Integrating industry 4.0 and sustainability (S-I4.0) in the supply chains of MSMEs: a practical guide based on a multiple case study

The development and evolution of Industry 4.0 (I4.0) results in the acceleration of digital and sustainable transformation that increasingly impacts the industrial environment globally, becoming a fundamental factor for their competitiveness (Pfaff, 2023; Akbari et al., 2024; Abdallah et al., 2025), involving both risks and opportunities for the sustainability of global supply chains (Schilling and Seuring, 2023). The challenges posed by the integration of I4.0 within supply chains are complex. Sustainability has emerged as intrinsic to this journey (S-I4.0) (Caiado et al., 2024), ensuring that the impacts of the results obtained in overcoming these complexities are effective, with positive and lasting effects on organizational performance (Taqi et al., 2023; Mubarik and Khan, 2024).

S-4.0 has focused attention on several areas with increasingly urgent needs for all industries and society (Homma, 2024), further underscoring that I4.0 adoption significantly enhances sustainable performance across sectors (Shahzad et al., 2025) while also reinforcing supply chain capabilities and innovation as mediators of improved performance outcomes (Abdallah et al., 2025), and emphasizing the importance of understanding the associated technologies, their interconnections with the environmental and social dimensions of sustainability, and how such integration enhances organizational operational performance (Kaswan, 2025), such as: (1) Circular Economy: Intensive adoption of digital technologies in an efficient way to promote reuse and recycling, resource optimization, and minimize waste, emissions, and non-value added activities by maintaining resources in use for long time (Mohan et al., 2025; Seyyedi et al., 2024; Sabale et al., 2024); (2) Green Automation: Implementation of automation systems that reduce energy consumption and environmental impact (Ghannouchi, 2023); (3) Digital twins: Use to simulate and optimize production processes, increasing test assertiveness, improving energy efficiency and sustainability (Moshood et al., 2024); (4) Artificial Intelligence, Blockchain, Big Data, and IoT: Application for real-time environmental monitoring, demand forecasting, and process optimization to minimize ecological impacts, in addition to increase transparency with the use of sensors and connected devices to monitor the use of resources in real-time and improve energy efficiency (Paramesha et al., 2024; Younis et al., 2024), and supply chain-related benefits included social, environmental, and economic benefits (Santiago et al., 2025; Younis et al., 2026).

Although S-I4.0 has been at the forefront of initiatives by academics and practitioners (Alonso et al., 2024a, b), there is still much to be done for organizations to reformulate their business strategies and adopt S-I4.0 digital models (Sundarakani et al., 2024; Caiado et al., 2024). This is particularly true for micro, small, and medium-sized enterprises (MSMEs) (Vaezinejad et al., 2024; Sabale et al., 2024), which count with a different reality than that of large enterprises (Machado et al., 2021, 2024; Orazi and Sofritti, 2024). Therefore, studies must be tailored to address their needs specifically (Maganga and Taifa, 2024). Scholars examining the context of MSMEs concerning S-I4.0 emphasize the pivotal role of key stakeholders in navigating the multifaceted challenges faced by these companies when attempting to operationalize this concept in practice (Kumar et al., 2023; Machado et al., 2024). This assertion applies to both developed economies, such as Italy (Orazi and Sofritti, 2024), and emerging economies, including Malaysia (Wei et al., 2024), India (Pulicherla et al., 2022; Gahlaut and Dwivedi, 2024), Thailand (Amornkitvikai et al., 2022), and Brazil (Caiado et al., 2024). Although the integration of S-I4.0 into supply chains introduces new layers of complexity for MSMEs, it ultimately becomes the responsibility of external stakeholders to facilitate these firms in pursuing a sustainable and digitally enabled transformation within their respective business contexts (Rossi et al., 2022; Pandya et al., 2024).

In this regard, the literature highlights the importance of understanding how MSMEs can effectively integrate S-I4.0 into their supply chains, while accounting for their specific constraints and capabilities. Within this scenario, a notable paucity of research remains on how MSMEs can effectively scale digital transformation by leveraging the expansion of S-I4.0 practices and the emerging opportunities associated with them (Anatan and Nur, 2024; Martínez-Peláez et al., 2023; Bhatt and Kumar, 2022). Consequently, the development of practical frameworks and methodological tools to guide S-I4.0 integration across MSME supply chains is both timely and essential, as these resources can serve as accessible instruments for practitioners and academics, fostering reflective, transformative, and sustainable organizational processes (Ejsmont et al., 2020; Alonso et al., 2024a, b). Moreover, the literature reveals an ongoing debate regarding the extent to which micro and small enterprises (MSEs) differ from medium enterprises (MEs) in terms of structural, operational, and strategic characteristics (Machado et al., 2024). This raises important questions about whether these categories should be analysed collectively or treated as distinct analytical units when examining their capacity to adopt and integrate S-I4.0 practices (Passaro et al., 2023; Azis, 2024; Hernández et al., 2024). Recent empirical investigations have begun to address some of these research gaps. (Chong et al., 2024) analyse how green human resource management and knowledge-sharing mechanisms drive the effective implementation of sustainability practices within these enterprises. Complementarily, (Alkhodair and Alkhudhayr, 2025) propose integrative frameworks for embedding Industry 4.0 technologies to mitigate adoption barriers and enhance sustainability outcomes among SMEs. Nonetheless, further research is required to explore how MSMEs, particularly MSEs and MEs, can navigate the integration of S-I4.0 within their supply chains, and whether these enterprises can follow similar or differentiated transformation pathways. This leads to the research question (RQ):

• RQ: How can MSMEs integrate S-I4.0 into their supply chains, and to what extent can MSEs and MEs follow a similar transformation path?

To answer this RQ, the main objective of this research is to develop empirically grounded guidance to support both MSEs and MEs on the journey to integrate S-I4.0 into supply chains. This research builds on Machado et al.(2024), who conducted the first attempt in this direction, proposing a novel S-I4.0 Framework that distinguishes between MSEs and MEs. However, this framework has not yet been applied in real-world settings, and there is a lack of empirical evidence regarding its practical utility in guiding MSMEs through the S-I4.0 integration process. Furthermore, existing literature reveals a gap in theory-driven studies that employ technology-adoption and related models within the MSME context (Loo et al., 2023; Amornkitvikai et al., 2022). Therefore, this study conducts empirical research involving six enterprises (three MSEs and three MEs) using a multiple-case study approach, employing the analytical lenses of the Practice-Based View (PBV) and Dynamic Capabilities Theory (DCT).

This approach provides new empirical insights into how MSMEs perceive and respond to external environmental changes, facilitating quick detection and response in decision-making related to adopting new technologies, processes, products, services, and markets (Mishra and Kiran, 2025); within a S-I4.0 perspective (Caiado et al., 2024). Recent high-quality studies from 2025 further underscore the relevance of this research: for instance, (Ingaldi et al., 2025) examine how collaborative platforms and shared infrastructures influence resource allocation among MSMEs to foster effective digital-sustainable integration, while (Abdallah et al., 2025) demonstrate that supply chain capabilities and innovation fully mediate the positive impact of Industry 4.0 adoption on supply chain performance, offering robust empirical support for firms pursuing S-I4.0 transitions. This approach enables the generation of novel insights into how MSMEs perceive and respond to external environmental shifts, thereby enhancing their capacity for timely decision-making in the adoption of new technologies, processes, products, services, and market strategies (Mishra and Kiran, 2025) within the context of S-I4.0 transformations (Caiado et al., 2024). Taken together, these elements reinforce the importance of advancing context-sensitive, evidence-based guidance to support MSMEs, particularly MSEs and MEs, in navigating the complexities of S-I4.0 integration within their supply chains.

To achieve its primary objective, this paper is structured in six sections, the first being this introduction. Section 2 provides the theoretical background supporting the research. Section 3 describes the adopted research method. Section 4 presents the results of the multiple case study. Section 5 presents the discussion, and Section 6 concludes the research.

This section introduces the two concepts that are the basis of this research (i.e. sustainability and I4.0). It then presents the need for integration as a main pillar for organizations' competitiveness nowadays, focusing on MSMEs. Additionally, it provides a foundation for research on the pressing need to further investigate the theories and models of technology adoption by MSMEs, as highlighted by Loo et al. (2023), suggesting the use of PBV and DCT as lenses for research on S-I4.0 integration.

Organizations have faced various challenges associated with emerging concepts that shape their organizational structures and impact industrial competitiveness. Herein, sustainability and I4.0 play important roles (Caiado et al., 2024), and their interplay serves as the background for this research. Sustainability is directly associated with the ability to satisfy the needs of the present without compromising the ability of future generations to meet their own (Brundtland, 1987). Its primary goal is to ensure long-term well-being, while the Triple Bottom Line (TBL) framework (Elkington, 1994) expanded its scope beyond economic performance to encompass environmental and social dimensions (Sahoo and Upadhyay, 2024, Abraham, 2024). Organizations adopting TBL principles began evaluating performance holistically—considering profit, people, and planet—as interdependent drivers of enduring success. Practicing sustainability is intrinsically associated with a holistic and responsible view of the role of organizations and their impacts on society. In business environments, it encompasses adopting practices and technologies that aim to minimize the adverse effects of human activities on the environment and culture, ensuring long-term viability (Florez-Jimenez et al., 2025). Also, it has become a differentiator and a fundamental tool for organizations to help mitigate urgent global problems, such as climate change, resource scarcity, environmental degradation, and increased social inequalities (Varzakas and Antoniadou, 2024, Kulkarni et al., 2024, Adanma and Ogunbiyi, 2024). Recent works further reinforce sustainability as a central pillar for innovation and competitiveness (Raymond et al., 2023, Fletcher et al., 2024), positioning it as a strategic necessity for industries seeking a balanced and inclusive future (Kaswan, 2025).

The term I4.0 emerged in 2011 as part of the German government's strategic vision to promote the computerization of manufacturing, in the context of discussions on integrating advanced digital technologies into the organizational environment (Galizia et al., 2023). The central objective was the transformation of the German industry through the exploration of new technologies in a highly flexible environment that enables the customization demanded by international markets (Parashar et al., 2023). The new era is based on intelligent industries, with the interconnection and interoperability of machines, systems, and processes, and the possibility of executing tasks in an autonomous and decentralized way, generating greater efficiency and competitiveness. In this context, there is a substantial transformation of traditional production models, with continuous innovation as the new normal in I4.0 organizations. (Kolasani, 2024, Tortorella et al., 2022). Other countries reacted quickly when they realized the success of the German vision, such as Japan with Society 5.0, France with the terms Industrie du Futur and New Industrial France, Italy with Piano Industria 4.0, the United States of America with Manufacturing USA (MUSA), China with Made in China (2025, Portugal with the same term Industria 4.0, among others, which demonstrates broad adherence to the I4.0 concept. The technologies inherent to I4.0 include Big Data Analytics, Additive Manufacturing/3D Printing, Sensor and Measurement Technologies, IoT, Virtual/Augmented Reality, Collaborative Robotics, Simulation, Artificial Intelligence, Wireless Connectivity, Cloud Computing, Industrial Cybersecurity, and Blockchain (Tiraboschi and Seghezzi, 2016, Li, 2018, Santos et al., 2018, Holroyd, 2019, Folgado et al., 2024). I4.0 requires a significant change in processes, people, and technologies (PPT). It is essential to structure new training and encourage the development of new skills, whether for company employees or to meet job-market training needs. In practice, the impacts of adopting I4.0 go beyond the internal environments of industries, requiring the direct involvement of society from the initial stages, with total commitment and co-responsibility (Frederico et al., 2023, De Giovanni, 2023). Building on a growing body of research, recent studies further emphasize the strategic and operational dimensions of digital transformation in supply chains. For instance, (Abdallah et al., 2025) demonstrate that Industry 4.0-enabled supply chain performance depends on supply chain capabilities and innovation, while (Abushaikha et al., 2025) emphasize the strategic role of Big Data Analytics in enhancing supply-chain resilience and quality management. Likewise, (Younis et al., 2026) propose a comprehensive framework for the successful adoption of IoT in supply chains, reflecting the growing complexity of digital transformation across industries. These findings align with the notion that the diffusion of I4.0 across global economies is both a technological and social transformation, requiring collaborative, adaptive, and ethical strategies (Younis et al., 2024).

In this context, integrating sustainability with the principles of I4.0 (S-I4.0), in addition to the organization's sustainability objective, aims to increase efficiency, reduce losses, and minimize environmental impacts, among others (Abdullah et al., 2023). Organizations are increasingly called upon for more active participation, where resilience, responsibility, and performance must be considered far beyond the economic dimension inherent to the process but also directly associated with best practices that contribute to a better world for all (Rocha et al., 2022, Tang et al., 2022, Behl et al., 2023, Nascimento, 2024). Some of the main benefits for organizations are (1) Resource efficiency (Javaid et al., 2022), (2) Transparency and Traceability (Gazzola et al., 2023), (3) Smart Manufacturing (Singh et al., 2023, Atieh et al., 2023), (4) Circular Economy (Kazancoglu et al., 2023, Alka et al., 2024), (5) Predictive Maintenance based on I4.0 technologies such as IoT and A.I. (Nagaty, 2023, Abbas, 2024), (5) Training (Sharma and Kohli, 2023, Ajayi and Udeh, 2024), and (6) Regulatory compliance (Tripathi and Gupta, 2021, Hajoary, 2022). Empirical evidence supports that S-I4.0 enhances competitiveness while fostering social and environmental performance (Rocha et al., 2022, Tang et al., 2022 and represents a strategic approach for organizations to advance technologically in a sustainable way (Qureshi et al., 2023, Caiado et al., 2025, Mackiewicz and Götz, 2024). Furthermore, Kaswan (2025) and Mohan et al. (2025) show that aligning digital transformation with environmental and social objectives, through approaches such as Green Lean Six Sigma, strengthens operational excellence in MSMEs. Complementarily, Kaswan et al. (2025) and Santiago et al. (2025) highlight the transition toward Industry 5.0, emphasizing human-centric and sustainable innovation principles. These contributions reinforce the need for digital supply chain transformation to be accompanied by sustainability-oriented frameworks to achieve long-term strategic alignment. As such, a more responsible and ethical path is paved, aligned with the United Nations (UN) Sustainable Development Goals (SDGs) (Varela et al., 2022, Abramovich and Vasiliu, 2023). Furthermore, concerning S-I4.0, a more holistic view positively impacts operational performance and, consequently, the organization's competitiveness. (Lista and Tortorella, 2022, Caiado et al., 2024, Syversen et al., 2024). Despite the substantial body of research addressing S-I4.0, additional efforts are still required to deepen understanding of its mechanisms and outcomes (Caiado et al., 2024, Sundarakani et al., 2024), particularly regarding its practical implementation within the specific context of Micro, Small, and Medium Enterprises (MSMEs). These organizations face unique constraints and opportunities that significantly differentiate them from larger firms (Machado et al., 2021, 2024, Vaezinejad et al., 2024).

MSMEs can be defined in different ways. The authors of this paper follow the European Union definition in Recommendation (2003/361/EC (European Commission, 2003), which member countries adopt to ensure uniform treatment of MSMEs. The ranges are based on the number of employees and turnover (revenue/annual balance), as follows: (1) Microenterprise: Number of employees: Less than 10, revenue or annual balance: Up to 2 million euros, (2) Small enterprise: Number of employees: Less than 50, revenue or annual balance: Up to 10 million euros; (3) Medium enterprise: Number of employees: Less than 250, revenue: Up to 50 million euros or Annual balance: Up to 43 million euros. This distinction is important because of the practices adopted, such as access to funds and financing explicitly targeted to each company size, primarily aimed at promoting economic development, innovation, and sustainability. In this study, the MSMEs are grouped into two blocks, one for MSEs and the other for MEs.

MSMEs are fundamental to the economy of any country (Loo et al., 2023), playing a crucial role in several aspects. The main contributions of MSMEs are: (1) Job Generation; (2) Contribution to gross domestic product (GDP); (3) Regional Development (decentralized economic growth); (4) Innovation and Diversification (despite the greater difficulty in obtaining capital and investing in new technologies, MSMEs have an excellent capacity for innovation due to their power to adapt to survive); (5) Social and Financial Inclusion (opportunity for entrepreneurs from less favored economic classes) and, finally, (6) Integration in the Supply Chain (MSMEs act as suppliers of inputs, products, and services for large companies. Therefore, they are part of essential production chains, especially in sectors such as agroindustry, commerce, and technology (Verma, 2019, Gupta et al., 2023, Amofa et al., 2023, Zaibun, 2024). These roles highlight that MSMEs are pivotal for sustainable and inclusive economic growth and should therefore be prioritized in digital and industrial transformation agendas.

MSMEs have aimed to adapt to the new reality caused by the integration of S-I4.0 in supply chains, aiming to be more efficient and competitive by combining the digital transformation of industrial processes with practices that promote economic, environmental, and social sustainability (Qureshi et al., 2023, Intalar et al., 2024). To make this happen, MSMEs have been implementing technologies aimed at sustainable practices, such as: (1) Adoption of green technologies such as IoT and Sensors (to monitor the use of resources such as water and energy) and renewable energy (solar or wind sources to reduce dependence on fossil fuels and costs) (Hui et al., 2023, Tripathi et al., 2024, Alkhodair and Alkhudhayr, 2025), (2) Energy efficiency (automation and digitalization allow MSMEs to use energy management systems, in addition to the use of data analysis and A.I. in preventive maintenance of equipment, avoiding unexpected downtime and waste) (Abouelyazid, 2023, Mohan et al., 2025), (3) Circular economy practices that promote resource recovery and waste minimization through machine learning–based frameworks (Mondal et al., 2023, Sabale et al., 2024), (4) flexible and customized production enabled by additive manufacturing and digital supply chain integration platforms that improve coordination and reduce transport-related impacts (Alves et al., 2024, Ingaldi et al., 2025), (5) employee training and awareness programs in sustainable and digital practices (Alfarizi et al., 2024), and (6) Collaboration and alliances so that MSMEs can access open innovation systems (sharing knowledge and resources to develop sustainable solutions collaboratively) and government support stimulated with financing and resources aimed at encouraging the adoption of sustainable practices (Phonthanukitithaworn et al., 2023, Agrawal et al., 2024). Consequently, the successful integration of S-I4.0 in MSMEs depends on the balance between barriers and enablers that shape their transformation pathways and long-term competitiveness. Machado et al. (2021) identified the main ones for MSMEs, as displayed in Table 1, together with their indicators, as reported in Machado et al. (2024).

The integration of S-I4.0 in supply chains is crucial for MSMEs to promote sustainable development and increase competitiveness in current and future markets (Alfarizi et al., 2024). Recent studies emphasize that digital transformation and sustainability-oriented practices, when properly aligned, allow MSMEs to increase efficiency, resilience, and innovation potential (Alkhodair and Alkhudhayr, 2025). Nevertheless, there remains a significant need for further research in the S-I4.0 domain, particularly focused on MSMEs, to better understand the mechanisms that facilitate the convergence of Industry 4.0 principles with sustainability imperatives across supply chains (Mohan et al., 2025). Advancing this line of inquiry is essential to equip MSMEs with strategic frameworks that enable them to overcome barriers, leverage enablers, and integrate S-I4.0 practices effectively. By filling this gap, the promotion of a more sustainable future for MSMEs becomes evident, allowing them to thrive in the rapidly evolving environment and integrate S-I4.0 into supply chains. This objective is encapsulated in RQ.

Machado et al. (2024) conducted the first attempt to address this RQ by offering a novel S-I4.0 Framework that highlights specific differences between MSEs and MEs. These differences stem from their characteristics, operational scales, access to resources, regulatory environment, and roles (Anaman et al., 2023, Bueno-Pascual, 2023). Treating MSEs and MEs as separate analytical entities allows for a more nuanced assessment of their roles within the broader economic, environmental, and social context. Comprehending these differences is significant for formulating effective sustainable development strategies (Hernández et al., 2024), as they influence resource allocation, business support mechanisms, and the overall impact of enterprises on sustainable growth trajectories. Acknowledging their differences can lead to more focused policies, tailored support, and better outcomes for businesses at all levels, fostering a vibrant and diverse landscape (Bradač Hojnik and Huđek, 2023). Although shared features may justify collective treatment in specific contexts, recognizing the unique needs of MSEs and MEs is fundamental for designing successful economic and sustainability initiatives (Ma et al., 2023). In this respect, Machado et al. (2021) identify the main barriers and enablers affecting MSMEs in the S-I4.0 context, as well as the causal relationships among these constructs, concluding that company size significantly influences their behaviour and transformation pathways. They suggest that the S-I4.0 journey for MSEs and MEs should be approached differently within their supply chains; however, such differentiation still requires further empirical validation to fully address the research question of this study. Accordingly, Figures 1 and 2 present the Machado et al. (2024) framework for S-I4.0, focusing respectively on MSEs and MEs. They embrace the dominance of each barrier and enabler concerning the TBL (economic, environmental, and social) dimensions (“X” axis) and their relationship to the PPT mechanisms (people, process, and technology) (“Y” axis). They distinguish causal (blue) and effect (red) conditions and depict influence relationships for the barrier and enabler groups (arrows in shades of green indicating the origin and destination of each relationship), that is, who influences whom in the established relationships.

PBV is a crucial perspective in strategic management, emphasizing the role of organizational practices in shaping performance and competitive advantage. Unlike traditional resource-based views that focus on tangible assets, the PBV highlights the dynamic activities organizations employ to leverage these resources effectively. Its core tenets include the emphasis on practices themselves, contextual interaction, performance replication, and the embedding of dynamic capabilities that evolve practices over time (Foss and Ishikawa, 2007, Tian et al., 2023, Supramono et al., 2025). From the PBV perspective, organizations are seen as dynamic entities that adapt through continuous refinement of their practices, thus enabling responsive adjustment to internal and external challenges (Skalli et al., 2024). This view provides insight into how everyday operations and practice innovation can serve as vehicles for sustainable competitive advantage and enhanced performance (Shahzadi et al., 2024, Caraka et al., 2025).

This research adopts a PBV theoretical perspective, as practices enable organizations to transfer and replicate activities. Moreover, the level of an organization's performance is contingent upon both the adoption and deployment of specific practices and the interplay among these practices (Bromiley and Rau, 2016). While the initial PBV elucidates the connection between organizational practices and performance, it can also be applied to an inter-organizational level of analysis (Carter et al., 2017). Within the S-I4.0 domain, PBV becomes instrumental in explaining which practices support or hinder sustainability, and how digital technologies, supply chain practices, and outcomes interrelate (El-Garaihy et al., 2022, Belhadi et al., 2021, Schilling and Seuring, 2023).

To complement this perspective, the study also draws on DCT, initially presented by Teece et al. (1997), which offers a strategic lens for understanding how organizations adapt to rapidly changing environments that continuously affect their resource bases. It goes beyond the traditional Resource-Based View (RBV) theory, focusing on reconfiguring resources to maintain competitiveness. DCT builds upon and extends the RBV of the organization (Ambrosini and Bowman, 2009), facilitating resource reconfiguration beyond the traditional RBV, particularly in the context of the need to adapt, innovate, and create sustained competitive advantage (Teece, 2007, 2014, Al-Khatib et al., 2024), which opens avenues for its use within the scope of S-I4.0 integration for MSMEs along their supply chains.

DCT identifies three core processes necessary to develop dynamic capabilities: (1) Sensing: Detection of opportunities and threats in the competitive environment, (2) Seizing: Mobilization of resources and quick responses, (3) Transforming: Reconfiguration of organizational assets to remain relevant and competitive (Teece, 2007). It comprises adaptive capabilities (i.e. aligning resources with environmental changes), absorption capacities (i.e. recognizing and applying external knowledge), and innovative capabilities (i.e. developing new products, services, or processes) (Pinto et al., 2023, Kong and Feng, 2024). In volatile, competitive, and globalized contexts, DCT helps firms sustain flexibility, competitive advantage, and survival under uncertainty (Teece, 2014, Farzaneh et al., 2021, Liu et al., 2024). Because MSMEs often operate with constrained resources, DCT is particularly relevant: it enables resource reconfiguration, agility, and strategic responsiveness, which are critical under rapid environmental shifts (Pertherban et al., 2023, Tarihoran et al., 2023, Beigi et al., 2023, Supramono et al., 2025).

Thus, based on the expositions, employing PBV and DCT theories in this research encompasses the environment in which MSMEs operate, making them particularly relevant lenses due to the dynamic nature of these organizations' activities.

A multiple case study (MCS) approach was adopted, given its strengths in enhancing the depth and reliability of findings (Ding and Hernández, 2023), and in offering a robust framework for applying and evaluating theoretical models (Kreuter et al., 2022). This methodological choice enriches the study and generates innovative knowledge to both academics and practitioners (Butt et al., 2024). The method followed the well-established structure proposed by Yin (2014), recognized for its rigor and systematic procedures in investigating complex phenomena within real-world contexts. To ensure ethical standards, a consent form was provided to the primary representative of each MSME prior to the interview, which was conducted using a structured script. The script included targeted questions and supplementary prompts, administered by one of the authors. The overall approach was primarily explanatory, aiming to capture the real-life business environments of the participating firms. It also incorporated a descriptive dimension, illustrating the phenomenon within each organizational context and analyzing causal relationships, effects, and influences related to main barriers, facilitators, and their respective indicators for S-I4.0 integration along their supply chains. The following subsections outline the methodological steps undertaken to develop the practical guide, as synthesized in Figure 3.

The unit of analysis comprised MSMEs, categorized into MSEs and MEs. To address the research question —whether these categories follow similar or differentiated pathways in integrating S-I4.0 into their supply chains —six cases were purposefully selected: three MSEs and three MEs (see Table 2). This balanced composition enables comparative analysis across firm sizes, reflecting the ongoing debate in the literature regarding structural and strategic differences between these groups (Machado et al., 2024, Passaro et al., 2023).

The selection was guided by theoretical sampling principles, ensuring that all cases share two critical characteristics: (1) they operate under significant resource constraints typical of smaller firms yet are strategically committed to integrating S-I4.0 into their supply chains; (2) they are impacted by digital transformation, requiring continuous adaptation to volatile environments.

This configuration allows the study to capture heterogeneity in transformation pathways while maintaining comparability across cases. Under the analytical lenses of DCT and PBV, these firms exemplify contexts in which rapid adaptation, innovation, and capability development are essential for achieving sustainable competitive advantage (Schilling and Seuring, 2023; Al-Khatib et al., 2024). Their inclusion is further justified by evidence that they actively pursue knowledge transfer, skill development, and process reconfiguration, which are critical enablers of resilience and competitiveness in a volatile business environment (Mishra and Kiran, 2025).

By selecting cases that meet these criteria, the study ensures analytical depth and theoretical relevance, enabling insights into how MSMEs operationalize S-I4.0 under resource constraints and whether firm size influences the trajectory of digital and sustainable transformation.

Different primary data collection methods were applied, as follows. Qualitative face-to-face interviews were conducted using the key informant technique (Marshall, 1996) with representatives from the six organizations listed in Table 2. The respondents from MSEs are directors and majority partners, while those from MSEs are executive directors (CEOs) and managers, with a complete view of the organization. The interviews were structured in parts: (1) a general description of the company; (2) fundamental processes and their applications; (3) applied technologies; (4) employees' way of working (in-person, remote, or hybrid); (5) relationship with main stakeholders (customers, suppliers, allies, among others); (6, 7 and 8) confirmation of the relevance for companies of barriers and enablers, and their respective indicators presented in the study; (9) verification of the suitability of the cause, effect, and influence relationships for the barriers and enablers presented in the study; (10) respondents' perception regarding the applicability of the Framework. Interviews were conducted in September and October 2024 and lasted an average of 130 min, with the shortest taking 120 min and the longest 140 min. An electronic report was generated for each interview in the original language (Alam, 2021). Direct on-site observation provided rich contextual data, allowing researchers to witness behaviors, interactions, and processes in natural environments, minimize recall bias, and capture nonverbal insights. This was combined with shadowing, which facilitated a holistic understanding of phenomena and enriched the overall results (McDonald and Simpson, 2014). Finally, internal corporate documents were analyzed to evaluate available data in each enterprise's corporate information systems, contextualize them, and consider the interpretative nature of documentary analysis contained in the data (Bowen, 2009). All collected data were linked to the research proposals by identifying patterns and constructing relevant explanations (Kreuter et al., 2021). The criteria used to determine significance included: (1) recognizing the interviewee's acknowledgment; (2) identifying barriers and enablers in the MSE or ME environment; (3) recognizing the applicability of indicators for each barrier and enabler as a basis for building a metrological indicator; (4) ensuring cause-effect-influence concordance; and (5) adhering to the S-I4.0 integration framework in the MSME business environment.

To ensure the robustness of the research, a structured fieldwork protocol was implemented for both interviews and direct observations. The interview process adhered to the qualitative guidelines proposed by Myers and Newman (2007), while observational data collection followed the established procedures outlined by Seeling et al. (2021), in alignment with (Yin, 2014)’s methodological framework for case study research, to ensure consistency and reliability. In addition to primary data, internal documents and reports were systematically reviewed to validate and enrich the understanding of practices within the participating enterprises. Respondents/observers reviewed all drafts captured throughout the research process. The technique of checking patterns against the respective frameworks was adopted. The adoption of a multiple-case study design addressed the inherent limitations of single-case studies, particularly concerning the generalizability of findings, thereby strengthening external validity through comparative analysis. Different data-gathering methods were applied to enhance the trustworthiness and validity of the findings through triangulation, by comparing and integrating data from multiple sources (Voss et al., 2002) to support a more nuanced and credible interpretation and reinforce the rigor of the data analysis process.

Research findings were analyzed in two steps: within-case and cross-case analysis. The within-case analysis focused on understanding each case in depth, offering practical strategies for systematic analysis, and emphasizing qualitative aspects of case study research (Stake, 1995; Yin, 2014). The cross-case analysis compared cases to derive insights that could contribute to theoretical frameworks, emphasizing coding, pattern identification, and comparisons across cases to conclude (Eisenhardt, 1989; Miles and Huberman, 1994). This research adopts DCT and PBV as complementary analytical lenses to examine the integration of S-I4.0 in MSMEs. DCT is particularly well-suited to the MSMEs context, where firms must respond swiftly and flexibly to rapidly changing environments shaped by digital transformation. The theory emphasizes the processes of sensing, seizing, and transforming, which align with the iterative nature of continuous improvement cycles such as Plan-Do-Check-Act (PDCA) (Realyvásquez-Vargas et al., 2018; Tsutsui, 1996), commonly observed in MSMEs navigating S-I4.0 transitions. Recent studies reinforce the relevance of dynamic capabilities in enhancing MSMEs' adaptability and resilience. For instance, (Baraka et al., 2025) identify key dynamic skills critical for navigating uncertainty, while (Islamuddin et al., 2025) demonstrate that agility, as a mediating dynamic capability, significantly boosts performance outcomes. Similarly, (Kahveci, 2025) presents a model linking dynamic capabilities, digital competencies, and leadership to competitive advantage under sustainability pressures. In parallel, PBV offers a complementary perspective by focusing on how firms develop and leverage internal routines and practices to build and sustain competitive advantage. Within the MSME context, PBV helps illuminate how repeated, adaptive practices —such as adaptive selling, continuous learning, and process reconfiguration —contribute to strategic positioning, particularly under resource constraints and volatile market conditions. By integrating DCT and PBV, this study conceptualizes MSMEs as dynamic entities whose competitiveness arises from the interplay between capability development and the deployment of strategic practices. This dual-lens approach enables a nuanced understanding of how MSMEs operationalize S-I4.0 initiatives, manage environmental uncertainties, and pursue sustainable performance across their supply chains.

This section presents the main research findings of this paper. It is organized into two main subsections: one focused on the multiple case study results, and the other on a practical guide to integrating S-I4.0 into the supply chains of MSMEs.

This section presents the six companies' perspectives on the S-I4.0 framework proposed by Machado et al.(2024).

The representative from MSE1 acknowledged the value of all dimensions of the TBL and PPT mechanisms, as its clients demand and monitor the provision of high-value services with direct impacts on the supply chain, particularly customers and suppliers. The DCT lens is highly suitable for the company, which operates in a sector characterized by rapid technological transformations. MSE1 continually adapts to changes and simultaneously innovates to remain sustainably competitive. The company fully agrees with the framework's adherence and applicability to operational reality.

The interviewee for MSE2 highly praised the framework's axes (TBL and PPT), highlighting the classification of dominance within them. He noted that the cause-and-effect classifications for each barrier and enabler enhance the understanding of the dynamics involved in mitigating barriers or enhancing enablers. He stated: “… visualizing the dominance on both axes also draws attention to the points of greatest impact”. The DCT lens is highly beneficial due to its adaptive capacity, which addresses external environmental changes and significant variations in customer demand. The framework can serve as a guide for bridging gaps in the conduct and control of sustainable adoption within the company. It was considered understandable, applicable, and valuable. The interviewee recommended developing a guidebook (printed and electronic) or an application to facilitate the framework's use, given its perceived applicability.

MSE3 found the dominance in the TBL and PPT axes very useful for understanding the potential impacts of acting on each barrier and enabler. It was perceived as more relevant for detecting opportunities and threats and for transforming available technical and human resources. The most important capabilities for the company are its adaptability and innovation. The interviewee stated that the framework could serve as an excellent guide for a structured and systematic process. The framework is viewed as understandable, applicable, and valuable.

The ME1 interviewee provided separate considerations for the TBL and PPT axes. The Framework is very applicable to economic and social impacts for the TBL axis. For the PPT axis, the impact on processes is crucial as it requires the involvement of the other axis mechanisms. The DCT lens is beneficial for the company, particularly in its ability to absorb external knowledge through technology transfer agreements or development alliances with research centers. The Framework could serve as a step-by-step guide, offering a clear overview of how to conduct and control sustainable adoption within the company. It suggests creating an APP to record the historical evolution of measurements. All interviewees, especially the CEO, expressed the Framework's usability and applicability to the company.

The ME2 interviewee emphasized the importance of understanding dominance within each axis (TBL and PPT). The company is particularly concerned with the PPT processes and technology axes, as well as the economic dimension of the TBL axis, given their relevance to operational performance. From the DCT perspective, all capabilities are valuable, with particular emphasis on the ability to absorb external knowledge through aggressive talent acquisition. The framework is very useful, especially for senior managers lacking technical knowledge. The applicability of the framework is complete and helps in reflecting on both mitigating barriers and encouraging enablers.

The interviewees from ME3 found the framework applicable to their company for several reasons. It facilitates the perception of barriers and enablers, their cause-and-effect relationships, and their influences. The dominance of the TBL and PPT axes is useful, even though non-dominant impacts are occasionally necessary. The interviewer highlighted that this research limitation could be explored in future studies. From the DCT lens, adaptive capacity is most relevant to the company's sector, as customer demands vary across contract characteristics and service environments. Intensive labor demands much attention to the people, processes, and social aspects involved. The framework provides materiality at all stages of implementation, helping senior management understand its importance throughout the digital transformation.

The three MSEs realize the importance of barriers B1, B5, and B7. Technical knowledge, economic aspects related to OSCM, and senior management's commitment were identified as key barriers in the business environment of MSEs. All MSEs perceive alignment between B7 and E1, obviously due to the importance of top management commitment and the importance of strategic alignment for the development and sustainability of MSEs. E4 is also perceived as a key enabler of this dynamic, particularly regarding the importance of data flow consistency for MSEs. Two of the three MSEs associated B3 with the mitigation of B7 and the enhancement of E1, which makes perfect sense in the Barriers Framework, remembering that this study does not cross cause, effect, and influence relationships between barriers and enablers. In the case of these three MSEs, senior management are the shareholders themselves who are directly involved in the activities. While this offers greater agility, it also creates an overload of activities. Added to this are the challenges posed by the growth of MSEs, where the economic costs and the importance of correct decisions regarding operational platforms do not lead to decision-making errors.

B2 is a topic considered necessary for MSEs, as the market consistently highlights cybersecurity-related issues. MSEs that do not have cybersecurity as their primary activity must be aware of decisions that require investments in systems and ensure that B2 mitigation is included in their solutions. Another concern is that excesses are not committed by MSEs, resulting in prohibitive fixed and recurring costs that negatively affect their competitiveness. B3 is also considered necessary, expressed strongly by MSE1 and MSE2. MSE1 highlights that adopting innovation in governance and compliance must be objective, without a finish line to be tirelessly pursued.

B4 follows a similar logic to B6: since R&D is not the MSEs' core business, this investment must be made through institutions dedicated to this purpose, with the scope of their projects to invest in small companies. Regarding B6, MSE2, and MSE3, they state that they do not have the structure to mitigate this barrier, whereas MPE1 operates through business representative institutions but recognizes that it is a slow process and requires continuous investment of time, usually from a partner dedicated to other strategic activities for the company. E8 is directly related to B4, and the procedure should be similar from the MSEs' point of view.

For B8, in energy terms, MSEs show interest in using renewable energy. The adoption of solar panels in the locations where they operate is well-regarded by MSEs. Regarding alternative resources, MSE1 and MSE3 mention that they prefer biodegradable items or those with low energy consumption in their purchasing processes. In general terms, these are the points available to MSEs in the view of those interviewed.

Returning to enablers, E2 draws the attention of MSEs. MSE1 systematically carries out actions aimed at empowering employees, sharing knowledge, and fostering effective communication, but emphasizes that these actions could be even more frequent and monitored. MSE2 makes a similar mention and highlights the lack of systematization and formalism to ensure further improvements. MSE3 highlighted that the company's growth will consequently open opportunities for employees who agree and practice activities in this direction.

For E3, MSE1 recently underwent an internal transformation driven by the evolution of I4.0. Its entire operational platform was migrated from a traditional solution to a modern cloud solution with automation and artificial intelligence. The other two, MSE2 and MSE3, did not exhibit materiality in their informal procedures and innovation incentives. In the view of MSEs, the stimulus for E5 must come from interdisciplinarity between activities and employees of MSEs, aimed at functional flexibility.

E6 should be seen as a great window of opportunities for MSEs. Directly and indirectly, all MSEs perceive participation in larger, more structured supply chains as a clear opportunity for sustainable growth. MSE1 seeks out its clients' customers to present its solutions and improve the conversion rate of commercial proposals. Regarding E7, perception and practice are similar to B6. Due to the size of the MSEs, the reaction is passive, with little room to change government pressure, especially. The shortest and most effective way is through institutions that represent companies with influence.

B1 and B7 are highlighted by the MEs as central barriers, in line with the Framework presented. Technical knowledge and senior management commitment were recognized as key barriers to be mitigated for the integration of S-I4.0 into MEs supply chains. They recognize alignment between B7 and E1, with ME1 and ME2 highlighting that the E1 enhancement must be recurring and formalized, as the increase in senior management's commitment is directly related to more efficient strategic alignment.

Regarding B2, the responses of the three MEs were significant and complementary. ME3 focuses its concern on employee and customer/contract data. ME2 is the most generic aspect of customer information and data security based on the automation developed that allows queries to customer databases, for example. Finally, the third ME1 is more concerned with employee access levels and control over information handling. B3, as B2, is perceived peculiarly by each of the three MEs. ME1 associates the barrier with the cultural aspect of insecurity generated by change, ME2 is more aggressive in creating incentives and benefits for changes that generate positive impacts, and finally, ME3, being a company with low use of technology, understands that technological innovations must be negotiated individually or in groups less formed by departmental leaders.

Concerning B4, ME2, and ME3, understand that it is a significant barrier and challenging to access, in addition to the excessive bureaucracy involved. ME1 already uses partnerships and alliances in R&D projects, mainly with university research centers, with good results, but, in the company's opinion, it could be much better if there were greater attention and focus from the research institutions. As commercial and marketing development is very costly, this aspect is often disconnected from the R&D process in most cases, and for ME1 there is no way to bear these risks and costs without contractual guarantees.

For B5, the three MEs realize the relevance and complexity of this barrier. For ME1, the most significant challenges are related to logistics and production capacity. For ME2, the economies of scale with robotization, but also remember that the adoption of cloud solutions mitigates, in the short term, some high investments in equipment and software. For ME3, the logistics issue is the biggest challenge due to the dispersion of contracts and locations to be served/supplied.

B6 has a different reality for each of the three MEs. ME3 does not perceive a low impact on the company and is not concerned with mitigating it. ME2 sees volatility in the high-tech market, with regulatory bodies and legislators lacking complete understanding, forcing the company to remain alert to respond to the changes imposed. Company ME1 experiences constant changes, for example, in import rates for inputs and products, which directly alter the market balance.

Considering now B8, ME1 invests in a system for capturing and storing rainwater. ME2 looks to reduce spending on alternative energy sources but does not have a short-term priority for these investments. ME3 constantly seeks inputs with a lower environmental impact. Despite different solutions, it can be said that B8 mitigation is a reality for MEs.

Returning to enablers, E2 draws the attention of MEs who agree with its relevance in the Framework. ME1 understands that the three aspects covered in the enabler must be enhanced in an aligned manner, as they are entirely related to one another. ME2 and ME3 state that they have systematized processes to stimulate this enabler. In a cross-case analysis, the difference perceived by the interviewer between the MEs is that in ME2, the direct support of senior management is formally evidenced through meeting minutes. For E3, ME1 has formal internal processes to encourage innovation, including financial incentives when applied with practical results (i.e. cost reduction). For ME2 and ME3, this practice is informal, but both agree and are interested in systematizing processes for stimulation and measurement.

Regarding E4, ME1 considers it essential that this flow of information works with a guarantee that it is reliable. For the company's CEO: “… it is essential for the company's sustainability that decision-makers have ready access to reliable data to make accurate decisions”. ME2 and ME3 follow the same line of thinking and have made significant investments in management and control systems in their respective companies. The difference between these two and ME1 is that the information flow is not at such an advanced stage.

For E5, the three MEs agree on encouraging interdisciplinary integration but see specific importance in projects and opportunities that require this integration across areas of competence or in the exchange of knowledge and experiences between employees. As they are service MEs, issues related to the product life cycle are minimized. E6 is relevant to ME1, especially for inputs and products with a validity of up to 60 days, which makes integration with input and logistics suppliers critical. For ME2 and ME3, this integration is also relevant because, if done well, it can positively impact on the adequate provision of services.

Regarding E8, the only company that operates in this facilitator is ME1, which encourages employees to improve relationships with research centers. In addition, it pays 100% of master's and doctoral scholarships for those employees who stand out the most. ME2 and ME3 claim to have already tried some actions, but were unable to advance in the systematization of programs. Both comment that these are laborious, bureaucratic processes that consume significant time for leaders.

For both MSEs and MEs, top management plays a pivotal role in mitigating barriers and enhancing enablers. B7 and E1 emerged in theory as fundamental, with significant influence. In practice, all interviewees emphasized the essential role of top management in integrating S-I4.0 into MSME supply chains. The lack of technical knowledge (B1) was universally recognized as critical for both MSEs and MEs. This barrier hinders the adoption and effective implementation of advanced technologies. B2 and B4 demand continuous, substantial economic investments, posing a constant challenge for MSMEs. The smaller the enterprise, the more challenging it is to overcome these financial barriers. B3 was perceived as a significant barrier by all MSMEs. Each interviewee provided complementary insights. Notably, the respondent from ME3 mentioned that, as a company with minimal use of technology in its core activities, resistance to change associated with the integration of S-I4.0 in supply chains is less significant for them. B5 was generally confirmed as a barrier for MSMEs, with challenges for MSEs due to their smaller size and greater difficulty compared to MEs. Regarding B6, there was a consensus that MSMEs have limited influence over regulatory authorities or legislative houses. Two interviewees indicated sporadic, rather than systematic, engagement with professional entities to exert influence. MSMEs are cognizant of B8, including energy consumption, waste disposal (organic or inorganic), and the purchase of environmentally friendly inputs. However, in practice, these issues have a relatively low practical impact on MSMEs´ operations.

Concerning E2, it is less of a concern for MSEs due to their smaller organizational structure. Conversely, MEs, with defined departments and hierarchical levels comprising strategic, tactical, and operational levels, place significant emphasis on employee empowerment, knowledge sharing, and effective communication processes. These factors are crucial for maintaining performance and competitiveness, justifying the greater relevance of E2 for MEs as presented in the framework. E3 is generally desired by MSMEs, which often face difficulties in structuring and systematizing processes. MEs, on the other hand, have better conditions for stimulating and rewarding innovation. Regarding solutions and consistent data flow (E4), MSEs highlighted challenges in accessing credit, which inhibit investments in overcoming this barrier. MEs provided structured responses, underscoring the importance of E4. As companies grow, addressing this barrier becomes increasingly critical, making early mitigation essential to their trajectory. Both E5 and E6 were mentioned marginally by MSE respondents and more emphatically by ME respondents. This difference is also related to the size of the company and the supply chain context in which the MSME operates. E7 proved difficult for MSMEs to address in practice. Some respondents considered it a medium-term concern or a specific action for the company. Two respondents (one from an MSE and one from an ME) expressed a desire to influence tariff increases on imports of similar products but noted that this would be a costly effort in terms of time and financial resources. E8 is relevant to MSEs and MEs, particularly those that recognize the importance of R&D and innovation in their operational matrices and value chains. However, the MEs consider the process bureaucratic, labor-intensive, and risky, as it requires effort from a structure not typically dedicated to these tasks.

Building upon the findings of the MCS, this research proposes a practical guide to support the integration of S-I4.0 into MSME supply chains. Structured into ten sequential steps aligned with the PDCA cycle, renewed upon completion of step 10 (Figure 4), the guide offers actionable insights for MSME managers. The theoretical lenses of PBV and DCT are instrumental in interpreting the dynamic environments in which these enterprises operate, with special attention to steps 2 and 10. These steps emphasize the need to assess and evolve organizational capabilities and resource configurations, which are central to both theories. While PBV helps explain how specific practices contribute to performance and value creation, DCT extends this understanding by focusing on how firms reconfigure resources to adapt, innovate, and sustain competitive advantage in volatile contexts. The integration of these perspectives not only strengthens the theoretical foundation of the guide but also informs future research by identifying mechanisms through which dynamic capabilities and resource orchestration drive effective S-I4.0 adoption in MSMEs.

The practical guide for MSMEs is structured around the four core phases of the PDCA cycle: Plan (Steps 1 and 2), Do (Steps 3 to 5), Check (Steps 6 to 8), and Act (Steps 9 and 10). In the Plan phase, enterprises identify their (MSEs or MEs), select the appropriate framework model, and define relevant indicators for each barrier and enabler, which are then measured (Step 1). These indicators are subsequently reviewed and adapted to reflect the organization's specific context and constraints (Step 2). This phase is particularly relevant from a DCT and RBV perspective, as it involves identifying and configuring internal resources and capabilities that shape the firm's readiness for S-I4.0 integration. Empirically, it enables the recognition of performance drivers, while practically, it equips managers with a structured approach to assess transformation potential. Socially, it fosters supply chain resilience and responsiveness to stakeholder expectations.

In the Do phase, managers verify whether established targets and goals align with, fall below, or exceed the company's current reality (Step 3). Based on this assessment, existing targets are maintained, or new goals are defined for each indicator related to barriers and enablers, alongside the cycle for the following review, initially recommended as 12 months but adjustable to company needs (Step 4). Simultaneously, resources are requested and managed to ensure objectives are attainable (Step 5). This phase operationalizes MSMEs' dynamic capabilities by reflecting their ability to mobilize and reconfigure resources in response to strategic goals. It also illustrates the PBV's emphasis on practice deployment and alignment with performance outcomes. From a societal standpoint, it promotes resource efficiency, environmental responsibility, and improved supply chain performance.

The Check phase begins with performance monitoring (Step 6), prioritizing the most influential indicators, B1/B5/B7/E1/E4 for MSEs, and B1/B7/E1/E2/E8 for Mes, and assessing their dominant impacts on the TBL and PPT axes of the framework (Step 7). This is followed by a comprehensive review of remaining indicators (Step 8). From a research standpoint, this phase allows evaluation of the interaction between dynamic capabilities and value generation, enriching empirical studies of S-I4.0 adoption in MSMEs. Practically, it supports evidence-based decision-making, while socially, it encourages accountability and transparency in sustainability and technological practices across the supply chain.

In the Act phase, results and impacts are evaluated with leaders and employees to foster engagement and alignment across teams (Step 9). Feedback is provided by identifying potential improvements and implementing them within the company's operational reality, promoting continuous learning and sustainable performance enhancement (Step 10). This iterative process exemplifies the dynamic nature of capability evolution and the strategic reconfiguration of resources, as emphasized by DCT. It also reflects PBV's focus on refining practices to enhance performance. Practically, it enables MSMEs to adjust strategies based on real outcomes, while socially, it contributes to the broader adoption of sustainable, digitally integrated supply chains, thereby generating shared value.

The guide offers multiple benefits for MSME practitioners seeking to implement S-I4.0 in their supply chains: (1) a step-by-step framework for structured implementation; (2) best practices and case studies for benchmarking; (3) tools and resources to support technology adoption and sustainability assessment; (4) resource management strategies to optimize operations and reduce environmental impact; (5) stakeholder engagement to foster collaboration across the supply chain; (6) performance metrics for continuous improvement; (7) guidance on regulatory compliance and standards; (viii) adaptability and scalability to fit diverse MSME contexts; (9) training and capacity-building for workforce empowerment; and (10) a long-term strategic vision for sustainable growth. Collectively, these elements reinforce the theoretical, practical, and societal relevance of applying DCT and PBV to guide MSMEs in navigating the complexities of S-I4.0 integration.

The findings highlight the wide range of opportunities that digital transformations present for MSMEs, addressing multiple calls in the literature (e.g. Mohan et al., 2025, Kaswan, 2025, Anatan and Nur, 2024, Martínez-Peláez et al., 2023, Bhatt & Kumar, 2022) to strengthen the integration of S-I4.0 in MSME supply chains. This research thereby contributes to filling the gaps identified by RQ posed in Section 1 (Ejsmont et al., 2020, Alonso et al., 2024a, b, Sabale et al., 2024, Abdallah et al., 2025). The results underscore the necessity of distinguishing between MSEs and MEs, a differentiation also noted by Passaro et al. (2023), Azis (2024), Hernández et al. (2024), as their differing scales, leadership maturity, and resource availability significantly influence how barriers and enablers shape transformation pathways. MSEs face greater constraints in terms of technological and financial capacities, while MEs tend to focus on amplifying enabling mechanisms, leveraging structured leadership, and utilizing accumulated managerial expertise. These findings align with recent advances that emphasize the importance of I-4.0 adoption in enhancing sustainable performance and innovation when aligned with environmental and social objectives through approaches such as Green Lean Six Sigma (Kaswan, 2025, Mohan et al., 2025, Shahzad et al., 2025). Furthermore, circular-economy practices and green automation, as shown by Mondal et al. (2023), Sabale et al. (2024), Ghannouchi (2023), demonstrate that digital technologies can minimize waste, optimize resource use, and extend product lifecycles, objectives that are especially relevant for resource-constrained MSMEs. By acknowledging these distinctions, stakeholders —including policymakers, industry leaders, and researchers —can design targeted frameworks that accommodate each enterprise's context and maturity level, ensuring that digital-sustainable transformation reinforces resilience, competitiveness, and inclusivity across the MSME landscape.

Building on these insights, the adoption of the S-I4.0 framework by MSME managers reveals a complex interplay of barriers, enablers, and indicators within their operational landscape, effectively converting daily challenges into concrete, actionable insights. This clarity not only elucidates the causal relationships and impacts within the framework's TBL and PPT axes but also provides a solid foundation for practical implementation. The iterative nature of the practical guide, as supported by studies conducted by Machado et al. (2024), underscores the inherent value of the framework, facilitating a continuous cycle of learning and improvement. Furthermore, integrating the Plan-Do-Check-Act (PDCA) cycle is crucial for fostering sustainable growth among MSMEs. This approach empowers managers to adapt specific indicators to their unique contexts while ensuring agility and flexibility, which is vital for navigating the complexities of sustainable business environments. As emphasized by Qureshi et al. (2023), Intalar et al. (2024), and Alfarizi et al. (2024), the ability to respond swiftly and effectively to changing dynamics is essential for long-term success. In this regard, the S-I4.0 framework functions not only as a diagnostic and planning tool but also as a strategic enabler, fostering innovation, adaptability, and resilience within MSMEs. By leveraging insights from this framework, managers can navigate the challenges of sustainable development, ultimately advancing the broader objective of cultivating more responsible, sustainable business practices. This dual function contributes to the broader goal of cultivating responsible, future-oriented business practices that align environmental objectives with operational efficiency. As a result, MSMEs are positioned as pivotal agents of transformation, driving the shift toward a more sustainable and inclusive economic landscape.

The theoretical integration of PBV and DCT provides a robust foundation for interpreting MSMEs behaviour in the face of digital-sustainable transitions. PBV emphasizes capabilities in the strategic domain, significantly influencing the performance of MSMEs by fostering agility and a heightened sense of urgency in operational processes and decision-making. This orientation is particularly critical for MSMEs in their early years, where survival and rapid adaptation to market pressures are paramount. From a research perspective, PBV provides a lens to investigate how strategic capabilities mediate firm performance under resource constraints and market volatility. For practice, it offers managers actionable guidance on prioritizing initiatives that generate tangible business value, while socially, it underscores the role of MSMEs in sustaining local economies and employment by efficiently leveraging limited resources.

Complementing PBV, DCT provides a robust framework for understanding the dynamic, evolving environments in which MSMEs operate, thereby promoting a long-term strategic perspective. By emphasizing the continuous reconfiguration of resources, innovation, and capability development, DCT enables MSMEs to build sustainable competitive advantages, adapt to volatile conditions, and respond effectively to emerging opportunities and threats. For research, DCT offers theoretical grounding to study the mechanisms through which dynamic capabilities drive resilience, competitiveness, and sustainable growth in MSMEs. Practically, it guides managers in developing adaptive strategies, while societally, it supports the creation of more resilient supply chains, environmentally conscious practices, and enterprises capable of contributing to broader economic stability and social value. This dual perspective of PBV and DCT facilitates a comprehensive understanding of MSMEs behavior, bridging short-term operational needs with long-term strategic development, as evidenced by Teece, (2007, 2014), Farzaneh et al. (2021), and Al-Khatib et al. (2024).

Finally, the within-case analysis and cross-case analyses provide nuanced insights into the differentiated experiences of MSEs and MEs in adopting the S-I4.0 framework. There is consensus among MSEs regarding the significance of B1, B5, B7, E1, and E4, while MEs align on B1, B7, E1, and E8. Although perceptions of E2 varied among Mes, no substantial modifications to the framework were deemed necessary. Cross-case analysis indicates that both MSEs and MEs recognize the importance of B7 and E1, suggesting that collaborative efforts could effectively address these issues. B1 is considered critical because technical knowledge is required to integrate S-I4.0, while concerns related to B2 increase as companies grow or innovate. In contrast, B3 is less relevant to ME3, which struggles with technology and innovation, thereby heightening sustainability risks. Continuous innovation is essential, even in traditional sectors, to mitigate such vulnerabilities. MSEs encounter challenges with B4 and B8, as they require professional financing structures for research and development (R&D) and policy implementation, alongside steep operational upgrade costs. Differences arise in how businesses engage with organizations, influencing their time management for effective representation. E2 is more significant for MEs, where information sharing enhances performance, while E3 raises cost concerns related to the structuring and monitoring of innovations. E4, like E2, stresses the importance of data-centric solutions for growth and agile decision-making. E5 and E6 present complexities due to ecosystem integration, and the absence of clear returns on investments poses significant challenges for MSMEs. E7 introduces notable difficulties, particularly in regulatory frameworks, though collaboration through cooperatives may lead to improved outcomes. While E8 offers substantial potential, excessive bureaucracy and insufficient support for R&D financing hinder MSME progress. Overall, these research findings underscore emerging literature on the distinct pathways of MSEs and MEs in integrating S-I4.0 within supply chains, as highlighted by Anaman et al. (2023), Bueno-Pascual (2023), and Hernández et al. (2024).

This paper addresses a critical gap in the literature by examining how MSMEs can effectively integrate S-I4.0 within their supply chains, providing a foundation for both academic inquiry and managerial application. It advances theoretical understanding by delving into the heterogeneity between MSEs and MEs, demonstrating how differences in firm size, resource endowment, organizational structure, and leadership maturity influence the pace and depth of adopting sustainable and digital technologies. These variations not only determine MSMEs' readiness to integrate smart and sustainable innovations but also reveal how context-dependent factors (such as institutional support, market volatility, and human capital) shape digital evolution trajectories. By clarifying these distinctions, the research contributes to a more nuanced comprehension of how smaller firms leverage dynamic capabilities to bridge structural limitations, fostering a more inclusive perspective on the digital-sustainability nexus within global value chains.

From a theoretical perspective, the study contributes to integrating the PBV and DCT lenses to explain how MSMEs combine operational efficiency with strategic adaptability. The PBV lens elucidates how performance outcomes arise from the effective configuration of tangible and intangible resources, while DCT provides insight into the mechanisms of learning, reconfiguration, and innovation that allow MSMEs to remain competitive amid technological turbulence. The deliberate choice to maintain flexible and context-specific indicators reinforces the notion of contextual dynamism, suggesting that MSMEs evolve through cycles of experimentation, feedback, and resource recombination. This adaptability not only enhances firm-level learning but also supports continuous improvement ecosystems across supply chains. The dominance patterns observed across the TBL and PPT axes establish a robust, multidimensional framework for analysing the interaction between sustainability and digitalization, offering a structured pathway for assessing trade-offs and synergies in managerial decision-making. Collectively, these insights pave the way for future research on adaptive measurement systems, resilience building, and innovation-driven growth, emphasizing how MSMEs can serve as catalysts for sustainable industrial transformation and socio-economic development.

This research also provides practical implications for integrating S-I4.0 into MSME supply chains, aiming to overcome barriers and strengthen enablers for both MSEs and MEs, while considering their distinct structural and operational characteristics. The offered practical guide emerges as a valuable resource for industry managers, grounded in findings from the MCS and reflecting the progression through OSCM amid ongoing digital transformations and S-I4.0 adoption. Additionally, it presents a comprehensive, step-by-step implementation framework, supplemented by cyclical follow-ups on specific policies established by MSMEs. This structure enables periodic reassessment and adjustment of policies, ensuring alignment with evolving technologies and sustainability imperatives.

From a managerial perspective, this study contributes by providing a flexible yet systematic framework that encourages firms to tailor indicators to their maturity level, resource capacity, and strategic priorities. By identifying where impacts are concentrated across the TBL and PPT axes, the framework empowers decision-makers to prioritize investments, enhance strategic coherence, and strengthen innovation capabilities. Embedding digital and sustainable objectives within operational practices fosters a culture of continuous improvement, resilience, and competitiveness, enabling MSMEs to position themselves as proactive actors in sustainable industrial ecosystems.

By integrating PBV and DCT lenses, MSMEs can leverage these concepts to improve their operational and strategic capabilities in rapidly evolving business environments. This approach assists MSMEs in mitigating barriers, enhancing enablers, addressing indicators, and fostering organizational agility, thereby enabling employees to navigate complex situations more effectively. Furthermore, it cultivates transformation capabilities, enhances performance measurement, promotes resource allocation to networks and alliances, and improves communication processes. As a result, MSMEs become better equipped to respond to change, focus on innovation, and sustain competitive advantages while preparing for future uncertainties.

Taken together, the offered practical guide equips MSME managers and supply chain professionals with a structured, actionable roadmap for implementing S-I4.0, aligning technological innovation with sustainability goals, while providing context-sensitive, evidence-based guidance that addresses the specific challenges these enterprises face and supports their transition toward more sustainable, digitally integrated supply chains.

This study offers valuable insights for policymakers and stakeholders seeking to empower MSMEs by enhancing their efficiency, resilience, and innovation capacity through evidence-based public–private initiatives. A lack of nuanced understanding of the distinct roles and challenges of MSEs and MEs often hinders the development of targeted, effective interventions. By integrating perspectives from PBV and DCT, this research provides a robust framework for designing policies that not only foster technological adoption and innovation but also strengthen MSMEs' dynamic capabilities, such as sensing opportunities, reconfiguring resources, and seizing emerging markets.

From a policy standpoint, the findings underscore the importance of cultivating multi-level collaboration ecosystems that connect government, academia, and industry to accelerate the diffusion of S-I4.0 practices. Recommended initiatives include fiscal incentives for digital adoption, sustainability-oriented procurement programs, and innovation hubs tailored to MSMEs' maturity levels. For stakeholders and development agencies, the study offers actionable guidance for designing context-sensitive support mechanisms, capacity-building programs, and digital infrastructure that help reduce structural asymmetries between smaller and larger enterprises.

Furthermore, developing a practical, adaptable guide based on the study's findings serves as a bridge between theory and implementation. This guide enables MSMEs to effectively integrate S-I4.0 principles into their supply chains, while also providing policymakers with tools to monitor impact through adaptive indicators aligned with the TBL and PPT dimensions. Ultimately, the research contributes to a comprehensive policy and managerial roadmap that promotes sustainable competitiveness, inclusive industrial development, and a more resilient innovation ecosystem.

Hence, this study provides policymakers and stakeholders with a strategic framework to support MSMEs —key contributors to national economies —by addressing structural challenges and enabling sustainable digital transformation, particularly in emerging economies where resource constraints and institutional gaps demand targeted, context-sensitive interventions to foster inclusive industrial development.

Distinct approaches are required for MSEs and MEs. While both groups can embark on a shared S-I4.0 journey, they must acknowledge their unique sizes, structures, and operational contexts. These differences profoundly affect the strategic and operational decisions and actions managers undertake. Although the foundational journey to incorporate S-I4.0 remains consistent, the practical guide application highlights the necessity of recognizing the distinct dynamics between MSEs and MEs. Variables such as company size, internal structure, production scale, employee expertise, resource accessibility, and financial capacity influence how barriers, enablers, and indicators interact across organizational types. An MSE ascending to ME status cannot merely replicate existing processes and anticipate equivalent outcomes; similarly, a company experiencing a decline in size may face different limitations and dependencies, particularly in maintaining innovation capacity. This heterogeneity reveals that assuming uniform scalability across MSMEs is overly simplistic, as contextual and institutional conditions critically influence digital-sustainable performance trajectories.

From a methodological standpoint, this research is not without limitations. The findings rely on a narrow set of indicators and a limited number of cases, which may not fully capture the complex, multidimensional, and evolving nature of MSMEs ecosystems. The exploratory character of the practical guide also constrains generalizability, as it was designed for adaptability rather than empirical standardization. Additionally, the framework's current focus on internal organizational processes leaves room for deeper analysis of external influences, such as policy environments, regional innovation systems, and supply chain dependencies. Future research should therefore adopt mixed-method approaches, combining longitudinal case studies, large-scale quantitative analyses, and cross-regional comparisons, to validate and refine the framework's applicability across diverse contexts.

Further investigations could pursue several promising directions: (1) expanding the empirical base to encompass MSMEs from varied sectors and geographic regions, accounting for differences technological readiness, leadership styles, and sustainability maturity; (2) conducting large-scale surveys integrated with advanced statistical and computational tools, such as structural equation modelling (SEM) or machine learning, to uncover latent relationships among barriers, enablers, and outcomes; (3) deepening the research within organizational contexts by employing ethnographic or longitudinal methodologies that incorporate document analysis, digital process tracking, and behavioural observation; (4) involving operational employees and frontline collaborators in both qualitative and quantitative inquiries to capture organizational learning and tacit knowledge; and (5) developing a digital platform or mobile application to support the continues use, monitoring, and benchmarking of the practical guide connecting MSMEs to broader innovation networks.

Advancing both empirical and theoretical research on S-I4.0 is essential to enhance the scalability, inclusivity, and long-term effectiveness of digital-sustainable transformation globally. By integrating broader comparative and interdisciplinary approaches—linking management science, sustainability studies, and technology policy—future work can better inform strategies that empower MSMEs to thrive amid digital disruption while contributing meaningfully to sustainable economic development and societal well-being.

The authors would like to thank the reviewer and the editor for their valuable suggestions.