From Adopting Industry 4.0 Technologies to Improving Operational Performance in Hospital Supply Chain: The Moderating Effect of HSC Complexity

Abstract

Background: The hospital supply chain (HSC) is one of the main levers for improving the performance of any healthcare organization. HSC stakeholders evolve in a dynamic environment marked by great complexity. This observation led us to conduct research, through which we examined several factors enabling operational performance to be achieved within the HSC. Methods: For the empirical verification, we opted for a survey of a relevant sample composed of health professionals operating in different Moroccan hospitals, particularly in the logistics departments. Afterwards, the data were analyzed using a Partial Least Squares-Structural Equation Modeling (PLS-SEM) method to test the hypothesized relationships in this study. Results: The results show that the adoption of Industry 4.0 technologies improve collaborative aspects between logistics processes and flows, and thus ensure better integration of HSC. The research also highlights the moderating effect of HSC complexity in the relationship between HSC integration and HSC operational performance, i.e., HSC integration increases HSC operational performance in a context marked by high complexity. Conclusions: This paper explores the impact of Industry 4.0 technologies on HSC operational performance. The study provides hospital managers and practitioners with insights to improve HSC operational performance through integration initiatives, ultimately better meeting the needs of healthcare professionals and contributing to improve the quality of care.

1. Introduction

Around the world, the well-being of societies depends to a large extent on the performance of their healthcare systems. Providing patients with timely, high-quality care is the main objective of every health care system. In reality, though, this is not as simple as it seems. Healthcare procedures are carried out in a dynamic setting and are extremely complex and diverse [1]. Despite the fact that the healthcare system is by definition a clinically driven setting, a variety of tasks support patient care, most notably inventory management, purchasing, and supply distribution to the point of care. These operations are related to the management of the supply chain in healthcare facilities, commonly known as Hospital Supply Chain (HSC) [2]. Increasing cost pressures, rising demand, and increased competitiveness have raised awareness of efficiency and interdependence in HSCs, resulting in greater complexity. As the complexity of a supply network grows, so does the risk, making the supply chain more vulnerable. These flaws became obvious when the COVID-19 epidemic posed serious problems to HSCs around the world [3].

To face this complexity and seek to achieve operational performance, several dimensions related to HSC management have been addressed in this research, starting with the adoption of Industry 4.0 technologies, going through the collaborative aspects within the HSC and reaching its integration. For the HSC operational performance dimensions, among those found in the literature, we selected the most relevant ones, which meet the specificities of the HSC, namely: efficiency, reliability and responsiveness, quality, cost optimization and sustainability [4,5,6,7,8]. During the survey conducted as part of this study, these dimensions were particularly observed. In addition, it should be recalled that HSCs are vastly different from traditional industrial supply chains in terms of client demand variability. As a result, they demand an appropriate and reliable flow of information tailored to the various needs of patients [1]. In this regard, it is worth noting that the adoption of Industry 4.0 technologies is data-driven due to the uniqueness of healthcare institutions. Hospitals that adopt these innovative technologies have a cutting-edge advantage over those that rely on the traditional approach to patient care delivery [9].

Furthermore, supply chain collaboration can be regarded as an important and vital aspect in maintaining chain stability. To achieve this goal, the chain must be updated in accordance with Industry 4.0 developments. The impact of these new technologies can be seen in organizations as one of the greatest challenges combined with industry 4.0 that contributes to improving supply chain performance [10]. Big data, artificial intelligence, machine learning, internet of Things, and blockchain are some of the technologies that are having a significant impact on supply chains, people, and businesses. Industry 4.0 technologies are shifting supply chain management from a linear approach to supply chain 4.0, which integrates processes [11]. Indeed, integrating the HSC entails coordinating activities including physical materials, services, and patient movement. They require thorough and accurate flow information based on patients’ various demands [1]. On the other hand, the literature on supply chain management indicates that the integration of functions and activities throughout the supply chain is regarded as a critical component of performance [12]. On his part, ref. [13] reconsidered the supposed favorable effect of supply chain integration on performance.

Collaboration and integration are two related but distinct aspects in HSC management. In this study, collaboration is understood as the ability of different logistics departments to work together to improve the overall performance of the HSC, which requires effective communication, information sharing and collaborative decision-making. While integration involves the removal of barriers and silos and the establishment of connections between logistics processes through information systems, which helps to streamline the HSC by reducing disruptions, duplications and delays.

However, no study has yet been conducted to examine the impact of Industry 4.0 technologies on collaborative aspects, and consequently the improvement of integration and performance within the HSC. Thus, the aim of this study is to contribute to filling this research gap by developing a comprehensive theoretical framework necessary to understand the relationship between Industry 4.0 technology adoption, collaboration, integration and operational performance within HSC, but also to explore the moderating effect of HSC complexity on the relationship between HSC integration and HSC operational performance. This framework will not only enhance researchers’ knowledge in this field, but will also provide a practical guide for HSC managers wishing to improve their supply chain operational performance. Following previous discussions, we posit five guiding research questions (RQs) as:

RQ1: How can collaborative aspects between HSC processes and flows be improved?

RQ2: What is the effect of adopting Industry 4.0 technologies on HSC integration?

RQ3: What is the effect of collaboration between processes and logistics flows on the HSC integration?

RQ4: To what extent does the integration of processes and logistics flows impact the HSC operational performance?

RQ5: How does integration impact HSC operational performance in a context marked by high complexity?

The remainder of the paper is structured as follows. Section 2 provides the development of hypotheses and the theoretical framework. Section 3 outlines the research methodology adopted and the analysis of the results. Section 4 is devoted to discussion; it includes theoretical and practical implications as well as research limitations. Section 5 concludes this study and summarizes our contribution.

2. Hypotheses Development and Theoretical Framework

2.1. Impact of Industry 4.0 Technologies on Collaborative Aspects Within the HSC

In supply chain management, the ability to establish collaboration by optimizing the use of digital technologies, such as cloud and big data, is becoming a crucial aspect in achieving performance [14]. According to [15], the implementation of Industry 4.0 in the industrial context has an impact on the entire supply chain and necessitates cooperation between suppliers, manufacturers, and financial consumers, including with regard to information flow. Ref. [16] emphasize the significance of having accurate, dependable, and up-to-date information available as much as possible throughout the supply chain in order to generate a coherent and stable demand value. The typical supply chain has a narrow view, which precludes efficient collaboration across the network’s many processes. The information is delayed in advancing to each of its stages and has varied planning cycles, resulting in delays and errors linked to data and information synchronization. In supply chain 4.0, information is available for all processes of the chain concurrently [17]. According to [18], Industry 4.0 technology will improve collaboration throughout the supply chain. Furthermore, Industry 4.0 technologies will achieve a high level of information sharing and openness, ultimately improving supply chain management. In the field of health systems, collaboration between staff within the same institution, between institutions within the same system, or with other systems and entities is necessary. The use of Industry 4.0 technologies will improve communication between all system components and can be built to allow links to other health systems that use the same technologies [19]. Ultimately, by aligning technology investments with organizational goals and objectives, improving collaboration and communication, and ensuring that data is collected and analyzed in meaningful and actionable ways, healthcare organizations can position themselves for successful Healthcare 4.0 implementation [20]. Hence, we hypothesize that the adoption of Industry 4.0 technologies promotes collaborative aspects within the HSC. Thus, we have our first hypothesis:

H1. 

Adopting Industry 4.0 technologies both within and between logistics processes has a positive and significant impact on collaborative aspects within the HSC.

2.2. Impact of Industry 4.0 Technologies on HSC Integration

Supply chains face several challenges, such as uncertainty, costs, complexity, and vulnerability. Supply chains need to be intelligent to overcome these challenges and equipped with technological infrastructure to integrate information and physical flows into supply chain processes, thereby reducing their complexity [21]. Industry 4.0 has brought a number of new disruptive technologies that have changed approaches to product or service delivery. For example, the integration and complexity of systems in Industry 4.0 will lead to the emergence of more complex and digital supply chain models, in which the barriers between information and physical structure are reduced, thus promoting more integration within supply chains [22]. Supply chain partners should create new solutions as well as an open and collaborative architecture to support effective information exchange, operational activity integration, and logistical synchronization [23]. To accomplish this, considerable modifications in business activities and routines must be done, which can be enabled and facilitated by the use of Industry 4.0 technologies [24]. According to the same author, the adoption of Industry 4.0 technologies promotes integration throughout the supply chain, facilitating the collaborative dimension that is critical to achieving the Circular Economy’s objectives in terms of improved resource use, resource allocation, optimization, and so on. For [11], adoption of Industry 4.0 enables the development and control of applications by enhancing physical resource integration in the warehousing, transportation, inventory management, and retail industries. In terms of integrating organizational relationships between suppliers, internal organizational links, and customers, Industry 4.0 technologies allow supply chain members and stakeholders to communicate in real time and are regarded as an important factor in facilitating integration and collaboration among supply chain actors, internal departments, and organizations. For Health Care Supply Chains (HCSCs) to be modernized in the fourth industrial revolution, enormous coordination and integration among stakeholders within the HCSC is required [11,25]. Ref. [26] argue that information sharing systems are required for coordination and integration in order to allow transparency and data sharing. For this aim, HCSCs rely on technological innovation, which may include medical Internet of Things (IoT), Radio Frequency Identification (RFID), big data, and predictive analytics. Accordingly, we suggest that the adoption of Industry 4.0 technologies promotes the integration of HSC. This provides our next hypothesis:

H2. 

Adopting Industry 4.0 technologies both within and between logistics processes positively and significantly impacts the HSC integration.

2.3. Impact of Collaboration Between Processes and Logistics Flows on HSC Integration

Supply chains can be defined as long, complex and intertwined sequences of firms connected by orders [27]. Management of such chains tries to establish an ideal approach for the entire chain, which induces the integration of business operations amongst a number of enterprises. This integration is based on different levels of interaction of the firms involved, ranging from harmonization or synchronization of activities: coordination; to working together as equal partners: cooperation and even acting as a single entity: collaboration [27]. Establishing a relationship of trust and collaboration between the different partners in the supply chain leads to the integration of processes and the interest in sharing benefits and costs [28]. Thus, supply chains tend to integrate their resources, while collaboration is identified as a key organizational element of this integration. This integration highlights the need to maintain strong symbiotic relationships between the different actors in the supply chain [29]. Research has shown that supply chain practices are reinforced by cultural influences that promote cooperative behaviors, suggesting that integration may be enhanced in firms with a strong collaborative culture [30]. For integration to improve performance, the right organizational and operational conditions seem to be necessary. A naturally appealing set of circumstances for achieving greater integration are the behavioral antecedents of collaboration [31]. On the other hand, relational embeddedness, according to [32], is predicated on value-creating interactions that enhance trust, curtail opportunistic behavior, and so facilitate supply chain integration and structural embeddedness. In summary, coordination of procedures pertaining to tangible supplies, services, and patient movement is a component of healthcare supply chain integration. According to the various patient needs, they require a thorough and accurate flow of information [1]. Hence, we hypothesize that as coordination and collaboration between logistics processes and flows increase, barriers are reduced and integration is better ensured. This leads to our next hypothesis:

H3. 

Collaboration between processes and logistics flows positively and significantly impacts the HSC integration.

2.4. Impact of the Integration of Logistics Processes and Flows on HSC Operational Performance

Integration is widely accepted and implemented to improve performance. Studies on integration highlight the importance of integration and its impact on performance. Moreover, supply chain integration and collaboration are considered fundamental to achieve strategic and sustainable performance [33]. For successful performance, a high level of integration of supply chain processes is considered crucial. Effective information exchange and integrated process design are considered essential and important [10]. For [34], supply chain integration has many benefits, including greater flexibility to meet individual customer demands, reduced delivery times, reduced logistics and material purchasing costs, reduced inventory levels, increased labor efficiency and market share, thus ensuring a very high level of performance. Research reveals that supply chain integration (internal and external integration) improves operational performance outcomes, including cost, speed of delivery, flexibility, and quality. According to [35], operational performance, including process efficiency, and internal integration are positively correlated. Organizations promote internal integration to its full potential in order to improve operational performance [5]. Although the possession of different resources explains differential firm performance, we argue that such collaborative assets, if deployed effectively in healthcare supply chains, can lead to successful integration and improved operational performance [8]. The same authors state that for effective delivery of the healthcare supply chain, collaborative assets must contribute significantly to successful integration. Such integration would have positive impacts on operational performance. On the other hand, poor integration between chain processes results in an inflexible chain and can lead to dysfunctional operational performance [1]. Supply chain integration is sought by organizations across industries worldwide as a key element to manage performance more effectively to deliver efficient and effective customer-centric services. Hospitals, like other organizations, are looking for ways to reduce costs, improve service levels, and enhance performance [1]. Accordingly, we suggest that integration of logistics processes and flows improves HSC operational performance. Hence, we proposed the following hypothesis:

H4. 

The integration of logistics processes and flows has a positive and significant impact on HSC operational performance.

2.5. Moderating Effect of HSC Complexity

In the literature, few studies have examined the impact of supply complexity on supply chain performance. For example, ref. [36] showed that operational performance is likely to be higher for firms with a high rather than a low level of upstream dynamic supply chain complexity. Along the same lines, ref. [37] showed that complexity drives operational performance with increasing supply chain adaptability. Furthermore, ref. [13] state that if the complexity of the supply is high, supply chain practices contribute to the improvement of one or more aspects of the service performance, especially in the context of the integrated supply chain. We can therefore suggest that under contextual conditions, such as in the case of significant integration, HSC complexity positively impacts HSC operational performance.

In the context of the global supply chain, and more specifically in buyer-supplier relationships, ref. [13] showed that supply chain integration is only effective in a context marked by high supply complexity. In other words, integration increases supply chain performance if supply complexity is high. Ref. [38] argue that the complexity of the supply chain increases in a context marked by the multitude of suppliers and buyers with a more complex construction. To manage this complexity of the supply chain, more generation and dissemination of information is necessary. The results of this study showed that supply chain complexity moderates the positive relationship between big data and supply chain resilience, which is one of the dimensions of performance, so that the relationship becomes stronger when supply chain complexity is higher. Ref. [39] examined the relationship between integration, complexity and operational performance in the industrial sector. The results revealed significant positive relationships between customer integration, internal integration, supplier integration, supply chain complexity and operational performance. In the context of HSC, we did not find in the literature studies that addressed the relationships between complexity, integration and performance within the HSC. Ref. [5] partially addressed these relationships by analyzing the contingent effects of integration on the dimensions of the management control system and the operational performance of the hospital supply chain. The results show that in the context of a highly integrated supply chain, the association between the management control system and the operational performance of the hospital, namely profitability, flexibility and quality, will be strengthened. In other words, the authors highlight the moderating role of integration (internal and external) in improving the performance within the HSC.

Hence, we proposed the following hypotheses:

H5a. 

In the context marked by significant integration, HSC complexity positively impacts the operational performance of the HSC.

H5b. 

In a context marked by high complexity, the relationship between HSC integration and HSC operational performance becomes strongly positive.

Based on the above-mentioned hypotheses, which are well supported by the literature review, Figure 1 illustrates the theoretical framework for understanding the relationships between aspects enabling operational performance within the HSC.

3. Research Methodology

This contribution examines the adoption of Industry 4.0 technologies in relation to collaboration and integration within HSC in the Moroccan context. Furthermore, it explores how HSC integration affects the operational performance of HSC. Lastly, this contribution investigates the moderating role of HSC complexity in the relationship between HSC integration and HSC operational performance.

To achieve the research objectives, a survey was designed to gather data from professionals in the healthcare sector, specifically in public hospitals. As detailed in Appendix A, the survey comprises two sections. The first section includes demographic questions to provide an overview of the respondents (e.g., gender, age, and experience). The second section was designed to measure the key variables of the study. Each latent variable was assessed using a set of constructs adapted from the literature and evaluated on a Likert scale ranging from 1 to 7.

To measure the adoption of Industry 4.0 technologies, questions were adapted from various contributions to assess the level of adoption of specific technologies within respondents’ hospitals, using a scale from 1 (not adopted at all) to 7 (fully adopted) [40,41]. The technologies assessed include biomedical/digital sensors, cloud computing, remote control or monitoring, Internet of Things (IoT), big data, Enterprise Resource Planning (ERP), and augmented reality/simulation. For the collaboration aspects in the HSC, constructs were derived from the works of [42,43], capturing four dimensions: information level, communication, intra-organizational, and inter-organizational collaboration. Constructs for the integration variable were adapted from [44] to evaluate the extent to which the HSC integrates customers and suppliers. To measure HSC complexity, constructs were borrowed from [45], focusing on the complexity level of the HSC. Lastly, HSC operational performance was assessed using five constructs that are, the efficiency in terms of minimizing waste and maximizing the use of available resources, reliability and responsiveness in terms of ensuring constant availability of essential medical supplies and equipment and responding quickly to unforeseen needs, quality in terms of reducing defective and expired products to ensure patient safety, cost optimization of inventory related expenses, and compliance with environmental regulations [4,5,6,7,8].

The survey was originally administered in French, as it is the most commonly used language in Moroccan workplaces [46]. To ensure accuracy, the back-translation technique was employed to translate items from French to English. Before initiating data collection, the survey was pre-tested with five healthcare professionals to confirm the appropriateness of its content and structure. Respondents provided feedback on how to enhance the survey experience. It is worth noting that the responses from this preliminary test were excluded from the final dataset used for analysis.

3.1. Data Collection and Sample

In this study, two non-probability sampling methods, namely self-selection and snowball sampling, were employed. These methods were chosen because the target population comprises individuals working in Moroccan hospitals, to which the authors had access through their personal networks. The survey was primarily distributed via hospital employees’ work emails, phone numbers, and LinkedIn accounts, allowing individuals to voluntarily participate in the study.

Additionally, respondents were encouraged to share the survey with their colleagues to help expand the sample size. To further increase participation, phone calls were made to contacts within the authors’ personal networks.

The descriptive statistics in

Table 1. Respondents profile descriptive statistics (n = 210).

Measure	Item	n	(%)
Gender	Male	111	52.86%
	Female	99	47.14%
Age	Less than 40	70	33.33%
	Between 40 and 50	79	37.62%
	50 or more	61	29.05%
Education	Less than high school	36	17.14%
	High school	28	13.33%
	Technician	34	16.19%
	Bachelor	35	16.67%
	Masters	27	12.86%
	PhD or more	50	23.81%
Contract	Part-time	48	22.86%
	Full-time	162	77.14%
Hierarchy	Subordinate	178	84.76%
	Manager/Director	32	15.24%
Experience	Less than 2 years	51	24.29%
	2 years or more	159	75.71%
Department	Clinical	84	40.00%
	Non-clinical	126	60.00%
Hospital age	Less than 20 years old	20	9.52%
	20 years old or more	190	90.48%
Hospital beds	Less than 100	35	16.67%
	100 or more	175	83.33%
Hospital employees	Less than 200 employees	45	21.43%
	200 employees or more	165	78.57%

provide a comprehensive overview of the respondents’ profiles. Out of the 210 collected answers, the sample is relatively balanced, with 52.86% male and 47.14% female participants. Regarding age, the majority of respondents are between 40 and 50 years old (37.62%), followed by those under 40 (33.33%) and those aged 50 or older (29.05%). Educational attainment varies significantly, with a notable proportion holding a PhD or higher (23.81%), while smaller groups have completed less than high school (17.14%), high school (13.33%), technician training (16.19%), bachelor’s degrees (16.67%), or master’s degrees (12.86%). Unlike other industries, the high level of education within the hospitals is explained by the expertise needed in the healthcare industry. But we can also note that 17.14% of respondents are less than high school, in this regard we recall that the typical logistics or support functions: stock managers, distributors, transporters, handlers etc. in Moroccan hospitals are generally occupied by logistics agents who are graduates of Professional Qualification Centers, they have very advanced professional knowledge in their areas of expertise and a technical background allowing them to respond to the survey without difficulty despite its more or less complex nature.

Concerning the employment profile of respondents, the data collected reveals that most participants are employed full-time (77.14%), with a majority occupying subordinate roles (84.76%) rather than managerial or director-level positions (15.24%). Additionally, a significant portion of respondents have over two years of experience (75.71%), and 60% work in non-clinical departments, compared to 40% in clinical roles.

Finally, and regarding hospital characteristics, most hospitals where respondents work have been established for 20 years or more (90.48%), have 100 or more beds (83.33%), and employ 200 or more staff members (78.57%). This data underscores the diversity of respondents’ profiles while highlighting trends in age, education, employment, and hospital demographics.

However, it is important to mention that this distribution is similar to the context of many hospitals in Morocco. For instance, we typically find 15–20% of staff with less than high school education, mainly employed in support roles such as transporters, security, and handlers among other jobs. High school graduates (10–15%) usually hold supervisory roles for these services. Technicians (15–20%) are essential technical support staff. Bachelor’s degree holders are often administrative employees and support medical staff, while master’s and PhD holders take on administrative leadership roles or work as doctors or engineers. Moreover, in Moroccan hospitals, it is common to have 20–25% of the staff directly involved in the management of the HSC to work part-time, particularly those working for external logistics service providers such as catering, medical waste management, cleaning and hospital hygiene, etc. The clinical vs. non-clinical ratio in our sample (40% clinical, 60% non-clinical) reflects the Moroccan hospital context in relation to the target population of the study, i.e., staff directly involved in HSC management, where non-clinical staff are generally more numerous. Therefore, this sample can be considered representative of Moroccan hospital staff composition, mitigating concerns of sample bias in relation to the target population.

Regarding the responses’ quality and reliability, although each participant’s perception may be subjective, it is crucial to underline that all hospital staff, including those with lower formal education, undergo professional training adapted to their specific roles. This ensures a shared understanding of hospital processes and systems, which contributes to reducing potential subjective biases. Furthermore, from a statistical perspective, a larger and diverse sample size (n = 210) contributes to minimizing individual bias effects, as larger samples tend to mitigate subjective variations. Thus, both professional training and sample size contribute to enhancing the reliability and robustness of the responses.

To investigate the hypotheses developed in this study, structural equation modeling (SEM) is employed. Accordingly, the next section presents the assessment of the measurement model, followed by the evaluation of the structural model, and concludes with the estimation results.

3.2. Results

The following section presents the study’s results. Given the model’s complexity, the study utilized SEM, specifically employing the partial least squares (PLS) method with SmartPLS 4.0 software. The PLS-SEM is used in this study to assess the proposed model. This is a prominent method for empirically evaluating the complex connections and interconnections between model constructs. PLS-SEM helps to evaluate multidimensional theories, multiple variables, and relationships without requiring a specific data allocation [47].

3.2.1. Assessment of the Measurement Model

To validate the model, the first step involves assessing the survey’s reliability using several key indicators. According to [48], Cronbach’s alpha (CA) and composite reliability (CR) must exceed the threshold of 0.7 to confirm the constructs’ reliability. Additionally, to ensure indicator reliability, refs. [48,49] suggest that the loadings should also exceed 0.7. Finally, to proceed with SEM, it is crucial to confirm convergent validity. Ref. [48] specify that the average variance extracted (AVE) values must be greater than 0.5. As shown in

Table 2. Factor loading, Cronbach’s Alpha, composite reliabilities, and average variance extracted (n = 210).

Constructs	Items	Loading	CA	CR	AVE
4.0 Technologies	4.0Tech1	0.900	0.951	0.955	0.770
	4.0Tech2	0.851
	4.0Tech3	0.869
	4.0Tech4	0.895
	4.0Tech5	0.872
	4.0Tech6	0.880
	4.0Tech7	0.877
Collaboration	Collab1	0.944	0.959	0.960	0.890
	Collab2	0.936
	Collab3	0.933
	Collab4	0.959
Integration	Integr1	0.790	0.904	0.909	0.723
	Integr2	0.878
	Integr3	0.826
	Integr4	0.878
	Integr5	0.874
Complexity	Complex1	0.676	0.851	0.883	0.695
	Complex2	0.888
	Complex3	0.906
	Complex4	0.845
Operational Performance	Perform1	0.871	0.919	0.921	0.757
	Perform2	0.835
	Perform3	0.895
	Perform4	0.894
	Perform5	0.853

, the results of this contribution meet all these conditions, ensuring the model’s validity.

In addition to the previously discussed conditions, ref. [50] emphasize the importance of establishing discriminant validity for the SEM model to be considered valid. The discriminant validity is tested using the Heterotrait-Monotrait (HTMT) ratio, which is presented in

Table 3. HTMT ratio.

	4.0 Technologies	Collaboration	Complexity	Integration	Operational Performance
4.0 Technologies
Collaboration	0.637
Complexity	0.629	0.795
Integration	0.560	0.615	0.601
Operational Performance	0.759	0.604	0.649	0.555

. The HTMT ratio is preferred over other traditional methods such as Fornell-Larcker because of its high sensitivity to detect discriminant validity, especially when the sample size is small [51]. Normally, values below 0.9 are acceptable, however, [51] suggests that a threshold of 0.85 is more conservative. In the context of this study, the discriminant validity condition is satisfied as all values shown in Table 3 are below 0.85.

3.2.2. Assessment of the Structural Model

The preceding section confirmed the validity of the conceptual model. This section evaluates the structural model and presents the estimation results. According to Chin (1998) [52], assessing the structural model through the coefficient of determination is a critical step. The author specifies that a value below 0.19 is unacceptable, while values above this threshold are acceptable. Values between 0.19 and 0.67 are categorized as moderate, and those exceeding 0.67 are considered high. In the context of this study, all the R-squared values for the sub-models within the conceptual framework exceed 0.19, confirming the validity of the structural 8 model, as shown in

Table 4. Coefficient of determination.

	R-Square	Chin (1998) [52]
Collaboration	0.375	Moderate
Integration	0.387	Moderate
Operational Performance	0.419	Moderate

.

Figure 2 shows the significance of the relationships found after conducting the SEM analysis, and the coefficients are presented in

Table 5. Estimation results.

Relationship		Std. Beta	Std. Error	T-Value	p-Value	Decision
Direct effects
H1:	4.0 Technologies → Collaboration	0.613	0.045	13.626	5.68 × 10−14	Supported
H2:	4.0 Technologies → Integration	0.289	0.054	5.349	9.25 × 10−8	Supported
H3:	Collaboration → Integration	0.401	0.064	6.234	4.93 × 10−10	Supported
H4:	Integration → Operational Performance	0.321	0.070	4.617	3.98 × 10−6	Supported
H5a:	Complexity → Operational Performance	0.433	0.061	7.097	1.42 × 10−12	Supported
Moderating effects
H5b:	Complexity × Integration → Operational Performance	0.112	0.030	3.756	0.000	Supported

. Results show a strong empirical support for the hypothesized relationships in the study. Regarding the influence of Industry 4.0 technologies on HSC, the findings confirm a significant positive impact of industry 4.0 technology adoption on collaboration aspects of HSC (H₁: β = 0.613, p < 0.01) and integration (H2: β = 0.289, p < 0.01). Additionally, collaboration is shown to significantly enhance HSC integration (H3: β = 0.401, p < 0.01).

The analysis also highlights the impact of integration and complexity on the operational performance of HSC. Integration positively influences operational performance (H4: β = 0.321, p < 0.01), while complexity is also a significant driver of operational performance (H5a: β = 0.433, p < 0.001). Furthermore, the moderating effect of complexity in the relationship between integration and operational performance is confirmed, demonstrating that complexity amplifies the positive influence of integration on operational performance (H5b: β = 0.112, p = 0.000).

Appendix B provides the framework from the SmartPLS 4.0 software including factor loadings, R-squared and the structural model estimation results.

Figure 3 illustrates the moderating effect of HDC complexity on the relationship between HSC integration and HSC operational performance. When HSC complexity is at its mean level, its moderating influence positively impacts operational performance in the HSC. However, as HSC complexity increases, the positive effect becomes more pronounced, indicating that higher complexity amplifies the benefits of integration on operational performance. Conversely, when complexity is lower, the benefits of integration on operational performance are less significant.

To provide a clearer understanding of these relationships, it is useful to summarize their magnitude in percentage terms. The results indicate that Industry 4.0 technology adoption increases collaboration by 61.3% and integration by 28.9%, while collaboration itself enhances integration by 40.1%. Regarding performance, integration improves operational performance by 32.1%, and complexity contributes an additional 43.3%. Moreover, complexity strengthens the relationship between integration and performance by 11.2%. These percentages highlight the practical relevance of the relationships identified, offering important insights into how technology, collaboration, integration, and complexity interact to enhance HSC operational performance.

Overall, these results highlight that there is a strong relationship between Industry 4.0 technologies and collaborative aspects in HSC. Additionally, the results indicate that there are moderate relationships between collaborative aspects in HSC and HSC integration, between HSC integration and HSC operational performance, and between HSC complexity and HSC operational performance. Finally, this study found empirical evidence of the significant, but weak, influence that Industry 4.0 technologies exhibit on HSC integration, and the weak significant moderating role of HSC complexity on the relationship between HSC integration and HSC operational performance.

Thus, the findings underscore the critical role of Industry 4.0 technologies in fostering collaboration and integration within HSCs, as well as the complex interplay between integration, complexity, and operational performance in achieving enhanced outcomes.

4. Discussion

The results of this study show six significant results. First, the adoption of Industry 4.0 technologies is linked to both the collaborative aspects within the HSC and the HSC integration. Then, the collaborative aspects within the HSC are linked to the HSC integration. Furthermore, integration is linked to the HSC operational performance. Finally, the relationship between HSC complexity and HSC operational performance as well as the moderating effect of HSC complexity in the relationship between HSC integration and HSC operational performance. The implications of these results are discussed below:

4.1. Theoretical Implications

This research is especially interesting because it analyzes the relationships between the factors that allow optimizing HSC management. First, this study presents a conceptual framework for achieving operational performance in HSC through the adoption of Industry 4.0 technologies, HSC collaboration, and HSC integration. Although this conceptualization concerns HSC, it remains in perfect agreement with previous research work on the supply chain in other contexts. This framework contributes to the development of theory relating to the different factors generating HSC operational performance while filling the research gap on these aspects of HSC.

Our first hypothesis, according to which the adoption of Industry 4.0 technologies is positively and significantly linked to collaborative aspects in HSC, highlights the importance of these technologies in improving collaboration both within and between HSC processes. Although our finding is consistent with previous studies on the role of Industry 4.0 technologies in improving collaborative aspects in the supply chain, e.g., [14,18,21,53], these studies, unlike ours, did not analyze the impact of Industry 4.0 technologies on all processes and flows in the supply chain. As such, we recall that during our survey we were interested in all HSC processes and flows, as the results show. At the same time, we focused almost on all Industry 4.0 technologies, unlike previous studies which focused on certain technologies, for example ref. [54] focused on the use of Cloud Computing and Big Data Analytics, refs. [55,56] dealt with the use of IoT, refs. [57,58] showed the use of Blockchain in the supply chain.

Second, our finding that the adoption of Industry 4.0 technologies has a positive and significant relationship with HSC integration, which means that the use of these technologies is likely to promote the integration of processes and flows within the HSC. Indeed, the HSC faces several challenges such as the compartmentalization between processes and flows, which constitutes an obstacle to the sharing of information and therefore negatively impacts the efficiency of the HSC. We believe that the use of Industry 4.0 technologies would allow the sharing of information between the different processes and logistics flows, and therefore to have more visibility and less uncertainty in the management of the HSC. The results of our research are consistent with previous studies on this aspect, in particular [21,23,24,59]; Although these works have examined the role of using Industry 4.0 technologies in global supply chain integration, our study is the first to focus on this aspect in a hospital context through an empirical study that covered all logistics processes and flows in the Moroccan hospitals targeted by the study.

Third, our finding that collaboration is positively and significantly related to HSC integration indicates that improving collaborative aspects within the HSC is likely to increase HSC integration. Our results in this aspect support several previous studies related to the global supply chain such as [27,28,29]. In a healthcare context, ref. [8] focused on the planning process, they showed that collaborative planning helps hospitals and other key entities achieve successful integration through better information sharing and operational transparency. Refs. [1,60] focused on patient and information flows. Our study is thus one of the first to focus on all the processes and flows of HSC thanks to the empirical study that we conducted.

Fourth, this paper contributes to understanding how the integration of logistics processes and flows improves operational performance within the HSC. Indeed, our finding that integration is positively and significantly related to HSC operational performance is consistent with several previous studies that have addressed the same issue in the context of the global supply chain, including [5,10,36]. But in the context that concerns us, namely healthcare, the authors who have addressed this relationship, have done so in a partial manner, i.e., by focusing on a few aspects of the HSC. For example, Ref. [1] focused on two aspects of HSC, showing that sharing patient data and knowledge among healthcare supply chain partners not only strengthens integration but also improves overall hospital performance. In our empirical study, we forced ourselves to analyze this relationship in HSC as a whole, which allowed us to obtain convincing results.

Finally, our results show that HSC complexity moderates and positively reinforces the relationship between HSC integration and HSC operational performance. That is to say, in an environment marked by high complexity, HSC integration significantly increases operational performance within the HSC. Some previous studies have shown the same results as ours but in the context of the global supply chain [13,38,61,62], these works have addressed the moderating role of supply complexity on global supply chain performance. Thus, our study is distinguished by the exploration of the moderating effect of supply complexity on HSC operational performance. Furthermore, our study showed that, under contextual conditions, such as the case of a significant integration, the HSC complexity positively impacts the operational performance of the HSC. Previous studies have shown similar results but in the case of the global supply chain [13,39,40], our approach has the merit of being the first to confirm this relationship in a hospital context.

4.2. Practical Implications

First, the empirical study carried out in this research is relevant insofar as the majority of the hospitals used as experimental fields to conduct the surveys (83.3%), have a bed capacity of over 100 beds, i.e., they are medium to large-sized care establishments. Thus, the results of this study can be generalized to a wide range of Moroccan and foreign hospitals.

Second, the findings of this research provide important insights for hospital managers as well as practitioners, particularly hospital logisticians, by first highlighting the relevance of taking advantage of the fourth industrial revolution by adopting Industry 4.0 technologies across all HSC links (processes and flows). It can be assumed that the adoption of these technologies such as Artificial Intelligence, Blockchain, IoT etc. are able to transform the HSC into an intelligent and responsive system, ensuring better use of resources and improving collaboration, coordination and interaction between logistics processes. In this respect, Artificial Intelligence can improve collaborative aspects within the HSC by analyzing data from all processes and logistics flows in real time to anticipate needs and avoid waste and inefficiencies. The use of Blockchain can strengthen collaboration within the HSC through secure and transparent sharing between HSC stakeholders. The use of IoT improves collaboration by ensuring greater transparency and proactive resource management. This can even extend to the care process, through the availability and instant updating of shared data and information, leading to an overall improvement in patient care.

In addition, the results highlight the essential role of HSC integration as a major lever for improving the operational performance of HSC-which is by nature a complex system-particularly in a context marked by great complexity. In the field, this integration can result in optimized collaboration and coordination of logistical processes and flows, centralized information management, greater responsiveness to emergencies and crisis situations, etc.

Regarding the practical implications of the moderating effect of HSC complexity, we recall that the more complex the HSC, the more logistics integration becomes an essential lever to improve operational performance, hence the need for advanced integration in a complex environment. Thus, HSC managers are called upon to align integration with the level of complexity, i.e., if the logistics complexity is low, a small integration may be sufficient, while if the logistics complexity is high, advanced integration should be favored. They will then be able to measure the moderating effect of complexity and adjust their integration strategy to improve the performance of their supply chains.

Indeed, the results of this research are likely to encourage hospital managers to implement strategies and invest in the means and resources necessary for integrated management of their supply chain, thus helping to optimize the quality of hospital services and, above all, improve patient care.

4.3. Limitations and Future Research

Although our research has important implications for HSC researchers and hospital managers, it has some limitations that should not be overlooked when interpreting the results. First, due to the limited number of hospitals used as experimental fields for our survey, as well as the more or less limited size of the sample, we were unable to collect sufficient relevant and objective data relating to the aspects of the research model. In addition, we analyzed the relationships between the different dimensions of our model in the context of the Moroccan HSC, which may limit the generalizability of the results in other contexts. Many studies have addressed the performance factors of the global supply chain, but those that have addressed the HSC are still in their early stages. Thus, other empirical analyses from other hospitals at the national or international level are needed to validate and enrich the theoretical model proposed in this study. Furthermore, although we focused on several dimensions of operational performance within the HSC during the survey, we did not study the different dimensions of HSC integration (internal, external and with the care process), in particular how they can mutually reinforce each other to further enhance the HSC’s operational performance. Similarly for complexity, we focused only on the complexity of logistics processes and flows within the hospital. The complexity resulting from the relationship with the care process, suppliers and external providers of logistics activities (subcontracting), was not addressed in this study.

This study paves the way for potential future research in this area. Empirical studies related to the aspects addressed in this work could be conducted in developed or developing countries with more advanced technological standards, i.e., where Industry 4.0 technologies are well established in hospital practices, particularly at the HSC level. Indeed, HSC management in a context marked by substantial use of new technologies could only confirm the results of our study, as the impact of Industry 4.0 technologies would be felt more pronouncedly.

Similarly to the moderating effect of HSC complexity, future research conducted in a more complex and highly digitalized environment could further corroborate our results, as the more complex and significantly digitalized the HSC, the more logistics integration becomes an essential lever for improving HSC performance.

Thus, further research along the lines of this paper could focus on these issues relating to the dimensions of HSC integration and complexity, to further expand on the results of this research and improve its perspectives.

5. Conclusions

HSC is essential not only for the daily functioning of hospitals, but also to ensure quality care. Poor management of HSC can have serious impacts both at the operational level and on patient health. To address this observation, this study presents a theoretical framework analyzing the relationships between several dimensions (Industry 4.0 technologies, HSC collaboration, HSC integration, HSC complexity) to achieve operational performance within HSC. Given its complexity, the developed model was empirically tested using structural equation modeling (SEM) by collecting data from a relevant sample of healthcare professionals working in Moroccan hospitals, especially in logistics departments.

The findings show that implementing Industry 4.0 technologies improves collaboration between logistical processes and flows, resulting in improved HSC integration. The study also emphasizes the moderating effect of complexity in the relationship between integration and operational performance, i.e., HSC integration improves HSC operational performance in a context of high complexity.

The work reported in this article is intended to contribute to closing the gap in the research field regarding the relationships between the adoption of Industry 4.0 technologies in HSC, collaborative aspects in HSC, HSC integration, HSC complexity and HSC operational performance. Furthermore, this research provides hospital managers and hospital logisticians with a roadmap encouraging them to implement strategies aimed at integrating HSC, particularly through the adoption of Industry 4.0 technologies. This would improve the collaborative aspects between logistics processes and flows, and ultimately achieve HSC operational performance.