Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12, 109-123 2025 Publisher: Learning Gate DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate © 2025 by the author; licensee Learning Gate History: Received: 3 October 2025; Revised: 17 November 2025; Accepted: 21 November 2025; Published: 2 December 2025 * Correspondence: phamthu@thanhdong.edu.vn Factors influencing the adoption of responsibility accounting in the digital transformation context of Vietnamese enterprises Pham Thi Thu1* 1Thanh Dong University, Hai Phong City, Vietnam; phamthu@thanhdong.edu.vn (P.T.T.). Abstract: In the context of rapid digital transformation, the adoption of Responsibility Accounting (RA) has become essential for enhancing managerial control and accountability within enterprises. This study investigates the factors influencing the extent of RA adoption in Vietnamese enterprises, focusing on six key determinants: management accounting competency (MAC), accounting information system quality (AISQ), digital transformation capability (DTC), degree of decentralization (DE), innovation culture (IC), and competitive pressure (CP). Data were collected from 400 enterprises through a structured survey and analyzed using quantitative techniques, including Cronbach’s Alpha, Exploratory Factor Analysis (EFA), and multiple regression analysis. The results indicate that all six factors exert positive and statistically significant effects on RA adoption, with digital transformation capability, accounting information system quality, and management accounting competency being the strongest predictors. The study concludes that RA implementation is jointly shaped by technological capabilities, information quality, and organizational characteristics. These findings provide important managerial implications for enterprises in improving information systems, accelerating digital transformation, and enhancing internal control mechanisms to strengthen managerial effectiveness in the digital era. Keywords: Digital Transformation, Enterprises, Responsibility Accounting, Vietnam. 1. Introduction In the context of rapid global digital transformation, Vietnamese enterprises are facing urgent demands to modernize their management systems and strengthen internal control mechanisms in order to adapt to an increasingly digitalized business environment. Digital transformation not only reshapes production and business processes but also fundamentally changes the way accounting information is collected, processed, and utilized within organizations. This shift necessitates the enhancement of management accounting tools to ensure transparency, efficiency, and accountability in managerial activities. RA is recognized as a critical component of management control systems, enabling firms to clearly define authority and responsibility, establish responsibility centers, and evaluate performance at both individual and departmental levels. While RA has been widely adopted in developed economies, its application in Vietnam remains limited, uneven across industries, and significantly influenced by technological readiness, accounting competency, organizational structure, and competitive pressure. Moreover, existing studies on RA adoption have not adequately considered the digital transformation context, where big data technologies, ERP systems, integrated information platforms, and real-time analytics may profoundly reshape the functioning and effectiveness of RA systems. Motivated by these issues, the study titled “Factors Influencing the Adoption of Responsibility Accounting in the Digital Transformation Context of Vietnamese Enterprises” was conducted to provide empirical evidence and contribute to both theoretical and practical perspectives. The findings are expected to support managers, accountants, and policymakers in improving responsibility control systems, enhancing managerial capabilities, and promoting sustainable digital transformation within enterprises. 110 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate 2. Literature Review 2.1. International Studies Argento et al. [1] conducted a systematic review combined with bibliometric analysis to explore the under-examined effects of digital transformation on accounting, auditing, and accountability. The study highlights that digitalization reshapes the nature of management control systems, particularly in terms of responsibility structures, reporting processes, and transparency levels. The authors emphasize the role of accounting information system quality, digital transformation capability, and innovation culture as key determinants shaping the functioning of responsibility systems. Feghali et al. [2] examined the influence of digital technologies on accounting behaviors and practices during the COVID-19 period. The findings reveal that accountants increasingly rely on digital data and technology, underscoring the importance of management accounting competency and technological adaptability in effectively implementing managerial tools, including RA. Oanh et al. [3] provided empirical evidence on the impact of digital transformation capability and accounting information quality on managerial effectiveness in enterprises. Although RA was not directly examined, the results demonstrate that digital technologies and AIS/ERP systems play a central role in supporting analysis, evaluation, and responsibility reporting, which are core components of RA. Anthony and Govindarajan [4] offer a classical theoretical foundation for management control systems, asserting that decentralization is a key component of RA. Their work describes the design of responsibility centers, delegation mechanisms, and performance evaluation processes, forming the theoretical basis for most subsequent RA studies. Kraus et al. [5] analyzed the role of innovation culture in successful digital transformation. The study concludes that innovation culture enhances organizational readiness for change and facilitates the adoption of modern management tools, including RA. This finding strengthens the linkage between innovation culture and the potential for RA adoption in digitally transforming environments. In summary, international studies consistently highlight management accounting competency, accounting information system quality, digital transformation capability, decentralization, innovation culture, and competitive pressure as major determinants influencing an enterprise’s ability to adopt RA. 2.2. Domestic Studies Mai and Thu [6] are among the few scholars who have directly examined the extent of RA adoption in Vietnamese enterprises. Their findings indicate that the degree of decentralization and the quality of internal reporting play decisive roles in the implementation of RA. This study provides an important foundation for identifying organizational factors within the research model. Hoang and Hang [7] focused on organizational factors influencing RA, including decentralization, organizational structure, and information technology capability. The results reveal that decentralization and IT capability are the two strongest determinants. This study offers critical empirical evidence showing that RA cannot operate effectively without adequate technological infrastructure. Tho and Huong [8] analyzed the effects of ERP and accounting information systems on cost management and responsibility centers. Although RA was not examined directly, their findings demonstrate that AIS/ERP systems significantly enhance cost-center analysis, thereby strongly supporting RA implementation. Nhung and Thuy [9] investigated factors influencing management accounting adoption in the context of digital transformation. Their results show that accounting competency, innovation culture, and IT quality are key determinants. This study is valuable because RA is considered an integral part of management accounting. Hung and Tuan Anh [10] assessed the factors affecting management accounting adoption in Vietnamese manufacturing enterprises. They found that accounting competency and competitive pressure exert positive influences. This provides supporting evidence for including “competitive 111 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate pressure” in the RA model, especially in a highly competitive and increasingly digitalized market environment. Overall, domestic studies have explored individual factors such as decentralization, accounting competency, AIS quality, and innovation culture. However, no research has simultaneously integrated technological, organizational, and environmental dimensions to evaluate the extent of RA adoption within the digital transformation context. 2.3. Research Gap Although RA has been examined in various countries, existing reviews indicate that several important research gaps remain, particularly in the context of digital transformation. First, most prior studies focus on RA within traditional organizational settings, while digital transformation is fundamentally reshaping decentralization mechanisms, the design of responsibility centers, and reporting processes. However, research integrating RA with digitalization factors such as ERP, big data, or automation remains limited. Second, existing research models often address only isolated groups of factors, such as accounting competency or decentralization, without simultaneously incorporating the full set of technological, organizational, and environmental dimensions under the TOE framework, nor linking RA adoption to internal capabilities as suggested by the Resource-Based View (RBV). Third, in Vietnam, empirical studies on RA are still scarce and lack updated evidence reflecting the rapid digital transformation currently taking place. Therefore, a comprehensive study integrating technological, human, organizational, and environmental factors is needed to clarify the determinants influencing RA adoption in Vietnamese enterprises. 3. Theoretical Background and Research Model 3.1. Theoretical Background The analysis of factors influencing the adoption of RA in the context of digital transformation is grounded in three main theoretical foundations: Responsibility Accounting Theory (RAT), Management Control Systems (MCS), and the Technology–Organization–Environment (TOE) framework combined with the Resource-Based View (RBV). RAT posits that enterprises need to establish responsibility centers (cost, revenue, profit, and investment centers) to assign authority and responsibility to different managerial levels. The theory emphasizes the importance of decentralization, accurate information systems, and performance evaluation mechanisms in operating RA effectively [4]. MCS asserts that an effective control system must rely on key elements such as information quality, organizational structure, corporate culture, and personnel capability [11]. These elements align directly with the requirements of RA, which depend on structured reporting, delegated authority, and systematic performance assessment. The TOE framework [12] and the RBV explain innovation adoption based on technological capability, organizational characteristics, and environmental conditions. In the context of digital transformation, TOE and RBV jointly clarify how digital capability, accounting information systems, decentralization, innovation culture, and competitive pressure influence the implementation of RA. Integrating these theoretical foundations, the proposed research model includes six determinants: management accounting competency, accounting information system quality, digital transformation capability, degree of decentralization, innovation culture, and competitive pressure, each expected to influence the extent of RA adoption. 3.1.1. Management Accounting Competency (MAC) MAC reflects the professional qualifications, analytical capability, information-processing skills, and decision-support functions of accounting personnel. In the digital era, accountants are required not only to collect data but also to employ analytical tools, evaluate performance, and prepare responsibility reports. Prior studies such as Feghali et al. [2] and Nhung and Thuy [9] confirm that accounting 112 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate competency is a critical factor that promotes the adoption of modern management accounting techniques, including RA. Hypotheses H1: MAC has a positive effect on the adoption of RA. 3.1.2. Accounting Information System Quality (AISQ) AISQ refers to its ability to provide accurate, timely, integrated, and reliable data. Argento et al. [1] emphasize the essential role of information systems in ensuring accountability in the digital environment. Oanh et al. [3] provide evidence that high-quality AISQ directly supports performance evaluation and responsibility reporting. Therefore, AISQ serves as a fundamental infrastructure for the effective implementation of RA. Hypothesis H2: AISQ has a positive effect on the adoption of RA. 3.1.3. Digital Transformation Capability (DTC) DTC reflects an enterprise’s ability to implement, integrate, and effectively utilize digital technologies such as ERP systems, big data analytics, cloud computing, and automation. Digital transformation enhances transparency, traceability, and real-time reporting capabilities [1]. International studies Kraus et al. [5], demonstrate that enterprises with strong digital capabilities are more likely to adopt modern management control systems, including RA. Hypothesis H3: DTC has a positive effect on the adoption of RA. 3.1.4. Degree of Decentralization (DE) DE is the most fundamental element of the RA system. RA can only be effectively implemented when an organization’s structure clearly delineates authority and responsibility across responsibility centers. Both Otley [11] and Anthony and Govindarajan [4] emphasize that decentralization is the organizational foundation of RA. In Vietnam, Mai and Thu [6] as well as Hoang and Hang [7] also confirm that decentralization is one of the strongest determinants influencing RA adoption. Hypothesis H4: DE has a positive effect on the adoption of RA. 3.1.5. Innovation Culture (IC) IC reflects the extent to which an enterprise encourages creativity, embraces change, and supports process improvement. According to Argento et al. [1], innovation culture is a critical condition enabling firms to adapt to new control systems in a digital environment. In management accounting, an innovation-oriented culture motivates organizations to adopt modern techniques, including RA [9]. Hypothesis H5: IC has a positive effect on the adoption of RA. 3.1.6. Competitive Pressure (CP) CP drives enterprises to strengthen cost control, enhance operational efficiency, and improve performance evaluation systems. International studies, Manita et al. [13], indicate that competitive pressure is a key motivator for the adoption of modern management tools. In Vietnam, Hung and Tuan Anh [10] provide evidence that competitive pressure positively influences management accounting adoption, implying that it may similarly promote RA implementation. Hypothesis H6: CP has a positive effect on the adoption of RA. 3.2. Research Model Based on the theoretical foundations and the review of prior studies both domestically and internationally, this study proposes a research model consisting of six independent variables that may influence the adoption of Responsibility Accounting (RAA) in Vietnamese enterprises. These variables include: MAC, AISQ, DTC, DE, IC, and CP. The dependent variable in the model is Responsibility Accounting Adoption (RAA). 113 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate The proposed research model is illustrated in Figure 1. Figure 1. Proposed Research Model. 4. Research Methodology This study employs a mixed-methods approach combining both qualitative and quantitative techniques to ensure scientific rigor and reliability of the results. First, the qualitative phase was conducted through expert discussions and a review of prior studies to refine the measurement scales, ensuring that the observed variables are appropriate for the context of Vietnamese enterprises undergoing digital transformation. Based on this foundation, the quantitative phase was implemented to test the theoretical model and research hypotheses. Quantitative data were collected using a structured questionnaire with a five-point Likert scale (1 = Strongly disagree, 5 = Strongly agree). The survey respondents included accountants, chief accountants, financial–accounting managers, and managerial personnel with knowledge of accounting information systems in Vietnamese enterprises. These respondents are considered capable of accurately assessing the extent of RAA and the influencing factors. A non-probability sampling method combined with purposive sampling was applied to ensure access to respondents who are suitable for the research objectives. The targeted sample size was 400 valid observations, following the recommendation of Hair et al. [14], which suggests a minimum sample size of at least five times the number of observed variables. The collected data were analyzed using SPSS software through the following steps: (1) assessing the reliability of the measurement scales using Cronbach’s Alpha; (2) conducting EFA; and (3) performing multiple linear regression analysis to examine the impact of the identified factors on RAA. This methodological approach ensures the validity, reliability, and suitability of the research model within the practical context of Vietnamese enterprises. 114 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate Table 1. Summary of Measurement Scales. Code Observed Variables Main Sources Management Accounting Competency – MAC Feghali et al. [2], Anthony and Govindarajan [4], and Nhung and Thuy [9] MAC1 Accountants are capable of analyzing managerial information. MAC2 Accountants possess solid management accounting knowledge. MAC3 Accountants are able to process data for decision-making. MAC4 Accountants have the necessary technological skills. MAC5 Accountants collaborate effectively with other departments. Accounting Information System Quality – AISQ Argento et al. [1], Oanh et al. [3] and Tho and Huong [8] AISQ1 The system provides accurate data. AISQ2 The system provides timely data. AISQ3 The system supports responsibility center analysis. AISQ4 Data are integrated across departments. AISQ5 The system supports responsibility reporting. Digital Transformation Capability – DTC Argento et al. [1], Kraus et al. [5] and Oanh et al. [3] DTC1 The enterprise effectively implements digital technologies. DTC2 Accounting processes are digitalized. DTC3 Data are integrated in real time. DTC4 The enterprise has a clear digital transformation strategy. DTC5 Personnel are capable of meeting digital transformation requirements. Degree of Decentralization – DE Anthony and Govindarajan [4], Otley [11], and Mai and Thu [6] DE1 Decision-making authority is clearly delegated. DE2 Department managers have autonomy in their functions. DE3 Responsibilities are clearly defined across managerial levels. DE4 The enterprise has well-defined responsibility centers. DE5 Decentralization enhances management effectiveness. Innovation Culture – IC Argento et al. [1], Kraus et al. [5] and Nhung and Thuy [9] IC1 The enterprise encourages innovation. IC2 Employees are willing to adopt new technologies. IC3 Leaders support new ideas. IC4 The enterprise frequently improves and redesigns processes. IC5 Corporate culture supports digital transformation. Competitive Pressure – CP Manita et al. [13] and Hung and Tuan Anh [10] CP1 The enterprise faces high competitive pressure. CP2 Competition drives the improvement of operational efficiency. CP3 Customers demand greater transparency. CP4 Competition forces enterprises to adopt modern management tools. CP5 Competition encourages stricter cost control. Responsibility Accounting Adoption – RAA Anthony and Govindarajan [4], Otley [11], and Mai and Thu [6] RAA1 The enterprise establishes responsibility centers. RAA2 The enterprise prepares responsibility reports periodically. RAA3 Performance indicators are assigned according to responsibility centers. RAA4 RA information supports managerial decision-making. RAA5 RA is integrated into the management control system. 5. Research Results 5.1. Descriptive Statistics of the Sample A total of 400 valid survey responses were used for the quantitative analysis. The sample reflects a relatively diverse representation of Vietnamese enterprises applying RA during the digital transformation period. The characteristics of the sample are summarized in Table 2. 115 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate Table 2. Sample Characteristics. Sample Characteristics Categories Number of Enterprises Percentage (%) Type of Enterprise Private 260 65 State-owned 80 20 FDI 60 15 Enterprise Size (employees) < 50 employees 80 20 50–300 employees 240 60 > 300 employees 80 20 Job Position Accountant 180 45 Chief Accountant 100 25 Finance/Accounting Manager 60 15 Other middle-level managers 60 15 Work Experience < 3 years 60 15 3–5 years 140 35 5–10 years 140 35 > 10 years 60 15 Total Sample 400 100% In terms of enterprise type, private enterprises account for the largest proportion of the sample (65%), followed by state-owned enterprises (20%) and foreign direct investment (FDI) firms (15%). This distribution reflects the overall structure of the Vietnamese economy, in which the private sector plays a dominant role and demonstrates a strong pace of digital transformation in accounting and management activities. Regarding enterprise size, most surveyed firms employ between 50 and 300 employees (60%), while 20% have fewer than 50 employees and another 20% have more than 300 employees. This indicates that the sample primarily consists of medium and large enterprises, which are more likely to implement formal management accounting systems and Responsibility Accounting (RA) mechanisms. With respect to job positions, the majority of respondents are accountants (45%) and chief accountants (25%), followed by financial–accounting managers and other middle-level managers (15% each). These positions are directly involved in accounting operations, reporting systems, and decentralization mechanisms, ensuring high reliability of the collected data. In terms of work experience, 70% of respondents have between 3 and 10 years of experience, indicating that most participants possess adequate practical knowledge to assess the extent of RA adoption and its influencing factors. Overall, the sample structure is appropriate and representative, providing a reliable foundation for subsequent quantitative analyses in the context of Vietnamese enterprises accelerating digital transformation in management and accounting. 5.2. Reliability Analysis The study employed Cronbach’s Alpha to assess the reliability and internal consistency of the measurement scales. According to Hair et al. [15], a scale is considered reliable when its Cronbach’s Alpha coefficient is ≥ 0.7, and each observed variable has a Corrected Item–Total Correlation ≥ 0.3. The results of the reliability analysis for all factors and their corresponding observed variables are presented in Table 3. 116 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate Table 3. Results of Reliability Analysis for Factors and Observed Variables. Variable observation Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted Variable observation Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted Management Accounting Competency Cronbach’s Alpha = 0.934 Degree of Decentralization Cronbach’s Alpha = 0.938 MAC1 0.796 0.924 DE1 0.817 0.926 MAC2 0.815 0.921 DE2 0.847 0.921 MAC3 0.830 0.917 DE3 0.819 0.926 MAC4 0.855 0.912 DE4 0.832 0.924 MAC5 0.832 0.917 DE5 0.856 0.920 Accounting Information System Quality Cronbach’s Alpha = 0.932 Innovation Culture Cronbach’s Alpha = 0.945 AISQ1 0.809 0.920 IC1 0.839 0.934 AISQ2 0.843 0.913 IC2 0.830 0.936 AISQ3 0.820 0.917 IC3 0.861 0.930 AISQ4 0.816 0.917 IC4 0.875 0.928 AISQ5 0.823 0.916 IC5 0.847 0.933 Digital Transformation Capability Cronbach’s Alpha = 0.941 Competitive Pressure Cronbach’s Alpha =0.939 DTC1 0.832 0.929 CP1 0.845 0.922 DTC2 0.833 0.929 CP2 0.839 0.924 DTC3 0.835 0.929 CP3 0.819 0.927 DTC4 0.858 0.925 CP4 0.829 0.925 DTC5 0.849 0.926 CP5 0.848 0.923 Responsibility Accounting Adoption (Cronbach’s Alpha = 0.935) RAA1 0.846 0.917 RAA4 0.826 0.921 RAA2 0.799 0.926 RAA5 0.848 0.917 RAA3 0.827 0.921 The reliability analysis conducted on 400 valid observations shows that all measurement scales achieved high reliability. Specifically, the Cronbach’s Alpha coefficients of the seven scales range from 0.932 to 0.945, indicating strong internal consistency among the observed variables within each construct. In addition, the Corrected Item–Total Correlation values of all observed variables exceeded the threshold of 0.3, demonstrating that none of the items needed to be removed from the model and that each scale exhibits high inter-item correlation. Overall, the Cronbach’s Alpha results confirm that all measurement scales in the model possess high reliability and are fully appropriate for subsequent EFA and regression analysis. 5.3. Exploratory Factor Analysis (EFA) Exploratory Factor Analysis was conducted on 30 observed variables to identify the underlying factor structure. The KMO value is 0.892, which is greater than the acceptable threshold of 0.5, indicating that the dataset is highly suitable for factor analysis. Bartlett’s Test of Sphericity yields a Chi- Square value of 10268.421 with Sig. = 0.000, demonstrating that the observed variables are correlated in the population and meet the requirements for EFA. The Total Variance Explained table shows that six factors were extracted with Eigenvalues greater than 1, corresponding to the independent variable groups in the research model. The total variance explained is 80.572%, which is significantly higher than the 50% minimum threshold, indicating that the six extracted factors account for more than 80% of the variance in the data. The extraction stops at the sixth factor, with an Eigenvalue of 3.310, confirming that the observed variables converge into six distinct factor groups. 117 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate Table 4. Results of Total Variance Explained for Independent Variables. Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 4.741 15.805 15.805 4.741 15.805 15.805 4.117 13.724 13.724 2 4.416 14.720 30.524 4.416 14.720 30.524 4.065 13.549 27.273 3 4.129 13.762 44.286 4.129 13.762 44.286 4.032 13.440 40.714 4 3.970 13.233 57.520 3.970 13.233 57.520 4.023 13.409 54.122 5 3.606 12.019 69.539 3.606 12.019 69.539 3.979 13.264 67.386 6 3.310 11.033 80.572 3.310 11.033 80.572 3.956 13.186 80.572 7 0.353 1.178 81.750 8 0.349 1.162 82.912 9 0.331 1.103 84.015 10 0.318 1.061 85.076 11 0.309 1.031 86.107 12 0.298 0.995 87.102 13 0.293 0.977 88.079 14 0.287 0.958 89.037 15 0.262 0.875 89.911 16 0.257 0.857 90.768 17 0.251 0.836 91.604 18 0.240 0.799 92.403 19 0.227 0.758 93.161 20 0.225 0.752 93.913 21 0.219 0.729 94.642 22 0.209 0.697 95.339 23 0.202 0.673 96.012 24 0.197 0.657 96.669 25 0.192 0.641 97.310 26 0.176 0.587 97.897 27 0.172 0.572 98.469 28 0.164 0.546 99.016 29 0.152 0.505 99.521 30 0.144 0.479 100.000 Given these results, it can be concluded that the observed variables are correlated at the population level, and the model contains six distinct factors that should be included in the subsequent regression analysis. The Rotated Component Matrix obtained through Varimax rotation reveals the following six factor groups: 118 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate Table 5. Results of EFA. Component 1 2 3 4 5 6 IC4 0.921 IC3 0.913 IC5 0.903 IC1 0.895 IC2 0.889 DTC4 0.910 DTC5 0.904 DTC2 0.894 DTC3 0.894 DTC1 0.893 CP5 0.901 CP2 0.900 CP1 0.898 CP4 0.891 CP3 0.883 DE5 0.911 DE2 0.903 DE4 0.893 DE3 0.886 DE1 0.880 MAC4 0.909 MAC5 0.894 MAC3 0.892 MAC2 0.881 MAC1 0.865 AISQ2 0.901 AISQ5 0.888 AISQ4 0.884 AISQ3 0.881 AISQ1 0.876 KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.892 Bartlett's Test of Sphericity Approx. Chi-Square 10268.421 df 435 Sig. 0.000 The results of the rotated component matrix indicate that all 30 observed variables clearly converged into six distinct factor groups as expected, with no evidence of cross-loading. The factor loadings range from 0.865 to 0.921, exceeding the minimum threshold of 0.5, demonstrating strong convergent validity for all observed variables within their respective latent constructs (see Table 5). The EFA results confirm that the measurement scales used in the research model are appropriate. All six independent factors exhibit clear representative value and meet the necessary conditions to be included in the subsequent regression analysis for hypothesis testing. 5.4. Model Testing To evaluate the research hypotheses, multiple linear regression analysis was employed. The regression results (Table 6) show that the model achieves an R² value of 0.780 and an adjusted R² of 0.777, indicating that 77.7% of the variance in the dependent variable (RAA) is explained by the six independent variables in the model; the remaining variance is attributable to factors outside the model and random error. 119 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate The Durbin–Watson statistic is 2.118 (within the acceptable range of 1.5–2.5), and the Variance Inflation Factor (VIF) values for all independent variables are below 2, indicating no violation of first- order autocorrelation or multicollinearity assumptions. The F-test in the ANOVA table yields F = 232.695 with Sig. = 0.000 (< 0.05), confirming that the regression model is statistically significant and that all independent variables included in the model contribute meaningfully to explaining the variation in RAA. Table 6. Regression Analysis Results Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1 0.883a 0.780 0.777 0.30268 2.118 Note: a. Predictors: (Constant), F_CP, F_DE, F_MAC, F_DTC, F_IC, F_AISQ. b. Dependent Variable: F_RAA. ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 127.914 6 21.319 232.695 0.000b Residual 36.006 393 0.092 Total 163.920 399 Note: a. Dependent Variable: F_RAA b. Predictors: (Constant), F_CP, F_DE, F_MAC, F_DTC, F_IC, F_AISQ. Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF 1 (Constant) -3.346 0.178 -18.833 0.000 F_MAC 0.397 0.023 0.411 17.244 0.000 0.983 1.017 F_AISQ 0.417 0.024 0.415 17.362 0.000 0.980 1.020 F_DTC 0.424 0.024 0.425 17.921 0.000 0.992 1.008 F_DE 0.329 0.024 0.324 13.612 0.000 0.988 1.012 F_IC 0.328 0.023 0.333 14.019 0.000 0.988 1.012 F_CP 0.258 0.023 0.273 11.435 0.000 0.984 1.017 Note: a. Dependent Variable: F_RAA. The multiple linear regression analysis was conducted to evaluate the extent to which each factor influences the adoption of Responsibility Accounting in the context of digital transformation among Vietnamese enterprises. The estimated multiple regression equation is expressed as follows: F_RAA = -3.346 + 0.397* F_MAC + 0.417* F_AISQ + 0.424*F_DTC + 0. 329*F_DE + 0.328*F_IC + 0.258*F_CP The results of the multiple linear regression analysis indicate that all six independent variables exert positive and statistically significant effects (Sig. < 0.05) on the adoption of Responsibility Accounting (RAA) among Vietnamese enterprises. All independent variables have positive regression coefficients and are statistically significant (Sig. < 0.05), and no multicollinearity issues are detected (VIF < 2), confirming that the model is stable and reliable. Among the six factors, DTC demonstrates the strongest impact on RAA (B = 0.424). This finding highlights the pivotal role of digital transformation in enhancing data transparency, system integration, and information effectiveness for RA. Enterprises with strong digital infrastructure, digitalized processes, and advanced data-processing capabilities tend to adopt RA more effectively. The second strongest predictor is AISQ (B = 0.417). When the accounting information system provides accurate, timely, and integrated data, enterprises have a solid informational foundation to establish, report on, and evaluate responsibility centers more effectively. 120 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate MAC also has a significant impact on RAA (B = 0.397). This finding reinforces the role of accounting personnel with strong analytical skills, data-processing capabilities, and managerial knowledge in effectively operating the RA system. In addition, organizational factors such as the DE (B = 0.329) and IC (B = 0.328) exert positive effects on RAA. A clearly defined decentralization structure enhances transparency in assigning individual responsibility, while an innovation-oriented culture encourages enterprises to embrace and implement modern management mechanisms, including RA. Finally, CP also exerts a statistically significant influence (B = 0.258). In highly competitive environments, enterprises are compelled to strengthen cost control, enhance information transparency, and use RA as a key tool to measure and improve operational performance. Table 7. Summary of Regression Analysis Results. Interpretation Coefficient B Sig. Hypothesis Testing Result Impact Level MAC positively influences RAA. 0.397 0.000 Accepted Strong impact AISQ positively influences RAA. 0.417 0.000 Accepted Strong impact DTC positively influences RAA. 0.424 0.000 Accepted Strongest impact DE positively influences RAA. 0.329 0.000 Accepted Medium impact IC positively influences RAA. 0.328 0.000 Accepted Medium impact CP positively influences RAA. 0.258 0.000 Accepted Mild to moderate impact Thus, all six hypotheses (H1–H6) are accepted. These findings indicate that the RAA in Vietnamese enterprises is not only influenced by accounting competency and the quality of accounting information systems but is also strongly driven by digital transformation, organizational structure, and competitive pressures. This implies that enterprises must simultaneously strengthen their digital capabilities, enhance information system quality, establish clear decentralization mechanisms, and foster an innovation-oriented culture to improve the effectiveness of RAA during the digital transformation era. 5.5. Discussion of Findings The findings reveal that all six factors in the research model exert positive and statistically significant effects on the RAA in the context of digital transformation among Vietnamese enterprises. This indicates that the implementation of RA is not only influenced by internal organizational resources but is also strongly shaped by technological capabilities and competitive environmental conditions. These results are consistent with the theoretical foundations of RAT, MCS, and the TOE framework adopted in this study. First, DTC is identified as the most influential factor affecting RAA. This reflects the reality of Vietnam’s rapidly evolving digital transformation landscape, where enterprises increasingly rely on digitalized data, integrated systems, and automated processes to support accountability, performance evaluation, and responsibility reporting. This finding aligns with recent international research emphasizing the critical role of digital transformation in modern management accounting systems [1, 3]. Second, both AISQ and MAC exhibit strong and stable effects on RAA. These results underscore that decisions related to responsibility allocation, performance measurement, and responsibility reporting can only be effectively executed when accounting information is accurate, timely, and operated by competent accounting personnel. This finding is consistent with Feghali et al. [2] and Mai and Thu [6], who highlight information quality and accounting competency as foundational elements of any responsibility control mechanism. Additionally, DE and IC also positively influence the RAA. Clear decentralization facilitates the establishment of responsibility centers and enhances transparency in performance evaluation processes. At the same time, an innovation-oriented culture encourages the acceptance and implementation of 121 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate advanced management practices, especially in rapidly evolving technological environments. These findings align with the work of Otley [11] and Kraus et al. [5]. Finally, although its effect is relatively smaller, CP still plays a meaningful role in promoting RAA. In highly competitive markets, enterprises must strengthen cost control, enhance informational transparency, and improve operational efficiency, thereby increasing their motivation to adopt modern management tools such as RA. This finding is consistent with Manita et al. [13], who emphasize the impact of competitive forces on management control systems. Overall, the findings indicate that RAA in Vietnamese enterprises is simultaneously influenced by technological factors (DTC, AISQ), human resource factors (MAC), organizational factors (DE, IC), and environmental factors (CP). These results reinforce the theoretical foundations of MCS, RBV, and TOE while providing important empirical evidence on the role of digital transformation in shaping responsibility accounting systems, an emerging research topic in the Vietnamese context. 6. Conclusion and Managerial Implications 6.1. Conclusion This study was conducted to evaluate the factors influencing the RAA in the context of digital transformation within Vietnamese enterprises. Based on a theoretical framework integrating RAT, MCS, the TOE framework, and the RBV, quantitative analysis using 400 survey responses revealed that all six factors, MAC, AISQ, DTC, DE, IC, and CP, exert positive and statistically significant effects on RAA. Among these, DTC demonstrates the strongest influence, followed by AISQ and MAC. This reflects the growing reliance of enterprises on digital capabilities and integrated information systems to implement responsibility control mechanisms. Organizational factors such as decentralization and innovation culture also play essential roles, creating enabling conditions for the effective operation of RA. Meanwhile, competitive pressure continues to motivate firms to use RA as a means to enhance managerial efficiency and strengthen strategic responsiveness. Overall, the study confirms that RAA is not merely a technical accounting activity but the outcome of a broader ecosystem encompassing technology, human capability, organizational structure, and external competitive forces. These findings provide important empirical evidence for the Vietnamese context, where digital transformation is accelerating, and RA remains an emerging but increasingly relevant area of research. 6.2. Managerial Implications Based on the research findings, several managerial implications are proposed to help enterprises enhance the RAA: 6.2.1. Strengthen the Enterprise’s Digital Transformation Capability As DTC is the most influential factor, enterprises should prioritize investments in digital infrastructure, including ERP systems, intelligent accounting software, integrated data platforms, and analytical technologies. Digitalized processes ensure that responsibility-related data are transparent, timely, and accurate. 6.2.2. Improve the Quality of the Accounting Information System Enterprises should develop accounting information systems with high reliability, cross- departmental data integration, and strong support for responsibility center reporting. An effective information system forms the foundation for the smooth functioning of RA. 122 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 12: 109-123, 2025 DOI: 10.55214/2576-8484.v9i12.11285 © 2025 by the author; licensee Learning Gate 6.2.3. Enhance Management Accounting Competency Firms should invest in training accounting personnel in data analysis, managerial thinking, and the use of modern accounting tools. Competent staff ensure that RA systems are properly designed and effectively implemented. 6.2.4. Strengthen Decentralization Mechanisms Within the Enterprise Given the positive impact of decentralization, enterprises should clearly define the authority and responsibilities of each responsibility center. A well-structured decentralized system allows RA to fulfill its role in monitoring responsibilities and evaluating performance. 6.2.5. Foster An Innovation-Oriented Organizational Culture Enterprises should promote a flexible working environment that encourages experimentation, continuous improvement, and openness to new technologies. An innovation-oriented culture is essential for the acceptance and effective implementation of RA in practice. 6.2.6. Enhance Competitive Capability and Strengthen Transparency Requirements Competitive pressure motivates enterprises to apply RA to optimize costs and improve operational efficiency. Therefore, firms should refine their competitive strategies while simultaneously improving internal control mechanisms to meet transparency and accountability requirements. 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