Food Supply Chain Resilience in the Digital Era: The Roles of Supply Chain Security Strategy, Organizational Digital Adaptability, and Industry 4.0 Implementation

Abstract

In response to escalating global volatility, organizations are prioritizing the adoption of Digital Industry 4.0 Technologies (DI4Ts) to improve efficiency and enhance decision-making capabilities. Refining Organizational Adaptation Theory (OAT), this research examines the factors influencing DI4Ts implementation success and their impact on organizational performance and resilience within Saudi Arabia’s food logistics firms. Using data from 191 managerial respondents processed through Partial Least Squares Structural Equation Modeling, the findings indicate that dynamic digital capability and effective digital leadership significantly promote the implementation of DI4Ts. Additionally, supply chain security and anti-counterfeiting strategies were shown to exert a stronger influence on operational outcomes and organizational resilience than technology adoption alone. In an institutional environment characterized by a high food import reliance and strict traceability mandates, government policies moderate the relationship between organizational digital adaptability and implementation success. Our research outcomes establish a comprehensive framework for the incorporation of DI4Ts where supply chain security functions as a foundational capability predicating digital effectiveness.

1. Introduction

Digital Industry 4.0 Technologies (DI4Ts) have become increasingly essential as they are being incorporated into logistics networks and food supply chains (FSCs) [1]. However, while DI4Ts can support resilience and sustainability [2,3], their impact is not automatic and depends on complementary strategies such as supply chain security and anti-counterfeiting measures to mitigate risks like cyber vulnerabilities and fraud [4]. Herein, a supply chain security strategy is conceptually defined as a proactive framework of policies, protocols, and cultural norms designed to protect digital and physical supply chain assets from malicious interference. Rather than being an automatic outcome of technology implementation, resilience is a capability dependent on specific organizational configurations [5]. Recent scholarship suggests that without complementary organizational mechanisms, such as data-driven culture and learning or robust risk management, digital investments may fail to yield performance returns [4,6]. The integration of DI4Ts introduces new vulnerabilities, including cybersecurity threats and data integrity issues, which can negate resilience benefits if not managed through a robust Supply Chain Security Strategy.

For the food sector, these technologies come with various challenges, including the necessity for substantial investment in infrastructure and training, alongside opportunities such as increased supply chain efficiency and improved food safety [7,8,9]. Growing climate pressures necessitate transparency, efficiency, and innovation in global food management [10]. DI4Ts enable organizations to optimize real-time decision-making and streamline food system operations. They enhance an organization’s absorptive capacity by enabling early detection of disruptions through real-time analytics, adaptive capacity by facilitating rapid resource reconfiguration, and restorative capacity by supporting accelerated recovery processes after shocks. To achieve these outcomes, firms should prioritize organizational dynamic digital capability and digital leadership, where the former pertains to the structural and procedural flexibility to continuously readjust resources in response to technological shifts and the latter encompasses the strategic intent and vision-setting capacity that fosters digital transformation.

1.1. Challenges and Barriers in DI4Ts Implementation

While DI4Ts offer substantial advantages, the FSC remains vulnerable to major disruptions, including climate change, population growth, and increased demand for certified products [11,12,13]. Integrating DI4Ts requires overcoming significant technological, financial, and organizational barriers [14]. Traditional FSC models must evolve to meet rapid technological advancement, where resilience management plays a pivotal role in integrating advanced digital systems to enhance food stability and security [15]. Specifically, factors such as insufficient expertise and data privacy concerns act as unavoidable barriers to DI4Ts adoption within the FSC [16]. Addressing the fragility of conventional FSCs requires diversified and localized approaches supported by DI4Ts [17]. Yet, successful implementation requires more than technical readiness; it demands innovation-oriented cultural capabilities and a proactive orientation toward risks such as counterfeiting [18]. Ultimately, DI4Ts enable organizations to get access to consumer data, enhance FSC flexibility, and respond to uncertain challenges related to logistics and food security [19,20].

1.2. Research Rationale and Objectives

The Saudi context presents a unique institutional landscape that deeply affects the adoption and implementation of novel technological solutions. The urgency of this research is underscored by recent disruptions in Saudi Arabia’s FSC, such as the 2022 grain import delays due to global trade instability and increasing counterfeiting concerns in perishable goods. Critically important given Vision 2030 goals regarding national food security and the reliance on food imports exceeding 80% for main commodities, these challenges highlight the pressing need for DI4Ts to enhance food security and supply chain resilience. Moreover, the Saudi Food and Drug Authority’s traceability regulations, Halal certification requirements, and other regulatory frameworks are beginning to approach technology adoption less as a competitive differentiator and more as a mandatory operational standard. Although previous studies have provided substantial insights into the impact of DI4Ts on resilience [21,22], most have focused on performance outcomes while largely overlooking the pre-implementation factors essential for successful integration. Furthermore, the existing literature has rarely examined how the implementation of DI4Ts enhances operational and resilience performance, particularly in the face of challenges like counterfeiting threats and supply chain security. This gap is significant, as operational performance directly affects food safety and national food security, making the DI4Ts implementation decision highly urgent.

Rather than simply replicating Organizational Adaptation Theory (OAT) and the Dynamic Capability View (DCV), this study contributes to the literature by refining them. Namely, the goal is to extend prior models by demonstrating that in highly regulated, import-dependent emerging economies, external institutional pressures and foundational supply chain security strategies represent essential prerequisites that predicate the success of DI4T implementation.

To address the gaps in existing literature and fulfil its objectives, this study develops a comprehensive framework to evaluate how pre-implementation factors drive DI4Ts adoption in Saudi food enterprises. Moreover, it examines the implications of DI4Ts implementation on both operational and resilience performance in the Saudi food industry, considering the influences of counterfeiting risk orientation and supply chain security measures. Specifically, this study addresses the following central research question: How do organizational adaptability and security strategies interact to drive DI4T effectiveness in a developing economy? This investigation provides empirical evidence regarding the implementation of DI4Ts in FSCs, enhancing the understanding of operational and resilience performance within a specific national context and serving as a reference for other nations. Based on the preceding discussion, this study aims to achieve the following research objectives:

• Objective 1: To critically evaluate critical factors that influence DI4Ts adoption within Saudi Arabia’s food manufacturing sector, as well as food wholesale, distribution, and logistics firms within the country
• Objective 2: To examine the implications of DI4Ts implementation on operational and resilience performance in the Saudi food industry
• Objective 3: To develop a comprehensive framework to understand the adoption of DI4Ts in the Saudi food industry.

Building on the presented background, the following sections delve into a detailed examination of the theoretical framework, the conceptual model, and the hypotheses drawn from existing literature. Subsequently, the Methods section outlines the measurement of constructs and data collection procedures adopted for this research. While the Results section presents the outcomes of data analysis and hypothesis testing, the Discussion section addresses managerial implications, study limitations, and directions for future research.

2. Literature Review and Theoretical Background

2.1. Resilience and Sustainability in Food Supply Chain Management (FSCM) and Logistics

Encompassing smart sensors, IoT, and blockchain, DI4Ts are transformative tools with profound implications for the food sector. Industry 4.0 integrates technology into production and logistics by leveraging the IoT and Services specifically for industrial operations [23], influencing value creation, reshaping business models, streamlining service delivery, and reorganizing workflows.

The food sector is characterized by complicated relationships between suppliers, processors, distributors, and retailers, where transparency, security, traceability, and sustainability are challenged by the increasing global demand, climate change, and health concerns [24]. Gómez and Lee [25] contend that the food and beverage sector is perceived as an inefficient marketplace attributable to its restricted transparency, insufficient transaction supervision, and vulnerability to fraudulent activities. According to Kamalahmadi and Parast [24], blockchain technology is considered to enhance data security and facilitate information sharing, thereby fostering trust, transparency, and the protection of data privacy among supply chain participants. Furthermore, Ivanova [26] emphasizes the IoT’s capability for real-time monitoring of environmental conditions, inventory, and logistical movements, yielding prompt operational advantages. Khan et al. [27] highlighted that the adoption of smart technologies played a crucial role in sustaining supply chain performance and mitigating supply chain disruptions during the pandemic. Engelseth [28] explores how local food suppliers can enhance customer responsiveness by adopting supply chain practices that ensure collaboration, improve service delivery, and influence consumers’ trust.

Achieving resilience and sustainable operations in FSCs and logistics has emerged at the forefront of the business agenda in the aftermath of the pandemic, revealing the shortcomings of traditional FSCs. It is noteworthy that the concepts of resilience, sustainability, and operational performance are intricately linked; however, each fulfills unique strategic and operational roles. Resilience in the supply chain is associated with risk management, and it pertains to the capacity of a supply chain to foresee, prepare for, react to, and recuperate from disturbances, thereby ensuring operational continuity and stability [29,30]. This concept emphasizes the critical importance of adaptive capacity when faced with unexpected events, encompassing, but not restricted to, environmental disasters, epidemic outbreaks, or technological interruptions. On the other hand, sustainability is concerned with the management of supply chain operations in a manner that fulfills current requirements while considering the needs of future generations by reducing negative environmental effects and fostering social equity in conjunction with economic efficiency [31,32]. Furthermore, operational performance evaluates the present efficiency and effectiveness of supply chain processes, often serving as a timely metric of organizational success [33].

Collaboration among diverse stakeholders, including local councils, social businesses, merchants, and charities, is essential for fostering resilience and sustainability in the FSC, particularly for addressing food security and waste issues. The research conducted by Rashid et al. [34] reveals that supplier trust and the implementation of emerging technologies such as blockchain, artificial intelligence, and advanced analytics augment an organization’s ability to effectively respond to disruptions and increase its sensing capacities and crisis management. This collaboration enhances adaptive and responsive capabilities to achieve sustainability and a resilient FSC [35]. Basit et al. [36] found that leadership competence, knowledge sharing capability, and strategic management capability influence the performance of sustainable supply chains during the COVID-19 pandemic. Finally, DI4Ts play a critical role in FSCM by facilitating the continuity of operations, building more resilient and sustainable supply chains, and equipping managers with the tools to utilize data-driven insights for effective risk prediction and mitigation [37].

2.2. Theoretical Background

Food supply chains face several challenges that stem from both internal dynamics and external pressures. This study adopts the OAT, which serves as a pivotal framework for evaluating an organization’s ability to make internal changes in response to an exogenous change in the external environment or to improve performance [38]. Organizational adaptation is the process through which organizations implement internal changes by modifying or altering their structures, resources, processes, and strategies in response to exogenous changes in the external environment or due to a firm’s pursuit of performance improvements [39]. Moreover, organizational adaptation is a dynamic process that entails replacing outdated strategies and structures with more appropriate alternatives to align more effectively with the new environment [40]. Cozzolino & Verona [41] assert the OAT is notably proficient in addressing radical changes, such as those brought by digital transformation, customer pressure, or market changes requiring firms’ significant adaptation to customer expectations, regulation, or business models.

Within the OAT framework, the DCV provides a critical lens for understanding the mechanisms of adaptation. Digital transformation often requires organizations to engage in dynamic adaptation, effectively balancing the exploitation of existing capabilities alongside the exploration of new opportunities to enhance their alertness and responsive capacity [42]. According to Rodrigues et al. [43], dynamic capabilities are the firm’s ability to integrate, build, and reconfigure internal and external competencies to address rapidly changing environments. Capabilities are defined as the ability to adapt to evolving environmental demands by integrating relevant technologies and resources to achieve a persistent competitive edge and sustained organizational performance [44]. When firms seek to adapt to changes in their external environments by relying on dynamic capabilities, they may do so poorly or well.

With the advent of DI4Ts, organizations are required to engage in dynamic adaptation—modifying existing capabilities and aligning internal processes with external digital trends. Such adaptation is essential to remain competitive, especially in sectors like food supply chains, where disruptions such as the recent pandemic have exposed vulnerabilities and accelerated the need for digital transformation. This study uses organizational adaptation theory to understand how food supply chain organizations might recognize digital opportunities and swiftly incorporate new technologies to better increase resilience and sustainability. Thus, OAT provides a robust theoretical foundation for understanding the dynamic changes required to respond swiftly to external changes and capitalize on digital transformation in FSCM effectively. To synthesize the theoretical framework guiding this study,

Table 1. Theory-to-Construct Mapping.

Theoretical Lens	Main Mechanism	Associated Construct(s)	Hypotheses
DCV	Sensing and seizing digital opportunities through strategic intent and flexible resource structures.	Organizational Dynamic Digital Adaptability & Capability; Digital Leadership	H1, H2
OAT	Strategic reconfiguration of operational processes to achieve efficiency and absorptive capacity.	Implementation of DI4Ts	H4, H5
OAT	Environmental calibration and recalibration of security protocols in response to external risks.	Supply Chain Security Strategy; Counterfeiting Risk Orientation	H6, H7, H8, H9
Institutional Theory/OAT	Coercive and normative pressures driving compliance and technology integration.	Government Policies and Audits; Competitive Priority	H3, H10

delineates the alignment between the foundational theories, their underlying mechanisms, and the proposed hypotheses.

2.3. Conceptual Model and Hypotheses Development

In this section, we elaborate on the employed conceptual framework and outline the study’s hypotheses. Figure 1 presents an overview of the proposed model. The constructs are modeled using a reflective specification, as the indicators are considered manifestations of the underlying latent capabilities. To address potential redundancy in constructs exhibiting exceptionally high AVE and factor loadings, indicators were scrutinized to ensure they capture unique facets of organizational capabilities within the highly standardized Saudi food safety environment. While interrelated, the model’s primary antecedents include organizational digital adaptability, digital leadership, and competitive priority, which are conceptualized as distinct drivers of DI4T implementation. Specifically, digital leadership represents the strategic intent and vision-setting capacity that initiates and promotes technological change. Competitive priority defines the market-facing goal that guides the application of these technologies. Finally, organizational digital adaptability reflects the firm’s underlying structural and procedural capability to effectively execute the intended changes and reconfigure resources. Thus, the model distinguishes between the strategic intent (leadership), the market target (priority), and the execution capacity (adaptability) required for successful digital transformation.

2.3.1. Organizational Dynamic Digital Adaptability & Capability

Organizational dynamic digital adaptability and capability are crucial for the implementation of DI4Ts in FSCs as they improve organizational efficiency and decision-making [45,46]. Digital adaptability equips organizations to handle disruptions with greater agility and responsiveness, fostering resilience in fluctuating supply chains [47,48]. This relationship is driven by the reduction in structural inertia; adaptability enables firms to rapidly reconfigure internal resources to match external technological requirements, a core mechanism of dynamic capabilities [43]. Moreover, studies suggest that adaptability improves communication within supply chain networks and stimulates innovation, which is critical for DI4Ts’ implementation [49,50]. Additionally, growing consumer demand for sustainable products promotes eco-friendly practices, further accelerating the implementation of DI4Ts [51,52]. Researchers argued that dynamic digital adaptability and capability positively influence the implementation of DI4Ts in the supply chain [53]. Evidence from previous studies shows that organizations with advanced digital capabilities are better equipped to implement DI4Ts effectively within supply chains. Accordingly, the following hypothesis is proposed:

H1. 

Organizational dynamic digital adaptability and capability have a positive influence on the implementation of DI4Ts in food supply chains.

2.3.2. Digital Leadership

Leadership in digital innovation plays a critical role in integrating complex technologies, particularly within FSCs, which face significant challenges related to food safety, security, and operational efficiency [54,55]. Studies reveal that digital leadership drives organizational progress by fostering a culture of innovation that supports the implementation of DI4Ts [56,57]. Digital leaders facilitate this process by championing a data-driven culture, which reduces resistance to change and accelerates the assimilation of new digital tools [18]. Additionally, researchers highlight the importance of advanced technologies, such as IoT, big data analytics, and blockchain, in enhancing supply chain coordination, ultimately boosting resilience and performance [58,59]. Li et al. [60] contend that the digital leadership exhibited by middle managers is crucial and plays an influential role in fostering employee engagement and commitment, especially in the context of progressively digitalized workplace settings. Furthermore, the significance of leadership and knowledge-sharing competencies, as articulated in the research by Basit et al. [61], is essential for organizations to effectively manage the complexities of maintaining supply chain performance during crises. In the FSC context, effective digital leadership ensures seamless integration of innovative technologies, thereby reducing transaction costs and enhancing overall organizational efficiency [49,55]. Therefore, strong digital leadership is beneficial for DI4Ts implementation, which improves FSC sustainability and competitiveness. Based on these findings, the research posits that digital leadership significantly influences the successful implementation of DI4Ts in FSCs. Accordingly, the following hypothesis is proposed:

H2. 

Digital leadership has a positive influence on the implementation of DI4Ts in food supply chains.

2.3.3. Competitive Priority and Orientation

Competitive priority and orientation denote the strategic management choices and organizational focus directed towards utilizing advancements in supply chain management to improve corporate performance, adapt to market exigencies, and cultivate a competitive position within the industry. Competitive priority and orientation may steer organizational initiatives towards quality, adaptability, or reliability in delivery to secure and sustain a competitive advantage in the market [62]. Porter’s [63,64] competitive strategy paradigm underscores the notion that competitive orientation is realized through processes of differentiation and the provision of unique value propositions.

The investigation undertaken by Barney et al. [65] highlights the proposition that resources and capabilities, including organizational routines, knowledge, and cultural characteristics, pose significant obstacles for competitors to replicate them. In fact, competitive orientation enables organizations to integrate advanced technologies that have a crucial role in tracing and improving transparency in the supply chain [50,58,66]. In addition, researchers highlight that firms’ adoption of blockchain, IoT, and other technologies is influenced by their competitive advantage and normative pressure in the industry [67]. Furthermore, competitive orientation facilitates supply chain collaboration, which positively influences the implementation of DI4Ts [68,69].

Conversely, Carr [70,71] posited that information technology (IT) has the capacity to function as a strategic differentiator, thus redirecting the focus toward operational excellence and risk management in lieu of distinct or sustainable advantages. In a comparable context, Seddon [72] posits that although Enterprise Resource Planning (ERP) systems possess the capacity to augment an organization’s efficiency through the optimization of operations and the minimization of costs, they do not inherently confer upon firms a competitive advantage. Moreover, Porter [64] underscores that competitive priority is intrinsically linked to the concept of differentiation, which requires the establishment of a distinctive value proposition that sets an organization apart from its competitors. Specifically, in markets driven by compliance and security concerns, organizations may view technology as a survival necessity rather than a competitive differentiator [6]. Based on the above discussion, the following hypothesis is proposed:

H3. 

Competitive priority and orientation have a positive influence on the implementation of DI4Ts in food supply chains.

2.3.4. The Implementation of Digital Industry 4.0 Technologies in FSC and Operational and Resilience Performance

The implementation of Digital Industry 4.0 Technologies significantly influences FSC resilience and performance by enabling real-time monitoring to enhance efficiency. Previous research indicates that DI4Ts improve collaboration, decision-making, and cost efficiency, facilitating seamless communication between supply chain partners [68,73,74]. Operational performance, defined as the optimization of cost, quality, and adaptability [33], is directly enhanced by DI4Ts through improved visibility and responsiveness [75]. By enabling real-time data collection and automated analysis, DI4Ts function as a sensing mechanism that allows firms to reconfigure resources swiftly during disruptions [43]. Moreover, past studies have proved that the implementation of DI4Ts in FSCs enables organizations to predict market changes, design swift responses, and enhance resilience during disruptions [76,77]. Research further demonstrates that advanced technologies are indispensable for strengthening an organization’s ability to handle supply chain disruptions [58,78,79]. By addressing traditional barriers, DI4Ts not only enhance operational performance but also bolster organizational resilience [11,80]. Within the FSCs, digitalization supports the development of risk management strategies, strengthening resilience in the face of disruptions [76,81]. Consequently, when supported by adaptive organizational configurations, the deployment of DI4Ts within FSC operations is widely regarded as a key driver of enhanced resilience and operational performance. Accordingly, the following hypotheses are proposed:

H4. 

The implementation of DI4Ts in food supply chains has a positive influence on operational performance.

H5. 

The implementation of DI4Ts in food supply chains has a positive influence on resilience performance.

2.3.5. Supply Chain Security Strategies and Operational and Resilience Performance

Developing a robust supply chain security strategy is crucial for enhancing operational performance, as integrating advanced technologies enhances both visibility and performance within supply chains. In developing markets, where privacy and security concerns are prevalent [82], security strategies act as a foundational capability that ensures the integrity of data feeding into DI4T systems, thereby preventing decision errors during crises. In this context, Asamoah et al. [83] contended that a positive organizational security culture is a vital precursor that facilitates the implementation of effective supply chain security measures. Moreover, Saglam et al. [84] underscore the importance of cultivating a risk-aware culture and promoting collaboration with suppliers to improve risk mitigation strategies in Turkish firms. A well-embedded culture not only reduces risks but also supports the successful implementation of DI4Ts within supply chains. Similarly, Kusrini and Hanim’s [85] findings indicate that supply chain security strategy is crucial to protect supply chain assets and maintain operational efficiency.

A well-formulated supply chain security strategy also strengthens an organization’s ability to build resilience. Researchers posit that a strong supply chain security strategy enhances organizational capability to adapt and overcome the challenges of FSCs during disruptions such as food security and unforeseen environmental events [19,86]. Therefore, a well-formulated supply chain security strategy is an effective enabler that stabilizes operations, allowing the organization to maintain functionality despite external threats. Based on previous findings, it is assumed that strong supply chain security strategy significantly influences operational and resilience performance. Accordingly, the following hypotheses are proposed:

H6. 

Supply chain security strategy has a significant influence on operational performance.

H7. 

Supply chain security strategy has a significant influence on resilience performance.

2.3.6. Counterfeiting Risk Orientation and Operational and Resilience Performance

Counterfeiting and fraud in the food business is very prevalent, which requires proper mitigation strategies. Counterfeiting Risk Orientation (CRO) represents a proactive organizational stance towards identifying and mitigating illicit activities, which is critical in maintaining the integrity of global FSCs [87]. The implementation of DI4Ts enhances organizational capabilities of monitoring and data sharing, which improves operational performance. Research indicates that robust CRO improves the effectiveness of DI4Ts and ensures food integrity [88,89]. CRO plays a critical role in fostering resilience and mitigating supply chain threats posed by counterfeit products. In the context of the Saudi food sector, where import reliance is high, CRO serves as a necessary condition for DI4Ts to function effectively; without a strategic orientation towards risk, digital tools cannot effectively filter fraudulent data or products [4]. Based on the obtained evidence, it is assumed that strong CRO significantly influences operational and resilience performances. Accordingly, the following hypotheses are proposed:

H8. 

Counterfeiting risk orientation has a significant influence on operational performance.

H9. 

Counterfeiting risk orientation has a significant influence on resilience performance.

2.3.7. Moderating Effects of Government Policies and Audits on the Relationship Between Organizational Dynamic Digital Adaptability and the Implementation of DI4Ts in FSCs

Government interventions, through incentives, regulations, and support programs, can substantially improve an organization’s capacity to adapt to changing market dynamics and technological requirements [90]. This study conceptualizes ‘Government policies and audits’ as a critical environmental constraint within the OAT framework that forces internal structural change [91]. In line with Institutional Theory, such government interventions are particularly potent in emerging economies, as they create coercive pressures that compel firms to adopt new technologies not just for efficiency, but to secure legitimacy and maintain their social license to operate. Moreover, government audits ensure a mechanism within organizations that facilitates the process of technology adoption. In general, government policies facilitate a proactive stance among organizations, enabling them to not only adapt but also excel in a progressively digital marketplace [92]. Based on previous findings, it is assumed that government policies and audits can enhance an organization’s adaptability, thereby facilitating the implementation of DI4Ts. Accordingly, the following hypothesis is proposed:

H10. 

Government policies and audits significantly moderate the relationship between organizational dynamic digital adaptability and the implementation of DI4Ts in food supply chains.

3. Research Methodology

This study investigated the key factors driving the implementation of Digital Industry 4.0 Technologies within food enterprises in Saudi Arabia. In fact, Saudi Arabia is leading a substantial digital transformation agenda, characterized by ambitious initiatives outlined in its Vision 2030 framework. This vision seeks to diversify the economy and establish Saudi Arabia as a leader in technological innovation in the region.

The research adopted a quantitative methodology, employing a cross-sectional survey design. The survey targeted decision-making managers within Saudi food enterprises, as they yield essential insights into diverse organizational dimensions and phenomena. Managers were recruited through professional networks, referrals, direct communication, and food industry databases in Saudi Arabia, using customized messaging that highlighted the study’s significance to enhance engagement.

The required sample size was calculated utilizing G*Power version 3, a widely preferred tool for power analysis in business and social science research [93,94]. Based on the prevalent guidelines for social and business science research [95], with an effect size of 0.15, α set at 0.05, and power at 0.80, G*Power calculated that the minimum sample size necessary for the proposed model was 170. Moreover, with a power specification of 0.95, G*Power calculated that the minimum sample size necessary for the simple model was 472.

A convenience sampling method was employed to select an initial pool of 500 managers from Saudi food manufacturing, wholesaling, distribution, and logistics firms. It is worth noting that, despite the limitations of convenience sampling such as potential sampling bias and skew toward accessible logistics firms, this method is widely adopted in social research and is particularly recommended for exploratory studies [96,97]. Importantly, this skew toward digitally mature logistics and distribution firms, representing 72.8% of the final sample, acted as a de facto control variable that homogenizes the variance related to subsector differences and digital maturity levels that might otherwise confound the results. To mitigate risks associated with this sampling approach, we increased participation rates through multiple data collection channels, targeted diverse managerial levels, and ensured data quality by implementing confidentiality measures to encourage honest responses. While cluster sampling was considered, it was ultimately decided not to employ this method. The rationale for this decision was twofold: first, cluster sampling would have required a more complex sampling frame to effectively identify and stratify the diverse categories of food enterprises [98]. Given the time constraints and logistical challenges inherent in identifying and accessing these clusters, we opted for convenience sampling, which allowed for a more straightforward and timely collection of data.

Data collection for the study was conducted through an online questionnaire shared via email, internal corporate channels, industry-specific forums, and social media platforms, including WhatsApp and LinkedIn. The survey was designed to collect relevant demographic information and evaluate the specified constructs. To ensure its reliability and validity, we conducted a pilot test involving 30 participants, which helped identify potential concerns regarding question clarity, response options, and overall survey structure. Cronbach’s alpha results further confirmed a high degree of internal consistency.

The initial data collection phase commenced on 10 August 2024, and concluded on 20 September 2024. We initially received 220 responses, issuing several reminders to encourage voluntary completion. Because certain items were not mandatory, some respondents chose not to answer all questions. We intentionally allowed non-obligatory items to capture a broader range of perspectives, even if not all responses were fully detailed. Subsequently, we excluded submissions with any missing data to maintain high-quality findings and arrived at 191 complete managerial responses. To mitigate the impact of Common Method Variance (CMV) in the design of surveys, we implemented a range of critical strategies. First, we ensured the anonymity of participants to encourage honest responses. Secondly, clear instructions were provided to ensure that participants fully understood each question within its specific context. The integration of these measures aimed to enhance the reliability and validity of the survey findings, thus yielding more accurate insights into the research topic.

Survey Instruments

Measurement scales for all constructs were derived from well-established academic sources to maintain methodological rigor and contextual relevance [99]. Specifically, four items each were utilized to evaluate ‘Organizational Dynamic Digital Adaptability & Capability’ and ‘Digital Leadership,’ adapted from Liu et al. [100] and Kusuma et al. [101], respectively. ‘Competitive Priority’ was measured using three items informed by Pozzi et al. [102] and Kusuma et al. [101]. Similarly, three items assessing ‘Government Policies & Audits’ were sourced from Dubey et al. [2] and Kumar et al. [77], treating regulatory compliance and financial incentives as a composite measure of institutional support. The construct ‘Implementation of Digital Industry 4.0 Technologies’ employed three items adapted from Tortorella et al. [103], Queiroz et al. [14] and Ivanov et al. [104]. Metrics for ‘Operational Performance’ and ‘Resilience Performance’ were based on Koçoğlu et al. [105] and Dubey et al. [2], along with Brandon-Jones et al. [106], respectively. Lastly, ‘Supply Chain Security Strategy’ and ‘Counterfeiting Risk Orientation’ were measured with three items each, drawing from Whipple et al. [107] and Kros et al. [108]. Constructs were assessed on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree), with additional details provided in Appendix A.

4. Results

4.1. Demographic Information

The demographic profile provides critical insights regarding the participant sample involved in this investigation. As illustrated in

Table 2. Demographic Profile.

Variables	Categories	Frequency	Percent	Valid Percent	Cumulative Percent
Gender	Male	124	64.9	64.9	64.9
	Female	67	35.1	35.1	100.0
Education	Diploma	25	13.1	13.1	13.1
	Bachelor’s Degree	39	20.4	20.4	33.5
	Master	75	39.3	39.3	72.8
	Doctorate	30	15.7	15.7	88.5
	Other	22	11.5	11.5	100.0
Role/Position	IT manager	21	11.0	11.0	11.0
	Supply chain project manager	35	18.3	18.3	29.3
	Operation manager	82	42.9	42.9	72.3
	manager/Director	32	16.8	16.8	89.0
	Supply chain analyst	21	11.0	11.0	100.0
Years of experience	2–4 years	50	26.17	26.17	26.17
	4–5 years	74	38.74	38.74	64.92
	6–10 years	47	24.60	24.60	89.52
	11–15 years	20	10.47	10.47	100
Scope	Manufacturing	17	8.9	8.9	8.9
	Grocery/food service retailer	35	18.3	18.3	27.2
	Food wholesalers/distributor/Logistics	139	72.8	72.8	100.0
Industry 4.0 technologies and solutions	Cloud computing	18	9.4	9.4	9.4
	Cybersecurity	29	15.2	15.2	24.6
	Smart devices and Internet of Things	88	46.1	46.1	70.7
	Big data analytics	40	20.9	20.9	91.6
	Digital twins	16	8.4	8.4	100.0

, the distribution of gender was markedly skewed towards males, with male participants comprising 64.9% of the total respondents, while females accounted for 35.1%.

Among the participants, 39.3% held a master’s degree and 15.7% held a doctorate, reflecting a highly educated sample. The roles represented reveal a diverse managerial landscape, with operation managers making up 42.9% and supply chain project managers at 18.3%, suggesting a pronounced focus on operational efficiency in the industry. The years of experience among respondents are varied, with a notable percentage (38.74%) having 4–5 years of experience, thereby emphasizing the presence of a relatively youthful workforce. A predominant majority are involved in food wholesaling, distribution, and logistics (72.8%), reflecting a significant concentration on supply chain dynamics within the sector. Finally, a considerable fraction of respondents reported the use of Industry 4.0 technologies, with smart devices and Internet of Things accounting for 46.1% of reported usage. Reflecting significant engagement with digital transformation, the demographic data points to the participants’ qualifications and professional experience, while providing a solid basis for analyzing advancements in modern technologies within the supply chain sector.

4.2. Measurement Model Assessment

Partial Least Squares Structural Equation Modeling was employed to evaluate the constructs’ validity and reliability. This approach included assessments of convergent validity, discriminant validity, and reliability. Convergent validity was examined using factor loadings above 0.70, average variance extracted (AVE) values greater than 0.50, and reliability indices such as Cronbach’s alpha and composite reliability, which are expected to exceed the 0.70 benchmark [109,110]. These criteria confirm the constructs’ internal consistency and robustness, strengthening the reliability of the measurement model. Convergent validity ensures that all items measure the same construct effectively [111]. As per Hair et al. [109], outer loadings above 0.7 are adequate for establishing convergent validity, a threshold met by all items in this dataset. However, we acknowledge the exceptionally high AVE values for constructs such as Resilience Performance (>0.90), which, while statistically robust, may reflect the high degree of protocol standardization among Saudi food safety managers. Additionally, Table 2 shows that all factor loadings exceed the 0.70 threshold, while AVE values meet the minimum requirement of 0.50 [99].

Together, these findings demonstrate the model’s robustness and support the credibility of the analysis. Moreover, consistent with [112] PLS-SEM evaluation methodologies, we assessed Common Method Variance (CMV) utilizing the variance inflation factor (VIF). The findings, with values spanning from 1.294 to 2.974, are below the 3.3 threshold, signifying that CMV is not a pervasive artifact in the data, though we acknowledge the inherent limitations of single-source self-reported surveys, as demonstrated in

Table 3. Convergent validity and reliability metrics.

Construct	Items	Factor Loadings >0.7	VIF	Cronbach’s Alpha (CA) >0.7	Composite Reliability (CR) >0.7	Average Variance Extracted (AVE) >0.5
Organizational Dynamic Digital Adaptability & Capability (ODC)	ODC1	0.858	2.411	0.917	0.918	0.801
	ODC2	0.926	2.354
	ODC3	0.881	2.851
	ODC4	0.913	2.184
Digital Leadership (DLE)	DLE1	0.950	2.950	0.890	0.909	0.820
	DLE2	0.901	2.974
	DLE3	0.863	2.229
Competitive priority (CMP)	CMP1	0.800	1.451	0.803	0.815	0.718
	CMP2	0.846	2.064
	CMP3	0.894	2.204
Government policies & audits (GOV)	GOV1	0.933	2.384	0.951	0.952	0.873
	GOV2	0.947	2.483
	GOV3	0.925	2.021
	GOV4	0.931	2.518
Implementation of digital industry 4.0 technologies (IMP)	IMP1	0.933	0.933	0.939	0.940	0.891
	IMP2	0.943	0.943
	IMP3	0.957	0.957
Operational performance (OPP).	OPP1	0.866	1.980	0.866	0.872	0.788
	OPP2	0.918	2.811
	OPP3	0.879	2.368
Resilience performance (RPF)	RPF1	0.965	2.522	0.962	0.962	0.929
	RPF2	0.968	2.219
	RPF3	0.958	2.695
Supply chain security strategy (SEC)	SEC1	0.942	1.697	0.938	0.940	0.890
	SEC2	0.959	1.636
	SEC3	0.929	1.407
Counterfeiting Risk Orientation (COR)	COR1	0.845	2.214	0.755	0.763	0.678
	COR2	0.906	2.578
	COR3	0.706	1.294

.

4.3. Discriminant Validity Assessment

Discriminant validity was thoroughly evaluated to confirm that each construct uniquely measures its intended concept. This research employed the heterotrait–monotrait ratio of correlations (HTMT) to assess discriminant validity [110]. The HTMT criterion functions as a substantial alternative to the traditional Fornell-Larcker criterion [111]. We utilized HTMT to evaluate the interrelations among constructs to determine their distinctiveness and unidimensionality. According to the extant literature, an HTMT value of 0.85 or less denotes sufficient discriminant validity, signifying that the constructs are empirically distinct [110]. This research analyzed HTMT values to validate the distinct representation of each construct, thereby reinforcing the validity of the research outcomes. The utilization of HTMT provides a more rigorous assessment of discriminant validity, consequently augmenting confidence in the study’s conclusions.

Table 4. Discriminant Validity using heterotrait–monotrait ratio of correlations (HTMT).

	CMP	COR	DLE	GOV	IMP	ODC	OPP	RPF	SEC
CMP
COR	0.442
DLE	0.755	0.637
GOV	0.587	0.458	0.738
IMP	0.540	0.502	0.668	0.827
ODC	0.415	0.411	0.437	0.545	0.631
OPP	0.630	0.755	0.749	0.776	0.722	0.595
RPF	0.618	0.515	0.698	0.687	0.785	0.705	0.771
SEC	0.539	0.482	0.702	0.779	0.832	0.540	0.793	0.807

presents the HTMT results for this study. The HTMT results validate the distinctiveness of the constructs, as each construct exhibits an HTMT value with respect to other constructs that is less than or equal to 0.85.

4.4. Model Fitness

The results derived from the model fit evaluation elucidate the resilience of the proposed conceptual framework. Model adequacy was assessed using the Standardized Root Mean Square Residual (SRMR), a key metric in structural equation modeling. The current study recorded an SRMR value of 0.075. Hu & Bentler [113] propose that SRMR values near 0.08 signify an acceptable correspondence between the model and the observed data. The SRMR value of 0.075 indicates a satisfactory fit for our model, wherein the differences between the predicted and observed correlations are relatively negligible. Moreover, findings indicated that the independent variables collectively explained 62.7% of the variance in the implementation of DI4Ts. Cohen [114] established criteria for the interpretation of R² in which R² values that are approximately 0.01 are deemed small, around 0.09 are regarded as medium, and approximately 0.25 or higher are classified as large. Consequently, an R² of 0.679 signifies considerable explanatory power, indicating that the independent variables significantly affect the implementation of DI4Ts. Additionally, the combined effects of IMP, SEC, and COR explained 64.4% of the variance in OPP and 72.6% in RPF. These findings, summarized in

Table 5. Model Fit results.

	R-Square (R2)	Standardized Root Mean Square Residual (SRMR)—Estimated Model
Implementation of DI4Ts in food supply chain (IMP).	0.679	0.075
Operational performance (OPP)	0.644
Resilience performance (RPF).	0.726

, validate the model’s predictive strength and its capacity to capture a large proportion of the factors influencing the implementation of DI4Ts in FSCs.

4.5. Structural Model Assessment

This study applied the bootstrapping method to evaluate the parameters of the structural model and explore the interrelations among the constructs. Bootstrapping, a widely used resampling technique, aids in assessing the robustness and dependability of parameter estimates derived from model analysis [109]. The analysis employed a 5% significance level, corresponding to a 95% confidence interval. To establish statistical significance, p-values were required to remain below 0.05, while t-values needed to exceed 1.96, signifying the strength of the relationships between the variables.

Table 6. Direct and moderating effects with hypotheses validations.

Hypotheses	Direct/Indirect Path	Beta Value (β)	t-Value	p Value	Hypothesis Validation
H1	ODC → IMP	0.261	5.059	<0.001	Supported
H2	DLE → IMP	0.125	2.056	0.040	Supported
H3	CMP → IMP	0.003	0.045	0.964	Not supported
H4	IMP → OPP	0.140	2.063	0.039	Supported
H5	IMP → RPF	0.219	3.536	<0.001	Supported
H6	SEC → OPP	0.459	6.094	<0.001	Supported
H7	SEC → RPF	0.629	10.569	<0.001	Supported
H8	COR → OPP	0.365	7.219	<0.001	Supported
H9	COR → RPF	0.087	2.052	0.040	Supported
H10	GOV × ODC → IMP	0.076	2.633	0.008	Supported

Note: CMP = Competitive priority; COR = Counterfeiting Risk Orientation; DLE = Digital Leadership; GOV = Government policies & audits; IMP = Implementation of DI4Ts; ODC = Organizational Dynamic Digital Adaptability & Capability; OPP = Operational performance; RPF = Resilience performance; SEC = Supply chain security strategy.

outlines the hypothesis testing results, whereas Figure 2 illustrates the structural equation model.

The results confirm that H1 establishes a significant positive relationship between ODC and the implementation of DI4Ts (β = 0.261, t = 5.059, p < 0.001). Likewise, H2 reveals that DLE positively influences IMP (β = 0.125, t = 2.056, p = 0.040). Conversely, H3 indicates that CMP does not have a notable effect on IMP (β = 0.003, t = 0.045, p = 0.964). On the other hand, the implementation of DI4Ts significantly enhances both operational performance (H4: β = 0.140, t = 2.063, p = 0.039) and resilience performance (H5: β = 0.219, t = 3.536, p < 0.001). Notably, Supply Chain Security Strategy emerged as the most dominant driver of resilience, exhibiting a substantially stronger influence than technology implementation alone (H6: β = 0.459, t = 6.094, p < 0.001); H8: β = 0.365, t = 7.219, p < 0.001; and resilience performance (H7: β = 0.629, t = 10.569, p < 0.001; H9: β = 0.087, t = 2.052, p = 0.040). The absence of multicollinearity was verified, as indicated by all variance inflation factor values being below 3.3 [115,116]. Finally, hypothesis H10, which examines the influence of government policies on the relationship between adaptability and the implementation of DI4Ts, appears to be statistically significant. The values (β = 0.076, t = 2.633, p = 0.008) substantiate this significant effect.

5. Discussion

This research highlights the significant relationship between organizational adaptability and dynamic digital capabilities, underlining their critical importance in successfully adopting Industry 4.0. Specifically, this study found that adaptability is a critical enabler for effective DI4Ts adoption, supporting OAT’s core premise that successful adaptation arises from an organization’s ability to align internal structures with external technological and environmental shifts. Our finding aligns with prior research [68,69] that emphasizes the imperative for organizations to develop dynamic capabilities to adeptly address the rapid demands of the digital environment.

While competitive orientation has been traditionally regarded as a key driver for technological adoption, this research suggests that Competitive Priority does not serve as a significant predictor of DI4Ts implementation in FSCs. This counterintuitive finding can be explained by the specific institutional context of the Saudi food sector. In a market heavily driven by national food security mandates and strict import regulations, technology adoption often functions as compliance and a baseline requirement for institutional legitimacy rather than a discretionary tool for competitive differentiation. Furthermore, consistent with the negative aspects of data-driven culture identified by Ayoub and Sopuru [6], the resource intensity required for strict regulatory compliance may constrain the strategic flexibility typically associated with competitive priority, forcing firms to prioritize stability over differentiation. Consequently, in highly regulated environments, the theoretical distinction between competitive priority and regulatory compliance becomes blurred, potentially leading to construct overlap where managers view adaptability through the lens of mandatory operational standardization driven by the pressures imposed by the Saudi Food and Drug Authority.

The study found that supportive governmental policies, encompassing financial incentives for digital transformation, can incentivize enterprises to allocate resources towards transformative technological advancements. Such external policy efforts validate the OAT concept of environmental pressure acting as a catalyst for internal structural change. The modest effect size of this moderation suggests that while government policies act as enablers, the ultimate success of implementation remains contingent on the firm’s internal dynamic capabilities. In developing economies like Egypt and Saudi Arabia, government support systems are not merely helpful but are essential structural antecedents for building absorptive capacity [91]. Consistent with Li et al. [60], our results underscore the significance of digital leadership in the adoption of DI4Ts and supply chain optimization. Digital leaders foster an innovative ecosystem through strategic investment in digital skills development, facilitating experimentation, and promoting knowledge-sharing culture. This is particularly pertinent in the Saudi context, where the Human Capability Development Program necessitates that leaders actively bridge the gap between local labor market skills and the advanced technical demands of Industry 4.0.

Finally, a critical finding of this study is that Supply Chain Security Strategy and CRO exerted a stronger influence on performance than DI4T implementation itself. In line with OAT, this suggests that organizations must continually recalibrate their processes in response to security threats for the sake of achieving sustained resilience. Given Saudi Arabia’s extensive reliance on food imports, the integrity of the supply chain is paramount; digital tools are effective only when underpinned by a robust security culture capable of managing the risks associated with global logistics, product authenticity, and the preservation of Halal integrity [4]. It is also important to acknowledge the potential for reciprocal causality. While this study models adaptability and security as drivers of DI4T adoption and performance, it is plausible that more resilient organizations are better positioned to successfully implement complex digital technologies, creating a virtuous cycle.

5.1. Theoretical Implication

This study represents a comprehensive refinement of OAT and DCV by demonstrating that in emerging, import-reliant economies, external institutional and environmental pressures exert a more decisive moderating influence on digital adaptation than internal strategic orientations. By integrating empirical evidence from Saudi Arabia’s food sector, the research validates the applicability of OAT in non-Western contexts, demonstrating that regulatory alignment is a structural prerequisite for digital transformation. Furthermore, this study identifies ‘Supply Chain Security’ and ‘Counterfeiting Risk Orientation’ as specific adaptive mechanisms through which organizations absorb environmental shocks, extending the theory beyond generic capabilities. Finally, in contrast to static models, OAT elucidates how organizations actively modify their strategies, structures, and cultures to leverage digital opportunities and mitigate related risks.

5.2. Practical and Societal Implications

The findings of this research present meaningful implications for stakeholders tasked with implementing Industry 4.0 technologies in FSCs. Specifically, for Saudi food enterprises, the non-significance of competitive priority suggests that digital adoption should be framed around ‘license to operate’ and regulatory compliance. Organizations are recommended to focus on building a robust framework for digital leadership that aligns internal capabilities with national mandates, such as the Saudi Food and Drug Authority’s track-and-trace requirements [117]. For policymakers, the strong moderating role of government policies indicates that financial incentives alone are insufficient; establishing supportive regulatory frameworks and instituting routine evaluations are critical for achieving successful outcomes [118]. In bridging theory and practice, this study’s empirical evidence underscores how OAT-based strategies can effectively translate into concrete steps for digital transformation across diverse market conditions.

Furthermore, given that supply chain security was found to be a stronger driver of performance than technology itself, managers must prioritize security as a foundational capability. The implementation of cybersecurity measures and protocols can enhance traceability and reduce the risks associated with cyberattacks. Investments in advanced analytics must be paired with robust physical and digital security protocols to prevent the downsides of data vulnerability [6].

Finally, the incorporation of DI4Ts within the FSC presents substantial opportunities for enhancing national food security. This study elucidates that augmented operational efficacy driven by security and adaptability can bolster product integrity, specifically Halal certification compliance, and consumer safety. As policymakers and industry stakeholders engage in collaborative efforts to formulate conducive structures for the proliferation of DI4Ts, the broader community stands to gain from a more robust and secure FSC. This aligns with Saudi Vision 2030’s goal of ensuring food security in an arid environment through technological innovation [119].

5.3. Limitations and Future Research Directions

Despite its notable theoretical and managerial implications, the study is prone to certain limitations which may be addressed in subsequent research endeavors. Convenience sampling can produce biased outcomes because it depends on easily accessible participants. Specifically, the sample was skewed toward logistics and distribution firms (72.8%) and digitally mature organizations, potentially limiting the generalizability of findings to upstream food producers or smaller enterprises with lower digital readiness, and possibly inflating the observed success rates of DI4T implementation due to the exclusion of less digitally mature firms. Future research should utilize cluster sampling to enhance representativeness and ensure diverse sample characteristics. The cohort comprising 191 managers from food enterprises in Saudi Arabia may not adequately encapsulate the region’s heterogeneity. The unique socio-economic, cultural, and regulatory landscapes of other GCC member states can significantly influence the deployment of DI4Ts. Therefore, further scholarly inquiry is necessitated to enhance our understanding of regional significance.

Methodologically, the primary limitation of our cross-sectional investigation resides in its ability to definitively ascertain causal relationships. While this study positions adaptability and security as drivers of performance, it is plausible that high-performing, resilient firms are simply more capable of adopting DI4Ts, suggesting potential reverse causality. Future research could benefit from employing longitudinal investigations to track the sequence of occurrences. Furthermore, while CMV was assessed using VIF < 3.3, the lack of a marker variable means that CMV cannot be fully ruled out. The exceptionally high factor loadings and AVE values in constructs like Resilience Performance suggest potential item redundancy; however, this reflective specification is justified by the high degree of protocol standardization and uniform safety mandates among Saudi food managers, in turn tightening indicator variance.

Regarding measurement, all performance outcomes were perceptual; future studies should incorporate objective operational metrics such as lead time reduction and waste reduction, to validate these findings. While statistical controls for firm size or sub-sector were not explicitly modeled, the significant homogeneity of the convenience sample serves as a contextual boundary that stabilizes sub-sector variance. Future studies should nonetheless incorporate these as formal controls to expand generalizability. Finally, the ‘Government policies’ construct aggregated incentives, regulation, and monitoring; future research should disentangle these dimensions to isolate their specific theoretical effects.

More importantly, future research might examine the implementation of digital Industry 4.0 technologies by integrating organizational adaptation theory and other frameworks, such as the Technology-Organization-Environment (TOE) framework, to examine the impact of contextual determinants like technology characteristics, social factors and leadership styles.

6. Conclusions

This research refines the application of OAT and DCV by examining the approaches Saudi food companies use to adopt DI4Ts, the types of Industry 4.0 solutions integrated into their operations, and the factors influencing successful implementation. The results demonstrate that organizations with high adaptability effectively translate strategic intent into operational DI4T implementation. Moreover, the study showed that adaptability improves the capability of responding swiftly to fluctuations in demand and supply, thus enabling operational continuity and resilience. As such, it refines OAT by framing supply chain security not merely as an operational strategy but as a core adaptive mechanism essential for resilience in import-reliant economies. Additionally, digital leadership was found to be an effective driving force for DI4T adoption in FSCs. Government policies and audits are the structural door openers to implementing DI4Ts in FSC and logistics by facilitating compliance, traceability, and operation resilience.

This study challenges the techno-centric view of resilience by demonstrating that Supply Chain Security Strategy and CRO are stronger drivers of performance than technology adoption alone. In the Saudi context, characterized by high regulatory pressure and SFDA oversight, digital tools function effectively only when underpinned by robust security protocols. The research offers significant insights for enterprises, policymakers, and researchers aiming to address the intricacies of digital transformation within the FSC. By articulating how DI4Ts interact with security strategies to contribute to absorptive, adaptive, and restorative capacities, the study also offers a framework for enhancing supply chain robustness against both predictable and emergent threats in developing economies.