussion of results, ensuring a thorough examination of each aspect of traceability technology adoption in the industry.

3.4. Reliability and Validity of the Findings

Ensuring the reliability and validity of findings is crucial to substantiate the contributions of this research. This study employed comprehensive methodological rigour to achieve these goals by drawing on the established academic references [121,122]. The validity of the study was supported through data triangulation, ensuring robust data collection from multiple sources. Information was gathered from semi-structured interviews and supplemented by reviews of dairy firm websites [123]. This approach not only corroborated the findings but also enhanced the depth and credibility of the data. Purposive sampling techniques were utilised to select twelve national Saudi dairy firms, representing the entire population within the dairy industry. Senior production and distribution managers from nine firms were interviewed based on their critical roles in decision-making processes relevant to the adoption of traceability technologies. This sampling strategy aligns with case study methodology recommendations [124] and ensures that the study captures comprehensive insights from key industry players.

To enhance reliability, the coding process was rigorously designed and implemented using NVivo software. The initial coding was performed by the researcher, followed by a review and verification by supervisors, ensuring consistency and accuracy in data interpretation. Discrepancies in coding were discussed and resolved through consensus, referring to the literature to address intercoder reliability issues effectively [125]. Confidentiality of the data from participating firms was strictly maintained, reinforcing the study’s ethical integrity and further supporting the validity and reliability of the findings.

The study’s internal validity, or credibility, was underpinned by the plausibility of data and the trustworthiness of participant responses, corroborated by a thorough review of the literature and secondary data from dairy firms’ website. External validity, or transferability, was addressed by detailed analysis within each interview context, allowing the findings to be applicable to similar regulatory and industrial environments both within and outside Saudi Arabia. Through these methodological measures, the study ensures that the findings are both reliable and valid, offering confident insights into the landscape of technology adoption in Saudi Arabian dairy firms.

4. Discussion and Implications

TOE framework has previously been used to understand the multifaceted process of adopting and successfully implementing traceability technologies. However, the TOE framework is to be modified to encapsulate critical factors emerged as the themes from the analysis of Saudi dairy firms in this study. The research unveiled key influencing factors, for example, organisational culture, the strategic plan ‘Vision 2030’, and the significant impact of consumer pressure post-COVID-19 pandemic. In addition, it highlighted the importance of cost, compatibility, and complexities in the technology adoption process, and notable resistance to technology adoption among employees and their cultural influence. Figure 1 below presents a modified TOE framework that explains how the adoption processes is guided by TOE dimensions leading to an improved firm performance measured on operational efficiency, product quality, information visibility, and logistics flexibility.

4.1. Development of Study Proposition

The Saudi dairy industry’s landscape of traceability technologies is evolving and being shaped by technological, organisational, and environmental factors. Therefore, we draw the following propositions in line with the revised framework.

Proposition 1 (P1):

Cost plays a significant role in the uptake of new technologies within the Saudi dairy sector.

The research reveals a varied perspective on the implementation of traceability technologies within the Saudi dairy sector. Although larger firms have started incorporating advanced systems like ERP and SCADA (Supervisory Control and Data Acquisition), enhancing certain aspects of supply chain efficiency and product quality, the industry as a whole still demonstrates a significant gap in fully embracing Industry 4.0. Many medium-sized and smaller firms predominantly rely on more traditional methods, such as manual tracking and basic barcode systems. Costs associated with acquiring, implementing, and maintaining these advanced technologies, can be particularly challenging for small and medium-sized enterprises. Addressing this barrier is essential for the successful integration of traceability technologies which are key to improving supply chain efficiency and meeting industry standards.

Proposition 2 (P2):

Compatibility plays a critical role in influencing the decision to adopt traceability technologies in the Saudi dairy industry.

The findings highlight the role of compatibility in the decision-making process for traceability technology adoption. Saudi dairy firms place significant emphasis on ensuring that new traceability technologies are interoperable with existing legacy systems and processes. This focus on compatibility extends beyond mere technical integration to include alignment, which is also crucial for facilitating employee acceptance and smooth implementation. Additionally, compliance with industry standards and regulations is also a key aspect of this compatibility. Therefore, this proposition reflects dairy firms’ approach to technology adoption, aligning with the broader objectives of operational efficiency and regulatory compliance.

Proposition 3 (P3):

The complexity of traceability technology is commonly underestimated and consequently not considered as a significant barrier in the decision-making process in the Saudi dairy industry.

This proposition is based on the finding that participants from Saudi dairy companies largely dismiss the complexity of new technologies as a concern in their adoption decisions. Contrary to the views in the existing literature which identify complexity as a notable barrier [62,126], the participants in this research believe that complexities can be readily overcome, primarily through appropriate training programmes. Such training, as noted by P1, P3, and P4, needs to be specifically designed to address the unique requirements of different traceability technologies. This ensures that employees are not only technically proficient but also comfortable and confident in using these new systems. Tailored training programmes can mitigate the challenges associated with learning new technologies, reducing anxiety and resistance encountered during such transitions. Equipping employees with necessary skills and understanding can facilitate a smooth transition. However, small and medium firms have issues with resources to undertake this. Further, this perspective could be a reflection of the high-power distance and hierarchical culture prevalent in Saudi Arabian organisations, where managerial decisions may overshadow the issues around technology usage at the employee level.

Proposition 4 (P4):

The adoption of traceability technologies in the Saudi dairy industry is significantly influenced by the organisational culture.

This proposition stems from the finding that more than 75% of top management in the Saudi dairy industry are Saudis, thereby embedding strong Saudi cultural values within the organisational culture. The top management’s cultural background not only influences their supportive stance towards technology adoption but also affects the overall organisational approach to embracing technological change. This cultural dynamic plays a crucial role in how technology adoption is perceived and implemented within these organisations. It suggests that understanding the nuances of Saudi culture is essential to comprehend the adoption of traceability technologies in the Saudi dairy industry.

Proposition 5 (P5):

Employee resistance in the Saudi Diary industry has significant influence on the decision to adopt traceability technology.

Saudisation policy on technology adoption has overly depended on Saudi nationals in leadership roles and the organisational culture reflective of Saudi Arabian societal values, as identified by Hofstede’s model. Characteristics such as high uncertainty avoidance, power distance, and collectivism may lead to a cautious approach towards new technologies [127]. This cultural disposition can manifest as employee resistance to change, particularly regarding the adoption of new and potentially disruptive technologies. Furthermore, the high-power distance characteristic prevalent in Saudi culture may result in centralised decision-making processes. Such concentration of power in the hands of a few senior managers favouring their own employees could slow down technology adoption due to bureaucratic hurdles. The study thus reveals that Saudisation, while aiming to empower the local workforce, may inadvertently create challenges in adopting new technologies.

Proposition 6 (P6):

Saudi Arabia’s Vision 2030 positively motivates dairy companies to invest in traceability technologies and align their strategies with national development goals.

The SFDA (Saudi Food and Drug Authority), which implements policies that mandate the adoption of technologies like sensors and GPS systems, plays a pivotal role in this process. These policies are part of a larger strategic framework that includes the National Industrial Development and Logistics Programme (NIDLP) and Saudi Vision 2030, which collectively aim to modernise the industry and integrate it into the global supply chain network. The government’s approach not only demands compliance but also supports companies in transitioning towards improved traceability capabilities. By necessitating the use of traceability technologies, the government is ensuring a more efficient and transparent supply chain, critical for managing safety risks and bolstering consumer trust. The study’s findings highlight the efficacy of government intervention as a catalyst in fostering technological adoption and innovation within the industry. The participants confirm that these investments are in response to the new requirements set forth by Vision 2030. The enforcement of stringent regulatory requirements under Vision 2030 has thus become a key environmental factor, compelling dairy companies to adopt advanced technologies. However, it needs to explore the long-term effects and broader implications of these policies, including the challenges faced by companies in complying and the overall impact on stakeholders.

Proposition 7 (P7):

Consumer pressure has a positive impact on the adoption of Food Traceability Technologies (FTT) in the Saudi dairy industry, driven by demands for more information about food safety and production, particularly in post-COVID-19.

This proposition demonstrates that consumer pressure plays a considerable role in motivating Saudi dairy companies to implement traceability technologies. Participants from the industry (e.g., P1) have acknowledged the growing consumer demand for detailed information about the food they consume, including its safety, production, and origin. This demand has led companies to consider more sophisticated traceability systems to meet these consumer expectations. However, the study also reveals variations in the intensity of this pressure. Some participants reported a lack of consumer pressure, attributing this to either the high perceived quality (P2, P6) of their products, which already fosters consumer trust, or to a general lack of consumer awareness about the concept and benefits of traceability (P2). The COVID-19 pandemic, contrary to the expectations and global trends, did not substantially expedite this process. Interviewees suggest that the adoption of these technologies continued at a measured pace, reflective of a long-term strategic approach rather than a rapid response to the pandemic. This variation indicates that consumer pressure is not uniform across all companies and depends on specific consumer segments and their levels of awareness and trust in the product quality.

Proposition 8 (P8):

Competitor pressure has a positive impact on the adoption of food traceability technologies in the Saudi dairy industry, driven by companies’ needs to stay competitive and maintain their market position.

The findings reveal that competitors’ actions and advancements play a critical role in influencing technology adoption decisions within the Saudi dairy industry. Participants in the study unanimously acknowledged the impact of their competitors’ technological strides, particularly in traceability technologies, on their own strategic decisions. This awareness of competitors’ advancements creates a sense of urgency and a need to keep pace, thereby motivating companies to adopt or upgrade their traceability systems. The desire to not fall behind in the market and to maintain their competitive edge is a key driver to embrace new technologies. This scenario mirrors similar findings in other industries, where competitor pressure is recognised as a pivotal factor to adopt new technologies to stay relevant and competitive.

Proposition 9 (P9):

Adopting traceability technologies has positive influence on operational efficiency, better product-quality control, greater information transparency, and logistical flexibility.

The findings suggest that adoption of traceability technologies likely enhances the supply chain performance in the Saudi dairy industry. Participants from the industry have noted several key improvements as a result of implementing these technologies. These include increased operational efficiency, which encompasses cost reductions and productivity enhancements; enhanced food quality, particularly in terms of safety and reliability; augmented information transparency throughout the supply chain, leading to improved accountability and consumer trust; and greater flexibility, allowing companies to adapt more effectively to changes and disruptions. These benefits reflect the direct experiences and observations of industry participants in this study, highlighting the substantial role that traceability technologies play in advancing the performance of the dairy supply chain in Saudi Arabia.

4.2. Theoretical Contribution

The study uniquely combines existing theories of technology adoption with specific domain knowledge, thus advancing our understanding in several ways: first, the study provides a significant extension to the well-accepted Technology–Organisation–Environment (TOE) framework by [55] in the context of dairy supply chain. The prior literature has applied this framework to understand technology adoption challenges primarily in the context of information systems [57], with less emphasis on its applicability to traceability technologies in supply chains. This research, however, incorporates traceability technologies into the TOE framework, thus augmenting the model’s versatility and applicability not just in an organisational context, but also in a supply chain context, similar to investigations into Industry 4.0 Technology [21], Blockchain technology [58,60], Artificial intelligence and robotics [59], Cloud computing [63], Big data analytics [64], and smart logistics of SMEs [56]. Second, by leveraging the TOE framework, this study encompasses a wider array of factors that include organisational factors, such as workforce localisation initiatives and management support, and environmental factors, such as government policy, COVID-19, and consumer pressure. Such a comprehensive view of technology adoption provides a richer, more nuanced understanding that can guide both academic research and practical implementation.

Third, the study contributes to the literature by bringing a cultural perspective to technology adoption. Despite the global relevance of technology adoption, most studies have been conducted in developed countries, such as the United States, Australia, and China [128]. By examining the issue in the context of Saudi Arabia, a developing country with a distinct cultural and regulatory environment, this study enriches our understanding of how cultural and environmental factors can shape technology adoption. Fourth, the study contributes to a new dimension, that is workforce localisation initiative, specifically the “Saudisation” policy in Saudi Arabia, as an environmental factor influencing technology adoption. Workforce localisation initiatives represent government policies designed to increase the proportion of local citizens in the workforce, which can significantly impact organisational decision-making and strategies. This research contributes to addressing this gap by investigating the role and impact of Saudisation policy in shaping the adoption of traceability technologies in Saudi Arabia’s dairy industry. This inquiry expands the TOE framework’s environmental dimension, from traditionally encompassing factors to include government workforce policies.

4.3. Practical Implications

The practical contributions of this research can be grouped into three primary categories: enhancing industry practices, improving policymaking, and contributing towards sustainable development goals. This research provides industry practitioners and managers with a clear understanding of the problems associated with current food traceability technologies in food processing, distribution, and retail. By proposing additional emerging and compatible technologies, the research offers practical solutions that can be integrated into food traceability processes. This will not only optimise the supply chain but also potentially increase operational efficiency. These aided benefits can easily overcome the issues of cost and complexities associated with the adoption of new traceability technologies. In the aftermath of the COVID-19 pandemic, the research assures managers that the adoption of traceability technologies can enhance consumer trust and confidence in food products, particularly in dairy items.

In addition, the insights gleaned from this research can assist policymakers in designing effective traceability programmes and establishing pertinent regulations. By understanding the barriers and enablers in the adoption of traceability technology, policymakers can develop regulations that promote the use of such technologies, meeting the strategic planning of Vision 2030. Additionally, the research underlines the importance of comprehensive training to help understand the complex technology and enable its smooth implementation within dairy firms. Finally, this research makes substantial contributions to several United Nations’ SDGs. It provides a practical solution for enhancing food safety, reducing waste, and promoting sustainable production and consumption patterns. Specifically, it aligns with SDG #3 (Good Health and Well-being) by improving food safety and reducing the prevalence of foodborne illnesses. It also supports SDG #12 (Responsible Consumption and Production) by advancing efficient food traceability systems that help to minimise food waste and losses, while also empowering consumers with information for sustainable consumption. Additionally, the research contributes to SDG #13 (Climate Action) by enabling a more resilient food supply chain that can adapt to climate-related disruptions and by promoting sustainable land use, thereby reducing the carbon footprint of food production.

5. Conclusions and Limitations

The current research has examined the adoption of food traceability technologies in the Saudi dairy industry, aiming to bridge a critical gap in both academic and practical understanding. The researcher has applied a revised TOE framework, emphasising technological, organisational, and environmental factors that influence the intention of Saudi dairy firms to implement traceability technologies in their operations and distribution networks. The main findings indicate a lag in the adoption of traceability technologies within the Saudi dairy sector, especially amongst small and medium enterprises. Despite awareness of the benefits of advanced traceability systems, the persistence of traditional methods such as manual reporting and excel sheet usage reflects a disparity between the reality on the ground and the goals of Saudi Vision 2030 [111]. Other factors include Saudi culture, which influences technology adoption decisions; the COVID-19 pandemic’s minor influence on technology adoption; and employee resistance, which highlights the importance of user-friendly technology and adequate training for successful technology adoption. The study drew on theoretical and practical implications.

The study acknowledges some limitations. First, the qualitative insights drawn from this study were largely based on nine managers from the dairy industry sharing their invaluable perspectives. Although it might not encompass the whole industry, it represents an informative cross-section of experiences where each voice added depth and nuance to the findings, painting a textured landscape of the industry’s attitude towards traceability technologies. Further studies could explore the richness of these insights across an even larger sample or expanding to cover the entire food industry. Second, the findings were deeply embedded within the cultural and regulatory context of Saudi Arabia’s dairy industry, which added layers of cultural specificity and regional relevance to the study. Herein lies a wonderful opportunity for future research to apply the same lens to different contexts, thus broadening our understanding of traceability technology adoption in diverse settings. Third, the qualitative study allowed the researcher to delve into detailed narratives and lived experiences of the participants. While this might introduce an element of subjectivity, future research could complement these findings with survey data to capture a wider range of participants and the effect of TOE dimensions on supply chain performance within a proposed framework may be tested objectively.