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<h2>Introduction</h2><p>Digital transformation (DT) has emerged as a strategic imperative for organizations seeking to enhance competitiveness and operational performance (Vial, 2019). For small and medium enterprises (SMEs), which constitute the backbone of many economies, DT offers opportunities to streamline processes, reduce costs, and improve customer responsiveness (Nwankpa & Roumani, 2016). However, the extent to which DT translates into operational efficiency gains remains contested, with studies reporting mixed results (Fitzgerald et al., 2014). This ambiguity is particularly pronounced in emerging economies, where SMEs face unique constraints such as limited financial resources, inadequate digital infrastructure, and a shortage of skilled labor (Matarazzo et al., 2021).</p><p>Operational efficiency, defined as the ability to deliver products and services with minimal waste and optimal resource utilization, is a key performance indicator for SMEs (Gunasekaran et al., 2017). While DT is often assumed to improve efficiency through automation, data analytics, and enhanced communication, the mechanisms through which these benefits materialize are not fully understood. Prior research has highlighted the importance of organizational capabilities, such as employee digital skills, as critical enablers of DT success (Kane et al., 2017). Yet, empirical evidence on the mediating role of these skills is scarce.</p><p>Furthermore, the organizational context, particularly culture, may moderate the effectiveness of DT initiatives. A culture that encourages innovation, risk-taking, and learning is likely to facilitate the adoption and utilization of digital technologies (Duarte & de Oliveira, 2020). Conversely, a rigid or risk-averse culture may impede the realization of efficiency gains. Despite the theoretical plausibility, few studies have empirically tested these moderating effects in the SME context.</p><p>This study addresses these gaps by examining the following research questions: (1) To what extent does digital transformation influence operational efficiency in SMEs? (2) Does employee digital skills mediate this relationship? (3) Does organizational culture moderate the direct effect of DT on operational efficiency? By answering these questions, the study aims to provide a nuanced understanding of the DT–efficiency nexus, offering both theoretical and practical contributions.</p><p>The remainder of this paper is organized as follows: Section 2 reviews the relevant literature and develops hypotheses. Section 3 describes the mixed-methods research design. Section 4 presents the quantitative and qualitative findings. Section 5 discusses the results, and Section 6 concludes with implications and limitations.</p><h2>Methods</h2><h3>Research Design</h3><p>This study employed a sequential explanatory mixed-methods design, consisting of a quantitative phase followed by a qualitative phase (Creswell & Plano Clark, 2017). The quantitative phase tested the hypothesized relationships using survey data, while the qualitative phase provided contextual explanations for the quantitative findings.</p><h3>Sample and Data Collection</h3><p>The target population comprised SMEs in Vietnam, defined as enterprises with fewer than 300 employees (Vietnamese Government, 2009). A stratified random sampling method was used to select 400 SMEs across manufacturing, services, and retail sectors. Between March and June 2023, an online survey was administered to managers or owners, yielding 312 usable responses (response rate = 78%). The sample included 58% manufacturing, 27% services, and 15% retail firms. The average firm size was 85 employees (SD = 62), and the average firm age was 12 years (SD = 8).</p><p>For the qualitative phase, 20 managers were purposively selected from the survey respondents to represent diverse industries and levels of DT adoption. Semi-structured interviews were conducted via video conferencing, each lasting 45–60 minutes. Interviews explored managers' perceptions of DT benefits, challenges, and the role of employee skills and culture.</p><h3>Measures</h3><p>All constructs were measured using validated scales adapted from prior literature. Digital transformation was assessed using a 7-item scale developed by Nwankpa and Roumani (2016), measuring the extent of adoption of digital technologies (e.g., cloud computing, big data analytics, IoT) in core business processes. Operational efficiency was measured using a 5-item scale adapted from Gunasekaran et al. (2017), capturing improvements in process speed, cost reduction, quality, and resource utilization. Employee digital skills were measured using a 6-item scale from Kane et al. (2017), assessing employees' proficiency in using digital tools and their ability to adapt to new technologies. Organizational culture was measured using a 6-item scale from Duarte and de Oliveira (2020), focusing on innovativeness, risk tolerance, and learning orientation. All items were rated on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).</p><p>Control variables included firm size (log of number of employees), firm age, and industry sector (dummy-coded).</p><h3>Data Analysis</h3><p>Quantitative data were analyzed using SPSS 27 and AMOS 27. First, confirmatory factor analysis (CFA) was conducted to assess the measurement model's validity and reliability. Then, structural equation modeling (SEM) was used to test the hypothesized relationships, including mediation and moderation effects. Bootstrapping with 5,000 resamples was used to test indirect effects. Moderation was tested by creating an interaction term between DT and culture, which was mean-centered to reduce multicollinearity.</p><p>Qualitative data were analyzed using thematic analysis (Braun & Clarke, 2006). Interviews were transcribed verbatim, and codes were generated inductively. Themes were then mapped to the quantitative findings to provide explanations.</p><h2>Results</h2><h3>Measurement Model</h3><p>The CFA results indicated a good fit for the four-factor model (χ²/df = 1.82, CFI = 0.95, TLI = 0.94, RMSEA = 0.05, SRMR = 0.04). All factor loadings were above 0.70, and composite reliabilities (CR) exceeded 0.80 for all constructs. Average variance extracted (AVE) values were above 0.50, 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 the means, standard deviations, and correlations among the study variables. Digital transformation was positively correlated with operational efficiency (r = 0.45, p < 0.01), employee digital skills (r = 0.52, p < 0.01), and organizational culture (r = 0.38, p < 0.01). Employee digital skills were also positively correlated with operational efficiency (r = 0.49, p < 0.01).</p><h3>Hypothesis Testing</h3><p>The SEM results (Table 2) showed that digital transformation had a significant positive direct effect on operational efficiency (β = 0.42, p < 0.001), supporting H1. Employee digital skills significantly mediated the relationship between DT and operational efficiency (indirect effect = 0.18, 95% CI [0.11, 0.25]), supporting H2. The direct effect remained significant after including the mediator, indicating partial mediation.</p><p>Moderation analysis revealed that organizational culture significantly moderated the direct effect of DT on operational efficiency (interaction term = 0.15, p < 0.01). Simple slopes analysis indicated that the positive effect of DT on efficiency was stronger for firms with a supportive culture (β = 0.57, p < 0.001) compared to those with a less supportive culture (β = 0.27, p < 0.01), supporting H3.</p><h3>Qualitative Findings</h3><p>The thematic analysis of interviews revealed three main themes: (1) Perceived benefits of DT, (2) Barriers to implementation, and (3) The role of culture and skills. Managers consistently reported that DT improved process speed and reduced errors, aligning with the quantitative findings. However, they also highlighted significant barriers, including high costs of technology, lack of technical expertise, and employee resistance. One manager noted, "We invested in new software, but our staff struggled to use it effectively; we had to hire external trainers." Another emphasized the importance of culture: "Our company encourages experimentation, so employees are more willing to try new tools." These insights corroborate the mediating and moderating effects found in the quantitative analysis.</p><h2>Discussion</h2><p>This study provides robust evidence that digital transformation enhances operational efficiency in SMEs, consistent with prior research (Fitzgerald et al., 2014; Vial, 2019). The significant direct effect underscores the importance of DT as a strategic lever for performance improvement. More importantly, the study reveals that employee digital skills serve as a key mechanism through which DT translates into efficiency gains. This finding aligns with the resource-based view, which posits that organizational capabilities are critical for leveraging technological resources (Barney, 1991). SMEs that invest in training and development are better positioned to reap the benefits of DT.</p><p>The moderating role of organizational culture adds a nuanced perspective. A culture that fosters innovation and learning amplifies the positive impact of DT, suggesting that technology alone is insufficient; the organizational context must be conducive to change. This finding echoes the socio-technical systems theory, which emphasizes the interplay between technical and social subsystems (Trist & Bamforth, 1951). Managers should therefore cultivate a supportive culture to maximize the returns on DT investments.</p><p>The qualitative findings provide practical insights into the challenges SMEs face. Resource constraints and resistance to change are common barriers, highlighting the need for phased implementation and change management strategies. The emphasis on training underscores the importance of developing human capital alongside technological adoption.</p><p>This study contributes to the literature by empirically testing a moderated mediation model in an emerging market context, where such research is scarce. It also offers practical implications for SME managers, who should prioritize both technological investments and organizational development. Policymakers can use these findings to design support programs that address skill gaps and promote digital readiness.</p><h2>Conclusion</h2><p>This mixed-methods study demonstrates that digital transformation significantly improves operational efficiency in SMEs, with employee digital skills acting as a mediator and organizational culture as a moderator. The findings highlight the need for a holistic approach to DT that integrates technology, skills, and culture. For SMEs, investing in employee training and fostering an innovative culture are essential to fully realize the benefits of digitalization. For policymakers, targeted interventions to enhance digital literacy and provide financial support for technology adoption are recommended.</p><p>Despite its contributions, the study has limitations. The cross-sectional design precludes causal inferences, and the reliance on self-reported data may introduce common method bias. Future research should adopt longitudinal designs and incorporate objective performance metrics. Additionally, the study focused on Vietnam, limiting generalizability to other contexts. Comparative studies across countries and sectors would enrich the understanding of DT's impact.</p><p>In conclusion, digital transformation is a powerful driver of operational efficiency for SMEs, but its success hinges on the development of employee skills and a supportive organizational culture. 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