The impact of digital transformation on the financial performance of logistics enterprises

In an economy undergoing profound transformations driven by the Fourth Industrial Revolution, DT has emerged as one of the most critical manifestations of these changes (Zaoui and Souissi, 2020). The integration of digital technologies into the real economy not only reshapes governance and economic development models (Peng and Tao, 2022), but also enhances national resilience in the face of disruptions. Since the COVID-19 pandemic, the pace of DT adoption has accelerated considerably across industries worldwide (Transport, 2020, 2021). DT refers to essential digital changes within and between enterprises, driven by digital strategies (Heilig et al., 2017), which create opportunities to improve efficiency and generate value for stakeholders (Kache and Seuring, 2017). Previous studies have primarily investigated the relationship between DT and FP, reporting both positive (Wang et al., 2022; Zhai et al., 2022; Xie and Wang, 2023) and negative outcomes due to high initial investment costs (Nga et al., 2023; Sui and Yao, 2023; Vo et al., 2024), while others suggest a non-linear relationship (Guo and Xu, 2021). These findings highlight the need to revisit DT not only from a firm-level efficiency lens, but also in light of industry-specific characteristics and broader strategic implications.

Vietnam provides a compelling case for such an inquiry. The logistics sector, with an annual market size of USD 20–22 billion and an average growth rate of 14–16%, contributes to 4–5% of the national gross domestic product (Finance, 2024). Recognised as a backbone of the economy, logistics services influence production, circulation and consumption across industries. However, logistics costs account for a significant share of business costs - estimated at 50–70% for logistics firms (Langley et al., 2019; Palkina, 2022) - much of which stems from outsourcing. Consequently, companies have turned to DT to digitise customs processes and transportation documentation, accelerate goods circulation and better manage costs (ElMassah and Mohieldin, 2020). In this context, customers, data and innovation are increasingly viewed as the central drivers of DT adoption for sustainable development. Beyond its economic role, however, logistics is increasingly regarded as a vital component of national defence and security. Secure and digitally enabled logistics networks ensure resilience of supply chains, which is critical during emergencies and geopolitical tensions (Yu et al., 2025). Furthermore, Li et al. (2025) have indicated that DT not only enhances FP but also strengthens organisational resilience and sustains performance amid uncertainty – an aspect particularly critical for logistics enterprises operating in highly volatile environments. For a country with Vietnam's strategic geographical position in Southeast Asia, strengthening logistics capacity through DT improves competitiveness while safeguarding the reliable flow of goods, energy and essential resources that underpin both economic stability and defence readiness.

Acknowledging this dual economic–security dimension, the Vietnamese government has identified logistics as one of eight priority sectors for DT by 2030 (Transport, 2020, 2021). Policies such as covering 50% of technology investment costs and subsidising digital workforce training (Decree, 2021) have been implemented to accelerate DT, particularly among small and medium-sized enterprises (SMEs), which continue to face financial and human resource challenges (VCCI, 2021). While large enterprises have made substantial progress in digitisation, SMEs remain more vulnerable to shocks and disruptions, underscoring the importance of state support in enhancing both operational efficiency and national security resilience (Hải et al., 2023; Dung et al., 2024). Moreover, DT encompasses more than simply embedding digital platforms in internal systems; it also involves combining internal with external resources to lower costs and enhance organisational efficiency (Feng et al., 2022; Ruan et al., 2022).

In light of this context, the present study examines the role of government support in reinforcing the relationship between DT and FP within logistics enterprises in Can Tho. By situating DT not only as a driver of firm-level competitiveness but also as a strategic enabler of supply chain security, this study contributes to bridging business-oriented analyses with broader defence and national security concerns. The findings offer both theoretical and practical implications for accelerating DT in logistics while aligning economic development with the safeguarding of national interests in an increasingly uncertain global environment.

The next part of the paper presents the background theory and research model, while the third part describes the data sources and analysis methods. Moreover, the fourth part presents the results and discussion, followed by the fifth part with conclusions and implications of the study.

Resource-based view (RBV) theory and transaction cost economics (TCE) are essential frameworks for examining the influence of DT on the FP of enterprises. Within this framework, RBV explains the strategic value of DT as an internal organisational capability. According to Barney (1991), a firm's resources encompass not only tangible assets but also intangible assets such as knowledge, processes and organisational culture - factors that determine the capacity to formulate and implement strategies aimed at enhancing performance outcomes. From the RBV perspective, DT is considered a distinctive strategic resource that enables firms to optimise processes, reduce costs and thereby achieve superior FP (Heredia et al., 2022; Peng and Tao, 2022). Accordingly, RBV underpins the direct linkage between DT and financial performance in the proposed framework.

Conversely, TCE strengthens the framework by explaining the economic mechanism through which DT improves FP. TCE emphasises transaction costs, which include the time, resources and efforts required to negotiate, monitor and enforce transactions (Coase, 1988). Investment in digital technologies can reduce production costs, lower product prices and consequently diminish transaction costs for both firms and customers (Foss, 1996). In the logistics sector, digital technologies facilitate the integration of activities through information sharing across networks, reducing coordination costs and enhancing decision-making efficiency (Loureiro et al., 2018). More recent studies also highlight that DT reduces internal transaction costs, reconfigures innovation processes and enhances the exploitation of external information, ultimately improving transaction efficiency and FP (Meng and Gong, 2024). Thus, TCE clarifies the cost-reduction logic embedded in the study framework.

Despite these potential benefits, the implementation of DT in enterprises often encounters significant barriers, particularly high initial investment costs, shortages of digital talent and technological risks (Nguyễn et al., 2026). In this context, government support plays an essential role. From the RBV lens, policies such as financial subsidies, digital workforce training and technological infrastructure development are viewed as complementary external resources that reinforce firms' internal capabilities in DT investment. From the TCE perspective, such support reduces transaction and investment costs associated with digital adoption, thereby helping firms overcome barriers and maximise the benefits of DT (Tran et al., 2024). Therefore, integrating RBV and TCE provides a more comprehensive theoretical explanation for how DT and government support jointly influence financial performance within the proposed framework.

In summary, the integration of RBV and TCE underscores that DT functions both as a strategic resource and as a transaction cost–reducing mechanism, while government support amplifies these effects, thereby enhancing firms' financial performance. Accordingly, this study investigates the impact of DT, together with government support, on the FP of logistics enterprises in Can Tho.

DT is increasingly recognised as a strategic resource that enhances firms' FP and strengthens their competitiveness (Peng and Tao, 2022). From the perspective of the RBV, DT represents an intangible resource that enables firms to reconfigure processes, optimise resources and increase profitability. Empirical studies have documented a positive association between DT and FP (Popović et al., 2019; Guo and Xu, 2021; Nhi et al., 2022; Peng and Tao, 2022), suggesting that DT can simultaneously improve cost efficiency and FP. However, evidence regarding the impact of DT on FP remains inconclusive. Jardak and Ben Hamad (2022) have highlighted a need for more consensus on the role of DT in improving FP, attributing this uncertainty to the fact that investments in information technology and the execution of DT can require several years to yield tangible results. Investments in information technology will raise costs for enterprises. Consequently, the return on assets may be adversely affected due to the elevated value of information technology assets that are not subject to depreciation.

In the same view, research on the level of DT of Vietnamese private enterprises negatively correlates with business efficiency (Nga et al., 2023). Vietnamese enterprises are investing in technology to operate businesses on a technology platform. They are still struggling to determine which steps to take first and which ones to take later, so the investment process has not brought positive results (Dung et al., 2024). As enterprises do not have experience or leading enterprises to guide them, the implementation of DT has not brought about the expected results. On the other hand, the capital for technology investment is quite large, so enterprises must use borrowed capital, which increases costs and leads to poor business efficiency (Dung et al., 2024).

Moreover, 97% of logistics companies in Can Tho are SMEs, with 57% of these businesses experiencing financial difficulties and 51% lacking staff with digital skills (VCCI, 2021). To tackle these challenges, the government has issued a Decree (2021), along with Transport (2020, 2021). These measures aim to promote the DT of SME logistics and recognise the logistics sector as a crucial component of the economy in the movement of goods. As a result, the study expects that greater government support will strengthen the motivation for DT, leading to improved FP in logistics enterprises.

Along with reducing costs and enhancing the speed of goods circulation, the anticipated outcomes of DT efforts in logistics enterprises in Can Tho are expected to provide significant benefits. From the TCE lens, DT will reduce transaction costs and improve collaboration among stakeholders (Kim and Cavusgil, 2020); enhance collaboration between the various departments of the enterprise to create value for the innovation ecosystem, and respond promptly to market demands (Stallkamp and Schotter, 2019; Patrucco et al., 2020).

The studies above indicate that implementing DT and its effects on enterprises' performance broadly extend across various sectors. The logistics industry is currently viewed as a crucial service sector with high added value, providing a foundation for trade development and bolstering the economy's competitiveness (Long, 2022). Consequently, DT in logistics enterprises is not only a trend but also a vital factor for achieving success and sustainable development in this sector. Moreover, logistics is a new and promising research area, especially concerning examining the impact of DT on enterprises' performance. This research is crucial for addressing the existing knowledge gap. However, the following question arises: What is the impact of DT on enterprise performance within logistics firms? Prior studies have indicated that the relationship between DT and enterprises' performance is not uniform. Consequently, to investigate this relationship within the context of logistics firms, the following hypotheses are proposed:

Knowledge from developed countries shows that investment in DT often requires substantial capital, and improvements in FP only emerge after a considerable time lag (Jardak and Ben Hamad, 2022). This finding poses a major challenge for enterprises, particularly SMEs, which are constrained by limited resources and a low tolerance for cost-related risks. The Vietnamese context makes this challenge even more pronounced, as approximately 97% of logistics enterprises are SMEs (VCCI, 2021), most of which face capital constraints and a shortage of digital workforce. This situation underscores the necessity of government intervention and supportive policies to remove initial barriers in the DT process.

Policies such as Decision No.749/QÐ-TTg (2020), the Decree (2021) and logistics development programmes (Transport, 2020, 2021) focus on providing financial support that covers 30–50% of technology and software costs, offering tax reductions for enterprises implementing DT projects, investing in digital infrastructure and improving the quality of the digital workforce. From the RBV theory's perspective, these complementary external resources enable SMEs to invest more strongly in DT to enhance FP. Meanwhile, under the TCE perspective, such support reduces transaction and technology investment costs, thereby lowering the cost-to-revenue ratio (CRR). Therefore, it can be expected that the level of government support plays a moderating role, amplifying the positive impact of DT on FP while simultaneously reducing the CRR in logistics enterprises.

As illustrated in Figure 1, this study develops an analytical model examining the impact of DT on the FP of logistics enterprises, measured by ROA and CRR. The theoretical foundation is grounded in the RBV (Barney, 1991) and TCE (Coase, 1988), with the expectation that DT enables firms to optimise internal resources and enhance coordination with partners, thereby reducing costs, improving processes and strengthening FP.

DT is also expected to stimulate revenue growth, helping firms sustain FP in a volatile environment (Nguyễn et al., 2026). Prior studies have likewise highlighted the importance of firm age and size, noting that larger and more established firms often enjoy advantages in technology investment and market reputation (Zhang et al., 2022; Nguyễn et al., 2026). Furthermore, market shocks such as COVID-19 have shaped the digitalisation landscape, exerting an influence on FP (Gazi et al., 2022).

In addition, the study incorporates control variables reflecting financial resources, such as financial leverage (Wang et al., 2022; Nguyễn et al., 2026), to provide a more comprehensive assessment of the impact on the FP of logistics enterprises in Can Tho. Finally, the study examines the moderating role of government support in the relationship between DT and FP. This support is expected to amplify the positive effects of DT, thus underscoring the importance of policy orientation in driving the digitalisation process within the logistics sector.

To conduct the analysis, the study employed two data sources. First, secondary data were collected from the Vietnam Enterprise Survey conducted by the General Statistics Office (GSO) of Vietnam for the publication of The Vietnam White Book on Enterprises. The enterprise survey is implemented nationwide and combines a full enumeration component with a sample survey component to enhance the depth of information collected (General Statistics Office of Vietnam, 2023). The dataset provides firm-level information on FP, firm characteristics and general indicators of technology adoption.

However, the GSO dataset does not provide a sufficiently detailed breakdown of investment specific to DT for logistics SMEs in Can Tho. In the Vietnamese context, most SMEs are not legally required to undergo mandatory financial audits, which limits the level of detail and transparency in publicly available financial disclosures (Ha and Nguyen, 2020). As a result, DT-related expenditures such as software acquisition, system upgrades, automation equipment investment, depreciation of digital machinery and annual maintenance costs are often recorded under aggregated operating expenses or broader asset categories rather than separately classified as digital investment.

This accounting practice makes it difficult to accurately identify investment specific to DT using archival accounting data alone. Therefore, to improve measurement precision, the study conducted a direct survey of logistics enterprises in Can Tho to collect detailed firm-level information on DT-related expenditures.

Specifically, the survey collected information on:

1. Annual expenditure on digital software systems;

2. Depreciation of technology and automation-related equipment;

3. Annual maintenance and upgrading costs associated with digital technologies; and

4. Whether the firm received government support for digital transformation activities.

Measuring these expenditures directly is appropriate in the context of Can Tho's logistics sector, where DT is strongly influenced by investment costs and external support conditions (Le and Dang Quoc, 2023).

After matching the GSO dataset with the primary survey data, 78 out of 106 active logistics enterprises in Can Tho met the criteria for inclusion in the empirical analysis (see Supplementary material). The final dataset enables measurement of the dependent variable (FP, measured by ROA and CRR), the main independent variable (DT), the moderating variable (government support) and relevant firm-level control variables.

The literature identifies three dominant approaches to measuring DT. First, many studies employ binary indicators capturing whether firms implement DT initiatives in a given year (Nhi et al., 2022; Peng and Tao, 2022; Zhang et al., 2022). Second, DT has been measured by the ratio of digital-related intangible assets to total intangible assets (Wang et al., 2022). Third, text-based indicators derived from the frequency of keywords related to DT in corporate reports have also been widely used (Guo and Xu, 2021; Ye and Tong, 2022; Ren et al., 2023).

However, these approaches rely heavily on transparent disclosure systems and clearly separated accounting classifications. In the Can Tho logistics sector, digital investments are rarely reported as separate accounting items, and firms do not publish detailed digitalisation reports. As a result, disclosure-based and accounting-ratio proxies may underestimate the actual level of digital resource commitment.

Given this context, the study operationalises DT using an expenditure-based measure. This approach is consistent with the IT investment literature, which treats technology expenditure as an observable indicator of technology capability development and strategic commitment (Brynjolfsson and Hitt, 1996; Tambe and Hitt, 2012). In addition, the RBV emphasises that the value of DT derives from the allocation and recombination of firm resources through investment in digital infrastructure and operational technologies (Bharadwaj, 2000; Nwankpa and Roumani, 2016; Verhoef et al., 2021). Accordingly, investment expenditure provides a direct indicator of transformation intensity at the firm level.

The DT variable includes expenditures on digital software systems, automation equipment, barcode scanners, RFID devices, GPS technologies and depreciation of digital-related equipment used in logistics operations. These components were identified through consultation with firm directors and alignment with core operational technologies in the logistics industry. Expenditure data were collected directly from firms and explicitly separated from general capital investment to reduce aggregation bias in accounting data (Nguyễn et al., 2026).

The full procedure for variable construction and classification is documented to ensure transparency and methodological rigor (Churchill, 1979; MacKenzie et al., 2011; DeVellis and Thorpe, 2021). This measure therefore captures observable digital resource allocation and provides a context-appropriate proxy for DT intensity in emerging-market logistics firms.

It is important to note that this measure captures DT as an input-based intensity indicator rather than an outcome-based performance metric. The focus is on observable resource commitment to digital infrastructure, consistent with RBV's emphasis on resource allocation as the foundation of capability development. Given the limited transparency of SME disclosures in emerging markets, this context-adapted measure provides a more accurate representation of DT intensity than archival disclosure-based proxies.

Panel regression models, including the fixed effects model (FEM) and the random effects model (REM), were employed to examine the impact of DT on FP of logistics enterprises. FEM and REM were treated as alternative specifications: FEM accounted for unobserved heterogeneity that may vary across firms, whereas REM captured random variation among firms. Evaluating both models allowed for robustness testing and facilitated the identification of the most appropriate specification for the dataset. Statistical tests were performed to identify the preferred model: the F-test was used to evaluate overall model significance, while the Hausman test was conducted to determine whether FEM or REM was more appropriate. To detect heteroskedasticity, the Wald test was applied in FEM (p < 0.05), and the Breusch–Pagan Lagrange test was applied in REM (p < 0.05). In addition, the Wooldridge test was used to identify autocorrelation in the panel data estimates (p < 0.05). When heteroskedasticity and autocorrelation were confirmed, the feasible generalised least squares (FGLS) estimator was employed to correct for these issues (Judge et al., 1991; Gujarati and Porter, 2009).

The study investigated the impact of DT on the performance of logistics enterprises in Can Tho. The estimation equation was specified as follows:

In this model, financial performance (FP) is measured using two dependent variables: (1) ROA = net profit after tax/total assets and (2) CRR = Cost to Revenue Ratio. These variables represent the FP of enterprise i (i = 1, …,78) in year t (t = 2021, …,2023).

The independent variables include DT (DT_it), which is the primary focus, and government support (Gov_it). The interaction term (DT_it × Gov_it) is used to examine the moderating role of government support in the relationship between DT and firm performance. In addition, several control variables are incorporated into the model to account for firm-specific characteristics, including firm size (Size_it), firm age (Age_it), financial leverage (ALR_it) and revenue growth rate (GROW_it). The COVID-19 variable (COVID_t) captures the macroeconomic shock associated with the pandemic and varies only across time.

The model parameters are defined as follows:

1. α₀ is the intercept;

2. α₁ to α₃ are the coefficients associated with the independent variables DT_it, Gov_it and their interaction term (DT_it × Gov_it);

3. α₄ to α₈ are the coefficients for the control variables Size_it, Age_it, ALR_it, GROW_it and COVID_t;

4. ε_it represents the error term.

Table 1 summarises the definitions and measurements of all variables used in the multiple regression models.

The statistical data shown in Table 1 reveal that the average investment ratio in DT within the Can Tho logistics sector from 2021 to 2023 was 17.10%, with a standard deviation of 1.90% and a maximum value of 24.97%. This study indicates that logistics enterprises had relatively low investment ratios in DT during this period. It highlights substantial differences in the prioritisation and focus on DT among firms, which varied based on their size and specific operations. Simultaneously, the ROA index for logistics enterprises exhibited considerable variability, with an average of 21.71%, a minimum of −66.03% and a maximum of 35.71%. This variation underscored that FP among Can Tho logistics firms is highly diverse, influenced by factors such as firm size, adaptability to DT and overall FP.

As can be seen in Table 2, the correlation coefficient between the variables DT, CRR and ROA demonstrated a positive relationship. In contrast, most other coefficients are small with values less than 0.5. This finding suggests that multicollinearity is absent in the multiple regression model (Gujarati and Porter, 2009).

Table 3 reports the estimated coefficients for four random-effects panel regression models examining the relationship between the explanatory variables and the performance measures ROA and CRR. In addition to coefficient (⁠$α$⁠) estimates, the table reports model diagnostics assessing overall model significance, explanatory power, the appropriateness of the random-effects specification relative to fixed effects, the presence of panel-level effects and potential serial correlation in the panel residuals. Models 2 and 4 include the DT × GOV term, while models 1 and 3 do not.

Before conducting the FEM and REM regressions, diagnostic tests were performed to ensure the reliability of the estimations. The Hausman test (see Table 3) indicated that the REM is the most appropriate specification for explaining the differential impacts of DT on CRR and ROA of logistics enterprises (p > 0.10). The Breusch–Pagan Lagrange test indicated the presence of heteroskedasticity in the model residuals. This suggests that the variance of the error terms is not constant across observations. To address this issue, the feasible generalized least squares (FGLS) estimator was employed to obtain more efficient estimates (see Table 4).

Table 4 displays the findings on the effects of DT on FP through ROA and CRR. The values reported in Table 4 represent the estimated regression coefficients obtained from the FGLS estimator. The values in Table 4, denoted by ***, ** and *, represent significance levels of 1%, 5% and 10%, respectively.

To improve clarity, four model specifications are reported. FGLS₁ and FGLS₂ estimate the impact of DT on ROA, whereas FGLS₃ and FGLS₄ estimate the impact of DT on CRR. The difference between the paired models lies in the inclusion of the interaction term between DT and government support. Specifically, FGLS₁ and FGLS₃ present the baseline models without the interaction term, while FGLS₂ and FGLS₄ include the interaction term (DT × GOV) to examine the potential moderating role of government support in the relationship between DT and FP.

FGLS results showed that DT is positively associated with ROA (p < 0.01). This result corresponds to the initial hypothesis and is consistent with previous studies (Popović et al., 2019; Guo and Xu, 2021; Nhi et al., 2022; Peng and Tao, 2022; Wang et al., 2022; Ye and Tong, 2022; Zhang et al., 2022; Chen and Xu, 2023). Meanwhile, the results showed that DT is negative associated with CRR (p < 0.01), which is consistent with the findings of Heredia et al. (2022), Feng et al. (2022), Ruan et al. (2022) and Peng and Tao (2022). However, this result contrasts with Guo et al. (2023), who have argued that DT reduces FP due to an increase in operational cost rates. An interesting finding indicates that the interaction between DT and government support is statistically significant in the CRR model (p < 0.01), suggesting that government support is associated with stronger cost-efficiency gains from DT. However, the moderating effect of government support is not statistically significant in the ROA model. Furthermore, the revenue growth rate, shown in Table 4, indicated a significantly positive coefficient (p < 0.01), suggesting that logistics enterprises with higher investment in DT tend to exhibit higher FP. This finding aligns with the original assumption and previous studies conducted by Nhi et al. (2022).

In addition, based on the estimated results in Table 4, enterprise characteristics are significantly associated with the FP indicators (ROA and CRR). Specifically, financial leverage is negatively associated with the logistics FP (p < 0.01). This result corresponds with the studies of Guo and Xu (2021), Zhang et al. (2022) and Ren et al. (2023). However, another interesting new finding reveals that financial leverage is positively associated with the logistics CRR (p < 0.01). In addition, the results indicate that government support is associated with better FP through improved cost efficiency (p < 0.1). Furthermore, the study found that firm size, age and the COVID-19 pandemic have no statistically significant associations with either ROA or CRR.

The regression results in Table 4 show a statistical relationship between DT and FP of logistics enterprises. Consistent with this pattern, Guo and Xu (2021) suggest that firms investing in DT may gain advantages through more efficient cost utilisation and stronger revenue growth, both of which are associated with improved FP. The findings from the FGLS₁, FGLS₃ and FGLS₄ models indicate that government support is associated with firms' ability to pursue DT more effectively and with stronger performance relative to firms lacking such assistance. These results highlight the potential role of government support in facilitating DT among logistics firms and suggest that timely support may help SMEs address capital constraints that are associated with improvements in CRR in the short term. Beyond the firm level, such support may also have broader implications for logistics system development. For example, policies that encourage digital logistics infrastructure may contribute to greater supply chain stability, which can be important for maintaining the flow of critical goods during periods of economic disruption, natural disasters or geopolitical tensions. However, the moderating effect of government support differs across the two FP indicators. The interaction term (DT × GOV) is not statistically significant in the ROA model, indicating no moderating effect on profitability. In contrast, the interaction term is statistically significant in the CRR model, suggesting that government support is associated with stronger cost-efficiency outcomes linked to DT. Therefore, future research should extend the analysis over a longer time horizon to better capture the potential longer-term effects of such support. More broadly, prior research suggests that DT may be associated with improved operational efficiency, lower costs and innovation outcomes that can contribute to improved FP (Ren et al., 2023).

Furthermore, the findings of this study suggested a strong alignment with RBV, emphasising the significant influence of contextual differences in DT on enterprises' FP. The majority of prior studies have utilised a lengthy time frame of 10 years to investigate the effects of DT on FP (Wang et al., 2022; Ye and Tong, 2022). For example, Jardak and Ben Hamad (2022) have argued that investments in DT necessitate several years to produce results; however, Guo and Xu (2021) have indicated that, generally, approximately two to four years are required to observe the benefits of DT. In practice, the DT of logistics enterprises in Vietnam remains in the early stages of the transition process (An, 2022). The year 2020 is regarded as the inaugural year for DT, with the year 2021 signifying the onset of implementation and practical experience in this area, particularly in the context of the pandemic. However, although logistics enterprises in Can Tho have only recently started to invest in technology and adopt DT, the outcomes suggest a strong alignment with the findings of Guo and Xu (2021). SMEs' logistics enterprises, including those in Can Tho, often find advanced technologies like AI, IoT, blockchain, robotics and automation to be beyond their reach due to limited financial resources and specialised human capital.

Regarding the current landscape for logistics enterprises in Can Tho, most enterprises are at an initial stage of DT, concentrating their investments on straightforward and commonly used technologies compatible with their existing management capabilities and resources. Moreover, these enterprises have reported a notable improvement in FP following the adoption of DT. DT is associated with various advantages, including time savings in task execution, reduced operational costs, improved access to a broader customer base on digital platforms, effective data utilisation, enhanced internal collaboration and increased competitive capacity. Thus, DT is positively associated with improved FP, aligning well with the current conditions of logistics enterprises in Can Tho.

This study suggests that larger logistics enterprises may have a significant capital advantage when investing in technology. As a result, these enterprises may be better positioned to utilise government support to finance DT activities. This finding helps address the limitation identified in the studies of Nga et al. (2023) and Nguyễn et al. (2026), as the present research specifies the proportion of fixed assets specifically allocated for DT and technology software investments, thereby identifying the individual association of these investments on FP. Therefore, this research makes a unique contribution compared to previous studies by introducing a new measurement scale for DT.

As the results suggest, financial leverage is negatively associated with FP, consistent with the assertion by Ren et al. (2023) that an increase in a firm's debt ratio diminishes ROA efficiency and increases CRR. Governmental support is associated with higher enterprises' financial leverage ratios, indicating that government policies may have assisted SMEs in overcoming capital barriers during the initial stages of DT. A firm with a moderate debt-to-assets ratio can effectively leverage financial advantages and tax shields. However, the results of the descriptive statistics revealed that some logistics enterprises in Can Tho have relatively high debt-to-asset ratios. This high debt level may indicate limited financial independence, exposing these firms to liquidity risks and potentially affecting their FP. This issue can largely be attributed to the fact that many logistics enterprises in Can Tho are SMEs with limited financial resources. Additionally, these firms frequently use debt to cover costs or meet other obligations. Instead of utilising equity for business services in the market, they may become heavily reliant on debt, which may contribute to an increase in the CRR and a decline in the ROA. Consequently, logistics enterprises in Can Tho may consider exploring alternative funding sources to reduce financial pressure and carefully consider the most effective application of financial leverage in their operations.

Finally, the results showed that the revenue growth rate is positively associated with the FP of logistics enterprises in Can Tho. This finding suggests that investments in DT may help firms increase their revenue, which is associated with improved FP. Research shows that DT may assist logistics companies in Can Tho in managing cost efficiency effectively, highlighted by the standard error metric of the revenue variable, which indicates significant growth in FP. As a result, logistics firms may maintain stability even amidst uncertainties, such as those brought on by the COVID-19 pandemic. Revenue growth reflects a company's economic capacity, stability and growth trajectory, in line with the findings of Nhi et al. (2022). Moreover, between 2021 and 2023, logistics enterprises in Can Tho that invested in DT reported improvements in FP by accessing a broader customer base through digital platforms, streamlining operational processes, enhancing customer experience and lowering operational costs. As a result, these firms experienced higher revenue growth rate, which was associated with greater effectiveness in their business operations.

This research utilises a sample of 78 logistics enterprises from the GSO of Vietnam and the enterprise survey, including 234 observations in 2021–2023, to examine the impact of DT on FP. The study presented empirical evidence that DT is associated with improved FP. This conclusion appears robust, having thoroughly addressed all identified limitations. The empirical findings of the study suggest that firms with higher levels of DT tend to exhibit higher efficiency. Furthermore, the research indicated that moderate investments in digital technology at relatively low cost may be associated with improved FP.

This research also identified that the level of DT and revenue growth rate are positively associated with FP. These results showed that a higher revenue growth rate is associated with a higher return on assets. DT may be carried out by implementing artificial intelligence, the Internet of things, blockchain, robotics, automation and technologies that may help reduce management transaction costs, and agency costs. Therefore, the results of this study may provide a valuable basis for firms to manage the revenue growth rate and improve FP. In addition, the study found that financial leverage is negatively associated with FP. The study offers management implications aimed at advancing DT in the logistics sector of the Can Tho market to improve business efficiency as follows:

First, the analysis indicated that DT is significantly associated with the FP of logistics enterprises in Can Tho. As a result, managers may consider prioritising DT initiatives. They should carefully assess the costs and benefits to craft a comprehensive strategy that seizes opportunities and effectively utilises government support policies.

Second, the study found that DT is associated with revenue growth and improved logistics FP. This finding aligns with the observation that longer operational duration is associated with greater effectiveness. Given the typical lag in DT outcomes, logistics enterprises may consider making long-term investments to achieve optimal results.

Third, the results suggest that it is important to manage and utilise financial leverage effectively. While financial leverage is a necessary “tax shield” for firms, its inappropriate use - resulting in excessively high ratios - may adversely affect business operations. Therefore, logistics enterprises may wish to assess the costs related to financial leverage and promote the use of internal funding sources for projects instead of relying heavily on debt. Firms may also consider designing a balanced capital structure to minimise dependency on borrowed funds, safeguarding profitability and future growth prospects.

The findings suggest that government support may play a partial moderating role in the relationship between DT and enterprise FP. While the moderating effect is not statistically significant in the ROA model, the interaction term between DT and government support is significant in the CRR model, indicating that government support may be associated with stronger cost-efficiency benefits from DT. This linkage may be relevant not only at the FP level but also may extend to broader dimensions of national security and resilience, as the government can play a pivotal role in promoting digital infrastructure and strategic readiness. The study suggests that the moderating effect of government support may reflect the transitional phase of Vietnamese enterprises, during which institutional support policies have begun to address barriers related to capital, technology and experience - factors that previously limited the effectiveness of DT during the 2018–2022 period (Nga et al., 2023). Therefore, this variable not only enhanced the model's explanatory power in capturing the DT – FP relationship but also provides a novel contribution by illustrating how public policy may help transform the initial costs of DT into long-term competitive and strategic advantages - an aspect of particular relevance to defence logistics capability and national economic resilience.

In addition to its theoretical and practical contributions, this study had certain limitations. Although the research focused on DT practices within logistics in Can Tho, future studies should broaden the market scope to improve the generality of the results. Additionally, extending the survey period is necessary to accurately determine whether the impact of DT follows a reverse U-shaped or linear relationship. This relationship may vary at different stages of enterprise development within the DT cycle.

The study analysed micro and macro factors that influence the FP of logistics in Can Tho. However, it did not consider the impact of the region's economic development pace, which is significant because the logistics sector relies heavily on infrastructure and the growth rate of each locality. Consequently, future research should account for the specific characteristics of each area. This approach would provide deeper insights and clarify the indirect effects, ultimately contributing more effectively to practical applications.

Although this study suggests that DT is associated with more efficient cost utilisation and improved FP among logistics enterprises in Can Tho, Vietnam, it has certain limitations because it does not concurrently consider other essential elements of DT, such as process reengineering, employee training and system integration. Therefore, future studies should extend the model by incorporating both technological and organizational dimensions to provide a more comprehensive understanding of the multifaceted associations between DT, FP and competitiveness.

The supplementary material for this article can be found online.