Understanding the Drivers and Impacts of Smart Manufacturing Information Systems Application in the Manufacturing Sector: Evidence from a Mixed-Methods Approach

Understanding the Drivers and Impacts of Smart Manufacturing Information Systems Application in the Manufacturing Sector: Evidence from a Mixed-Methods Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Understanding the Drivers and Impacts of Smart Manufacturing Information Systems Application in the Manufacturing Sector: Evidence from a Mixed-Methods Approach Shu-Hui Chuang, Jih-Chuan Jan, Shinyi Lin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7654072/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract To advance organizational flexibility and adaptability in the era of digital transformation, this study investigates the application of Smart Manufacturing Information Systems (SMIS) through the lens of the Technology–Organization–Environment (TOE) framework. Adopting a mixed-methods approach, we first conducted semi-structured interviews with senior managers and integrated insights from the literature to develop a robust survey instrument. Data were collected from 83 medium- and large-sized Taiwanese manufacturing firms that had already implemented SMIS. The study examines critical antecedents to assess their influence on SMIS application. SMIS utilization is conceptualized as a multi-dimensional capability, and its impact is evaluated across four key performance outcomes: production efficiency, product quality, cost control, and market competitiveness. Using structural equation modeling with SmartPLS, the results reveal that employee digital skills, top management support, and external pressure significantly enhance SMIS application, which in turn leads to improvements across all performance dimensions. This study contributes to the flexible systems management literature by embedding flexibility-oriented constructs within the TOE framework and demonstrating how SMIS can serve as a strategic enabler of organizational agility and resilience. Practical implications are offered for managers seeking to navigate digital disruption through context-aware and capability-driven system deployment. Smart manufacturing information systems Technology-organization-environment framework Digital transformation Firm performance Figures Figure 1 Figure 2 1 Introduction Amid the accelerating pace of digital transformation in the global manufacturing landscape, Smart Manufacturing Information Systems (SMIS) have become vital enablers of organizational agility and flexible system management. By integrating advanced digital technologies—including the Internet of Things (IoT), artificial intelligence (AI), and big data analytics—SMIS facilitates real-time data visibility and intelligent decision-making across the production lifecycle. These capabilities empower firms to respond swiftly to market fluctuations, adapt operational strategies with greater flexibility, optimize resource deployment, and improve cost-efficiency. As such, SMIS plays a pivotal role in fostering enterprise responsiveness and resilience in dynamic industrial environments (Ma et al. 2022 ; Zhang and Ming 2021 ). Despite the promising advantages, the implementation of SMIS is often meet with significant challenges. These include the lack of sophisticated IT infrastructure needed to support complex system integration (Pérez-Encinas et al. 2025), organizational silos that hinder cross-functional collaboration, and insufficient digital skills among employees, which may result in resistance to change or inappropriate system usage. Furthermore, the absence of top management support and strategic alignment can severely limit the effectiveness of SMIS adoption. Previous studies have confirmed several critical benefits associated with information systems (e.g., SMIS) adoption, including improved production efficiency (Tu et al. 2025 ), cost reduction, and enhanced resource coordination (Wu and Zhong 2025 ). For instance, technologies such as IoT and big data analytics enable real-time monitoring and predictive maintenance, thereby minimizing unplanned downtime and improving equipment reliability (Bhati et al. 2024 ). SMIS also facilitates interdepartmental collaboration through centralized data access and real-time communication. Empirical evidence further suggests that smart manufacturing provides predictive insights that enhance managerial decision-making, particularly in rapidly changing market environments (Bhatia and Diaz-Elsayed 2023 ). Despite the widespread recognition of the technical and operational advantages of SMIS, relatively few studies have examined its adoption from a comprehensive organizational perspective that integrates both internal capabilities and external pressures. Most prior research has focused on specific aspects, such as system functionality or user acceptance, while overlooking broader organizational and environmental factors that influence implementation outcomes. To address this research gap, this study adopts the Technology–Organization–Environment (TOE) framework, which categorizes adoption drivers into technological, organizational, and environmental contexts (Benchis et al. 2025 ; Kumar and Shankar 2024 ). This structured approach facilitates a comprehensive analysis of how firms align internal resources and external pressures to adopt SMIS. Specifically, the study examines five key factors—technological infrastructure maturity, employee digital skills, top management support, external environmental pressure, and organizational innovation capacity—and their influence on SMIS application and firm performance outcomes, including production efficiency, product quality, cost control, and market competitiveness. 2 Theoretical background 2.1 Smart Manufacturing Information Systems (SMIS) Smart Manufacturing Information Systems (SMIS) have emerged as foundational enablers of flexibility and responsiveness in the Industry 4.0 era. By embedding technologies such as the Internet of Things (IoT), artificial intelligence (AI), and big data analytics, SMIS supports real-time monitoring, adaptive control, and predictive maintenance—enhancing firms' capacity to swiftly respond to disruptions and evolving market demands (Ma et al. 2022 ; Zhang and Ming 2021 ). These integrated capabilities not only improve production efficiency and reduce operational costs but also promote organizational agility and strategic adaptability. As a result, SMIS is increasingly recognized as a critical lever for digital transformation and a key mechanism for sustaining competitive advantage in dynamic industrial environments (Qian 2023 ; Zhang et al. 2025 ). Prior research highlights that effective information systems (e.g., SMIS) implementation relies on a combination of organizational and technical capabilities (Kong and Feng 2025 ). Four critical dimensions consistently identified include: system integration capability, user acceptance, cross-departmental coordination, and data management capability. System integration capability ensures seamless connectivity between SMIS and legacy systems such as ERP, MES, and CRM. Weak integration often results in data silos and operational inefficiencies (Febrianto et al. 2025 ). User acceptance, shaped by factors like perceived usefulness and ease of use (Chandani et al. 2025 ), remains essential, as resistance or low digital literacy can hinder adoption. Cross-departmental coordination enables synchronized decision-making by fostering collaboration among departments, yet organizational silos often obstruct this process. Finally, data management capability underpins the value of SMIS analytics, requiring sound data governance and infrastructure to ensure quality and accessibility (Kim et al. 2025 ; Leng et al. 2025 ). Together, these four dimensions offer a holistic framework for assessing and enhancing SMIS application in smart manufacturing contexts. 2.2 Technology–Organization–Environment (TOE) The TOE framework, originally proposed by Tornatzky and Fleischer ( 1990 ), provides a comprehensive lens to examine the multidimensional factors that influence the adoption of technological innovations in organizations. This framework emphasizes organizational flexibility and responsiveness by integrating three interrelated contexts: (1)Technological context refers to both the internal and external technologies relevant to the firm, including existing systems, available technologies, and the perceived benefits and complexity of the innovation. (2)Organizational context encompasses the internal characteristics of the firm, such as firm size, managerial structure, employee competence, communication processes, and rethereforeurce availability. (3)Environmental context includes the external forces affecting the organization, such as competitive pressure, regulatory environment, and relationships with business partners or customers. TOE framework offers a robust and integrative perspective for examining enterprise-level technology adoption, particularly in dynamic and complex organizational contexts. Its tripartite structure—encompassing technological readiness, organizational capabilities, and environmental pressures—enables a flexible systems approach to understanding how firms adapt to digital transformation. By capturing the interplay among internal resources, structural agility, and external demands, the TOE framework facilitates a holistic analysis of the enablers and barriers to the implementation of systems such as SMIS. This makes it particularly suitable for research aiming to enhance organizational adaptability, strategic alignment, and long-term competitiveness through information system innovation. 2.3 Infuencing factors While the original TOE framework identifies three high-level dimensions—technology, organization, and environment—this study refines and operationalizes these categories by specifying five distinct and interrelated factors. Specifically, the technological context is represented by technological infrastructure maturity, the environmental context by external environmental pressure, and the organizational context is further disaggregated into employee digital skills, top management support, and organizational innovation capacity. This refinement is necessary because the organizational dimension in the digital manufacturing context encompasses multiple internal drivers that function differently and exert distinct influences on SMIS application. Technological infrastructure maturity ensures system compatibility, data integration, and real-time connectivity. Firms with advanced IT infrastructure are better equipped to integrate IoT, analytics, and AI tools for smart manufacturing (Yang et al. 2023 ). Employee digital skills reflect frontline readiness to interact with SMIS. Digital literacy and system competence enhance utilization and reduce resistance, especially when supported by adequate training (Ali et al. 2025 ; Jiang et al. 2025 ). Top management support provides strategic direction and resource commitment, facilitating cross-departmental coordination and driving organizational alignment for successful SMIS adoption (Khan and Khan 2025 ; Zhang et al. 2024 ). External environmental pressure—including market competition, customer demands, and regulatory compliance—motivates firms to adopt SMIS for differentiation and operational transparency (Deng et al. 2025 ; Lin et al. 2025 ). Lastly, organizational innovation capacity enhances a firm’s ability to adapt, experiment, and optimize SMIS use through agile workflows and cross-functional collaboration (Brix 2020 ). 2.4 Firm performance In recent years, researchers have increasingly employed the TOE framework to investigate the adoption and outcomes of information technology (Hadwer et al. 2021 ; Malik et al. 2021 ), which serve as integrated digital platforms to enable real-time data processing, predictive maintenance, and production optimization through the utilize of IoT, big data analytics, and AI (Amankwah-Amoah and Adomako 2019 ; Onu et al. 2025 ). These systems are particularly relevant in the context of Industry 4.0, where data-driven manufacturing is essential to maintaining competitive advantage. Recent studies have linked TOE factors to firm performance, showing that SMIS implementation under favorable conditions enhances multiple outcomes. Production efficiency improves through real-time monitoring and predictive maintenance (Imran et al. 2019 ; Menghi et al. 2020 ). Product quality is elevated by data-driven defect detection and process control (Yang et al. 2024 ). Cost control benefits from automated decision support and optimized resource allocation (Wang et al. 2026 ). Market competitiveness is strengthened by faster response to market demands and improved customization (Huang and Sun 2025 ). Overall, the TOE framework provides a robust lens to assess how technological, organizational, and environmental factors jointly shape SMIS application and its performance impact. 3 Research model and hypotheses 3.1 Research model The present study develops a research model based on the TOE framework to explore the factors influencing the application of SMIS and their impact on firm performance. The model integrates external and internal antecedents, SMIS application as a second-order construct, and firm-level outcomes in Fig. 1. Fig. 1 here To explore the flexible and dynamic nature of SMIS implementation, this study constructs a research model grounded in the TOE framework. Five key enablers are identified: technological infrastructure maturity, employee digital skills, top management support, external environmental pressure, and organizational innovation capacity. Recognizing the multifaceted organizational demands of digital manufacturing, the organizational context is further elaborated into leadership, skills, and innovation capabilities. SMIS application is conceptualized as a second-order construct encompassing four capabilities—system integration, user acceptance, cross-departmental coordination, and data management—reflecting both technical configuration and organizational adaptability. Firm performance is evaluated through four critical outcomes: production efficiency, product quality, cost control, and market competitiveness. This holistic model captures the interdependencies among flexibility-enabling capabilities and their strategic and operational contributions in digitally transforming enterprises. 3.2 Hypotheses 3.2.1 Infuencing factors and SMIS application Technological infrastructure maturity refers to the advancement of a firm's hardware, software, and network systems. High levels of infrastructure maturity support system compatibility, operational stability, and efficient data processing (Serrano and Pereira 2020; Williams et al. 2019), thereby enhancing SMIS deployment and utilization (Onu et al. 2025). A well-developed infrastructure enables seamless integration of SMIS with enterprise systems such as ERP and MES, facilitating real-time analytics and cross-functional data exchange. Stable technical environments combined with adequate support services contribute to greater employee adoption and effective use of SMIS (Purnamasari et al. 2025). Robust infrastructure also encourages cross-departmental collaboration by enabling data sharing and synchronized operations, while improving data management through enhanced data model such as collection, processing, and analysis of production information (Cao et al. 2025). H1 : Technological infrastructure maturity positively influences SMIS application. Employee professional skill level encompasses the knowledge, techniques, and experience required to operate advanced systems, solve problems, and adapt to technological change. In smart manufacturing environments, highly skilled employees facilitate SMIS adoption by efficiently managing complex equipment, data analysis, and system integration (Kim et al. 2025). Higher professional skill levels contribute to effective system integration (Fitzenberger and Speckesser 2007; Krpálek et al. 2021), enabling smoother interactions with ERP or MES platforms. Skilled employees demonstrate greater acceptance of new systems and adapt more readily, thereby improving operational efficiency. Enhanced skill sets also strengthen cross-departmental coordination by aligning technical understanding across units (Jiang and Cheng 2024), and improve data management through more accurate analysis and application of security information (e.g., SMIS) insights (Tendikov et al. 2024). H2 : Employee professional skill level positively influences SMIS application. Top management support denotes the extent to which senior executives actively champion technology adoption through strategic direction, resource provision, and cultural leadership (Khan and Khan 2025). This support includes financial investment, employee training, and fostering an innovation-oriented environment. During SMIS implementation, leadership commitment facilitates system integration, accelerates transformation, and enhances organizational alignment. Stronger top management support leads to more effective system integration by streamlining cross-departmental coordination and ensuring consistent resource allocation (Sun et al. 2025; Thong et al. 1996; Young and Jordan 2008). Top management support provides the strategic vision, resource commitment, and organizational encouragement necessary for successful SMIS application. When leadership actively endorses smart manufacturing initiatives, employees are more likely to engage with the system, interdepartmental alignment improves, and necessary investments in infrastructure and training are secured, fostering effective implementation. H3: Top management support positively influences SMIS application. External environmental pressure arises from market competition, technological advancements, regulatory requirements, and customer demands (Cui and Wang 2021; Liu 2009). These forces compel firms to adopt advanced systems such as SMIS to sustain competitiveness and respond to dynamic changes (Deng et al. 2025; Lin et al. 2025). External pressures such as market competition, customer demands, regulatory compliance, and industry standards compel firms to adopt advanced digital systems. Under such pressure, companies are more motivated to implement SMIS to enhance responsiveness, streamline operations, and maintain competitiveness in dynamic environments. H4 : External environmental pressure positively influences SMIS application. Organizational innovation capability represents a firm's capacity to adapt, create, and implement new technologies, processes, or services in response to uncertainty and market shifts. This capability reflects not only investment in R&D but also a culture that supports experimentation and agility (Ma and Ji 2024). High innovation capability promotes faster technology integration, greater employee openness to system use, and stronger interdepartmental collaboration (Camisón and Villar-López 2014; Fruhling and Siau 2016). For example, effective internal collaboration mechanisms further support cross-functional coordination during SMIS implementation. Firms with strong innovation capability are more likely to embrace new technologies (Acosta-Prado 2020; Kerstens and Langley 2025), experiment with digital tools, and adapt processes for transformation. This proactive mindset fosters a favorable environment for SMIS application, as organizations seek innovative solutions to enhance efficiency, flexibility, and competitiveness in smart manufacturing. H5 : Organizational innovation capability positively influences SMIS application. 3.2.2 SMIS application and firm performance SMIS enhances efficiency through automation, analytics, and process optimization. Greater system integration capability allows seamless data flow across platforms like ERP and MES, improving scheduling and reducing cycle times(Çakır et al. 2022; Kang et al. 2025). For example, strong user acceptance enables employees to manage tasks more accurately and efficiently, raising productivity; effective cross-departmental coordination accelerates responses to changes and streamlines resource use. IS enhance real-time data integration, automate production workflows, and enable rapid decision-making (Durmuşoğlu and Barczak 2011; Saarinen and Sääksjärvi 1992). These capabilities streamline resource allocation, reduce downtime, and minimize operational errors. Therefore, firms that effectively apply SMIS are expected to achieve higher production efficiency through improved coordination and process optimization. H6 : SMIS application positively influences production efficiency. SMIS enhances product quality through data analytics, monitoring, and automation (Lee et al. 2025; Suwattananuruk and Chien 2025). For example, strong system integration capability allows real-time monitoring and data sharing with quality management systems, reducing errors and improving precision; high user acceptance ensures employees can detect and respond to production issues quickly, enhancing reliability. Effective information systems enables timely issue resolution across production, quality, and supply chain teams (Durmuşoğlu and Barczak 2011). Advanced data management capability supports predictive maintenance and compliance, ensuring consistent output and regulatory alignment (Davenport, 1997). SMIS facilitate real-time monitoring, precise process control, and seamless data exchange across production stages. These functions reduce defects, improve consistency, and enhance traceability. As a result, organizations applying SMIS are more likely to deliver high-quality products that meet customer expectations and regulatory standards. H7 : SMIS application positively influences product quality. Implementing SMIS enhances resource allocation, streamlines operations, and reduces inefficiencies, thereby improving cost control (Li et al. 2025). For example, system integration capability supports cost control by connecting IS, enabling real-time data sharing and process automation (Cordelia 2006; Irani et al. 2006), which reduce redundancy and operational errors; strong user acceptance ensures employees can utilize SMIS effectively, minimizing human error and waste. SMIS enhances cost control by enabling real-time tracking of resources, automating manual processes, and reducing inefficiencies in production workflows. With integrated data analysis and process monitoring, firms can identify waste, optimize inventory, and streamline operations (Yu et al. 2025). This operational visibility and control help reduce unnecessary expenses and improve overall cost efficiency. H8 : SMIS application positively influences operating cost control. SMIS empower firms to enhance market competitiveness by enabling customer and market changes, agile decision-making, and operational transparency (Huang and Sun 2025). Through system integration, data analytics, and cross-functional collaboration, organizations can swiftly respond to changing market conditions, customize products, and shorten time-to-market (Caldwel et al. 2005). Enhanced data management allows better understanding of customer preferences (Zhang et al. 2022), competitor behavior, and industry trends, facilitating strategic differentiation . Moreover, user acceptance of SMIS promotes internal process alignment, leading to consistent quality and service reliability—critical components in sustaining competitive advantage. Therefore, higher levels of SMIS application are expected to yield improved competitive positioning in dynamic market environments. H9 : SMIS application positively influences market competitiveness. 4 Methods The present study adopts a mixed-methods research design, integrating both qualitative and quantitative approaches to ensure a comprehensive understanding of the factors influencing SMIS application and its impact on firm performance. In the qualitative phase, semi-structured interviews were conducted with senior executives from manufacturing firms experienced in digital transformation. The interview protocol was developed based on a comprehensive review of literature related to technology adoption, organizational capabilities, and smart manufacturing. Insights from the interviews were used to revise and refine the questionnaire items, ensuring their practical relevance and clarity. These qualitative findings also guided the identification of key dimensions and the precise wording of items for the subsequent survey instrument. In the quantitative phase, a structured questionnaire was administered to firms that had already implemented SMIS. The survey measured constructs such as technological infrastructure maturity, employee digital skills, top management support, environmental pressure, and organizational innovation capacity, along with four dimensions of SMIS application and firm performance outcomes. The collected data were analyzed using statistical methods to examine the hypothesized relationships proposed in the theoretical model. 4.1 Mesurement of constructs The measurement of the constructs influencing SMIS application in this study—namely technological infrastructure maturity, employee digital skills, top management support, environmental pressure, and organizational innovation capacity—was developed through a combination of literature review and qualitative inquiry. These constructs have been consistently identified in prior studies as critical determinants of information system adoption and integration within manufacturing contexts (Ali et al. 2025 ; Brix 2020 ; Deng et al. 2025 ; Jiang et al. 2025 ; Khan and Khan 2025 ). Building on foundational literature, the study developed semi-structured interview questions to explore the practical operationalization of each construct. For example, senior managers were asked, “What types of digital capabilities or infrastructure does your company currently rely on for smart manufacturing?” In-depth interviews with executives from firms that had adopted SMIS, followed by thematic content analysis, revealed key indicators for each construct. For instance, technological infrastructure maturity was commonly associated with stable system operation, seamless connectivity with production equipment, and access to AI-powered data analytics tools. Insights from the interviews were used to refine each construct into three measurable items, ensuring both theoretical coherence and contextual relevance. These items informed the development of the survey instrument used in the quantitative phase. For example, employee digital skills were assessed through items on the frequency of digital tool usage, confidence in operating smart systems, and participation in upskilling programs—guided by prior research (Ali et al. 2025 ; Jiang et al. 2025 ) and validated through field input. By integrating literature review with empirical insights, the final measurement model effectively captures the multidimensional nature of the key drivers influencing SMIS application. This study conceptualizes SMIS application as a second-order construct comprising four formative dimensions: system integration capability, user acceptance, cross-departmental coordination, and data management capability. These dimensions emerged from prior literature (Chandani et al. 2025 ; Febrianto et al. 2025 ; Kim et al. 2025 ; Leng et al. 2025 ) and were refined through interviews with senior executives in SMIS-adopting firms. Each dimension represents a key operational mechanism that drives firm performance. System integration capability captures the extent of SMIS integration with existing systems (e.g., ERP, MES) and the ability to support seamless data exchange (Febrianto et al. 2025 ). User acceptance assesses employee willingness to use SMIS, perceived usefulness, and confidence in system operation (Chandani et al. 2025 ). Cross-departmental coordination measures the system's role in promoting collaboration among departments such as production, and supply chain. Data management capability reflects the firm’s ability to collect, store, analyze, and apply SMIS-generated data for informed decision-making (Kim et al. 2025 ; Leng et al. 2025 ). Each first-order construct was measured using three reflective items adapted from validated scales and contextualized for smart manufacturing. Interview findings helped ensure content validity and practical relevance. Academic and industry experts reviewed and revised the final items during the pretest phase. Following Hair et al. ( 2021 ), a two-stage measurement approach was used to assess the formative structure of the first-order constructs and the second-order SMIS application construct. Firm performance was measured as a multidimensional construct covering four outcome areas: production efficiency, product quality, cost control, and market competitiveness. These dimensions represent both operational and strategic impacts of SMIS. Semi-structured interviews and literature (Huang and Sun 2025 ; Imran et al. 2019 ; Wang et al. 2026 ; Yang et al. 2024 ) guided the development and refinement of performance measures: (1)Production efficiency evaluates improvements in resource utilization and cycle time reduction (Imran et al. 2019 ). (2)Product quality assesses consistency, reliability, and customer satisfaction gains (Yang et al. 2024 ). (3)Cost control measures reductions in operational expenses, waste, and improvements in resource allocation (Wang et al. 2026 ). (4)Market competitiveness captures responsiveness to market changes and enhancement of strategic agility (Huang and Sun 2025 ). A pilot test confirmed the reliability and validity of the measurement items, with feedback from practitioners ensuring both theoretical rigor and industry relevance (see Appendix A). 4.2 Control constructs To account for organizational characteristics affecting SMIS application and effectiveness, this study includes three commonly referenced control variables: firm size, firm age, and firm capital. These factors help isolate the influence of core explanatory variables and enhance model accuracy. Firm size, typically measured by employee count, reflects a firm’s capacity in financial, technological, and human resources. Larger firms often demonstrate stronger abilities to implement IS and manage digital transformation projects (Tsou and Chen 2012 ). Firm age, defined by years since establishment, suggests accumulated operational experience and process maturity. Older firms may leverage institutional knowledge to support IS adoption, though some may face innovation resistance due to organizational inertia (Baum et al. 2000 ). Firm capital, measured by registered or operating capital, indicates financial strength available for strategic investments. Higher capital levels enable greater flexibility in acquiring, customizing, and scaling IS platforms (Florin and Lubatkin 2003 ). Inclusion of these variables enhances the robustness of the empirical model and ensures that observed effects stem from TOE-related factors rather than organizational heterogeneity. 4.3 Quantitative survey collection To examine the flexible enablers and performance outcomes of SMIS application, this study employed a structured survey methodology targeting medium and large manufacturing firms in Taiwan. The sampling frame was derived from the “Top 5,000 Largest Corporations in Taiwan” published by the China Credit Information Service, Ltd. The manufacturing sector was chosen due to its central role in Taiwan’s industrial transformation and its proactive adoption of Industry 4.0 technologies. The implementation of SMIS in this context typically involves the integration of complex platforms such as ERP, MES, and IoT—making it an ideal setting to study technological readiness, cross-departmental coordination, and data-driven decision-making. Moreover, in the face of intensifying global competition, the strategic need for organizational adaptability and operational agility makes these firms particularly relevant for assessing the flexible impact of SMIS on firm performance. The tarobtain respondents were high-level managers who have experience with or oversight of smart manufacturing initiatives, such as digital transformation directors, IT managers, production supervithereforers, or plant managers. These individuals were in the best position to evaluate organizational digital capabilities and SMIS usage, as well as its influence on production efficiency, product quality, cost control, and market competitiveness. The sample for this study was drawn from the Top 5,000 Largest Corporations in Taiwan, focusing on the top 350 medium-to-large-sized enterprises. Survey packages were mailed to the selected firms and included a cover letter explaining the purpose of the study, the questionnaire, and a self-addressed stamped envelope. In the first round of distribution, 45 valid responses were received. To improve the response rate, a follow-up was conducted via phone calls and emails, yielding an additional 58 responses in the second round. After removing incomplete or invalid questionnaires, a total of 103 valid responses were retained, representing an effective response rate of 24%. Among these, 83 firms confirmed that they had implemented SMIS, and these 83 responses were used for the final analysis. 5 Analysis and results Survey data analysis was conducted using partial least squares (PLS), a structural equation modeling (SEM) technique well-suited for exploratory research involving complex models with both formative and reflective constructs. PLS is particularly advantageous for its ability to handle smaller sample sizes and its minimal assumptions regarding data distrihoweverion and measurement scales. Given that the SMIS application construct was modeled as a second-order construct with multiple first-order formative dimensions, PLS offered the methodological flexibility required for this research. The analysis followed a two-step approach: (1) assessment of the measurement model to examine the reliability and validity of all constructs, and (2) evaluation of the structural model to test the hypothesized relationships among variables. All statistical analyses were carried out using SmartPLS 4.0 (Ringle et al., 2022), which enabled the validation of the measurement properties and estimation of the structural paths within the research framework. 5.1 Measurement model Table 1 presents the standardized loadings, reliability, and validity metrics for all item measures. The factor loadings of the items in the measurement model range from 0.557 to 0.971. While a loading above 0.70 is generally considered ideal (Hair et al., 2010), items with loadings between 0.50 and 0.70 may still be retained if they contrihowevere to content validity and the overall construct reliability remains acceptable. In this study, all constructs demonstrate composite reliability values ranging from 0.790 to 0.967, exceeding the 0.70 threshold recommended by Segars ( 1997 ), indicating good internal consistency. Furthermore, the average variance extracted (AVE) for each construct exceeds the recommended benchmark of 0.50, supporting convergent validity. Table 2 reports the results of discriminant validity assessment using the Fornell-Larcker criterion. For satisfactory discriminant validity, the square root of the AVE for each construct should be greater than its correlations with any other construct (Fornell and Larcker 1987 ). The results confirm that this condition is met for all constructs in the model. Additionally, the analysis of cross-loadings (Appendix B) further supports the presence of acceptable discriminant validity. Table 1 here Table 2 here 5.2 Structural model Figure 2 illustrates the structural model results, including path coefficients and their significance levels. The application of SMIS was significantly influenced by employee digital skills (β = 0.206, p < .01), top management support (β = 0.344, p < .01), and external environmental pressure (β = 0.250, p < .01). These three variables collectively explained 76.1% of the variance in SMIS application, thereby supporting hypotheses H2, H3, and H4. In contrast, technological infrastructure maturity (β = 0.081, p > .05) and organizational innovation capacity (β = 0.083, p > .05) did not exhibit significant effects on SMIS application, leading to the rejection of H1 and H5. SMIS application, in turn, exerted a significant positive influence on all four dimensions of firm performance: production efficiency (β = 0.683, p < .001), product quality (β = 0.626, p < .001), cost control (β = 0.463, p < .001), and market competitiveness (β = 0.659, p < .001), thereby supporting hypotheses H6 through H9. The explanatory power (R²) of SMIS application on each performance outcome is as follows: production efficiency (46.7%), product quality (39.1%), cost control (21.4%), and market competitiveness (43.5%). These results highlight the critical role of SMIS in enhancing key operational and strategic performance indicators within manufacturing firms. Finally, the analysis of control variables indicates that firm size, firm age, and firm capital do not have statistically significant effects on SMIS application or firm performance in this context. Figure 2 here 6 Discussion Contrary to expectations, the hypothesis that technological infrastructure maturity positively influences SMIS application was not supported. This finding suggests that while robust infrastructure—such as advanced networks and data systems—provides a necessary foundation, it alone may not drive flexible and adaptive use of SMIS. From a flexible systems perspective, effective application depends more on an organization’s ability to align technology with cross-functional workflows, cultivate user engagement, and adapt systems to evolving strategic needs. Without organizational responsiveness and interdepartmental collaboration, even the most advanced infrastructure may fall short in supporting agile manufacturing processes and dynamic decision-making.This finding contrasts with prior studies (Serrano and Pereira 2020 ; Williams et al. 2019 ) that emphasized the foundational role of infrastructure maturity in reducing technical uncertainty and enabling system integration. It may be that other factors—such as management commitment, innovation culture, or change readiness—play a more critical mediating role in realizing the benefits of technological infrastructure. Future research should explore these mediating mechanisms to better understand how infrastructure maturity translates into actual system application outcomes. The empirical results support the hypothesis that employee digital skills are positively asthereforeciated with SMIS application. This indicates that employees with higher levels of digital proficiency are more capable of operating smart systems, interpreting data insights, and adapting to new technologies. The finding aligns with previous studies indicating that workforce competency is a key enabler of IT assimilation and innovation adoption (Fitzenberger and Speckesser 2007 ; Krpálek et al. 2021 ). The hypothesis regarding the positive influence of top management support on SMIS application is furthermore supported. The findings validate that visible leadership commitment—such as providing strategic direction, rethereforeurces, and encouragement—facilitates smoother implementation and higher system usage. This echoes the notion that top-down support is crucial for overcoming resistance to change and fostering cross-functional alignment(Thong et al. 1996 ; Young and Jordan 2008). The analysis reveals a significant positive relationship between external environmental pressure and SMIS application, confirming the corresponding hypothesis. This indicates that market competition, regulatory changes, and customer expectations motivate firms to adopt advanced information systems to maintain competitiveness. These results are consistent with prior literatures, which indicates that external forces drive organizational behavior and technological innovation (Cui and Wang 2021 ; Liu 2009 ). The hypothesis that organizational innovation capacity positively influences SMIS application is not supported. This result indicates that having a strong innovation orientation alone may not directly translate into the effective application of SMIS. One possible explanation is that while innovation capacity may foster openness to new ideas, it does not necessarily guarantee successful system integration, user adoption, or cross-departmental coordination—key elements required for SMIS implementation. This finding diverges from previous literature (Camisón and Villar-López 2014 ; Fruhling and Siau 2016 ), which emphasized the enabling role of organizational innovation in technological change. It is possible that structural rigidities, lack of digital leadership, or resistance to operational changes may offset the potential benefits of innovation capacity. Future research should examine under what conditions innovation capacity can more effectively contrihowevere to the implementation of digital systems like SMIS. The implementation of SMIS is widely regarded as a strategic enabler for enhancing organizational agility, responsiveness, and performance. This study empirically examined the effects of SMIS application on four critical performance dimensions: production efficiency, product quality, cost control, and market competitiveness. Results confirm that a well-integrated and flexibly applied SMIS significantly contributes to these outcomes. From a flexible systems perspective, the value of SMIS lies not only in technological functionality but also in its ability to support adaptive decision-making, streamline interdepartmental processes, and enhance the organization’s capacity to respond to dynamic market shifts. These findings underscore the importance of aligning digital systems with flexible organizational practices to achieve sustainable competitive advantage. The details are as follows: The results indicate a significant positive relationship between SMIS application and production efficiency, confirming that enterprises effectively applying smart manufacturing information systems experience improved rethereforeurce utilization and faster production processes. This finding indicates that the integration of SMIS facilitates real-time data sharing, automation, and better coordination across production units, which enhances production scheduling, reduces waste, and shortens lead times. This study supports prior research that emphasizes the importance of digital systems in improving operational agility and throughput (Durmuşoğlu and Barczak 2011 ; Saarinen and Sääksjärvi 1992). The analysis confirms that SMIS application has a significant positive impact on product quality. Companies that actively apply SMIS are more capable of maintaining consistency and precision throughout the production process. This supports the view that SMIS can improve quality control through automated monitoring, real-time defect detection, and predictive maintenance. Enhanced product quality contrihoweveres to customer satisfaction and brand reputation, aligning with previous research such as (Durmuşoğlu and Barczak 2011 ), which link information systems with quality assurance mechanisms. SMIS application is found to be positively asthereforeciated with cost control. Firms utilizing SMIS more extensively are better at reducing production waste, minimizing downtime, and optimizing rethereforeurce allocation. The result demonstrates the cost-saving potential of SMIS through digital coordination, reduction in manual errors, and data-driven decision-making. This prior literature (Cordelia 2006 ; Irani et al. 2006 ) that identifies IT-enabled integration as a critical enabler of leaner operations and lower overhead. The results show a statistically significant and positive relationship between SMIS application and market competitiveness. Firms that effectively leverage SMIS are more capable of responding to market changes and customer demands swiftly. This finding highlights the strategic value of SMIS in enhancing market agility, innovation speed, and customer responsiveness. This study confirms that smart systems not only optimize internal operations however furthermore enable firms to differentiate themselves in competitive markets, supporting theories such as those by Caldwel et al. ( 2005 ). 7 Conclusion This study investigated the antecedents and performance impacts of SMIS application through the lens of the TOE framework. The findings highlight that employee digital skills, top management support, and external environmental pressure are critical enablers for effective SMIS adoption, reinforcing the importance of both internal readiness and adaptive response to external dynamics. Interestingly, technological infrastructure maturity and innovation capacity alone did not significantly influence SMIS application, suggesting that flexible implementation requires more than just technical or strategic intent—it demands coordinated organizational alignment and agile integration practices. Furthermore, the positive effects of SMIS application on production efficiency, product quality, cost control, and market competitiveness underscore its role as a catalyst for enhancing organizational responsiveness and sustainable performance in dynamic manufacturing environments. These insights contribute to the broader discourse on flexible systems management by illustrating how digital tools must be embedded within adaptive organizational contexts to achieve transformative outcomes. 7.1 Theoretical Implications This research offers several contributions to the academic literature. First, the study extends the TOE framework by examining five theoretically grounded and context-specific antecedents of SMIS application. While only employee digital skills, top management support, and external environmental pressure showed significant effects, the inclusion of all five factors provides a nuanced understanding of the diverse conditions shaping SMIS adoption. This balanced perspective clarifies both the enablers and constraints of system application in digital manufacturing contexts. Second, this study contributes methodologically by combining insights from prior literature with semi-structured interviews of senior manufacturing executives to refine the measurement items. This qualitative–quantitative approach strengthens construct validity and ensures that the survey instrument is both theoretically robust and practically relevant, offering a replicable framework for future research in smart manufacturing and information systems. Finally, by empirically examining the relationship between SMIS application and multiple performance outcomes—production efficiency, product quality, cost control, and market competitiveness—the study provides evidence supporting a positive association between SMIS use and organizational performance. However, these findings should be interpreted with caution given the cross-sectional design, the limited sample of 83 firms already implementing SMIS, and potential contextual differences across industries. Future research could address these limitations by employing longitudinal designs, broader samples, and comparative analyses across sectors. 7.2 Managerial Implications This study provides valuable managerial insights for enhancing organizational flexibility and responsiveness through the strategic application of SMIS. The significant influence of employee digital skills highlights the importance of cultivating a flexible and future-ready workforce. Companies should invest in continuous learning, hands-on digital training, and cross-functional collaboration, all of which improve not only system usage but also the organization’s capacity to adapt to rapidly evolving technologies and processes. The critical role of top management support further emphasizes the need for leadership to champion digital transformation efforts. By actively engaging in strategic prioritization, resource reallocation, and promoting a change-oriented culture, executives can facilitate flexible decision-making structures that are crucial for agile execution across departments. Moreover, the impact of external environmental pressures—including market volatility, customer demands, and regulatory shifts—reinforces the need for organizations to enhance their environmental scanning and adaptive capabilities. Firms that proactively adjust SMIS implementation in response to external dynamics are better positioned to maintain strategic alignment and operational resilience in turbulent business environments. Interestingly, the non-significant role of technological infrastructure maturity suggests that technical resources alone are insufficient to drive successful system adoption. This insight cautions managers against over-relying on hardware or system upgrades without accompanying changes in organizational processes, people engagement, and change-readiness frameworks. A flexible implementation strategy requires alignment across people, processes, and platforms. Similarly, the insignificant influence of innovation capacity implies that innovation, while important, must be tethered to practical implementation pathways. Managers should ensure that creative efforts translate into actionable digital initiatives that align with operational goals and real-world use cases, thereby bridging the gap between strategic vision and execution. Finally, since the findings confirm that SMIS application positively influences production efficiency, product quality, cost control, and market competitiveness, managers are encouraged to treat SMIS not merely as a technical upgrade, but as a strategic enabler of enterprise-wide flexibility. By leveraging SMIS for real-time data analytics, interdepartmental integration, predictive maintenance, and data-driven decision-making, firms can significantly enhance their capacity to respond to internal and external changes while driving sustainable performance gains. These insights support the broader paradigm of flexible systems management, where digital tools are embedded within agile, responsive, and coordinated organizational structures—enabling enterprises to thrive in dynamic manufacturing environments. 7.3 Limitations and Future Research Directions Several limitations of this study should be acknowledged, which provide avenues for future research within the domain of flexible systems management. First, while this study specifically focused on firms that have already implemented SMIS, it did not distinguish between different stages of SMIS maturity, such as pilot adoption, partial deployment, or full-scale integration. Since flexibility often evolves over time, future research could adopt a longitudinal design to examine how firms dynamically adapt their SMIS usage across different stages of digital transformation—capturing the evolution of both technological and organizational flexibility. Second, although the measurement constructs were carefully developed through a mixed-methods approach—integrating prior literature with semi-structured interviews from senior executives—this design primarily captures the perspectives of early adopters. While this strengthens the study’s relevance to current industry practice, it also limits the generalizability to firms that have not yet begun or are struggling with SMIS implementation. Broader sampling across adoption readiness levels would allow for more comprehensive modeling of organizational flexibility and resistance. Third, the final dataset consists of 83 valid responses from medium and large manufacturing firms in Taiwan. This sample reflects the current stage of SMIS diffusion in the region, where many enterprises are still in the early or transitional phases of digital adoption. Although the sample is analytically adequate for partial least squares (PLS) analysis, future research could benefit from larger and more diverse samples—including firms from different industries, countries, or organizational structures—to further validate the findings and explore contextual differences in SMIS flexibility. Lastly, this study focused on cross-sectional data, which limits the ability to capture dynamic interactions between environmental changes and system reconfiguration—a critical element of flexible systems management. Future research could adopt process-based or interpretive approaches to investigate how SMIS-enabled organizations continuously recalibrate their processes, structures, and resource allocation in response to external volatility and internal shifts. Table 1 Standardized factor loading, t-value, CR, and AVE. Construct Indicator Factor loading t-value Composite Reliability Average Variance Extracted Cross- CDC1 0.945 10.377 0.962 0.792 Departmental CDC2 0.753 2.606 Coordination CDC2 0.957 10.853 Data DMC1 0.949 18.766 0.936 0.884 Managmenet DMC2 0.916 14.610 Capability DMC3 0.955 18.832 Employee EDS1 0.946 16.920 0.933 0.866 Digital Skills EDS2 0.905 14.232 EDS3 0.939 16.131 External EEP1 0.834 7.339 0.851 0.742 Environmental EEP2 0.886 10.845 Pressure EEP3 0.863 10.003 Organizational OIC1 0.884 8.935 0.920 0.846 Innovation OIC2 0.940 14.524 Capacity OIC3 0.934 13.661 Cost PCC1 0.843 4.439 0.820 0.649 Control PCC2 0.666 1.299 PCC3 0.891 4.614 Market PMC1 0.913 8.989 0.844 0.688 Competitiveness PMC2 0.725 3.716 PMC3 0.840 7.191 Production PPE1 0.860 10.358 0.901 0.813 Efficiency PPE2 0.935 11.181 PPE2 0.909 11.618 Product PPQ1 0.924 9.485 0.882 0.772 Quality PPQ2 0.857 8.042 PPQ3 0.852 7.126 Systems SIC1 0.938 21.339 0.919 0.856 Intergration SIC2 0.885 17.387 Capability SIC3 0.952 25.364 Technological TIM1 0.965 15.112 0.967 0.923 Infrastructure TIM2 0.946 10.870 Maturity TIM3 0.971 16.685 Top TMS1 0.938 13.819 0.790 0.647 Management TMS2 0.866 9.777 Support TMS3 0.557 4.597 User UAP1 0.911 12.713 0.890 0.818 Acceptance UAP2 0.896 11.064 UAP3 0.906 11.326 Table 2 Discriminant validity. CDC DMC EDS EEP OIC PCC PMC PPE PPQ SIC TIM TMS UAP CDC 0.890 DMC 0.815 0.940 EDS 0.587 0.707 0.930 EEP 0.690 0.807 0.632 0.861 OIC 0.552 0.734 0.576 0.843 0.920 PCC 0.430 0.475 0.574 0.472 0.474 0.805 PMC 0.685 0.736 0.781 0.699 0.723 0.749 0.829 PPE 0.550 0.693 0.524 0.601 0.520 0.510 0.563 0.901 PPQ 0.536 0.612 0.497 0.508 0.477 0.662 0.624 0.649 0.879 SIC 0.878 0.718 0.673 0.694 0.543 0.444 0.609 0.643 0.615 0.925 TIM 0.563 0.691 0.681 0.715 0.671 0.578 0.797 0.604 0.586 0.639 0.961 TMS 0.777 0.796 0.771 0.822 0.665 0.531 0.675 0.628 0.474 0.833 0.789 0.804 UAP 0.625 0.859 0.642 0.738 0.651 0.430 0.722 0.632 0.606 0.591 0.625 0.801 0.904 Notes: 1.CDC: Cross-departmental coordination; 2. Data managemnet capability; 3. EDS: Exployee digital skills; 4. EEP: External environmental pressure; 5. OIC: organizational innovation capability; 6. PCC: Cost Control; 5. PMC: Market compeitieness; 7. PPE: Production efficiency; 8. PPQ: Product quality; 9. TIM: Technological infrastureture maturity; 10. TMS: Top Management support; 11. Top management support; 12. User acceptance; Diagonals represent the square root of average variance extracted, while the other matrix entries represent the correlations. Declarations Funding Declaration This research was supported by a grant from the National Science and Technology Council (NSTC 112-2221-E-468-015), Taiwan. Relevant funding details have already been provided in the journal’s submission system. Ethics Declaration All procedures performed in this study complied with ethical standards. Participants were informed of the research purpose, and their participation was voluntary and anonymous. No identifiable personal data were collected. Author Contribution Shu-Hui Chuang wrote the main manuscript text, conducted data collection, and performed data analysis. Shinyi Lin and Jih-Chuan Jan contributed to the data collection process and provided support in organizing field interviews. 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Heliyon , 10 (10), e31579 (2024). https://doi.org/10.1016/j.heliyon.2024.e31579 Zhang, X.,Ming, X. An implementation for Smart Manufacturing Information System (SMIS) from an industrial practice survey. Computers & Industrial Engineering , 151 , 106938 (2021). https://doi.org/10.1016/j.cie.2020.106938 Additional Declarations No competing interests reported. Supplementary Files AppendixAB.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7654072","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":519398668,"identity":"ef36689f-7239-48b5-8de3-7ca3d0007696","order_by":0,"name":"Shu-Hui Chuang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDACCQY2BgYDhgQw5wMQs7GTooVxBkgLM1FaGCBamHnAJAEd8rN7zB7zFNjlGRw/e/i1za9t8nzMDIwfPubg1mJw54y5MY9BcrHBmbw069y+24ZtzAzMkjO34dEikWMmzWNwIHHDgRwz49ye24xALWzMvHi0yM+AaTn/xszYsue2PUEtDDdgWm7kGD9m+HE7kaAWgxtpZZJzDJITZ954Y8bY23A7uY2ZsRmvX+RnJG+TePPHLrHvfI7xhx9/btvOb28++OEjPochATYJxjYQzdhAnHogYP7A8IdoxaNgFIyCUTCCAABaR0/WbCjaxgAAAABJRU5ErkJggg==","orcid":"","institution":"Asia University","correspondingAuthor":true,"prefix":"","firstName":"Shu-Hui","middleName":"","lastName":"Chuang","suffix":""},{"id":519398669,"identity":"2577f15c-b00c-4bd4-a038-a168bab91c9a","order_by":1,"name":"Jih-Chuan Jan","email":"","orcid":"","institution":"Asia University","correspondingAuthor":false,"prefix":"","firstName":"Jih-Chuan","middleName":"","lastName":"Jan","suffix":""},{"id":519398670,"identity":"681f7951-8431-4a3d-912f-6036d62c4200","order_by":2,"name":"Shinyi Lin","email":"","orcid":"","institution":"National Taichung University of Education","correspondingAuthor":false,"prefix":"","firstName":"Shinyi","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2025-09-19 03:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7654072/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7654072/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94481292,"identity":"a6ac820c-d47b-4e05-9f4b-560935b14f96","added_by":"auto","created_at":"2025-10-27 16:13:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":58118,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResearch model\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7654072/v1/ad92580e1be252d1ec333165.png"},{"id":94481677,"identity":"f0a07a9f-d627-4b95-a7a7-851ab8977119","added_by":"auto","created_at":"2025-10-27 16:14:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":121948,"visible":true,"origin":"","legend":"\u003cp\u003ePath diagram for research model.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7654072/v1/f3a060c621f5dc95b877a56a.png"},{"id":99789196,"identity":"fba3fd0e-26c1-4924-82fa-c67248e3cd18","added_by":"auto","created_at":"2026-01-08 12:49:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1363393,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7654072/v1/0e8c43b9-76b3-4278-b65c-ff24d5f1cdee.pdf"},{"id":94481309,"identity":"6eeba171-9d4c-47b4-8242-6c0d2dab46bc","added_by":"auto","created_at":"2025-10-27 16:13:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":28311,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixAB.docx","url":"https://assets-eu.researchsquare.com/files/rs-7654072/v1/6310fb2f4eced51ae69af9b5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding the Drivers and Impacts of Smart Manufacturing Information Systems Application in the Manufacturing Sector: Evidence from a Mixed-Methods Approach","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eAmid the accelerating pace of digital transformation in the global manufacturing landscape, Smart Manufacturing Information Systems (SMIS) have become vital enablers of organizational agility and flexible system management. By integrating advanced digital technologies\u0026mdash;including the Internet of Things (IoT), artificial intelligence (AI), and big data analytics\u0026mdash;SMIS facilitates real-time data visibility and intelligent decision-making across the production lifecycle. These capabilities empower firms to respond swiftly to market fluctuations, adapt operational strategies with greater flexibility, optimize resource deployment, and improve cost-efficiency. As such, SMIS plays a pivotal role in fostering enterprise responsiveness and resilience in dynamic industrial environments (Ma et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang and Ming \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite the promising advantages, the implementation of SMIS is often meet with significant challenges. These include the lack of sophisticated IT infrastructure needed to support complex system integration (P\u0026eacute;rez-Encinas et al. 2025), organizational silos that hinder cross-functional collaboration, and insufficient digital skills among employees, which may result in resistance to change or inappropriate system usage. Furthermore, the absence of top management support and strategic alignment can severely limit the effectiveness of SMIS adoption.\u003c/p\u003e\u003cp\u003ePrevious studies have confirmed several critical benefits associated with information systems (e.g., SMIS) adoption, including improved production efficiency (Tu et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), cost reduction, and enhanced resource coordination (Wu and Zhong \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). For instance, technologies such as IoT and big data analytics enable real-time monitoring and predictive maintenance, thereby minimizing unplanned downtime and improving equipment reliability (Bhati et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). SMIS also facilitates interdepartmental collaboration through centralized data access and real-time communication. Empirical evidence further suggests that smart manufacturing provides predictive insights that enhance managerial decision-making, particularly in rapidly changing market environments (Bhatia and Diaz-Elsayed \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite the widespread recognition of the technical and operational advantages of SMIS, relatively few studies have examined its adoption from a comprehensive organizational perspective that integrates both internal capabilities and external pressures. Most prior research has focused on specific aspects, such as system functionality or user acceptance, while overlooking broader organizational and environmental factors that influence implementation outcomes.\u003c/p\u003e\u003cp\u003eTo address this research gap, this study adopts the Technology\u0026ndash;Organization\u0026ndash;Environment (TOE) framework, which categorizes adoption drivers into technological, organizational, and environmental contexts (Benchis et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Kumar and Shankar \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This structured approach facilitates a comprehensive analysis of how firms align internal resources and external pressures to adopt SMIS. Specifically, the study examines five key factors\u0026mdash;technological infrastructure maturity, employee digital skills, top management support, external environmental pressure, and organizational innovation capacity\u0026mdash;and their influence on SMIS application and firm performance outcomes, including production efficiency, product quality, cost control, and market competitiveness.\u003c/p\u003e"},{"header":"2 Theoretical background","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Smart Manufacturing Information Systems (SMIS)\u003c/h2\u003e\u003cp\u003eSmart Manufacturing Information Systems (SMIS) have emerged as foundational enablers of flexibility and responsiveness in the Industry 4.0 era. By embedding technologies such as the Internet of Things (IoT), artificial intelligence (AI), and big data analytics, SMIS supports real-time monitoring, adaptive control, and predictive maintenance\u0026mdash;enhancing firms' capacity to swiftly respond to disruptions and evolving market demands (Ma et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang and Ming \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These integrated capabilities not only improve production efficiency and reduce operational costs but also promote organizational agility and strategic adaptability. As a result, SMIS is increasingly recognized as a critical lever for digital transformation and a key mechanism for sustaining competitive advantage in dynamic industrial environments (Qian \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePrior research highlights that effective information systems (e.g., SMIS) implementation relies on a combination of organizational and technical capabilities (Kong and Feng \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Four critical dimensions consistently identified include: system integration capability, user acceptance, cross-departmental coordination, and data management capability. System integration capability ensures seamless connectivity between SMIS and legacy systems such as ERP, MES, and CRM. Weak integration often results in data silos and operational inefficiencies (Febrianto et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). User acceptance, shaped by factors like perceived usefulness and ease of use (Chandani et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), remains essential, as resistance or low digital literacy can hinder adoption. Cross-departmental coordination enables synchronized decision-making by fostering collaboration among departments, yet organizational silos often obstruct this process. Finally, data management capability underpins the value of SMIS analytics, requiring sound data governance and infrastructure to ensure quality and accessibility (Kim et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Leng et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Together, these four dimensions offer a holistic framework for assessing and enhancing SMIS application in smart manufacturing contexts.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Technology\u0026ndash;Organization\u0026ndash;Environment (TOE)\u003c/h2\u003e\u003cp\u003eThe TOE framework, originally proposed by Tornatzky and Fleischer (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), provides a comprehensive lens to examine the multidimensional factors that influence the adoption of technological innovations in organizations. This framework emphasizes organizational flexibility and responsiveness by integrating three interrelated contexts: (1)Technological context refers to both the internal and external technologies relevant to the firm, including existing systems, available technologies, and the perceived benefits and complexity of the innovation. (2)Organizational context encompasses the internal characteristics of the firm, such as firm size, managerial structure, employee competence, communication processes, and rethereforeurce availability. (3)Environmental context includes the external forces affecting the organization, such as competitive pressure, regulatory environment, and relationships with business partners or customers.\u003c/p\u003e\u003cp\u003eTOE framework offers a robust and integrative perspective for examining enterprise-level technology adoption, particularly in dynamic and complex organizational contexts. Its tripartite structure\u0026mdash;encompassing technological readiness, organizational capabilities, and environmental pressures\u0026mdash;enables a flexible systems approach to understanding how firms adapt to digital transformation. By capturing the interplay among internal resources, structural agility, and external demands, the TOE framework facilitates a holistic analysis of the enablers and barriers to the implementation of systems such as SMIS. This makes it particularly suitable for research aiming to enhance organizational adaptability, strategic alignment, and long-term competitiveness through information system innovation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Infuencing factors\u003c/h2\u003e\u003cp\u003eWhile the original TOE framework identifies three high-level dimensions\u0026mdash;technology, organization, and environment\u0026mdash;this study refines and operationalizes these categories by specifying five distinct and interrelated factors. Specifically, the technological context is represented by technological infrastructure maturity, the environmental context by external environmental pressure, and the organizational context is further disaggregated into employee digital skills, top management support, and organizational innovation capacity. This refinement is necessary because the organizational dimension in the digital manufacturing context encompasses multiple internal drivers that function differently and exert distinct influences on SMIS application.\u003c/p\u003e\u003cp\u003eTechnological infrastructure maturity ensures system compatibility, data integration, and real-time connectivity. Firms with advanced IT infrastructure are better equipped to integrate IoT, analytics, and AI tools for smart manufacturing (Yang et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Employee digital skills reflect frontline readiness to interact with SMIS. Digital literacy and system competence enhance utilization and reduce resistance, especially when supported by adequate training (Ali et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Jiang et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Top management support provides strategic direction and resource commitment, facilitating cross-departmental coordination and driving organizational alignment for successful SMIS adoption (Khan and Khan \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). External environmental pressure\u0026mdash;including market competition, customer demands, and regulatory compliance\u0026mdash;motivates firms to adopt SMIS for differentiation and operational transparency (Deng et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Lin et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Lastly, organizational innovation capacity enhances a firm\u0026rsquo;s ability to adapt, experiment, and optimize SMIS use through agile workflows and cross-functional collaboration (Brix \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Firm performance\u003c/h2\u003e\u003cp\u003eIn recent years, researchers have increasingly employed the TOE framework to investigate the adoption and outcomes of information technology (Hadwer et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Malik et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which serve as integrated digital platforms to enable real-time data processing, predictive maintenance, and production optimization through the utilize of IoT, big data analytics, and AI (Amankwah-Amoah and Adomako \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Onu et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These systems are particularly relevant in the context of Industry 4.0, where data-driven manufacturing is essential to maintaining competitive advantage.\u003c/p\u003e\u003cp\u003eRecent studies have linked TOE factors to firm performance, showing that SMIS implementation under favorable conditions enhances multiple outcomes. Production efficiency improves through real-time monitoring and predictive maintenance (Imran et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Menghi et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Product quality is elevated by data-driven defect detection and process control (Yang et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Cost control benefits from automated decision support and optimized resource allocation (Wang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). Market competitiveness is strengthened by faster response to market demands and improved customization (Huang and Sun \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Overall, the TOE framework provides a robust lens to assess how technological, organizational, and environmental factors jointly shape SMIS application and its performance impact.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Research model and hypotheses","content":"\u003cp\u003e\u003cstrong\u003e3.1 Research model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study develops a research model based on the TOE framework to explore the factors influencing the application of SMIS and their impact on firm performance. The model integrates external and internal antecedents, SMIS application as a second-order construct, and firm-level outcomes in Fig. 1.\u003c/p\u003e\n\u003cp\u003eFig. 1 here\u003c/p\u003e\n\u003cp\u003eTo explore the flexible and dynamic nature of SMIS implementation, this study constructs a research model grounded in the TOE framework. Five key enablers are identified: technological infrastructure maturity, employee digital skills, top management support, external environmental pressure, and organizational innovation capacity. Recognizing the multifaceted organizational demands of digital manufacturing, the organizational context is further elaborated into leadership, skills, and innovation capabilities. SMIS application is conceptualized as a second-order construct encompassing four capabilities—system integration, user acceptance, cross-departmental coordination, and data management—reflecting both technical configuration and organizational adaptability. Firm performance is evaluated through four critical outcomes: production efficiency, product quality, cost control, and market competitiveness. This holistic model captures the interdependencies among flexibility-enabling capabilities and their strategic and operational contributions in digitally transforming enterprises.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Hypotheses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.1 Infuencing factors and SMIS application\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTechnological infrastructure maturity refers to the advancement of a firm's hardware, software, and network systems. High levels of infrastructure maturity support system compatibility, operational stability, and efficient data processing (Serrano and Pereira 2020; Williams et al. 2019), thereby enhancing SMIS deployment and utilization (Onu et al. 2025). A well-developed infrastructure enables seamless integration of SMIS with enterprise systems such as ERP and MES, facilitating real-time analytics and cross-functional data exchange. Stable technical environments combined with adequate support services contribute to greater employee adoption and effective use of SMIS (Purnamasari et al. 2025). Robust infrastructure also encourages cross-departmental collaboration by enabling data sharing and synchronized operations, while improving data management through enhanced data model such as collection, processing, and analysis of production information (Cao et al. 2025).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH1\u003c/strong\u003e: Technological infrastructure maturity positively influences SMIS application.\u003c/p\u003e\n\u003cp\u003eEmployee professional skill level encompasses the knowledge, techniques, and experience required to operate advanced systems, solve problems, and adapt to technological change. In smart manufacturing environments, highly skilled employees facilitate SMIS adoption by efficiently managing complex equipment, data analysis, and system integration (Kim et al. 2025). Higher professional skill levels contribute to effective system integration (Fitzenberger and Speckesser 2007; Krpálek et al. 2021), enabling smoother interactions with ERP or MES platforms. Skilled employees demonstrate greater acceptance of new systems and adapt more readily, thereby improving operational efficiency. Enhanced skill sets also strengthen cross-departmental coordination by aligning technical understanding across units (Jiang and Cheng 2024), and improve data management through more accurate analysis and application of security information (e.g., SMIS) insights (Tendikov et al. 2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH2\u003c/strong\u003e: Employee professional skill level positively influences SMIS application.\u003c/p\u003e\n\u003cp\u003eTop management support denotes the extent to which senior executives actively champion technology adoption through strategic direction, resource provision, and cultural leadership (Khan and Khan 2025). This support includes financial investment, employee training, and fostering an innovation-oriented environment. During SMIS implementation, leadership commitment facilitates system integration, accelerates transformation, and enhances organizational alignment. Stronger top management support leads to more effective system integration by streamlining cross-departmental coordination and ensuring consistent resource allocation (Sun et al. 2025; Thong et al. 1996; Young and Jordan 2008). Top management support provides the strategic vision, resource commitment, and organizational encouragement necessary for successful SMIS application. When leadership actively endorses smart manufacturing initiatives, employees are more likely to engage with the system, interdepartmental alignment improves, and necessary investments in infrastructure and training are secured, fostering effective implementation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH3:\u003c/strong\u003e Top management support positively influences SMIS application.\u003c/p\u003e\n\u003cp\u003eExternal environmental pressure arises from market competition, technological advancements, regulatory requirements, and customer demands (Cui and Wang 2021; Liu 2009). These forces compel firms to adopt advanced systems such as SMIS to sustain competitiveness and respond to dynamic changes (Deng et al. 2025; Lin et al. 2025). External pressures such as market competition, customer demands, regulatory compliance, and industry standards compel firms to adopt advanced digital systems. Under such pressure, companies are more motivated to implement SMIS to enhance responsiveness, streamline operations, and maintain competitiveness in dynamic environments. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH4\u003c/strong\u003e: External environmental pressure positively influences SMIS application.\u003c/p\u003e\n\u003cp\u003eOrganizational innovation capability represents a firm's capacity to adapt, create, and implement new technologies, processes, or services in response to uncertainty and market shifts. This capability reflects not only investment in R\u0026amp;D but also a culture that supports experimentation and agility (Ma and Ji 2024). High innovation capability promotes faster technology integration, greater employee openness to system use, and stronger interdepartmental collaboration (Camisón and Villar-López 2014; Fruhling and Siau 2016). For example, effective internal collaboration mechanisms further support cross-functional coordination during SMIS implementation. Firms with strong innovation capability are more likely to embrace new technologies (Acosta-Prado 2020; Kerstens and Langley 2025), experiment with digital tools, and adapt processes for transformation. This proactive mindset fosters a favorable environment for SMIS application, as organizations seek innovative solutions to enhance efficiency, flexibility, and competitiveness in smart manufacturing. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH5\u003c/strong\u003e: Organizational innovation capability positively influences SMIS application.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.2 SMIS application and firm performance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSMIS enhances efficiency through automation, analytics, and process optimization. Greater system integration capability allows seamless data flow across platforms like ERP and MES, improving scheduling and reducing cycle times(Çakır et al. 2022; Kang et al. 2025). For example, strong user acceptance enables employees to manage tasks more accurately and efficiently, raising productivity; effective cross-departmental coordination accelerates responses to changes and streamlines resource use. IS enhance real-time data integration, automate production workflows, and enable rapid decision-making (Durmuşoğlu and Barczak 2011; Saarinen and Sääksjärvi 1992). These capabilities streamline resource allocation, reduce downtime, and minimize operational errors. Therefore, firms that effectively apply SMIS are expected to achieve higher production efficiency through improved coordination and process optimization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH6\u003c/strong\u003e: SMIS application positively influences production efficiency.\u003c/p\u003e\n\u003cp\u003eSMIS enhances product quality through data analytics, monitoring, and automation (Lee et al. 2025; Suwattananuruk and Chien 2025). For example, strong system integration capability allows real-time monitoring and data sharing with quality management systems, reducing errors and improving precision; high user acceptance ensures employees can detect and respond to production issues quickly, enhancing reliability. Effective information systems enables timely issue resolution across production, quality, and supply chain teams (Durmuşoğlu and Barczak 2011). Advanced data management capability supports predictive maintenance and compliance, ensuring consistent output and regulatory alignment (Davenport, 1997). SMIS facilitate real-time monitoring, precise process control, and seamless data exchange across production stages. These functions reduce defects, improve consistency, and enhance traceability. As a result, organizations applying SMIS are more likely to deliver high-quality products that meet customer expectations and regulatory standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH7\u003c/strong\u003e: SMIS application positively influences product quality.\u003c/p\u003e\n\u003cp\u003eImplementing SMIS enhances resource allocation, streamlines operations, and reduces inefficiencies, thereby improving cost control (Li et al. 2025). For example, system integration capability supports cost control by connecting IS, enabling real-time data sharing and process automation (Cordelia 2006; Irani et al. 2006), which reduce redundancy and operational errors; strong user acceptance ensures employees can utilize SMIS effectively, minimizing human error and waste. SMIS enhances cost control by enabling real-time tracking of resources, automating manual processes, and reducing inefficiencies in production workflows. With integrated data analysis and process monitoring, firms can identify waste, optimize inventory, and streamline operations (Yu et al. 2025). This operational visibility and control help reduce unnecessary expenses and improve overall cost efficiency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH8\u003c/strong\u003e: SMIS application positively influences operating cost control.\u003c/p\u003e\n\u003cp\u003eSMIS empower firms to enhance market competitiveness by enabling customer and market changes, agile decision-making, and operational transparency (Huang and Sun 2025). Through system integration, data analytics, and cross-functional collaboration, organizations can swiftly respond to changing market conditions, customize products, and shorten time-to-market (Caldwel et al. 2005). Enhanced data management allows better understanding of customer preferences (Zhang et al. 2022), competitor behavior, and industry trends, facilitating strategic differentiation . Moreover, user acceptance of SMIS promotes internal process alignment, leading to consistent quality and service reliability—critical components in sustaining competitive advantage. Therefore, higher levels of SMIS application are expected to yield improved competitive positioning in dynamic market environments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH9\u003c/strong\u003e: SMIS application positively influences market competitiveness.\u003c/p\u003e"},{"header":"4 Methods","content":"\u003cp\u003eThe present study adopts a mixed-methods research design, integrating both qualitative and quantitative approaches to ensure a comprehensive understanding of the factors influencing SMIS application and its impact on firm performance.\u003c/p\u003e\u003cp\u003eIn the qualitative phase, semi-structured interviews were conducted with senior executives from manufacturing firms experienced in digital transformation. The interview protocol was developed based on a comprehensive review of literature related to technology adoption, organizational capabilities, and smart manufacturing. Insights from the interviews were used to revise and refine the questionnaire items, ensuring their practical relevance and clarity. These qualitative findings also guided the identification of key dimensions and the precise wording of items for the subsequent survey instrument.\u003c/p\u003e\u003cp\u003eIn the quantitative phase, a structured questionnaire was administered to firms that had already implemented SMIS. The survey measured constructs such as technological infrastructure maturity, employee digital skills, top management support, environmental pressure, and organizational innovation capacity, along with four dimensions of SMIS application and firm performance outcomes. The collected data were analyzed using statistical methods to examine the hypothesized relationships proposed in the theoretical model.\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Mesurement of constructs\u003c/h2\u003e\u003cp\u003eThe measurement of the constructs influencing SMIS application in this study\u0026mdash;namely technological infrastructure maturity, employee digital skills, top management support, environmental pressure, and organizational innovation capacity\u0026mdash;was developed through a combination of literature review and qualitative inquiry. These constructs have been consistently identified in prior studies as critical determinants of information system adoption and integration within manufacturing contexts (Ali et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Brix \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Deng et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Jiang et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Khan and Khan \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBuilding on foundational literature, the study developed semi-structured interview questions to explore the practical operationalization of each construct. For example, senior managers were asked, \u0026ldquo;What types of digital capabilities or infrastructure does your company currently rely on for smart manufacturing?\u0026rdquo; In-depth interviews with executives from firms that had adopted SMIS, followed by thematic content analysis, revealed key indicators for each construct. For instance, technological infrastructure maturity was commonly associated with stable system operation, seamless connectivity with production equipment, and access to AI-powered data analytics tools.\u003c/p\u003e\u003cp\u003eInsights from the interviews were used to refine each construct into three measurable items, ensuring both theoretical coherence and contextual relevance. These items informed the development of the survey instrument used in the quantitative phase. For example, employee digital skills were assessed through items on the frequency of digital tool usage, confidence in operating smart systems, and participation in upskilling programs\u0026mdash;guided by prior research (Ali et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Jiang et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and validated through field input. By integrating literature review with empirical insights, the final measurement model effectively captures the multidimensional nature of the key drivers influencing SMIS application.\u003c/p\u003e\u003cp\u003eThis study conceptualizes SMIS application as a second-order construct comprising four formative dimensions: system integration capability, user acceptance, cross-departmental coordination, and data management capability. These dimensions emerged from prior literature (Chandani et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Febrianto et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Kim et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Leng et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and were refined through interviews with senior executives in SMIS-adopting firms. Each dimension represents a key operational mechanism that drives firm performance. System integration capability captures the extent of SMIS integration with existing systems (e.g., ERP, MES) and the ability to support seamless data exchange (Febrianto et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). User acceptance assesses employee willingness to use SMIS, perceived usefulness, and confidence in system operation (Chandani et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Cross-departmental coordination measures the system's role in promoting collaboration among departments such as production, and supply chain. Data management capability reflects the firm\u0026rsquo;s ability to collect, store, analyze, and apply SMIS-generated data for informed decision-making (Kim et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Leng et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEach first-order construct was measured using three reflective items adapted from validated scales and contextualized for smart manufacturing. Interview findings helped ensure content validity and practical relevance. Academic and industry experts reviewed and revised the final items during the pretest phase. Following Hair et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), a two-stage measurement approach was used to assess the formative structure of the first-order constructs and the second-order SMIS application construct.\u003c/p\u003e\u003cp\u003eFirm performance was measured as a multidimensional construct covering four outcome areas: production efficiency, product quality, cost control, and market competitiveness. These dimensions represent both operational and strategic impacts of SMIS. Semi-structured interviews and literature (Huang and Sun \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Imran et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2026\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) guided the development and refinement of performance measures: (1)Production efficiency evaluates improvements in resource utilization and cycle time reduction (Imran et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). (2)Product quality assesses consistency, reliability, and customer satisfaction gains (Yang et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). (3)Cost control measures reductions in operational expenses, waste, and improvements in resource allocation (Wang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). (4)Market competitiveness captures responsiveness to market changes and enhancement of strategic agility (Huang and Sun \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA pilot test confirmed the reliability and validity of the measurement items, with feedback from practitioners ensuring both theoretical rigor and industry relevance (see Appendix A).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Control constructs\u003c/h2\u003e\u003cp\u003eTo account for organizational characteristics affecting SMIS application and effectiveness, this study includes three commonly referenced control variables: firm size, firm age, and firm capital. These factors help isolate the influence of core explanatory variables and enhance model accuracy.\u003c/p\u003e\u003cp\u003eFirm size, typically measured by employee count, reflects a firm\u0026rsquo;s capacity in financial, technological, and human resources. Larger firms often demonstrate stronger abilities to implement IS and manage digital transformation projects (Tsou and Chen \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Firm age, defined by years since establishment, suggests accumulated operational experience and process maturity. Older firms may leverage institutional knowledge to support IS adoption, though some may face innovation resistance due to organizational inertia (Baum et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Firm capital, measured by registered or operating capital, indicates financial strength available for strategic investments. Higher capital levels enable greater flexibility in acquiring, customizing, and scaling IS platforms (Florin and Lubatkin \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Inclusion of these variables enhances the robustness of the empirical model and ensures that observed effects stem from TOE-related factors rather than organizational heterogeneity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Quantitative survey collection\u003c/h2\u003e\u003cp\u003eTo examine the flexible enablers and performance outcomes of SMIS application, this study employed a structured survey methodology targeting medium and large manufacturing firms in Taiwan. The sampling frame was derived from the \u0026ldquo;Top 5,000 Largest Corporations in Taiwan\u0026rdquo; published by the China Credit Information Service, Ltd. The manufacturing sector was chosen due to its central role in Taiwan\u0026rsquo;s industrial transformation and its proactive adoption of Industry 4.0 technologies. The implementation of SMIS in this context typically involves the integration of complex platforms such as ERP, MES, and IoT\u0026mdash;making it an ideal setting to study technological readiness, cross-departmental coordination, and data-driven decision-making. Moreover, in the face of intensifying global competition, the strategic need for organizational adaptability and operational agility makes these firms particularly relevant for assessing the flexible impact of SMIS on firm performance.\u003c/p\u003e\u003cp\u003eThe tarobtain respondents were high-level managers who have experience with or oversight of smart manufacturing initiatives, such as digital transformation directors, IT managers, production supervithereforers, or plant managers. These individuals were in the best position to evaluate organizational digital capabilities and SMIS usage, as well as its influence on production efficiency, product quality, cost control, and market competitiveness.\u003c/p\u003e\u003cp\u003eThe sample for this study was drawn from the Top 5,000 Largest Corporations in Taiwan, focusing on the top 350 medium-to-large-sized enterprises. Survey packages were mailed to the selected firms and included a cover letter explaining the purpose of the study, the questionnaire, and a self-addressed stamped envelope. In the first round of distribution, 45 valid responses were received. To improve the response rate, a follow-up was conducted via phone calls and emails, yielding an additional 58 responses in the second round. After removing incomplete or invalid questionnaires, a total of 103 valid responses were retained, representing an effective response rate of 24%. Among these, 83 firms confirmed that they had implemented SMIS, and these 83 responses were used for the final analysis.\u003c/p\u003e\u003c/div\u003e"},{"header":"5 Analysis and results","content":"\u003cp\u003eSurvey data analysis was conducted using partial least squares (PLS), a structural equation modeling (SEM) technique well-suited for exploratory research involving complex models with both formative and reflective constructs. PLS is particularly advantageous for its ability to handle smaller sample sizes and its minimal assumptions regarding data distrihoweverion and measurement scales. Given that the SMIS application construct was modeled as a second-order construct with multiple first-order formative dimensions, PLS offered the methodological flexibility required for this research. The analysis followed a two-step approach: (1) assessment of the measurement model to examine the reliability and validity of all constructs, and (2) evaluation of the structural model to test the hypothesized relationships among variables. All statistical analyses were carried out using SmartPLS 4.0 (Ringle et al., 2022), which enabled the validation of the measurement properties and estimation of the structural paths within the research framework.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Measurement model\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the standardized loadings, reliability, and validity metrics for all item measures. The factor loadings of the items in the measurement model range from 0.557 to 0.971. While a loading above 0.70 is generally considered ideal (Hair et al., 2010), items with loadings between 0.50 and 0.70 may still be retained if they contrihowevere to content validity and the overall construct reliability remains acceptable. In this study, all constructs demonstrate composite reliability values ranging from 0.790 to 0.967, exceeding the 0.70 threshold recommended by Segars (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), indicating good internal consistency. Furthermore, the average variance extracted (AVE) for each construct exceeds the recommended benchmark of 0.50, supporting convergent validity.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reports the results of discriminant validity assessment using the Fornell-Larcker criterion. For satisfactory discriminant validity, the square root of the AVE for each construct should be greater than its correlations with any other construct (Fornell and Larcker \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). The results confirm that this condition is met for all constructs in the model. Additionally, the analysis of cross-loadings (Appendix B) further supports the presence of acceptable discriminant validity.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e5.2 Structural model\u003c/h2\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the structural model results, including path coefficients and their significance levels. The application of SMIS was significantly influenced by employee digital skills (β\u0026thinsp;=\u0026thinsp;0.206, p\u0026thinsp;\u0026lt;\u0026thinsp;.01), top management support (β\u0026thinsp;=\u0026thinsp;0.344, p\u0026thinsp;\u0026lt;\u0026thinsp;.01), and external environmental pressure (β\u0026thinsp;=\u0026thinsp;0.250, p\u0026thinsp;\u0026lt;\u0026thinsp;.01). These three variables collectively explained 76.1% of the variance in SMIS application, thereby supporting hypotheses H2, H3, and H4. In contrast, technological infrastructure maturity (β\u0026thinsp;=\u0026thinsp;0.081, p\u0026thinsp;\u0026gt;\u0026thinsp;.05) and organizational innovation capacity (β\u0026thinsp;=\u0026thinsp;0.083, p\u0026thinsp;\u0026gt;\u0026thinsp;.05) did not exhibit significant effects on SMIS application, leading to the rejection of H1 and H5.\u003c/p\u003e\u003cp\u003eSMIS application, in turn, exerted a significant positive influence on all four dimensions of firm performance: production efficiency (β\u0026thinsp;=\u0026thinsp;0.683, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), product quality (β\u0026thinsp;=\u0026thinsp;0.626, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), cost control (β\u0026thinsp;=\u0026thinsp;0.463, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), and market competitiveness (β\u0026thinsp;=\u0026thinsp;0.659, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), thereby supporting hypotheses H6 through H9. The explanatory power (R\u0026sup2;) of SMIS application on each performance outcome is as follows: production efficiency (46.7%), product quality (39.1%), cost control (21.4%), and market competitiveness (43.5%). These results highlight the critical role of SMIS in enhancing key operational and strategic performance indicators within manufacturing firms. Finally, the analysis of control variables indicates that firm size, firm age, and firm capital do not have statistically significant effects on SMIS application or firm performance in this context.\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here\u003c/p\u003e\u003c/div\u003e"},{"header":"6 Discussion","content":"\u003cp\u003eContrary to expectations, the hypothesis that technological infrastructure maturity positively influences SMIS application was not supported. This finding suggests that while robust infrastructure\u0026mdash;such as advanced networks and data systems\u0026mdash;provides a necessary foundation, it alone may not drive flexible and adaptive use of SMIS. From a flexible systems perspective, effective application depends more on an organization\u0026rsquo;s ability to align technology with cross-functional workflows, cultivate user engagement, and adapt systems to evolving strategic needs. Without organizational responsiveness and interdepartmental collaboration, even the most advanced infrastructure may fall short in supporting agile manufacturing processes and dynamic decision-making.This finding contrasts with prior studies (Serrano and Pereira \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Williams et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) that emphasized the foundational role of infrastructure maturity in reducing technical uncertainty and enabling system integration. It may be that other factors\u0026mdash;such as management commitment, innovation culture, or change readiness\u0026mdash;play a more critical mediating role in realizing the benefits of technological infrastructure. Future research should explore these mediating mechanisms to better understand how infrastructure maturity translates into actual system application outcomes.\u003c/p\u003e\u003cp\u003eThe empirical results support the hypothesis that employee digital skills are positively asthereforeciated with SMIS application. This indicates that employees with higher levels of digital proficiency are more capable of operating smart systems, interpreting data insights, and adapting to new technologies. The finding aligns with previous studies indicating that workforce competency is a key enabler of IT assimilation and innovation adoption (Fitzenberger and Speckesser \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Krp\u0026aacute;lek et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe hypothesis regarding the positive influence of top management support on SMIS application is furthermore supported. The findings validate that visible leadership commitment\u0026mdash;such as providing strategic direction, rethereforeurces, and encouragement\u0026mdash;facilitates smoother implementation and higher system usage. This echoes the notion that top-down support is crucial for overcoming resistance to change and fostering cross-functional alignment(Thong et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Young and Jordan 2008).\u003c/p\u003e\u003cp\u003eThe analysis reveals a significant positive relationship between external environmental pressure and SMIS application, confirming the corresponding hypothesis. This indicates that market competition, regulatory changes, and customer expectations motivate firms to adopt advanced information systems to maintain competitiveness. These results are consistent with prior literatures, which indicates that external forces drive organizational behavior and technological innovation (Cui and Wang \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe hypothesis that organizational innovation capacity positively influences SMIS application is not supported. This result indicates that having a strong innovation orientation alone may not directly translate into the effective application of SMIS. One possible explanation is that while innovation capacity may foster openness to new ideas, it does not necessarily guarantee successful system integration, user adoption, or cross-departmental coordination\u0026mdash;key elements required for SMIS implementation. This finding diverges from previous literature (Camis\u0026oacute;n and Villar-L\u0026oacute;pez \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Fruhling and Siau \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which emphasized the enabling role of organizational innovation in technological change. It is possible that structural rigidities, lack of digital leadership, or resistance to operational changes may offset the potential benefits of innovation capacity. Future research should examine under what conditions innovation capacity can more effectively contrihowevere to the implementation of digital systems like SMIS.\u003c/p\u003e\u003cp\u003eThe implementation of SMIS is widely regarded as a strategic enabler for enhancing organizational agility, responsiveness, and performance. This study empirically examined the effects of SMIS application on four critical performance dimensions: production efficiency, product quality, cost control, and market competitiveness. Results confirm that a well-integrated and flexibly applied SMIS significantly contributes to these outcomes. From a flexible systems perspective, the value of SMIS lies not only in technological functionality but also in its ability to support adaptive decision-making, streamline interdepartmental processes, and enhance the organization\u0026rsquo;s capacity to respond to dynamic market shifts. These findings underscore the importance of aligning digital systems with flexible organizational practices to achieve sustainable competitive advantage. The details are as follows:\u003c/p\u003e\u003cp\u003eThe results indicate a significant positive relationship between SMIS application and production efficiency, confirming that enterprises effectively applying smart manufacturing information systems experience improved rethereforeurce utilization and faster production processes. This finding indicates that the integration of SMIS facilitates real-time data sharing, automation, and better coordination across production units, which enhances production scheduling, reduces waste, and shortens lead times. This study supports prior research that emphasizes the importance of digital systems in improving operational agility and throughput (Durmuşoğlu and Barczak \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Saarinen and S\u0026auml;\u0026auml;ksj\u0026auml;rvi 1992).\u003c/p\u003e\u003cp\u003eThe analysis confirms that SMIS application has a significant positive impact on product quality. Companies that actively apply SMIS are more capable of maintaining consistency and precision throughout the production process. This supports the view that SMIS can improve quality control through automated monitoring, real-time defect detection, and predictive maintenance. Enhanced product quality contrihoweveres to customer satisfaction and brand reputation, aligning with previous research such as (Durmuşoğlu and Barczak \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), which link information systems with quality assurance mechanisms.\u003c/p\u003e\u003cp\u003eSMIS application is found to be positively asthereforeciated with cost control. Firms utilizing SMIS more extensively are better at reducing production waste, minimizing downtime, and optimizing rethereforeurce allocation. The result demonstrates the cost-saving potential of SMIS through digital coordination, reduction in manual errors, and data-driven decision-making. This prior literature (Cordelia \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Irani et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) that identifies IT-enabled integration as a critical enabler of leaner operations and lower overhead.\u003c/p\u003e\u003cp\u003eThe results show a statistically significant and positive relationship between SMIS application and market competitiveness. Firms that effectively leverage SMIS are more capable of responding to market changes and customer demands swiftly. This finding highlights the strategic value of SMIS in enhancing market agility, innovation speed, and customer responsiveness. This study confirms that smart systems not only optimize internal operations however furthermore enable firms to differentiate themselves in competitive markets, supporting theories such as those by Caldwel et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e"},{"header":"7 Conclusion","content":"\u003cp\u003eThis study investigated the antecedents and performance impacts of SMIS application through the lens of the TOE framework. The findings highlight that employee digital skills, top management support, and external environmental pressure are critical enablers for effective SMIS adoption, reinforcing the importance of both internal readiness and adaptive response to external dynamics. Interestingly, technological infrastructure maturity and innovation capacity alone did not significantly influence SMIS application, suggesting that flexible implementation requires more than just technical or strategic intent\u0026mdash;it demands coordinated organizational alignment and agile integration practices. Furthermore, the positive effects of SMIS application on production efficiency, product quality, cost control, and market competitiveness underscore its role as a catalyst for enhancing organizational responsiveness and sustainable performance in dynamic manufacturing environments. These insights contribute to the broader discourse on flexible systems management by illustrating how digital tools must be embedded within adaptive organizational contexts to achieve transformative outcomes.\u003c/p\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e7.1 Theoretical Implications\u003c/h2\u003e\u003cp\u003eThis research offers several contributions to the academic literature. First, the study extends the TOE framework by examining five theoretically grounded and context-specific antecedents of SMIS application. While only employee digital skills, top management support, and external environmental pressure showed significant effects, the inclusion of all five factors provides a nuanced understanding of the diverse conditions shaping SMIS adoption. This balanced perspective clarifies both the enablers and constraints of system application in digital manufacturing contexts.\u003c/p\u003e\u003cp\u003eSecond, this study contributes methodologically by combining insights from prior literature with semi-structured interviews of senior manufacturing executives to refine the measurement items. This qualitative\u0026ndash;quantitative approach strengthens construct validity and ensures that the survey instrument is both theoretically robust and practically relevant, offering a replicable framework for future research in smart manufacturing and information systems.\u003c/p\u003e\u003cp\u003eFinally, by empirically examining the relationship between SMIS application and multiple performance outcomes\u0026mdash;production efficiency, product quality, cost control, and market competitiveness\u0026mdash;the study provides evidence supporting a positive association between SMIS use and organizational performance. However, these findings should be interpreted with caution given the cross-sectional design, the limited sample of 83 firms already implementing SMIS, and potential contextual differences across industries. Future research could address these limitations by employing longitudinal designs, broader samples, and comparative analyses across sectors.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e7.2 Managerial Implications\u003c/h2\u003e\u003cp\u003eThis study provides valuable managerial insights for enhancing organizational flexibility and responsiveness through the strategic application of SMIS. The significant influence of employee digital skills highlights the importance of cultivating a flexible and future-ready workforce. Companies should invest in continuous learning, hands-on digital training, and cross-functional collaboration, all of which improve not only system usage but also the organization\u0026rsquo;s capacity to adapt to rapidly evolving technologies and processes.\u003c/p\u003e\u003cp\u003eThe critical role of top management support further emphasizes the need for leadership to champion digital transformation efforts. By actively engaging in strategic prioritization, resource reallocation, and promoting a change-oriented culture, executives can facilitate flexible decision-making structures that are crucial for agile execution across departments.\u003c/p\u003e\u003cp\u003eMoreover, the impact of external environmental pressures\u0026mdash;including market volatility, customer demands, and regulatory shifts\u0026mdash;reinforces the need for organizations to enhance their environmental scanning and adaptive capabilities. Firms that proactively adjust SMIS implementation in response to external dynamics are better positioned to maintain strategic alignment and operational resilience in turbulent business environments.\u003c/p\u003e\u003cp\u003eInterestingly, the non-significant role of technological infrastructure maturity suggests that technical resources alone are insufficient to drive successful system adoption. This insight cautions managers against over-relying on hardware or system upgrades without accompanying changes in organizational processes, people engagement, and change-readiness frameworks. A flexible implementation strategy requires alignment across people, processes, and platforms.\u003c/p\u003e\u003cp\u003eSimilarly, the insignificant influence of innovation capacity implies that innovation, while important, must be tethered to practical implementation pathways. Managers should ensure that creative efforts translate into actionable digital initiatives that align with operational goals and real-world use cases, thereby bridging the gap between strategic vision and execution.\u003c/p\u003e\u003cp\u003eFinally, since the findings confirm that SMIS application positively influences production efficiency, product quality, cost control, and market competitiveness, managers are encouraged to treat SMIS not merely as a technical upgrade, but as a strategic enabler of enterprise-wide flexibility. By leveraging SMIS for real-time data analytics, interdepartmental integration, predictive maintenance, and data-driven decision-making, firms can significantly enhance their capacity to respond to internal and external changes while driving sustainable performance gains.\u003c/p\u003e\u003cp\u003eThese insights support the broader paradigm of flexible systems management, where digital tools are embedded within agile, responsive, and coordinated organizational structures\u0026mdash;enabling enterprises to thrive in dynamic manufacturing environments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e7.3 Limitations and Future Research Directions\u003c/h2\u003e\u003cp\u003eSeveral limitations of this study should be acknowledged, which provide avenues for future research within the domain of flexible systems management. First, while this study specifically focused on firms that have already implemented SMIS, it did not distinguish between different stages of SMIS maturity, such as pilot adoption, partial deployment, or full-scale integration. Since flexibility often evolves over time, future research could adopt a longitudinal design to examine how firms dynamically adapt their SMIS usage across different stages of digital transformation\u0026mdash;capturing the evolution of both technological and organizational flexibility.\u003c/p\u003e\u003cp\u003eSecond, although the measurement constructs were carefully developed through a mixed-methods approach\u0026mdash;integrating prior literature with semi-structured interviews from senior executives\u0026mdash;this design primarily captures the perspectives of early adopters. While this strengthens the study\u0026rsquo;s relevance to current industry practice, it also limits the generalizability to firms that have not yet begun or are struggling with SMIS implementation. Broader sampling across adoption readiness levels would allow for more comprehensive modeling of organizational flexibility and resistance.\u003c/p\u003e\u003cp\u003eThird, the final dataset consists of 83 valid responses from medium and large manufacturing firms in Taiwan. This sample reflects the current stage of SMIS diffusion in the region, where many enterprises are still in the early or transitional phases of digital adoption. Although the sample is analytically adequate for partial least squares (PLS) analysis, future research could benefit from larger and more diverse samples\u0026mdash;including firms from different industries, countries, or organizational structures\u0026mdash;to further validate the findings and explore contextual differences in SMIS flexibility.\u003c/p\u003e\u003cp\u003eLastly, this study focused on cross-sectional data, which limits the ability to capture dynamic interactions between environmental changes and system reconfiguration\u0026mdash;a critical element of flexible systems management. Future research could adopt process-based or interpretive approaches to investigate how SMIS-enabled organizations continuously recalibrate their processes, structures, and resource allocation in response to external volatility and internal shifts.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStandardized factor loading, t-value, CR, and AVE.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstruct\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndicator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFactor loading\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eComposite\u003c/p\u003e\u003cp\u003eReliability\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAverage\u003c/p\u003e\u003cp\u003eVariance\u003c/p\u003e\u003cp\u003eExtracted\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCross-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCDC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.945\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.962\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.792\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepartmental\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCDC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.753\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.606\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoordination\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCDC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.957\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.853\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eData\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDMC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.949\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.766\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.936\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.884\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eManagmenet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDMC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.916\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.610\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCapability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDMC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.955\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployee\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEDS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.946\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16.920\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.933\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.866\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDigital Skills\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEDS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEDS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.939\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16.131\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExternal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEEP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.834\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.851\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.742\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnvironmental\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEEP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.845\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePressure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEEP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.863\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrganizational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOIC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.935\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.920\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.846\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInnovation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOIC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.940\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.524\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCapacity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOIC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.934\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.661\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCost\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePCC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.439\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.820\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.649\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePCC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.666\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePCC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.891\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarket\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.913\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.844\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.688\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompetitiveness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.725\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.716\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.840\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProduction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPE1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.901\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.813\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEfficiency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPE2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.935\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPE2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.909\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.618\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProduct\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPQ1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.924\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.485\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.882\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.772\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQuality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPQ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.857\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPQ3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystems\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSIC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21.339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.919\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.856\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntergration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSIC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.885\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17.387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCapability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSIC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.952\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25.364\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTechnological\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTIM1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.965\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.967\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.923\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfrastructure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTIM2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.946\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.870\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaturity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTIM3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.971\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16.685\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTop\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTMS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.819\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.790\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.647\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eManagement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTMS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.866\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSupport\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTMS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.557\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUser\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUAP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.911\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.713\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.890\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.818\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcceptance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUAP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.896\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUAP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.906\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.326\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDiscriminant validity.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"14\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCDC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDMC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEDS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEEP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOIC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePCC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePMC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ePPE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003ePPQ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eSIC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTIM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eTMS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003eUAP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCDC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.890\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.940\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEDS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.587\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.707\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.930\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEEP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.690\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.807\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.632\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.861\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.552\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.734\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.576\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.920\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.430\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.475\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.574\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.474\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.805\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.685\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.736\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.781\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.699\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.723\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.749\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.829\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePPE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.524\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.601\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.520\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.510\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.563\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.901\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePPQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.536\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.612\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.477\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.662\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.624\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.649\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.879\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.718\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.673\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.694\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.543\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.609\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.643\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.615\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e0.925\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTIM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.563\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.691\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.681\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.715\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.671\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.578\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.797\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.604\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.586\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.639\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.961\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.796\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.771\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.665\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.675\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.628\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.474\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.833\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e0.804\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUAP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.625\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.859\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.642\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.738\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.651\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.430\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.722\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.632\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.606\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.591\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.625\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e\u003cb\u003e0.904\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"14\"\u003eNotes: 1.CDC: Cross-departmental coordination; 2. Data managemnet capability; 3. EDS: Exployee digital skills; 4. EEP: External environmental pressure; 5. OIC: organizational innovation capability;\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e6. PCC: Cost Control; 5. PMC: Market compeitieness; 7. PPE: Production efficiency; 8. PPQ: Product quality; 9. TIM: Technological infrastureture maturity; 10. TMS: Top Management support; 11. Top management support; 12. User acceptance; Diagonals represent the square root of average variance extracted, while the other matrix entries represent the correlations.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Declaration\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by a grant from the National Science and Technology Council (NSTC 112-2221-E-468-015), Taiwan. Relevant funding details have already been provided in the journal’s submission system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Declaration\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in this study complied with ethical standards. Participants were informed of the research purpose, and their participation was voluntary and anonymous. No identifiable personal data were collected.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eShu-Hui Chuang wrote the main manuscript text, conducted data collection, and performed data analysis. Shinyi Lin and Jih-Chuan Jan contributed to the data collection process and provided support in organizing field interviews.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAcosta-Prado, J. C. Relationship between Organizational Climate and Innovation Capability in New Technology-Based Firms. 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An implementation for Smart Manufacturing Information System (SMIS) from an industrial practice survey. Computers \u0026amp; Industrial Engineering\u003cem\u003e, \u003c/em\u003e\u003cstrong\u003e151\u003c/strong\u003e, 106938 (2021). https://doi.org/10.1016/j.cie.2020.106938\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Smart manufacturing information systems, Technology-organization-environment framework, Digital transformation, Firm performance","lastPublishedDoi":"10.21203/rs.3.rs-7654072/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7654072/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo advance organizational flexibility and adaptability in the era of digital transformation, this study investigates the application of Smart Manufacturing Information Systems (SMIS) through the lens of the Technology\u0026ndash;Organization\u0026ndash;Environment (TOE) framework. Adopting a mixed-methods approach, we first conducted semi-structured interviews with senior managers and integrated insights from the literature to develop a robust survey instrument. Data were collected from 83 medium- and large-sized Taiwanese manufacturing firms that had already implemented SMIS. The study examines critical antecedents to assess their influence on SMIS application. SMIS utilization is conceptualized as a multi-dimensional capability, and its impact is evaluated across four key performance outcomes: production efficiency, product quality, cost control, and market competitiveness. Using structural equation modeling with SmartPLS, the results reveal that employee digital skills, top management support, and external pressure significantly enhance SMIS application, which in turn leads to improvements across all performance dimensions. This study contributes to the flexible systems management literature by embedding flexibility-oriented constructs within the TOE framework and demonstrating how SMIS can serve as a strategic enabler of organizational agility and resilience. Practical implications are offered for managers seeking to navigate digital disruption through context-aware and capability-driven system deployment.\u003c/p\u003e","manuscriptTitle":"Understanding the Drivers and Impacts of Smart Manufacturing Information Systems Application in the Manufacturing Sector: Evidence from a Mixed-Methods Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-27 15:29:59","doi":"10.21203/rs.3.rs-7654072/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"85ac576f-405f-436f-a11a-26245b28574b","owner":[],"postedDate":"October 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-02T05:24:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-27 15:29:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7654072","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7654072","identity":"rs-7654072","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}