Accounting Research Festival 2025 P-ISSN: x-x.
E-ISSN: x-x Website : https://publikasiilmiah.
id/fra4 Redefining Accounting Education: Balancing Technological Innovation with Ethics and Sustainability Digital Transformation in Accounting: The Role of Employee Competence and Infrastructure in Promoting Financial Transparency Eka Fitriani 1 * .
Naili Sa'adah 2 .
Sri Retnoningsih 3 1 Accounting.
Wahid Hasyim University.
Semarang.
Indonesia.
Email: ek.
fitriani2003@gmail.
2 Accounting.
Wahid Hasyim University.
Semarang.
Indonesia.
Email: nailisaadah2402@gmail.
3 Accounting.
Wahid Hasyim University.
Semarang.
Indonesia.
Email: sri_retnoningsih@unwahas.
ABSTRACT
Digital transformation demands that retail companies increase the transparency of their financial reports, but the effectiveness of each digital component still produces mixed results.
This study analyzes the effect of digital accounting adoption, employee training, and digital infrastructure on the transparency of financial reports of retail companies listed on the Indonesia Stock Exchange for the period 2022 to 2024.
Quantitative methods were used with secondary data from 25 IDX retail companies selected through purposive sampling.
Multiple linear regression analysis shows that digital infrastructure has a positive and significant effect, while digital accounting adoption and employee training have no significant effect.
Simultaneously, the three variables form a significant model.
These results confirm that transparency depends on the synergy between technological readiness, human resource competency, and the quality of digital infrastructure.
The findings provide practical implications for companies in designing digital strategies focused on increasing transparency .
Keywords: financial reporting transparency, digital accounting, employee training, digital infrastructure, retail companies .
INTRODUCTION
transformation in accounting has become a global trend, transforming the way companies manage and report their financial information.
Digitization enables greater efficiency, accuracy, and transparency through the implementation of cloud accounting , blockchain ledgers , and Enterprise Resource Planning (ERP) systems.
However, many companies still face challenges in human resource (HR) training and technological infrastructure, particularly in the competitive and transaction-intensive retail sector (OECD.
World, 2.
This situation creates disparities in transparency levels between companies, even though financial reporting transparency is a key foundation for investor trust and effective corporate governance (Hapsoro & Suryanto, 2.
In this context, financial reporting transparency (Y) depends on the integration of three internal First, the adoption of digital accounting (XCA) plays a crucial role in improving the quality and speed of financial reporting because technologies such as ERP, cloud accounting, and blockchain ledgers can accelerate and improve the accuracy of financial data recording (Krahel & Titera, 2.
However, the successful adoption of this technology is highly dependent on the readiness of human resources.
Second, employee training (XCC) is therefore needed to improve digital literacy so that system effectiveness does not decrease due to limited skills (Bonsyn & Bednyrovy, 2.
Third, digital infrastructure (XCE) is the foundation that determines the success of digitalization, ensuring the system runs safely and efficiently.
Good infrastructure allows the digital reporting process to be carried out without technical obstacles such as network disruptions or data security risks (Al-Htaybat & von AlbertiAlhtaybat, 2.
The synergy of these three internal factors is believed to be able to strengthen the transparency of the company's financial reports (Nguyen & Le, 2.
These three independent variables conceptually influence financial report transparency (Y).
Transparency reflects the extent to which financial information is disclosed openly, accurately, and timely to the public.
In other words, a high level of transparency will emerge if a company is able to integrate digital systems, improve human resource competencies, and strengthen its technological infrastructure.
Accounting Research Festival Proceedings | 4 13 Empirically, although many Indonesian public companies have adopted digital accounting systems, transparency gaps still exist due to differences in internal readiness and investment in human resources and digital infrastructure.
(Omar et al.
, 2.
Previous research tends to only partially highlight one factor, such as digital technology (Smith et al.
, 2.
, employee training (Johnson & Lee, 2.
, or digital infrastructure, without integrating all three into a comprehensive model.
Consequently, none of these previous studies have comprehensively explained how the adoption of digital accounting, employee training, and digital infrastructure simultaneously affect financial report transparency.
Furthermore, previous studies have been mostly conducted in developed countries, while the context of Indonesian public companies, particularly the highly digitalized and transaction-intensive retail sector, remains very limited (Omar et al.
, 2.
The gap between the level of technology adoption and the results of financial transparency in the field creates a research gap that indicates the need for empirical research that simultaneously analyzes the influence of digital accounting adoption, employee training, and digital infrastructure on financial report transparency, particularly in the Indonesian public retail sector which is facing rapid and massive digital transformation.
This study fills this gap by analyzing the simultaneous influence of digital accounting adoption, employee training, and digital infrastructure on financial reporting transparency in public retail companies in Indonesia.
Thus, this study broadens the empirical scope and provides an integrated model that can serve as a reference for further research in digital accounting.
Analysis of the Hypothesis and Theoretical Basis Section Researchers use four main theories to explain the relationship between independent and dependent variables, namely Resource-Based View (RBV).
Technology Acceptance Model (TAM).
Institutional Theory , and Stakeholder Theory .
Table 1the Hypothesis Section and Theoretical Basis Hypothesis Basic Theory Relationship between H1:
Adoption digital Resource-Based View (Barney.
The RBV emphasizes the accounting has a positive effect 1.
importance of a company's on the transparency of financial leveraging strategic resources such as digital technology.
Adopting digital accounting systems creates competitive accuracy, thereby enhancing H2: Employee training has a Technology Acceptance Model TAM explained that perceived positive effect on financial (Fred D.
Davis, 1.
benefits and ease of use of report transparency.
technology increase through training and user experience.
Employee training improves their ability to operate digital systems and enhances the quality of reporting.
H3: Digital infrastructure has a Institutional Theory (DiMaggio Institutional theory highlights the and Walter W.
Powell, 1.
international regulations and standards .
OJK and IFRS) that encourage companies to build digital infrastructure that transparency and legitimacy.
H4:
Adoption digital Stakeholder Theory (Freeman.
According to stakeholder theory , accounting, employee training, 1.
transparency is a form of organizational accountability to simultaneously have a positive The effect on the transparency of between technology adoption.
Accounting Research Festival Proceedings | 380 financial reports.
building, and infrastructure readiness creates a more open and publicly trusted reporting The relationships between the variables in this study are mutually supportive.
Digital accounting adoption provides tools and systems, employee training provides skills and competencies, and digital infrastructure provides technical support.
Together, these three factors strengthen the transparency of financial reports, which serves as the basis for corporate accountability and legitimacy in the public eye.
This study addresses this empirical gap by testing a comprehensive model based on RBV.
TAM.
Institutional, and Stakeholder theories, explaining how accounting digitalization can promote transparency and public trust in Indonesia's public retail sector.
This research framework illustrates the causal relationship between three independent variables and the dependent variable.
Increased adoption of digital accounting (XCA), employee training (XCC), and digital infrastructure readiness (XCE) are expected to strengthen financial reporting transparency (Y).
This relationship confirms that the effectiveness of financial reporting digitalization is determined not only by technology but also by human readiness and comprehensive system support.
Adopsi Akuntansi Digital (X.
Transparansi Laporan Keuangan (Y) Pelatihan Karyawan (X.
Infrastruktur Digital (X.
Figure 1of Thought Thus, this research is expected to provide empirical contributions to strengthening digital accounting literature and become a basis for analysis in increasing the transparency of financial reporting through optimizing technology, human resource competencies, and digital infrastructure in the Indonesian public company environment.
RESEARCH METHODS
This study uses a quantitative approach with a causality design, which aims to test the causal relationship between independent and dependent variables (Sugiyono, 2.
This approach was chosen because it aligns with the research objective of providing empirical evidence regarding the effect of digital accounting adoption (XCA), employee training (XCC), and digital infrastructure (XCE) on financial report transparency (Y) in retail companies listed on the Indonesia Stock Exchange (IDX).
The study population includes all retail companies listed on the IDX during the 2022Ae2024 period.
Sample selection was carried out using a purposive sampling method based on the following criteria: .
companies actively listed on the IDX for three consecutive years .
2Ae2.
companies that have adopted a digital accounting system as stated in their annual report or sustainability report .
companies that have complete and publicly accessible financial data.
Based on these criteria, out of a total of 31 retail companies, 25 companies were selected as research samples.
The data used are secondary data obtained through documentation from annual reports , sustainability reports , and annual financial reports published on the official IDX website ( w.
and the official websites of related companies.
Data collection was carried out using a quantitative analysis method based on financial ratios, where each variable is measured using numerical indicators sourced directly from financial report data and processed into an interval/ratio scale.
The variable measurements are explained operationally in the following table:
Accounting Research Festival Proceedings | 4 13 Table 2Operational Definition of Variables Variables Definition Indicator Digital Accounting Adoption (XCA) The level of implementation of digital systems in the company's accounting and financial reporting Employee Training (XCC) The intensity and effectiveness of HR training in supporting digital Digital Infrastructure (XCE) Readiness of IT facilities and infrastructure that support digital Financial Report Transparency (Y) The level of openness and accuracy of the information to the Percentage of ERP ( Enterprise Resource Planning ) usage to total accounting Number of active digital accounting IT investment to total assets ratio Number of digital trainings per year The ratio of employees who attended training to total employees Total training costs against total HR (Human Resource.
IT spending to revenue ratio Number of active cyber security budget to total IT budget Disclosure index Timeliness of submission of financial reports Ratio of mandatory disclosures to total report items Measuring X1 = IT value / Total assets y100% Source Annual Report.
Sustainability Report X2 = Total Training Cost / Total HR Burden x 100% Annual Report.
Corporate Governance Report
X3 = IT
Spending / Revenue x Annual Report.
Sustainability Report Y = Number of items disclosed / Number of required items x 100% Annual Report.
BEI Disclosure Index To test the research hypothesis, the Multiple Linear Regression method was used with the help of SPSS version 25 software.
This method was chosen because all research variables were measured in numerical form .
nterval/ratio scal.
and met parametric assumptions.
The regression model is formulated as follows:
Y= 1X1 2X2 3X3 A
Information:
Y = Transparency of Financial Reports XCA = Digital Accounting Adoption XCC = Employee Training XCE = Digital Infrastructure = constant = regression coefficient A = error term Accounting Research Festival Proceedings | 382 Before the regression test was conducted, classical assumption tests were conducted, including: .
normality test with KolmogorovAeSmirnov to ensure the residuals were normally distributed.
multicollinearity test with Variance Inflation Factor (VIF < .
to detect correlation between variables.
heteroscedasticity test with Glejser test to ensure constant residual variance.
autocorrelation test using DurbinAeWatson.
After all assumptions were met, a t-test was conducted to assess the partial effect of each independent variable on financial report transparency, as well as an F-test to test the simultaneous effect of all three variables.
The coefficient of determination (RA) value was used to measure the extent to which variations in financial report transparency can be explained by the adoption of digital accounting, employee training, and digital infrastructure.
RESULTS AND DISCUSSION
This section presents the results of a multiple linear regression analysis to assess the effect of digital accounting adoption (XCA), employee training (XCC), and digital infrastructure (XCE) on financial report transparency (Y) in retail companies listed on the IDX for the 2022-2024 period.
Secondary data were analyzed using SPSS version 25 software, and the main results discussed include descriptive statistics, classical assumption tests, and partial and simultaneous hypothesis testing.
Table 3and Sample Data Information Amount Population: Retail Companies listed on the IDX Sampling based on criteria ( purposive samplin.
Companies that are not listed on the IDX consecutively from 2022-2024 Companies that do not report financial reports for the 2022-2024 period Amount Research Sample Total sample .
x research perio.
x 3 year.
Source: Processed IDX data
Sample Research data
Table 4Determination Coefficient Data
Coefficient of Determination Model
R Square Adjusted R Square Standard Error of the Estimate Durbin-Watson
1,697
Predictors: (Constan.
,X1,X2,X3 Dependent Variable: Y The coefficient of determination shows that the R Square value is 0.
158 or 15.
8 percent, which means that variables X1.
X2, and X3 are able to explain variations in variable Y by 15.
8 percent, while the 2 percent is influenced by other factors outside the model.
The Adjusted R Square of 0.
indicates that after adjusting the number of variables, the model still has a fairly consistent explanatory Accounting Research Festival Proceedings | 4 13 The Durbin-Watson value of 1.
697 indicates that there is no significant autocorrelation problem in the residuals .
Table 5Hypothesis Test Data
HYPOTHESIS TESTING
Unstandardized Coefficients Standardized Coefficients Std.
Error Beta (Constan.
2,218 415,764 Model Sig.
1,218
520,719
Dependent Variable: Y The results of the hypothesis test in the regression table indicate that all independent variables do not have a significant influence on the dependent variable.
This can be seen from the significance value of each variable which is all far above 0.
05, namely X1 with B = Oe0.
790 and Sig = 0.
X2 with B = Oe0.
and Sig = 0.
442, and X3 with B = 415.
764 and Sig = 0.
The Standardized Beta of the three variables is also very small, indicating a weak influence.
Meanwhile, the constant has a B value of 5294.
556 with Sig = 227 which is also insignificant.
Overall, these results indicate that variables X1.
X2, and X3 are unable to explain changes in the dependent variable, so the regression model is considered weak and does not support the proposed hypothesis.
Table 6Regression Model Test Data Model Regression Sum Squares Residual 2,614 Total ANOVA a Mean Square 4,442 Sig.
Dependent Variable: Y Predictors: (Constan.
X 1,X2,X 3 results indicate that the regression model consisting of the variables digital accounting adoption, employee training, and digital infrastructure jointly has a significant effect on financial report transparency.
This is indicated by the F value of 4.
442 with a significance level of 0.
006 (<0.
, indicating that the regression model is suitable for use and able to explain variations in the dependent variable.
Thus, it can be concluded that the three independent variables simultaneously have a significant effect on financial report Discussion The results of the study indicate that the use of digital accounting systems does not significantly impact the transparency of financial reports.
This finding indicates that the application of modern technology has not automatically increased transparency .
It is likely that the implementation is still superficial or not deeply integrated with the core reporting process, so the transparency benefits are not optimal (Krahel & Titera, 2.
Similarly, the insignificant effect of employee training may be due to the Accounting Research Festival Proceedings | 384 training not specifically addressing the complex aspects of digital financial reporting or not directly measuring its effectiveness on reporting outcomes (Bonsyn & Bednyrovy, 2.
On the other hand, the significance of digital infrastructure strengthens the propositions of institutional theory.
Regulatory pressure from the Financial Services Authority (OJK) and the adoption of global standards such as IFRS encourage companies to invest in reliable infrastructure, which in turn provides the technical foundation for more accurate, secure, and timely reporting (Al-Htaybat & von Alberti-Alhtaybat, 2018.
DiMaggio & Powell, 1.
The significance of the simultaneous model, despite its limited explanatory power, supports Stakeholder Theory.
(Freeman, 1.
This finding implies that stakeholders .
uch as investors and regulator.
view transparency as the result of a comprehensive digital ecosystem, a synergy between technology, human resources, and infrastructure, rather than a single factor.
This finding aligns with research by Nguyen & Le .
, which emphasizes the importance of a holistic approach to accounting digitalization.
Adoption of digital accounting has a positive impact on the transparency of financial reports.
The results of the analysis show that the adoption of digital accounting (X.
does not have a significant effect on the transparency of financial reports, indicated by a significance value of 0.
(>0.
and a negative regression coefficient of -0.
This finding indicates that the use of a digital accounting system has not been able to increase the transparency of financial reports in the research context, possibly because the level of utilization of digital features is not optimal or is still in the early stages of implementation, so that the H1 hypothesis is not proven.
Employee training has a positive impact on the transparency of financial reports.
The employee training variable (X.
also showed no significant effect on financial report transparency, with a significance value of 0.
442 (>0.
and a regression coefficient of -0.
These results indicate that the training provided has not directly improved employees' ability to produce transparent financial reports.
The training provided may not have been specific to the reporting aspect or has not been implemented consistently, thus hypothesis H2 is not proven.
Digital infrastructure has a positive impact on the transparency of financial reports.
Digital infrastructure (X.
is proven to have a significant effect on financial report transparency, as seen from the significance value of 0.
001 (<0.
and a positive coefficient of 415,764.
This indicates that the better the digital infrastructure an organization has, the higher the level of transparency of its financial reports.
Adequate digital infrastructure supports the quality of recording, storing, and reporting information, so H3 is proven.
Adoption of digital accounting, employee training, and digital infrastructure simultaneously have a positive impact on the transparency of financial reports.
The ANOVA test results indicate that the regression model consisting of the variables digital accounting adoption, employee training, and digital infrastructure jointly has a significant effect on financial report transparency.
This is indicated by the F value of 4.
442 with a significance level of 0.
(<0.
, indicating that the regression model is suitable for use and able to explain variations in the dependent variable.
Thus, it can be concluded that the three independent variables simultaneously have a significant effect on financial report transparency.
Research result The results show that digital infrastructure significantly influences financial report transparency, while digital accounting adoption and employee training are partially insignificant.
However, these three variables simultaneously form a significant model, confirming that financial report transparency results from the interaction and synergy between digital components within a company.
CONCLUSION
This study examines the influence of digital accounting adoption, employee training, and digital infrastructure on the transparency of financial reports in retail companies listed on the Indonesia Stock Exchange (IDX) from 2022 to 2024.
The analysis shows that digital accounting adoption and employee Accounting Research Festival Proceedings | 4 13 training do not significantly influence financial report transparency.
Digital infrastructure has been shown to have a significant effect and contribute positively to increasing transparency.
Simultaneously, these three variables form a significant model, indicating that financial report transparency is strengthened through the synergy between technological readiness, human resource competency, and digital infrastructure support.
These findings emphasize the importance of prioritizing investment in digital infrastructure and evaluating the implementation of digital accounting systems and training programs to improve the quality and transparency of financial information.
This study is limited by the limited sample size in the retail sector and the use of independent variables that do not comprehensively capture aspects of system implementation.
Potential mediating and moderating variables, as well as organizational factors, have not been analyzed.
Potential further research includes expanding the sector coverage, increasing the observation period, and incorporating process variables to produce a more robust model.
REFERENCE