The Role of Strategic Partnerships and Digital Transformation in Enhancing Supply Chain Agility and Performance

Abstract

In times of disruption, a company’s ability to manage its supply chain effectively can determine its success or failure. This paper explores the extent to which strategic partnership development, mediated by digital transformation, enhances supply chain effectiveness during such periods. A mixed methods approach was used, involving surveys and interviews with professionals from the Saudi Arabian manufacturing sector. The study’s findings reveal that digital transformation and strategic partnerships work synergistically together to enhance supply chain resilience and effectiveness, resulting in improved operational agility and adaptability. Four key enablers of supply chain digital transformation were identified: inter-business coordination, leadership, technological culture, and recruitment management. These insights contribute significantly to our understanding of how businesses can build resilient supply chains in uncertain environments.

1. Introduction

Since the start of the ‘digital era’ the business environment has become increasingly volatile. While digitization offers businesses many benefits, including increased efficiency, innovation, and global reach, it also introduces complexities and challenges that can make business success, and even survival, considerably more difficult. In order to compete effectively, companies must navigate issues such as rapid technological change, cybersecurity threats, complex decision-making, and shifting consumer expectations, all of which can lead to instability and uncertainty.

In fact, the rise of digitalization has profoundly transformed global business landscapes, introducing both unprecedented opportunities and significant challenges. While other factors such as globalization have historically been viewed as key contributors to uncertainty, digitalization, by contrast, introduces unique complexities that are critical in contemporary business environments [1,2]. Digitalization affects every facet of organizational operations, often leading to rapid technological shifts, evolving consumer behaviors, and new cybersecurity risks. These effects create an inherently unstable environment, where companies must constantly adapt their processes, technologies, and customer engagement strategies. These issues lead to unpredictability, not only in regard to technological adoption, but also in terms of supply chain management, customer expectations, and regulatory compliance [3].

Therefore, prioritizing digitalization as a source of uncertainty sharpens the focus of this paper, by ensuring that it aligns with the current, fast-evolving technological landscape, where businesses must respond swiftly to remain competitive. As this paper examines how digital transformation mediates the effects of strategic partnerships on supply chain agility and adaptability, it becomes clear that the volatility caused by digital transformation plays a more immediate and operational role in shaping modern supply chains than more traditional macroeconomic forces, like globalization.

At this point, it is important to note that, although there are some superficial similarities between the concepts of business agility and adaptability, there are also some key differences. Business agility refers to an organization’s ability to adapt rapidly, in near real-time, to changes in market conditions, with minimal disruption. Business adaptability, on the other hand, while also involving the ability to change, is a longer-term concept, involving the capacity of a company to adjust its strategies, operations, and structures in the face of evolving external conditions, such as economic shifts, technological advancements, and market demand [4].

The increasing volatility of the business context and the power of unexpected events to disrupt supply chains and cause severe operational problems was well-illustrated during the COVID-19 pandemic [5,6,7], which highlighted the fragility of global supply chains and accelerated the need for businesses to adopt digital transformation strategies. By understanding how companies responded to these challenges, we can better appreciate the role of strategic partnerships and digital tools in maintaining supply chain resilience during crises [8,9]. However, while the COVID-19 pandemic had a devastating effect on many organizations, it served to highlight some of the essential requirements for building agility and adaptability and, in particular, the importance of businesses’ networking capability and collaborative inter-organization relationships [7,10,11,12]. Although it is widely recognized that such relationships are generally significant and a ‘good thing’ [13,14,15], there remains a lack of clarity concerning the precise benefits of strategic partnership development competency (SPDC) in the context of increasing business instability.

In order to understand the operational and strategic benefits of SPDC, it is useful to look more closely at its structure. In fact, three distinct but related components of SPDC have been identified so far, namely business coordination, communication, and relationship development [14,16,17]. Together, these components provide organizations with a means of improving their ability to improve several important operational issues, such as working with limited resources, maintaining financial growth, and remaining competitive [18,19]. While business relationships and partnerships often form organically, over time, as a natural result of doing business [18,20,21], it is not clear how alliances can be deliberately and specifically developed in order to strengthen supply chains in periods of volatility [19,22,23]. This is a significant question, as flexible, resilient, and secure supply chains are often key to business success. Until now, however, although there exists considerable research on the development and implementation of business collaboration and partnerships, there have been very few studies that provide insights on how to leverage business relationships to ensure the resilience and effectiveness of supply chains during periods of heightened uncertainty [20,22,24]. This study aims to enhance our understanding of the role of business partnerships during a crisis, particularly in optimizing both supply chain capabilities and overall business performance [22,23]. In doing so, the study addresses the following two key questions:

RQ1: What is the impact of SPDC on logistical and supply chain agility (LSCA) and adaptability (LSCAD) when mediated by digital transformation (DT)?

RQ2: What is the impact of SPDC on business performance (BP) when mediated by digital transformation (DT)?

By answering these RQs, this study will provide evidence-based insights into the role of SPDC in the development of key competencies and strengths that enable a business to dynamically adjust its logistical systems to new situations. This contributes to the literature by explaining how organizations can quickly adapt in crisis conditions and maintain operational effectiveness.

Another important issue this paper explores is the role of digital transformation (DT) in building responsive logistical and supply chain infrastructures [25,26]. Before discussing this question further, it is important to be clear on what is meant by DT. While the many working definitions of DT may differ in regard to the detail, there is a consensus that, in a business context, the term refers to the rethinking of business models, processes, and other aspects of organizational infrastructure to leverage digital tools, data, and innovation to drive efficiency, growth, and competitiveness [27]. Effectively, DT involves the integration of digital technologies into all areas of a business, in order to fundamentally change how the business operates and delivers value to customers [25,26,28]. Many advanced and emerging technologies can contribute to the process of DT within an organization, including AI, IoT (the Internet of Things), and machine learning [26,29,30], and the transition in regard to the use of these technologies has often proved itself to be beneficial [29,31,32]. However, in a significant number of cases where supply chain improvement was the aim, DT has not ‘lived up to its promise’ [33,34], which implies a need to better understand the ways in which DT impacts the supply chain and business outcomes [35,36,37].

In order to explore these questions, it is important to note that DT can act either as a mediator between two variables or interact with them. In the first case (mediator), DT would serve as an intermediary, or bridge, between two variables, helping to explain the connection between them [38,39,40]. In contrast, an interactive effect means that DT alters the strength or direction of the relationship between the variables [33,34]. In the context of this study, DT is more likely to play a mediating role in the relationship between SPDC, logistical flexibility, and business performance (BP), although the precise nature and extent of this mediating effect is unclear. RQ2, in this study, is intended to clarify the issue.

The remaining sections in this paper are organized as follows. First, the theoretical basis of the paper is discussed and the research hypotheses are presented. The research methodology is then described. The next section presents the analysis of the quantitative (survey) and qualitative (interview) data, and the results of the hypothesis testing. This is followed by the findings and implications for theory and practice, as well as the limitations of the study and possible directions for future research. The final section outlines the study’s conclusions, which reveal the complex relationship between the various aspects of dynamic competency, BP, and DT.

2. Literature Review

2.1. Dynamic Logistical and Supply Chain Competencies

Unlike static competencies, which focus on existing strengths, the concept of dynamic competencies (DCs) refers to the capacity for innovation, adaptation, and continuous improvement, which enables businesses to maintain a competitive advantage in the face of uncertainty and change [41,42]. Based on this concept, the Dynamic Competencies View (DCV) is a theoretical framework used in strategic management to understand how organizations develop, adapt, and reconfigure internal and external competencies to address rapidly changing environments [43,44]. This extends the traditional Resource-Based View (RBV), by focusing on how firms can maintain a competitive advantage in dynamic markets and offers several significant benefits to businesses in today’s rapidly changing, digitally oriented environment, such as enhanced adaptability, improved resilience, better resource management, lower risk, and greater customer alignment [42,43].

The DCV framework is based on three principal factors [45,46]. One of these factors is the supply chain’s ability to detect and identify changes, trends, and disruptions in the external environment. Often called ‘market sensing’ [47,48], this ability involves monitoring both internal and external factors, such as market conditions, customer demand, technological advancements, and supplier performance, which can impact the supply chain’s efficiency and effectiveness. This competency allows the organization to develop and implement appropriate risk mitigation strategies [49,50]. Another key component of the DCV framework is the competency of continuous renewal [45,48], which refers to the ongoing process of evaluating and updating organizational processes to ensure that they remain effective and relevant. In some cases, when incremental changes are not sufficient, the organization should have the ability to implement more holistic transformation, which could include adopting new technologies, restructuring the organization, or revising business models to better meet strategic goals [46,49].

The third basic element of the DCV is an organization’s ability to effectively capture opportunities that have been identified through its market sensing capabilities, described above. Known as ‘seizing’ [43,47], this capability involves rapid and effective decision-making, coupled with appropriate resource allocation, in order to exploit an opportunity or mitigate a threat. For example, if a company senses a growing demand for a specific type of product, seizing that opportunity might involve the rapid development of a new product line that meets relevant standards, the reconfiguration of the supply chain to source necessary materials, or the development of a marketing campaign to target potential purchasers.

However, while our understanding of the structure and implementation of the DCV has benefited from the results from a variety of studies, this understanding remains limited by a number of ambiguities in the conceptualization of dynamic competencies and the nature of their relationship with BP [41,43,45,48].

2.2. Strategic Partnership Development Competency (SPDC)

SPDC, in a business context, is an organization’s ability to effectively establish, manage, and sustain strategic partnerships or alliances with other companies, institutions, or stakeholders. This typically involves coordinating and combining the strengths and resources of the concerned parties to achieve mutual goals and generate value in a synergistic way, i.e., a way that would be difficult or impossible to accomplish as independent parties [51,52,53].

SPDC can be considered to be a meta-level competitive advantage, i.e., an overarching, systemic capability that, unlike advantages tied to specific products, technologies, or market positions, is rooted in the organization’s ability to innovate, adapt, and evolve its strategies and operations in response to changing environments [54,55]. A competency that usually develops over time, SPDC is considered valuable, as it can deliver a range of significant business benefits, including enhanced innovation, market expansion possibilities, cost efficiency, risk mitigation, and better resource utilization. However, it is also a competency that can be difficult to grow, as it usually involves building a comprehensive set of skills, processes, and structures that enable the organization to effectively establish, manage, and sustain strategic partnerships [56,57].

2.3. Digital Transformation (DT)

The definition of DT was discussed briefly in the introduction to this paper. Expanding on this definition slightly, DT can be considered as the comprehensive integration of digital technologies into all areas of an organization/business, in a way that radically changes how it operates and delivers value to customers. It is important to note that DT involves not just the adoption of new technologies, but also an internal cultural shift that fosters continuous innovation and business agility, together with the re-evaluation of traditional business practices to improve efficiency, the customer journey, and the overall business performance [39,58,59].

In the context of supply chains, DT refers to the integration of advanced digital technologies and practices into supply chain operations to enhance its efficiency, visibility, agility, and general performance. Such transformation leverages advances in technologies, such as data analytics, cloud computing, the Internet of Things (IoT), artificial intelligence (AI), machine learning, and blockchain (see Section 2.3.1), to modernize and streamline supply chain processes [60,61]. The benefits of DT, which can be highly significant and often transformative, include increased efficiency, enhanced visibility, improved agility, and greater accuracy [62,63,64]. On a wider scale, beyond the supply chain context, DT can also play a major role in improving an organization’s market sensing competency, as discussed above, by helping it identify opportunities and threats [58,59], and to meet the challenges presented by a dynamic and rapidly evolving market environment [38,40,65,66].

2.3.1. The Contribution of Blockchain Technology

One technology that has played a particularly significant role as a key driver of supply chain transparency, traceability, and efficiency, by facilitating strategic partnerships and DT, is blockchain technology. This technology has contributed to innovation in this area in a number of ways, such as enabling secure, immutable transactions across a decentralized network, ensuring that all parties involved in the supply chain have access to the same verifiable data. This enhances trust and collaboration among different parties, which is a critical aspect of strategic partnerships [67].

However, blockchain technology also offers other major benefits in the context of SPDC. It enables, for example, real-time visibility of assets as they move through the supply chain, helping to address challenges such as fraud, counterfeit goods, and operational inefficiencies [68]. This improved visibility supports supply chain transparency, fostering trust among different partners, by ensuring that all parties have access to accurate, up-to-date information, which is critical for forming and maintaining strategic partnerships. Trust and reliable information sharing also reduce the risk of disputes, making collaboration more efficient, and encouraging long-term business relationships.

Blockchain also contributes to improved BP, by reducing the costs and errors associated with manual processing. This technology’s role in risk mitigation is particularly significant, as blockchain can automatically log events, such as delays, product damage, and inventory shortages, enabling companies to proactively manage risks and maintain supply chain resilience [69]. Furthermore, blockchain’s decentralized nature can foster innovation in strategic partnerships, which includes encouraging the creation of new business models based on shared data and collaborative networks [70]. As blockchain continues to evolve, its role in enhancing supply chain agility and BP is expected to expand, driving further innovations in terms of strategic partnerships and digital transformation efforts.

3. Hypotheses Development

The theoretical foundation of this study derives from two central themes: the role of strategic partnerships and the concept of digital transformation (DT) in enhancing supply chain agility and performance.

(a) Strategic partnerships: Theories relevant to strategic partnerships often draw on the Resource-Based View (RBV), which argues that firms gain a competitive advantage by leveraging unique resources and capabilities, often through collaborative alliances [71]. In the context of supply chain management, such business alliances empower firms to access complementary resources, reduce operational inefficiencies, and mitigate risks associated with the volatility of demand [72]. These alliances are particularly significant to the development of agility, as they allow firms to rapidly adapt resources and respond to market changes, which is key to success in today’s unpredictable environment [73]. The integration of partners through digital tools also enhances the speed and efficacy of supply chain operations, further reinforcing the importance of strategy partnerships.

(b) DT: The concept of digital transformation is founded on theories of technological innovation and organizational change [74]. As noted in Section 2.3, DT refers to the integration of digital technologies into all areas of business, fundamentally changing how companies deliver value to customers. DT can be examined through the lens of a number of theoretical frameworks, such as Dynamic Capabilities Theory [75], which emphasizes the need for a firm to develop its ability to build, integrate, and reconfigure internal and external competencies, in order to adapt to rapidly changing environments. In the context of supply chains, DT enables firms to improve its information flow, transparency, and decision-making processes, which are critical for achieving agility [76].

The research model used in this study is based on an established organizational model that integrates these theoretical frameworks and which seeks to understand and explain how firms develop and manage their capabilities in dynamic environments [60,77]. The model is known for its emphasis on dynamic competencies and organizational adaptation, as well as its focus on how organizations can strategically respond to change in order to maintain a competitive advantage (Figure 1).

In the model used in this study, the relationships between SPDC, DT, and LSCA/LSCAD are examined, along with their impact on business performance (BP). As discussed above, DT is considered as a mediating entity, based on a hierarchical view of the dynamic competencies [74,78], and the analysis is based on the findings in the literature that found DT to be a dynamic competency [58,66,79]. However, more research is needed to explore how the DT capability compares with other dynamic capabilities.

3.1. SPDC and LSCA/LSCAD

Strategic partnership development competence (SPDC) is an essential element of ensuring that a supply chain is, and remains, effective [80,81]. Such competency refers to an organization’s ability to establish, nurture, and manage strategic partnerships with other businesses/organizations to deliver long-term mutual benefits [82,83], and encompasses a range of processes, skills, and frameworks that allow a business to identify potential partners, build strong relationships, and align their strategic goals [82,84]. By developing their SPDC, businesses can benefit in a number of significant ways, such as gaining cost advantages from the co-development of new products and/or technologies, gaining access to new markets/segments, sharing risks and resources, adding distribution channels, and sharing creative ideas [85,86].

SPDC also plays a critical role in the development and efficiency of supply chains, by enhancing collaboration, improving efficiency, and creating value through synergies with partners [83,87]. The use of SPDC to build effective inter-organizational alliances can result in the seamless integration of processes, systems, and workflows between partners, leading to smoother operations, increased efficiency, lower costs, enhanced agility and flexibility, lower risk, and collaborative innovation. Overall, effective strategic partnerships can yield sustained supply chain performance and long-term business success [88,89].

One of the principal benefits of effective SPDC is its ability to play a ‘protective’ role by enhancing a supply chain’s adaptability and agility. These are critical factors in maintaining operational efficiency and competitiveness during periods of crisis [90], as they allow the organization to flex its supply chain dynamically in response to rapidly evolving circumstances [82,84,88]. This means that the organization is more robust in terms of its preparedness for unexpected and potentially disruptive events [83,87,89]. The above points lead to the following hypotheses:

H1. 

Strategic partnership development competence (SPDC) is positively related to logistical and supply chain agility (LSCA).

H2. 

Strategic partnership development competence (SPDC) is positively related to logistical and supply chain adaptability (LSCAD).

3.2. SPDC and DT

The importance and benefits of SPDC to organizations and their supply chains has been discussed above, and DT can play a key role in enabling and enhancing the processes of SPDC in a number of ways. The deployment of digital platforms, for example, can facilitate seamless communication between partners, regardless of their location, as well as improve coordination through the integration of systems [59,65,91]. Digital technologies can also help automate repetitive tasks within partnerships, leading to increased efficiency and reduced operational costs, while combining datasets allows partners to make informed decisions based on real-time data, improving the effectiveness of the partnership [61,92]. Furthermore, through DT, partners can jointly invest in and adopt emerging technologies (e.g., blockchain, IoT, AI), which can contribute to the creation of new business models and give the partnership a competitive edge, while the adoption of digital tools enable partners to identify and manage risks more effectively [93,94].

DT also strengthens the resilience of supply chain partnerships by improving visibility and agility, allowing partners to respond swiftly to disruptions [40,65]. In the context of today’s globalized and rapidly changing market, DT enhances the formation of strategic partnerships in the supply chain industry because, for example, it facilitates instant, real-time communication between supply chain partners, enabling better coordination and decision-making [92,95,96]. DT also introduces automation into key supply chain processes, such as order processing and inventory management, thus reducing errors, speeding up systems, and lowering operational costs [92,95,96].

A good example of the power of SPDC to enhance supply chain resilience, flexibility, and agility is the US company, Walmart, which collaborates with its partners on inventory management and demand forecasting. This enables seamless communication, real-time data sharing, and more effective planning, leading to efficient operations and strong partnerships. We therefore propose the following hypothesis:

H3. 

Strategic partnership development competence (SPDC) is positively related to digital transformation (DT).

3.3. DT and LSCA/LSCAD

LSCA and LSCAD are critical components of any business strategy designed to ensure that an organization remains competitive in times involving unforeseen crises or unusual volatility [86,97,98]. The integration of enhanced technologies into the core infrastructural processes of an organization, in other words, digital transformation, can help that organization develop both of these components [81,86,99,100]. There are a variety of studies that have found a significant positive relationship between the adoption of advanced technologies, such as AI, cloud computing, and machine learning, and LSCA/LSCAD [80,85,98,101]. These studies show that DT can be an essential component of a business’s rapid and efficient response to disruptive events, ensuring that the connection between the company and the customer is affected as minimally as possible, if at all [38,58,64]. Overall, recent research strongly suggests that DT is a ‘must do’ for any organization seeking to enhance their supply chain resilience in a highly unpredictable and volatile market environment [95,102].

The ability of DT to enhance LSCA is well-illustrated by Nike. When the company found that its traditional processes were too slow to keep up with the rapidly changing footwear market, it transformed its supply chain through the use of advanced data analytics, automation, and machine learning. The transformation gave Nike the agility to respond rapidly to market trends, scale production efficiently, and meet consumer demand more effectively. As a result, Nike improved its market position and customer satisfaction [85,99,101]. Based on the above discussion, it is hypothesized that:

H4. 

Digital transformation (DT) has a positive impact on logistical and supply chain agility (LSCA).

Adaptability, which is related to but different from agility, is another factor that is critical to establishing and maintaining business growth [97,103], and there is evidence that this adaptability can be enhanced considerably through business partnerships and alliances [104,105]. A culture of DT can contribute significantly to the development of such alliances [58,63].

One real-world example of how DT has enabled the development of adaptability is the case of Procter & Gamble (P&G), a global consumer goods company. When P&G recognized that it needed to adapt to rapidly evolving consumer preferences and global market conditions, the company implemented an organization-wide strategy on digital transformation that included the use of AI, big data analytics, and cloud computing. This strategy allowed P&G to gather and analyze consumer data from various sources in real-time, which enabled the rapid and dynamic adaptation of product lines, marketing strategies, and supply chains to meet changing consumer needs. This adaptability allowed P&G to maintain its competitive edge and continue to thrive in a dynamic market environment [105,106]. This leads to the hypothesis:

H5. 

Digital transformation (DT) has a positive impact on logistical and supply chain adaptability (LSCAD).

3.4. LSCA/LSCAD and BP

A variety of studies have shown that there is a clear and positive association between LSCA/LSCAD and BP [107,108,109]. LSCA, for example, can improve cost efficiency [110,111,112] through a variety of mechanisms, such as helping to avoid overproduction, better allocation of resources, reducing waste, eliminating non-value-adding processes, and improving the time to market [108,111,113]. The result of this, ultimately, is better BP [107,110,114], through effects such as improved financial growth and increased market share [109,113,114]. We therefore propose the following hypothesis:

H6. 

Logistical and supply chain agility (LSCA) has a positive association with business performance (BP).

As discussed above, supply chain agility and adaptability are related but different. While both refer to the ability to respond to changes, agility is concerned with the capacity to react quickly and appropriately to short-term changes in demand or supply conditions, while adaptability refers to the ability to evolve over time in response to long-term changes in the environment [107,110,113]. Businesses that develop logistical and supply chain adaptability (LSCAD) show increased resilience (the ability to withstand disruptions or volatile environments), higher cost efficiency, increased long-term competitiveness, improved customer satisfaction, and a higher level of environmental sustainability [108,111,114]. This is likely to lead to better business performance. Hence, we hypothesize that:

H7. 

Logistical and supply chain adaptability (LSCAD) has a positive association with business performance (BP).

3.5. DT as a Mediator

It has been well-established that DT can improve business performance through direct mechanisms. DT can, for example, directly increase operational efficiency by streamlining processes and lowering operational costs. It can also have a direct impact on sales and profits, by enhancing the customer experience through tools such as mobile apps, chatbots, and personalized marketing [115,116].

The indirect impact of DT, however, has been less thoroughly explored. DT can, for instance, help businesses grow by enabling them to explore new business models, products, or services using data analysis. It can also help to foster a more agile and adaptable organizational culture [2,116]. Another important way that DT can indirectly impact BP is by enhancing the processes of SPDC. It (DT) achieves this in several ways, such as by enhancing communication and collaboration, and by improving decision-making through data sharing, and enabling end-to-end supply chain transparency, which improves efficiency, mitigates risk, and increases resilience [74,117,118]. The resulting improvement in the volume and quality of strategic partnerships can lead to a more dynamic and context-sensitive approach to supply chain management, allowing organizations to respond more quickly to evolving market conditions [78,119,120]. The role of DT as a mediator in the relationship between SPDC and LSCA/LSCAD is, therefore, crucial. By embracing DT, firms can significantly improve their SPDC and, therefore, enhance their supply chain competencies. Ultimately, this leads to improved BP. We, therefore, propose that:

H8. 

Digital transformation (DT) acts as a mediator between SPDC and LSCA.

H9. 

Digital transformation (DT) acts as a mediator between SPDC and LSCAD.

4. Methodology

This research employs a mixed methods approach, as defined by Johnson and Onwuegbuzie [121], which integrates both quantitative and qualitative research techniques, methods, and concepts within a single study. The choice of this approach is grounded in its ability to capitalize on the strengths of both methodologies, leading to more comprehensive findings that might not be possible through the use of a single method alone. To systematically address the research questions, the study was conducted in two distinct phases.

The study focused on two key elements of data collection and analysis: (a) a quantitative component designed to test the proposed hypotheses and (b) a qualitative component aimed at enhancing the validity of the quantitative findings. This dual approach ensures a more robust and nuanced understanding of the research problem.

Before data collection, ethical considerations were thoroughly addressed throughout the study. All participants were informed, both at the outset and via the survey’s website, that the research adhered to the ethical guidelines approved by the Research Ethics Committee at King Saud University. The participants were assured of the anonymity of their data to protect their privacy, were informed of their right to withdraw at any time, and were told that there were no right or wrong answers. It was also emphasized that participation was voluntary, with no direct benefits or incentives offered.

5. Quantitative Stage

5.1. Development of the Survey Instrument

The questionnaire used in this study used a standard (5-point) Likert scale approach to examine the constructs shown in Table 1. Although some items were based on previous studies [122,123,124,125], most were designed specifically for this study, following accepted guidelines [126,127]. This approach was chosen to ensure that the survey was accurately aligned with the specific goals of our study.

The survey was organized into three sections: (1) an introduction that explained the study’s objectives and participant eligibility criteria, specifically targeting individuals with experience in regard to the subject matter; (2) data collection on various metrics related to our research constructs/factors; and (3) collection of demographic information from the respondents.

To ensure the survey items accurately measured the study’s constructs, the survey’s content validity was evaluated prior to data collection [128,129]. This was achieved by seeking input from 24 suitably qualified professionals on the relevance and clarity of the items. As a result of the feedback gathered, the original set of 22 items was reduced to 20. This stage was followed by a pilot study involving 58 professionals and led to a number of minor changes in the items.

5.2. Sampling

To test the study’s model and hypotheses, quantitative data were captured by surveying 393 professionals from 10 manufacturing companies in Saudi Arabia (Table 2). These sectors (food and beverages, textiles and apparel, consumer electronics, and personal care products) were chosen because they are integral to Saudi Arabia’s retail industry and operate in highly competitive environments, where robust and flexible supply chains are critical. The retail environment is also well-known for being sensitive to disruption [130,131,132], as was demonstrated during the COVID-19 pandemic [133,134,135], so effective measures, such as strategic partnerships, to help ensure business stability are important.

The participants were identified using a mixture of industry directories and regional business registries. Initially, 103 suitable companies were identified and invited to participate. Of these, 89 agreed to contribute to the research and nominated related people to complete the survey (via Google Forms) on behalf of the business. We used an online survey method due to its wide geographical reach, higher response rates, cost effectiveness, flexibility, and ability to accommodate larger sample sizes [136,137].

The individuals were then informed (via email) of the purpose of the study, together with the ethical guidelines. No incentives, financial or otherwise, were offered to the participants. Over a 5-month period, a total of 401 questionnaires had been completed, of which 8 were considered invalid for one or more reasons (e.g., unclear or incomplete responses), resulting in 393 valid responses.

As a significant number of participants (who had agreed to contribute to the study) did not complete the survey, it was considered important to test for non-response bias. This was carried out by comparing early and late respondents [138], by using a t-test (p > 0.05). As the resulting t-statistic was not significant, suggesting that there was no meaningful difference between the two groups, it was concluded that non-response bias was not an issue.

5.3. Method of Analysis

This study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) as the analytical framework, chosen for several key reasons. PLS-SEM is widely recognized for its effectiveness in facilitating theory development, as supported by numerous authoritative sources [139,140,141]. Additionally, PLS-SEM excels in analyzing complex structural models, with multiple constructs and intricate interrelationships. Furthermore, its suitability for studies with smaller sample sizes makes it a more appropriate choice than Covariance-Based Structural Equation Modeling (CB-SEM) in such contexts.

5.4. Evaluating the Measurement Model

This study applied factor analysis (FA) to identify the underlying factors represented by a series of variables or items, as suggested by previous research [142,143]. In addition to discovering these hidden dimensions, our evaluation also included an assessment of the model’s fit, along with checks for both convergent and discriminant validity to ensure that the analysis was thorough. Factor analysis was selected for its effective capability to uncover latent constructs behind observed variables [142,144], which is central to achieving our research aims.

To determine whether our sample was appropriate for FA, we first used the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy, which returned a value of 0.832. This value is well above the generally recommended minimum of 0.7 [145,146], indicating that our sample size was adequate and suitable for this analysis. Additionally, Bartlett’s test of sphericity was applied to assess whether the variables were correlated, testing the null hypothesis that the correlation matrix is an identity matrix. The test yielded a significant result (p-value < 0.05), confirming that the variables shared enough common variance to justify the use of FA [143,145]. The combined results from the KMO measure and Bartlett’s test confirm the appropriateness of FA for our dataset, thereby supporting the soundness of our chosen methodology.

Regarding the model’s fit, the indices produced align with the standards established by Hu and Bentler [147], as presented in Table 3, which outlines the fit of the structural model. This compliance with well-recognized benchmarks demonstrates the reliability of our analytical method, affirming the validity of our model and the accuracy of our factor analysis. As a result, our findings are built on a solid foundation, further validating their reliability and relevance to the latent constructs under investigation.

As illustrated in Table 1, the factor loading for each item was significant, ranging between 0.803 and 0.931. These figures highlight the strong correlation between the items and their respective factors, affirming the convergent validity of the analysis. This indicates that each item effectively measured its corresponding factor, thereby enhancing the reliability of the findings. Establishing convergent validity is essential, as it ensures that the identified constructs are accurately represented by the measured variables, reinforcing the robustness and relevance of the factor analysis results.

To assess the internal consistency of the constructs, Cronbach’s alpha (CA) was employed. The results, summarized in Table 4, reveal CA values for each construct ranging from 0.81 to 0.87. Additionally, the Composite Reliability (CR) scores varied from 0.75 to 0.84, exceeding the recommended threshold of 0.70. These results indicate a high degree of internal consistency across the constructs, reflecting the accurate measurement of the intended latent variables [140,148].

To ensure the distinctiveness between the constructs and their measurements, a test for discriminant validity was performed, following the procedures outlined by Hair et al. [140,148]. This procedure involves comparing the square root of the Average Variance Extracted (AVE) for each construct with its association coefficients, requiring that the square root of the AVE exceeds an association threshold of 0.50. The results, as shown in Table 4, demonstrate that our study meets these essential criteria, confirming the adequacy of discriminant validity.

Additionally, the study addressed multi-collinearity, which arises when independent variables are highly correlated with each other. We evaluated this issue by analyzing both the Variance Inflation Factor (VIF) and tolerance values. The results revealed that the VIF values were under 3 and the tolerance values were above 2, consistent with the guidelines provided by Hair et al. [140,149]. This compliance with standard practices reduces the effects of multi-collinearity, preserving the integrity of our analysis.

Overall, these thorough evaluations affirm the validation and reliability of the measurement model, demonstrating a strong model fit, convergent validity, discriminant validity, and controlled multi-collinearity. These findings collectively validate the robustness of our model, confirming its accuracy and reliability in capturing the complexities of the latent constructs being studied.

5.5. Common Method Bias (CMB)

Common Method Variance (CMV) represents a possible source of systematic error when data is gathered from a single source [150,151]. To address this in our research, we implemented Harman’s single factor test, which did not reveal any evidence of CMV. Furthermore, we evaluated Common Method Bias (CMB), a specific form of CMV that may occur when consistent response scales are employed [152,153]. To identify CMB, we used the common latent factor method, which also showed no signs of bias. Therefore, we can confidently state that the findings in this study are free from both CMV and CMB, thereby enhancing the reliability and validity of the results.

5.6. Findings in Terms of the Research Hypotheses

Prior to the hypothesis-testing stage of the analysis, it was important to establish that endogeneity was not a significant issue, as this could undermine the validity of the study’s conclusions. This was evaluated using three regression models, which showed that endogeneity was not a concern. This stage was followed by hypothesis testing using PLS-SEM, as implemented in a wide variety of other studies [5,47,109,154,155].

Table 5 shows the outcome values of this analysis. These values support the proposed relationships (expressed by H1–H4) between SPDC, LSCA, LSCAD, and DT, and the validity of the final model. This suggests that the role of SPDC, enhanced by DT, is critical to the development of the level of supply chain competencies required for organizations to remain competitive and profitable in periods of uncertainty. Overall, the results support the contention that SPDC, mediated by DT, contributes significantly to business performance by enhancing the development of supply chain adaptability and agility [74,115,156]. As a further test of the validity of the key proposal in this study (the mediating effect of DT between SPDC and LSCA/LSCAD), indirect effects were also analyzed. This process used the method developed by Kock [157]. This analysis found that DT has a partially mediating effect between SPDC and LSCA/LSCAD.

6. Qualitative Component

6.1. Qualitative Validation—Semi-Structured Interviews

While the quantitative phase provided broad, statistically significant insights into the relationships between SPDC, DT, and supply chain competencies, it was considered that the inclusion of qualitative research could enhance the quantitative aspect of the study by providing a deeper, more nuanced understanding of these relationships [158,159]. A qualitative phase would enable the researchers to explore the reasoning, experiences, and contextual factors behind the quantitative results, thereby providing rich, contextual data that could not be captured through the survey alone.

More specifically, a qualitative element to the study would help to do the following:

• (a). Validate the quantitative findings. By interviewing a sub-group of survey respondents, the study could ensure that the quantitative patterns observed (e.g., SPDC’s impact on LSCA and LSCAD) were aligned with real-world experiences and organizational behaviors. Such triangulation would strengthen the study’s overall validity [160];

• (b). Reveal underlying mechanisms. While the quantitative analysis showed that DT mediated the relationship between SPDC and supply chain competencies, qualitative interviews could offer insights into how and why this occurs [161];

• (c). Contextualize the data. Interviews would facilitate the exploration of specific contexts (e.g., industry-specific challenges, organizational size) and, thereby, add depth to the quantitative findings. This combination of methods enables the study to draw more comprehensive conclusions that are applicable across different sectors.

A qualitative phase would, therefore, ensure that the findings were not only statistically robust, but also practically meaningful, thereby strengthening the study’s contributions to both theory and practice.

As a result of this reasoning, semi-structured interviews [158,159] were carried out with a sub-group (N = 38) of the phase 1 participants. Table 6 provides information on the interviewees’ characteristics.

The interview process was discontinued at N = 38, as no new information/themes were emerging, suggesting that the saturation point had been reached [162,163]. The analysis itself followed the approach developed by Gioia [163], which is a qualitative research method designed for conducting rigorous and systematic data analysis, particularly in organizational and management studies. The method emphasizes the development of grounded theory through a structured process of coding and categorization, allowing researchers to build theory from rich, qualitative data. Further details on the interviews and the results obtained can be found in later sections.

The interviews themselves consisted of two stages: (a) questions about the strategic partnership development competence and its effect on supply chain performance and (b) the effect of DT on business performance and supply chain competencies. A dynamic interview adjustment approach was taken, during which the questions were amended, based insights gained from earlier interviews [96,118].

6.2. Interview Results

6.2.1. Partner Coordination

The analysis revealed that partner coordination is a crucial factor for effective resource allocation and strategic decision-making within organizations. Strong coordination with partners ensures alignment of efforts and enables organizations to collaboratively address challenges, leading to mutual success. As one Senior Manager in planning highlighted:

We always consult with our partners before making decisions on resource allocation. This collaborative approach ensures that everyone is on the same page, and it helps prevent conflicts or misunderstandings that could arise from unilateral decisions.

Another Senior Manager in logistics emphasized the value of coordination in maintaining strong partnerships:

Successful partnerships are built on good coordination—it helps ensure we move forward together, not grow apart. Without this level of communication and alignment, it’s easy for partners to drift apart, which can weaken the relationship and undermine our collective goals.

This theme also underscores the importance of strategic alignment with partners to enhance responsiveness and capitalize on opportunities. A General Manager noted:

When our business partners are in sync with us, we can respond to challenges and seize opportunities more effectively. It’s not just about being reactive; it’s about being proactive together, anticipating market shifts, and preparing for them in a way that benefits all parties involved.

Another perspective from a Senior Manager in logistics highlighted the practical benefits of effective coordination:

Effective coordination with our supply chain partners turns potential problems into collaborative solutions, helping to deliver mutual success. For example, when a supply issue arises, instead of it becoming a bottleneck, our coordinated efforts allow us to quickly find an alternative solution, minimizing disruptions.

Finally, a General Manager emphasized the strategic value created through partner coordination:

Coordination with our partners is a key strength in my view—together, we create more value than we could create separately. This synergy not only improves our operational efficiency but also strengthens our market position, making us more competitive as a collective unit.

In conclusion, strong partner coordination is essential for achieving alignment, enhancing responsiveness, and creating mutual value, which ultimately strengthens the overall strategic position of the organization.

6.2.2. Agile Competency

Agile competency emerged as another critical theme, with participants noting that digital tools have greatly enhanced their organization’s agility, enabling faster decision-making and better responsiveness to market changes. A Senior Manager in distribution commented:

The agility we’ve gained through digital tools allows us to [change] strategies and take advantage of opportunities faster than ever before. We can pivot quickly when market conditions shift, which has become increasingly important in today’s fast-paced environment.

This newfound agility has also allowed organizations to maintain a competitive edge. A General Manager explained:

Embracing digital technology has empowered [my organization] to make faster decisions, keeping us ahead in an increasingly unpredictable and competitive landscape. The ability to quickly analyze data and generate insights means we can stay one step ahead of our competitors, which is critical for long-term success.

Additionally, the digital transformation journey was credited with unlocking new levels of flexibility, as noted by a Manager in product development:

I’d say that our digital transformation journey has unlocked new levels of flexibility, enabling the business to innovate and respond to customer needs pretty much in real-time. We’re no longer tied down by outdated processes; instead, we can adapt to meet changing customer expectations almost instantly.

Another Senior Manager in procurement highlighted how digital technologies have shifted their approach from being reactive to proactive:

Digital technologies have helped us move from reactive to proactive—so now we’re more of an industry leader than a follower of trends. We can anticipate market changes before they happen and adjust our strategies accordingly, which has given us a significant competitive advantage.

Finally, a Senior Manager in planning discussed the broader organizational impact of agility:

Agility isn’t just about speed; it’s about being able to adapt to whatever comes our way, whether it’s a new market trend or an unexpected challenge. Digital tools have given us the flexibility we need to thrive in this environment, and that’s something we continue to build on every day.

In conclusion, the development of agile competency through digital tools is pivotal in enabling organizations to adapt swiftly to market changes, stay ahead of the competition, and maintain a flexible approach to innovation and customer needs.

6.2.3. Digital Adaptability

Digital adaptability was highlighted as a significant factor in driving innovation and streamlining operations. Participants discussed how the ability to quickly integrate and leverage new technologies has been crucial in achieving these goals. A Senior Manager in IT stated:

I think the ability of our team to see the potential of the latest tech has played a major role in helping us streamline operations and drive innovation across the entire organization. This forward-thinking approach has allowed us to stay ahead of the curve and implement solutions that not only meet current needs but also anticipate future challenges.

The positive impact of digital adaptability on organizational growth was also noted. A General Manager shared:

When I joined the company, we were a pretty ordinary outfit, but ever since I recruited section leaders with a digital mindset, we’ve grown significantly, and now we’re one of the leaders in the industry. It’s incredible to see how quickly we’ve been able to scale and improve our processes just by having the right people in place who understand the importance of digital transformation.

This adaptability has also helped organizations stay ahead of market changes, as highlighted by a Manager in IT:

There’s no doubt in my mind that our enthusiasm for making use of the latest tech—especially AI and machine learning—has helped us not just keep up with changes in the market, but to get and stay ahead. These technologies have become integral to our strategy, enabling us to predict trends and act on them before our competitors even see them coming.

Another Senior Manager in IT elaborated on the role of digital adaptability in fostering innovation:

Digital adaptability isn’t just about using new tools; it’s about embracing a mindset that values continuous learning and innovation. By staying adaptable, we’ve been able to create a culture where experimentation is encouraged, and that’s where some of our most successful initiatives have come from.

Finally, a Consultant discussed the strategic advantages of digital adaptability:

The more digitally adaptable we are, the better equipped we are to turn challenges into strategic advantages. It’s about being flexible enough to change course when needed, but also being smart enough to recognize when a new technology or approach can give us a competitive edge.

In conclusion, digital adaptability is crucial for organizations to stay ahead of market trends, foster innovation, and create a culture that values continuous learning and strategic flexibility.

6.2.4. Driving Digital Transformation

The theme of driving digital transformation focused on the challenges associated with change management and fostering a culture of innovation. Participants pointed out that the most challenging aspect of digital transformation is not the technology itself, but overcoming resistance to change and developing an innovative culture. A Senior Manager in procurement remarked:

The hardest part of digital transformation isn’t really the technology itself. In my experience, it’s overcoming resistance to change and developing a culture of innovation. You can have the best tools in the world, but if your team isn’t on board, those tools won’t be used to their full potential.

Another participant, a Data Analyst, discussed the ongoing challenges of adapting to new digital infrastructures, which requires continuous learning and resource management:

Changing infrastructure to be digitally driven from the core requires constant learning and adaptation, which can strain resources and test resilience. Unless you’ve got the right people with the right attitudes, you can face major problems. It’s not just about plugging in new software; it’s about rethinking how your entire organization operates.

A General Manager highlighted the importance of problem-solving during the integration of new digital tools:

Integrating new digital tools often exposes gaps in existing systems and processes, and creates unforeseen hurdles that require fast and effective problem-solving. It’s a continuous learning process, and you have to be ready to tackle these issues head-on if you want to succeed.

A Senior Manager in IT emphasized the importance of leadership in driving digital transformation:

Leadership plays a crucial role in digital transformation. If leaders aren’t fully committed to the process, it’s easy for initiatives to stall. Leaders need to be the ones championing the change, setting the vision, and guiding their teams through the challenges that inevitably arise.

Finally, a Consultant discussed the cultural shift required for successful digital transformation:

Driving digital transformation isn’t just about implementing new technologies; it’s about changing the way people think and work. You need to create a culture where innovation is valued and where people are encouraged to experiment and take risks. Without this cultural shift, digital transformation efforts are likely to fall short.

In conclusion, successfully driving digital transformation requires overcoming resistance to change, fostering a culture of innovation, and ensuring strong leadership commitment to guide the organization through the challenges faced during this transition.

6.2.5. Lack of Digital Leadership

The absence of strong digital leadership was identified as a significant barrier to successful digital transformation. Participants emphasized that without clear guidance and commitment from top management, transformation efforts risk losing momentum, resulting in misalignment with strategic goals. A Manager in distribution commented:

Without strong leadership from the top down, transformation efforts have a real risk of stalling, as teams lack the clear vision and direction needed to drive change. It’s not enough to just have a plan; you need leaders who are actively pushing that plan forward and making sure everyone is aligned with it.

A Manager in IT elaborated on the impact of weak leadership on digital transformation:

The absence of clear commitment [to DT] from management creates a sense of uncertainty throughout the entire organization, leading to poorly implemented initiatives that almost always fail to align with overall strategic goals. I’ve seen it happen in many other organizations, and I’m glad it’s not the case in ours.

A Consultant pointed out the importance of having experienced leaders in navigating industry shifts:

In this industry, it’s easy to miss opportunities, and struggle to keep pace with technological advancements and industry shifts. Experienced leaders who understand the need to leverage the latest tech can make a real difference. Without that guidance, even the best-intentioned efforts can fall flat.

A Senior Manager in logistics emphasized the role of leadership in fostering a culture of innovation:

Leaders set the tone for the entire organization. If they aren’t championing innovation and encouraging their teams to think creatively, it’s unlikely that digital transformation will succeed. Leaders need to be the ones driving change, inspiring their teams, and removing obstacles to innovation.

Finally, a General Manager discussed the long-term impact of digital leadership on organizational success:

Digital leadership is about more than just implementing technology; it’s about creating a vision for the future and guiding the organization towards it. Leaders who can do this effectively will ensure that their organization not only survives, but thrives in an increasingly digital world.

In conclusion, strong digital leadership is crucial for aligning digital transformation efforts with strategic goals, fostering innovation, and ensuring long-term organizational success in a rapidly evolving digital landscape.

6.2.6. Digital Culture

Cultivating a digital culture was another critical theme that emerged from the interviews. Participants stressed that for digital transformation to be successful, there must be a widespread shift toward digital thinking within the organization. This cultural shift is essential for fostering innovation and adaptability. A Manager in IT stated:

If digital transformation is to work, every team member needs to be aligned with the business’s technological goals. Without this mindset shift, even the best tools and strategies will fall short. It’s about getting everyone on board with the idea that technology is at the core of everything we do.

A General Manager highlighted the role of a strong digital culture in encouraging quick adaptation and innovation:

A strong digital culture encourages our staff to innovate and adapt quickly, which is essential in today’s rapidly evolving market. It’s not just about adopting new technologies; it’s about fostering an environment that thrives on change. When everyone is on the same page, we can move faster and more effectively.

Another Senior Manager in planning emphasized the importance of embedding this digital mindset across all levels of the organization:

For successful digital transformation, you need to cultivate an environment where digital thinking is the norm. Our success hinges on our ability to embed this mindset across all levels of the organization. It’s not enough for just the IT department to be digitally savvy; every team needs to embrace digital tools and approaches.

A Senior Manager in IT discussed the impact of a digital culture on employee engagement:

A strong digital culture doesn’t just improve our ability to innovate; it also enhances employee engagement. When people feel like they’re part of a forward-thinking organization that values their contributions, they’re more motivated to go above and beyond. This culture of innovation is what drives our success.

Finally, a Manager in product development talked about the long-term benefits of cultivating a digital culture:

Cultivating a digital culture isn’t just about short-term gains; it’s about setting the foundation for long-term success. By embedding digital thinking into our DNA, we’re ensuring that we’ll be able to continue innovating and adapting to whatever the future holds.

In conclusion, fostering a digital culture is essential for driving innovation, enhancing employee engagement, and ensuring the long-term success of digital transformation efforts across the organization.

6.2.7. Talent Recruitment

Finally, the theme of talent recruitment was underscored as being central to driving digital transformation. Participants emphasized the necessity of attracting and retaining top digital talent to fully realize the potential of digital tools and strategies. A Data Analyst remarked:

Recruiting top digital talent is the very core of successful digital transformation. Their expertise and fresh perspectives are key to driving the innovative solutions we need to stay competitive. Without the right people in place, even the best technology can fall flat.

The challenges associated with recruiting the right talent were also acknowledged. A Senior Manager in IT stated:

To truly align ourselves with the digital age, we need to bring in the best digital minds who can lead and inspire our teams. I’m convinced that without the right talent even the most ambitious strategies will struggle to take off. It’s not just about finding people who can do the job; it’s about finding people who can push us to the next level.

Another participant, a General Manager, discussed the importance of retaining digital talent:

Attracting and retaining the best digital talent can be difficult and expensive. But it has to be done, as they’re the key to unlocking the full potential of our technology investments and achieving long-term success. The real challenge is keeping these talented individuals engaged and motivated, so they stay with us for the long haul.

A Senior Manager in procurement emphasized the strategic importance of digital talent:

In the digital age, talent is one of our most valuable assets. The right people can take our digital transformation efforts to new heights, while the wrong hires can set us back. It’s crucial that we invest in attracting and developing top talent to stay ahead of the competition.

Finally, a Manager in product development highlighted the link between talent recruitment and innovation:

The quality of the talent we bring in directly impacts our ability to innovate. If we want to continue leading the market, we need to make sure we’re recruiting individuals who not only have the technical skills, but also have the creativity and vision to drive innovation.

In conclusion, recruiting and retaining top digital talent is critical for driving innovation, fully leveraging digital tools, and achieving the long-term success of digital transformation initiatives.

7. Discussion

Taken together, the findings from the two stages (quantitative and qualitative) of this study significantly enhance the current understanding on the associations between SPDC, LSCA, LSCAD, DT, and BP, and have valuable implications for theory and practice. This study strongly supports the contention that as markets become more globalized, while also more susceptible to disruption, the use of digital technology to ensure the adaptability and agility of supply chains becomes ever more important [5,164,165]. While RQ1 focuses on how SPDC impacts supply chain outcomes through the mediating role of digital transformation, RQ2 broadens the scope to explore how SPDC and digital transformation jointly influence overall business performance. By doing so, this study not only addresses the operational challenges faced in terms of supply chain management, but also offers insights into the broader strategic impact on business success.

While the study’s results do not explicitly examine the role of blockchain technology, they strongly support the existing literature, which highlights blockchain’s significant contribution to enhancing trust, transparency, and collaboration in strategic partnerships. The ability to track and trace products in real-time using blockchain’s decentralized structure aligns with the study’s finding that agility is heavily dependent on real-time data availability and response mechanisms. Furthermore, the results suggest that cost reduction and risk management, which are both key BP metrics, are optimized through blockchain’s ability to eliminate intermediaries and automate processes via smart contracts, reinforcing its contribution to overall supply chain efficiency.

In essence, the study’s results show that digital transformation, when integrated properly with strategic partnerships, improves not only logistical performance, but also directly contributes to better business outcomes, such as improved financial stability, market competitiveness, and operational flexibility.

7.1. Implications for Theory

Digital technologies are well-established as drivers of supply chain performance. However, successful digital transformation requires a strong digital culture and leadership [155,156]. This study contributes to the literature by addressing significant gaps in the current understanding on how these elements impact supply chain adaptability and agility, informing future research. To achieve this, the study builds on the hierarchical structure of dynamic capabilities [153,159,160,161], focusing on the strategic partnership development competence (SPDC), digital transformation (DT), and supply chain agility/adaptability. These dynamic capabilities are important for organizations to maintain their competitiveness in a volatile market. By understanding the importance of these capabilities in the hierarchical structure of dynamic capabilities, businesses can better navigate the changing landscape in terms of the current market environment, in order to develop and sustain a competitive advantage.

Drawing from Dynamic Capabilities Theory (DCT) [154,159,160,161,162], this study enhances the understanding of how DT mediates the relationship between SPDC and supply chain capabilities, enabling businesses to adapt and thrive in uncertain environments. This, in turn, will help businesses respond rapidly and improve their performance in volatile trading environments.

The findings in this research suggest that DT mediates the relationship between strategic partnership development and supply chain competencies. By enhancing communication, data sharing, decision-making, and trust, DT strengthens partnerships and improves supply chain effectiveness [144,163]. This demonstrates how integral DT is to both business partnerships and operations.

The ability of SPDC to enhance supply chain competencies, while always important, is particularly important in an era characterized by change and unpredictability [164,166]. This study shows that DT mediates SPDC’s impact on supply chain agility and adaptability, with collaboration and trust driving improved business performance. This means that organizations investing in SPDC are better equipped to handle supply chain disruptions.

In summary, this study found the following with regard to the proposed hypotheses (Table 7).

These insights, while extremely valuable, also point to a need for ongoing research in this area, as the rapidly changing business environment, the increasing complexity of global supply chains, the advances in digital technologies, and the development of new and disruptive services all raise their own questions that need to be answered [73,167,168]. Such ongoing research will help to ensure that strategic partnerships continue to deliver value and drive supply chain effectiveness in the face of new challenges and opportunities.

Another benefit of this study, which will be useful in the theoretical context, is that it also clarifies DT’s role within the Dynamic Capabilities View (DCV). Digital transformation, while complex, requires the reshaping of business models and organizational culture [169]. This research finds a positive relationship between SPDC, DT, and supply chain adaptability/agility, offering deeper insights into how organizations can adapt in the digital age. By integrating these findings into the DCV, businesses can enhance their agility, resilience, and competitiveness in today’s volatile environment.

7.2. Implications for Practice

This study offers practical insights for managers aiming to improve supply chain resilience. Strategic partnerships, enhanced by digital transformation (DT), are key to boosting collaboration, efficiency, and supply chain agility. DT enhances coordination, innovation, and risk management within partnerships. These benefits help all parties in the alliance to achieve their strategic goals more effectively and sustain long-term success. This study also highlights that successful DT requires a thorough evaluation of the business’s needs and capabilities. Companies should assess their resources and infrastructure, while prioritizing leadership with a digital mindset, to foster innovation and collaboration.

This last point is especially important, as fostering a collaborative culture is crucial for effective DT in supply chains. This requires creating an environment of mutual respect, where staff are encouraged to be creative and experimental. Leaders should focus on communication, digital leadership, the company mindset, and recruitment to strengthen partnerships, reduce risk, and position supply chains for optimal performance in the digital age.

This study’s results also have significant implications for policymakers. Economic and business policies should prioritize digital transformation to promote strategic partnerships, which foster growth and contribute to overall economic development. By supporting the development of dynamic capabilities, policymakers can help businesses navigate unpredictable events like the COVID-19 pandemic, improving the resilience of industries, and benefiting broader social and economic infrastructure.

8. Limitations and Recommendations for Future Research

As with any research, this study has some limitations. One of these is that the analysis was based on data collected from a single industry sector (manufacturing) in a single country (Saudi Arabia), so the results may not be globally representative. Another consideration which may affect the generalizability of the results is the relatively small sample size of the quantitative phase (N = 393). Further, it should be noted that the data were collected during a relatively narrow space of time, making the study cross-sectional. As digital technologies are known for their rapid pace of change, this might result in findings which do not reflect the longer-term picture. To improve the accuracy of the model, a longitudinal study may be useful.

Another possible limitation is that the study used a single informant questionnaire, which could raise concerns about the reliability and validity of the data collected. Although a qualitative phase, employing semi-structured interviews, was used to enhance the validity of the results, future studies could consider triangulating the findings with data from other sources.

In terms of future research, one useful area of investigation would be the impact of institutional and other external pressures on the development of supply chain and DT strategies. This is an important issue, as DT, especially where supply chains are involved, is a complex and challenging process, which is strongly influenced by such factors. Finally, it would be valuable to explore, using relevant theoretical frameworks, how businesses can develop the required resources and capabilities to successfully implement DT. Such research could make a considerable contribution to our understanding of the challenges and opportunities associated with DT in the context of supply chains.

9. Conclusions

This study examined two specific questions concerning the agility and adaptability of supply chains:

RQ1: To what extent are LSCA and LSCAD impacted by SPDC?

RQ2: What is the impact of SPDC on BP when mediated by digital transformation (DT)?

To explore these questions, the study proposed a model derived from the dynamic capability framework, and the model was then tested using a quantitative (survey) approach supported by a qualitative (semi-structured interviews) stage, to enhance the validity of data collected during the first phase.

The analysis of the data demonstrated that the strategic partnership development competence (SPDC) is positively related to both logistical and supply chain agility (LSCA) and logistical and supply chain adaptability (LSCAD), demonstrating the importance of SPDC in maintaining high levels of business performance in a rapidly changing and often unpredictable trading environment.

More specifically, and equally important, this study found that digital transformation (DT) plays a key mediating role in the relationship between SPDC and LSCA/LSCAD, facilitating greater levels of coordination and collaboration between partners. This leads to a wide range of significant benefits, such as faster and more informed decision-making, quicker reaction times, enhanced supply chain and organizational agility and adaptability, and improved overall business performance. More specifically, by addressing RQ1 and RQ2, this study highlights the dual impact of SPDC and DT on both the supply chain and the overall business performance. While many studies have focused primarily on operational agility, this research extends the understanding on how these factors affect broader business outcomes. The findings provide new insights into how firms can leverage partnerships not only to enhance supply chain effectiveness, but also to drive financial performance, market competitiveness, and long-term resilience.

In summary, this study adds a valuable new dimension to the current understanding of the precise role of digital transformation in the development of supply chain agility and adaptability, while also highlighting the need for further research on the topic.

Institutional Review Board Statement

The study was carried out in accordance with the principles outlined in the Declaration of Helsinki and received approval from the Institutional Review Board (Human and Social Research) at King Saud University.

Informed Consent Statement

All participants involved in the study provided informed consent.

Data Availability Statement

Data can be made available upon request to ensure that the privacy re-strictions are upheld.

Acknowledgments

The author would like to extend his sincere appreciation to the Researchers Supporting Project (RSP2024R233), King Saud University, Riyadh, Saudi Arabia.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figure and Tables

Figure 1. Research model.

Table 1

The constructs, together with their respective questionnaire items and related factor loadings.

Construct/Factor	Item	Factor Loading
Strategic partnership development competence	We coordinate supply chain activities with our business partners.	0.838
	We always align the allocation of specific tasks with our partners’ competencies.	0.881
	We carefully consider and discuss areas of collaboration with our supply chain partners.	0.875
	Our partnership results in valuable knowledge that continuously improves our supply chain.	0.877
	We have a good reputation for building strong partnerships.	0.921
Digital transformation	Our senior management have strong backgrounds in digital technologies.	0.919
	Our team managers are also well-qualified in digital technologies.	0.875
	Our workforce is generally very comfortable with digital technologies.	0.914
	Our organization values external partnerships and strongly encourages collaboration to improve its digital competencies.	0.848
	Our organization invests significantly in its digital capability.	0.923
Logistical and supply chain agility	Our organization implements processes designed to identify short-term changes in the market environment.	0.849
	Our organization is able to rapidly scale or reduce its production systems to meet changes in market demand.	0.931
	Our supply chain is able to dynamically respond to market changes or disruptions.	0.826
Logistical and supply chain adaptability	Our organization is built around flexible technology that can be adapted to meet any identified longer-term trends.	0.803
	Our organization implements the latest technologies in our processes and systems.	0.884
	We invest significantly in systems designed to predict and address market changes by adjusting our supply chain.	0.829
Business performance	Our organization consistently achieves a strong return on assets (ROAs).	0.871
	We maintain a high inventory turnover ratio.	0.884
	Our market capitalization reflects our strong market position.	0.851
	We excel in on-time delivery to our customers.	0.838

Table 2

An outline of the respondents’ characteristics.

	Characteristics	Participants %
Industry	Food and beverages	31
	Textiles and apparel	28
	Consumer electronics	14
	Personal care products	27
Business size	<50 employees	18
	51–100 employees	39
	101–500 employees	25
	>500 employees	18
Years in business	<10	41
	10–19 years	29
	20–29 years	20
	>30 years	10

Table 3

Model fit indices and criteria compliance.

Fit Measure Category	Fit Measure	Result	Meets Criteria?	Recommended Criteria
Absolute Fit Measures	Chi-Square (χ2/DF)	2.58	Yes	<3.0
	SRMR	0.890	Yes	>0.80
	GFI	0.962	Yes	>0.90
	RMSEA	0.038	Yes	<0.05
Parsimonious Fit Measures	PNFI	0.642	Yes	<0.05
	PGFI	0.683	Yes	<0.05
Incremental Fit Measures	CFI	0.920	Yes	>0.90
	NFI	0.933	Yes	>0.90
	IFI	0.934	Yes	>0.90
	AGFI	0.955	Yes	>0.90

Table 4

Results of correlations, CR, CA, and AVE.

Construct/Factor	CA	CR	AVE	1	2	3	4	5
Strategic partnership development competence	0.82	0.85	0.75	0.87
Digital transformation	0.84	0.83	0.73	0.62	0.86
Logistical and supply chain agility	0.83	0.84	0.66	−0.69	−0.70	0.82
Logistical and supply chain adaptability	0.85	0.80	0.63	0.57	0.65	0.68	0.80
Business performance	0.87	0.79	0.65	−0.58	0.69	0.62	0.57	0.81

Table 5

Hypothesis test values.

Hypothesis	Driving Variable	Outcome Variable	β
H1	SPDC	LSCA	0.81 *
H2	SPDC	LSCAD	0.68 *
H3	SPDC	DT	0.87 *
H4	DT	LSCA	0.18 **
H5	DT	LSCAD	0.25 *
H6	LSCA	BP	0.42 *
H7	LSCAD	BP	0.44 *
Mediation Test Hypothesis	Sobel Value	Mediation
H8 (SPDC–DT–LSCA)	2.88 at p < 0.01	partial
H9 (SPDC–DT–LSCAA)	4.08 at p < 0.01	partial

Note: *: 0.005 significance, **: 0.001 significance.

Table 6

Information on the characteristics of the participants.

Management Role	No. Participants
Logistics and supply chain	7
Procurement	5
Planning	7
IT/data analyst	5
Product development	1
Distribution and warehouse	4
Consultant/business analyst	3
General management	6
Total	38

Table 7

Findings in terms of the proposed hypotheses.

Hypothesis	Confirmed?	Key Finding
H1. SPDC is positively related to LSCA.	Yes	SPDC significantly enhances supply chain agility.
H2. SPDC is positively related to LSCAD.	Yes	SPDC improves adaptability, allowing firms to adjust to long-term market shifts.
H3. SPDC is positively related to DT.	Yes	SPDC fosters digital transformation through better communication and collaboration between partners.
H4. DT has a positive impact on LSCA.	Yes	DT enhances supply chain agility by facilitating rapid responses to market changes.
H5. DT has a positive impact on LSCAD.	Yes	DT allows supply chains to adapt to longer-term trends and disruptions.
H6. LSCA is positively associated with business performance (BP).	Yes	Higher agility improves operational efficiency and competitiveness, boosting BP.
H7. LSCAD is positively associated with BP.	Yes	Adaptable supply chains are more resilient and improve BP over the long term.
H8. DT mediates the relationship between SPDC and LSCA.	Partially	DT partially mediates the impact of SPDC on LSCA, enhancing agility through digital tools.
H9. DT mediates the relationship between SPDC and LSCAD.	Partially	DT also partially mediates the effect of SPDC on adaptability, fostering flexibility and responsiveness.

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