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<h2>Introduction</h2><p>Digital transformation (DT) refers to the integration of digital technologies into all areas of business, fundamentally changing how organizations operate and deliver value to customers (Vial, 2019). For small and medium enterprises (SMEs), DT offers opportunities to enhance operational efficiency, improve customer experiences, and gain competitive advantage (Eller et al., 2020). However, SMEs often face unique challenges, including limited resources, lack of digital skills, and organizational inertia, which may hinder successful DT adoption (Zhu et al., 2021). Despite the growing body of research on DT, empirical evidence on its direct and indirect effects on SME performance outcomes remains fragmented and inconclusive (Nwankpa & Roumani, 2016).</p><p>Operational efficiency, defined as the ratio of outputs to inputs in production processes, is a critical performance metric for SMEs (Gunasekaran et al., 2019). DT can improve efficiency through automation, data analytics, and streamlined workflows (Fitzgerald et al., 2014). Similarly, customer satisfaction, a key driver of loyalty and profitability, can be enhanced through personalized services, omnichannel engagement, and faster response times enabled by digital tools (Parasuraman & Grewal, 2000). Yet, the mechanisms through which DT influences these outcomes are not fully understood. Organizational agility—the ability to sense and respond to market changes rapidly—has been proposed as a mediator (Teece et al., 2016). Additionally, firm size may moderate the DT-performance link, as larger SMEs may have more slack resources to invest in digital capabilities (Müller et al., 2018).</p><p>This study addresses the following research questions: (1) To what extent does DT adoption affect operational efficiency and customer satisfaction in SMEs? (2) Does organizational agility mediate these relationships? (3) Does firm size moderate the DT–efficiency relationship? By answering these questions, we aim to provide a comprehensive understanding of DT's impact on SME performance, offering both theoretical and practical insights.</p><h2>Methods</h2><h3>Research Design</h3><p>We employed a sequential explanatory mixed-methods design (Creswell & Plano Clark, 2017), consisting of a quantitative phase followed by a qualitative phase. The quantitative phase tested the hypothesized relationships using survey data, while the qualitative phase provided deeper explanations of the quantitative results through interviews.</p><h3>Sample and Data Collection</h3><p>The target population comprised SMEs (10–250 employees) operating in manufacturing and service sectors in Spain, the United States, China, and the United Arab Emirates. Using stratified random sampling, we distributed an online questionnaire to 1,000 SME managers, yielding 312 usable responses (response rate = 31.2%). The sample included 58% service firms and 42% manufacturing firms, with an average firm size of 78 employees (SD = 52). Data were collected between March and June 2023.</p><p>For the qualitative phase, we purposively selected 20 managers from the survey respondents who indicated willingness to participate in follow-up interviews. The interviews were semi-structured, lasting 45–60 minutes, and covered topics such as DT initiatives, challenges, and perceived impacts. All interviews were audio-recorded and transcribed verbatim.</p><h3>Measures</h3><p>All constructs were measured using validated scales from prior literature, adapted to the SME context. DT adoption was assessed using a 7-item scale based on Fitzgerald et al. (2014), capturing the extent of digital technology use in operations, marketing, and customer service. Operational efficiency was measured with a 5-item scale adapted from Gunasekaran et al. (2019), focusing on cost reduction, process speed, and resource utilization. Customer satisfaction was measured using a 6-item scale from Parasuraman and Grewal (2000), reflecting perceived service quality and customer feedback. Organizational agility was measured with a 6-item scale from Teece et al. (2016), assessing responsiveness to market changes and flexibility. Firm size was measured as the natural logarithm of the number of employees. All items were rated on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree).</p><h3>Data Analysis</h3><p>Quantitative data were analyzed using SPSS 27 and AMOS 27. We first conducted confirmatory factor analysis (CFA) to assess the measurement model's validity and reliability. Then, we tested the structural model using structural equation modeling (SEM) with maximum likelihood estimation. Mediation was tested using bootstrapping (5,000 resamples) to calculate indirect effects. Moderation was tested by creating interaction terms and examining their significance. Qualitative data were analyzed using thematic analysis (Braun & Clarke, 2006), with codes and themes derived inductively.</p><h2>Results</h2><h3>Measurement Model</h3><p>The CFA results indicated a good fit: χ²/df = 1.82, CFI = 0.95, TLI = 0.94, RMSEA = 0.05, SRMR = 0.04. All factor loadings were significant and above 0.70. Composite reliabilities (CR) ranged from 0.84 to 0.91, and average variance extracted (AVE) ranged from 0.58 to 0.68, supporting convergent validity. Discriminant validity was confirmed as the square root of AVE for each construct exceeded its correlations with other constructs.</p><h3>Descriptive Statistics and Correlations</h3><p>Table 1 presents means, standard deviations, and correlations. DT adoption was positively correlated with operational efficiency (r = 0.45, p < 0.01), customer satisfaction (r = 0.41, p < 0.01), and organizational agility (r = 0.52, p < 0.01).</p><h3>Hypothesis Testing</h3><p>The structural model demonstrated good fit (χ²/df = 1.95, CFI = 0.94, TLI = 0.93, RMSEA = 0.06). DT adoption had a significant positive effect on operational efficiency (β = 0.42, p < 0.001) and customer satisfaction (β = 0.38, p < 0.001), supporting H1 and H2. Organizational agility significantly predicted both operational efficiency (β = 0.31, p < 0.001) and customer satisfaction (β = 0.27, p < 0.001). The indirect effects of DT on operational efficiency (β = 0.16, p < 0.01) and customer satisfaction (β = 0.14, p < 0.01) via agility were significant, indicating partial mediation (H3 supported). The interaction between DT and firm size was significant for operational efficiency (β = 0.12, p < 0.05), indicating that the positive effect of DT on efficiency was stronger for larger SMEs (H4 supported).</p><h3>Qualitative Findings</h3><p>Thematic analysis revealed three main themes: (1) Resource constraints, (2) Skill gaps, and (3) Change management. Managers frequently cited limited budgets and time as barriers to DT implementation. One manager noted, "We wanted to adopt cloud-based ERP, but the cost was prohibitive for our size." Skill gaps were also prevalent, with many employees lacking digital competencies. A service firm manager stated, "Our staff are excellent at their jobs, but they struggle with new software." Change management emerged as a critical success factor; firms that phased implementation and provided training reported smoother transitions. For example, a manufacturing manager explained, "We rolled out the new system in stages, which helped reduce resistance." These findings explain why agility mediates the DT-performance link: firms that can adapt their processes and upskill employees are better able to translate DT investments into efficiency and satisfaction gains.</p><h2>Discussion</h2><p>This study provides robust evidence that DT adoption positively influences operational efficiency and customer satisfaction in SMEs, consistent with prior research (Eller et al., 2020; Nwankpa & Roumani, 2016). The significant mediation by organizational agility suggests that DT's benefits are not automatic; rather, they depend on the firm's ability to reconfigure resources and respond to changes (Teece et al., 2016). This finding extends the dynamic capabilities view to the SME context, highlighting agility as a key mechanism.</p><p>The moderation by firm size indicates that larger SMEs reap greater efficiency gains from DT, possibly due to economies of scale and more slack resources (Müller et al., 2018). Smaller SMEs may need targeted support to overcome resource constraints, as echoed in the qualitative findings. The qualitative insights also underscore the importance of change management and skill development, aligning with organizational readiness literature (Zhu et al., 2021).</p><p>Our study contributes to the literature by integrating quantitative and qualitative approaches, offering a holistic view of DT's impact. Practically, managers should invest in building organizational agility through flexible processes and continuous learning. Policymakers could design support programs that address SMEs' specific needs, such as subsidized training and technology adoption grants.</p><h3>Limitations and Future Research</h3><p>Several limitations should be acknowledged. First, the cross-sectional design precludes causal inferences; future research could employ longitudinal designs. Second, self-reported measures may introduce common method bias, although we used procedural remedies (e.g., anonymity, item counterbalancing). Third, the sample was drawn from four countries, which may limit generalizability; cross-cultural comparisons could be explored. Finally, we focused on two performance outcomes; future studies could examine other metrics such as innovation or financial performance.</p><h2>Conclusion</h2><p>This mixed-methods study demonstrates that digital transformation significantly enhances operational efficiency and customer satisfaction in SMEs, with organizational agility acting as a partial mediator and firm size as a moderator. The findings underscore the need for SMEs to develop agility and manage change effectively to fully realize DT benefits. For practitioners, our results suggest that a phased approach, coupled with employee training, can mitigate challenges. 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