Impact of Digital Accounting Tools on ESG (Environmental, Social, Governance) Reporting Accuracy and Corporate Sustainability Strategies: Moderating Role of Regulatory Environment

3. Materials and Methods

3.1. Data Collection and Sample

A questionnaire survey (Appendix A) was distributed to 800 professionals holding relevant experience in various functions related to ESG reporting, corporate governance, and sustainability management. Perceptions and experience of the respondents on the use of digital accounting tools in the ESG reporting and corporate sustainability strategies were measured on a 5-point Likert scale as 1 (Strongly Agree) to 5 (Strongly Disagree) using the questionnaires. The respondents were ESG managers, corporate sustainability officers, accountants, auditors and financial analysts. They were incorporated because they possessed diverse knowledge about matters regarding the ESG reporting, and financial analysis. To determine that the participants had knowledge and experience concerning the use of digital accounting solutions to report the ESG, the purposive sampling strategy was used as outlined in the study of (Campbell et al., 2020).

Moreover, to achieve the illustrative heterogeneous sample, the participants were also chosen in a number of industries such as finance, energy, manufacturing and technology. Moreover, the companies that focused on the implementation of a digital accounting system to improve the ESG reporting was chosen. The sample was spread evenly across the industry with a 25% sample to the finance industry, 25% sample to the energy industry, 25% sample to the manufacturing industry, and 25% sample of the technology industry. The questionnaire was posted on professional networks such as LinkedIn, email lists of organisations’ business segments, and even individual rejection of companies with well-defined ESG strategies. The response rate amounted to 56%, and 450 completed questionnaires were obtained. Following the removal of unfinished or invalid responses, it could be seen that 420 valid responses were obtained, which is a good set of data to be analysed.

The effect of non-response was quantified by comparing late respondents and early respondents using the independent sample t-test, as mentioned in (Kline, 2023; and Si et al., 2023). The findings provided that there was no remarkable variation between the two groups, and this indicated that there was no bias in the sample and the results were accurate for the whole population. The sample was heterogeneous and the data collection process resulted in the reliability of the research but also in an adequate body of knowledge on the relationship between digital accounting solutions and the quality of ESG reporting. In order to measure the risk of common method bias, the study applied Harman Single Factor Test to establish the percentage of variance in the data that could be attributed to a single factor. The test revealed that the ratio of the variance attributed to the single factor was not exceeding 50, and it means that there was no severe common method bias. This enhance the validity and reliability of the findings, whereby the results were not influenced by the time of data collection or other biases. Since the study involved human participants, ethical approval from the institutional board was obtained. Further to ensure ethical considerations are kept intact, informed consent was obtained from the participants for participation in the survey and voluntary inclusion and withdrawal from the participation was also informed and communicated.

3.2. Data Analysis

Partial Least Squares Structural Equation Modelling (PLS-SEM) was aligned to analyse the data because it is appropriate to study such complex relations among several variables and process relatively small sample groups (Sarstedt & Cheah, 2019). In order to provide the measurement model validity and reliability, Confirmatory Factor Analysis (CFA) helped to test the factor loading, the composite reliability, and the Average Variance Extracted (AVE). These tests established that the measurement model was sufficient. After confirming the constructs, a path analysis was applied to examine how the digital accounting tools affected their performance on the accuracy of their ESG reporting and corporate sustainability strategies.

4. Results

4.1. Demographics

Table 1 demographic data show more men in the sample for the study, at 250 men, representing 59.5% of the sample. In comparison to this number, 170 participants were women, representing 40.5% of the sample. This reflects the predominance of men in the sample representation of the study, which may be reflective of the overall gender makeup in the professional fields covered by the survey, particularly fields that involve ESG reporting, company governance, and computerised accounting programs.

Table 1. Demographics.

The age group has a wide distribution, with the most concentrated group being the 30-39 years age group, with 160 respondents or 38.1% of the sample population. This is trailed by the 20-29 years of age with 120 respondents (28.6%). The 40-49 years of age had 90 respondents (21.4%), while the 50 years and older age group had 50 respondents (11.9%). The mainstream of respondents in this study are falls in the age bracket of 20 and 39, and they are a young and potentially more technologically savvy population.

The results indicate that 25% of the sample study population is evenly represented across four major industries, including Finance, Energy, Manufacturing, and Technology. This equitable allocation means that the current article covers a broader variety of views on digital accounting technology and ESG reporting in different sectors. The homogeneity of the sample makes the conclusions about the study more robust and generalisable.

4.2. Measurement Model Using Confirmatory Factor Analysis

Table 2 shows the measurement of reliability and convergent validity of constructs used in the study employing well-tested measures. The main indicators of internal constancy of latent constructs are Cronbach’s alpha and composite reliability. As (Kline, 2023) explains, the value of Cronbach’s Alpha that portends reasonable reliability of a construct is at least 0.7. The values in the current study surpass this threshold, and the values of Cronbach’s Alpha of Digital Accounting Tools (DAT) of 0.849, ESG Reporting Accuracy (ESGRA) of 0.823, Corporate Sustainability Strategies (CSS) of 0.882, and Regulatory Environment (RE) of 0.903. These values indicate a very strong internal consistency of each construct and indicate that the items representing the measure are trustworthy. Composite reliability values (0.850 to 0.918) also validate consistency and robustness in the measurement model, showing that indicators of each construct coincide with corresponding latent variables.

Table 2. Reliability and convergent validity testing.

Regarding convergent validity, the Average Variance Extracted (AVE) was also tested. It was determined by (Hair et al., 2017) that the value of AVE surpassing its threshold of 0.5 signifies an adequate convergent validity and, hence, substantial variance was covered by constructs rather than the measurement error. The AVE values of those variables to be assessed, Digital Accounting Tools, ESG Reporting Accuracy, Corporate Sustainability Strategies, and Regulatory Environment, are large (0.768, 0.738, 0.809, 0.837) and well above the 0.5 rule, which signifies strong convergent validity. It is also indicated that the factor loadings of all variables in the measurement surpasses the 0.6 level, further indicating the validity as well as internal constancy of the measurement model. The results ensure the reliability, consistency as well as validity of the study variables, which forms a strong basis for path analyses and the determination of the meaning of the relationship in the structural model.

As indicated by the statistical results in Table 3, the discriminant validity of constructs of the study is measured with Heterotrait-Monotrait (HTMT) ratio, which is a reliable approach to measure the uniqueness of latent variables and avoid such problems as multicollinearity. (Yusoff et al., 2020) state that values of HTMT that move below the critical level of 0.85 will confirm that discriminant validity is sufficient. The HTMT values, as depicted in Table 3, are below 0.85, confirming discriminant validity. The results support the studies by (Henseler et al., 2015; Hair et al., 2019), emphasising the importance of discriminant validity in confirming robustness of the measurement model.

Table 3. Discriminant validity.

4.3. Path Analysis

Table 4 path coefficients show positive, strong, and statistically significant relationships between the constructs. Digital Accounting Tools directly relate to Corporate Sustainability Strategies as (β = 0.385, p < 0.001), which means corporate sustainability strategies are significantly affected by digital accounting tools. Similarly, the Digital Accounting Tools to ESG Reporting Accuracy has a coefficient of (β = 0.430, p < 0.001), signifying that digital tools significantly contribute to the accuracy of ESG reporting. From these findings, the effectiveness of digital tools in improving both sustainability approaches and the accuracy of ESG disclosures becomes evident.

Table 4. Path coefficients.

Note: *(p < 0.10): Indicates statistical significance at the 10% level.

**(p < 0.05): Indicates statistical significance at the 5% level.

***(p < 0.001): Indicates statistical significance at the 1% level.

Moreover, Regulatory Environment influences Corporate Sustainability Strategies (β = 0.495, p < 0.001) and ESG Reporting Accuracy (β = 0.240, p < 0.001) considerably, reflecting that the regulations have a considerable influence on sustainability practices and enhance the accuracy of reporting on ESG. The Interaction effect of Regulatory Environment and Digital Accounting Tools on Corporate Sustainability Strategies shows a coefficient of (β = 0.072, p < 0.01), which is statistically significant at the 0.01 level and hence implies that regulatory environments have a moderate influence on the relationship between digital accounting tools and sustainability strategies. Similarly, the interaction effect on ESG Reporting Accuracy is (β = 0.119, p < 0.01), which represents a marginally significant effect.

4.4. Model Explanatory Power

The R-square in Table 5 indicates the explanatory level of the model in the explanation of the variability of the dependent variables. In the case of Corporate Sustainability Strategies, the R-squared equals 0.538, implying that variation in corporate sustainability strategies can be explained by the various independent variables incorporated in this model, accounting for around 53.8%. This implies a low to high explanatory strength of the model for the sustainability strategies. In the case of ESG Reporting Accuracy, R-squared is 0.297, indicating that the model explains 29.7% of the variance in ESG reporting accuracy. It shows that it has a relatively low explanatory power, implying that there might be other aspects that might affect the ESG reporting accuracy, other than the variables that were taken into consideration in this research.

Table 5. Predictive relevance and quality assessment.

5. Discussion

The findings have shown that there is a robust optimistic correlation amid digital accounting tools (ERP systems, blockchain) and enhanced ESG reporting accuracy and corporate sustainability strategies among UK enterprises. These findings confirm the initial hypothesis (H1), which indicates that digital devices support the ESG reporting practices and sustainability initiatives. Path analysis proved that digital tools are instrumental in guaranteeing accurateness of the data on ESG and the strategies are properly implemented. Also, the regulatory environment was found to be one of the important moderators that support the application of digital tools for complying with the requirements of the strict frameworks, such as the Sustainability Disclosure Requirements of the UK and the Corporate Sustainability Reporting Directive (CSRD) of the EU.

With results showing a strong, positive relationship between the usage of digitally advanced tools, such as ERP systems and blockchain, and better ESG reporting practices, which also enhance corporate sustainability strategies of the business enterprises in the UK. The path analysis also produced high coefficients for Digital Accounting Tools and Corporate Sustainability Strategies, highlighting that the utilisation of digitally advanced tools has a substantial impact on the accuracy of ESG information and the effectiveness of sustainability strategy within corporations. These findings can be attributed to certain industrial and sectoral factors within the context of the UK commercial enterprises. To illustrate, in the UK, (FCA, 2023) states that the finance, energy, and manufacturing industry is faced with aggressive examination by regulators and stakeholders on matters of ESG performance.

In addition, (Furness, 2025) also echoed that the Sustainability Disclosure Requirements established by the UK Government had been consistent with the TCFD principles that require firms to use modern digital accounting software to ensure proper monitoring of emissions, social performance, and governance reporting. Therefore, companies that embraced the use of digital accounting instruments were positively affected in respect to their ESG reporting effectiveness and company sustainability initiatives.

These results also correlate with the Technology Acceptance Model (TAM), which interprets the adoption behaviour, suggesting that managers perceive the digital accounting instruments as very useful towards improving the compliance of ESG and sustainability reporting. Consequently, it is likely to lessen the reputation risk and permit the amalgamation of sustainability into the corporate strategies in the long-run. This ultimately results in the adoption of high-tech, digitally furnished accounting tools in UK companies.

These results are also aligned with the existing literature, such as research by (De Silva et al., 2025; and Taha & Alshurafat, 2025), indicating that the ESG reporting process can become efficient, transparent, and timely due to new technologies. Earlier literature has been inclined to confirm that the digital transformation in the corporate systems can bring a better result in the ESG reporting procedure; however, this study can provide novel evidence and demonstrate how these tools can directly affect the quality and accuracy of the ESG disclosures made by industries and their corporate sustainability strategies. This research paper provides an improved understanding of the ways digital accounting systems work in various organisational contexts and consequently enhances sectoral variation in ESG reporting by analysing various sectors, such as finance, energy, and manufacturing.

In terms of the second hypothesis H2 of the research that tests the moderating effect of digital accounting tools on the effects of digital accounting tools on ESG reporting and corporate sustainability strategies, the results showed that there is a significant effect. The above results in the UK context are an indication of how the external regulatory environment and pressure shape the introduction of digital accounting technology in the UK firms argued by (Ge, 2025) also. In line with the disclosures of (Gonzalez et al., 2025) in the highly controlled industries of services, energy, and utilities, businesses are faced with the stringent disclosure rules of the UK disclosure regulations and the principles of the Corporate Sustainability Reporting Directive (CSRD) of the EU. This complex regulatory environment enhances the perceived usefulness of digital accounting tools aligned with TAM theory, as accounts and finance managers perceive those tools as important for competitive legitimacy and regulatory compliance.

The environment of laws and regulations was significant regulator of the association amid initiatives of corporate sustainability and digital accounting solutions because the effects of solutions would be increased with higher regulations. Such results and findings are in accordance with present literature results and indicate the significance of the regulatory environment in the acceptance and implementation of corporate ESG practices (Krueger et al., 2024; Singhania et al., 2024). The research, however, being undertaken is not limited to general regulation compliance, like in the previous studies (Pack & Sami, 2025), but includes the strict regulatory market of the UK, as a special case study, with its complicated policies developing on how ESG disclosures, which are growing more sophisticated, are affecting the conduct of the companies.

Existing literature has emphasised the significance of enhancing and harmonising ESG reporting considerably less than it has focused on the importance of varying regulations across different regions in shaping the effectiveness of digital accounting practices in increasing the precision of reporting (Lodhia et al., 2025; Lukács & Molnár, 2025). It is depicted and evidenced by the study that regulatory stringency promotes the adoption of digital tools by demonstrating that the regulatory pressure urges the acceptance and implementation of digital tools, but also by fuelling the implementation of such tools to satisfy the increased demands of similar and transparent ESG disclosures.

Conclusion

The current study highlights the critical importance of digital accounting tools in enhancing the accuracy and reliability of ESG reporting in the business environment in the UK, as well as analysing the moderating effect of the regulatory environment. As revealed by the findings, the uptake of modern technologies like ERP and blockchain has become all the more crucial in the UK context as companies react to Sustainability Disclosure Requirements (SDR), compulsory TCFD-compliant reporting, as well as to an increasing level of investor scrutiny. The tools are found to increase transparency, comparability, and timeliness of ESG reports, and these tools have a direct link to more credible corporate sustainability planning. The results prove that the efficiency of such technologies is highly determined by the changing regulatory environment in the UK, as it not only enforces their use but also increases their influence in the realisation of the sustainability goals in key sectors of the economy, including finance, energy, and manufacturing.

Limitations

While the contribution of this research is priceless, some limitations must be mentioned. First, the study geographically takes place in the UK, and therefore, the results have the potential to limit the external validity of the study to other regions with different regulatory systems. The nature of the study using self-reported survey responses can cause bias, especially in the perceptions of the participants towards digital accounting tools. Although the research explores the role of online tools in ESG reporting, it cannot quantify the long-term sustainable impact of the tools and the industry-specific issues that need to be addressed in further research.

Policy Recommendations

The findings of the study lead to certain major policy recommendations.

Regulatory Standardisation: The UK regulators are advised to consider more standardized and more detailed policies of ESG reporting to improve the accuracy and consistency of ESG reporting. These policies will improve the current issues in ESG reporting by enhancing the use of digital accounting tools.

Government Incentives: The UK government ought to provide incentives, including tax reliefs and subsidies, to encourage the use of digital accounting tools, especially to SMEs. This would also assist businesses in enhancing their accuracy in reporting of ESG, and in line with the dynamic regulatory requirements.

International Cooperation: The international regulatory cooperation should be encouraged as a way of harmonising ESG standards in the international system. Through the development of international cooperation, UK firms will be in a more favourable position to adhere to global ESG requirements and homogeneous and transparent reporting standards in various markets.

Future Implications

Future studies must investigate the use of digital accounting tools in ESG reporting among the UK’s various industries to understand how these tools behave in other environments. More studies on the role of digital tools on the sustainability of the UK firms in the long term and their capacity to generate both environmental and social impacts would give a more in-depth insight into their possibilities. It would also focus on the research on the impact of different standards in the UK local and global regulations on the adaptation and efficiency of these solutions, providing a broader picture of how companies within various countries can successfully employ digital solutions in their ESG practices. Moreover, longitudinal analyses may look at the evolving effectiveness of digital bookkeeping technologies over time, particularly as regulatory frameworks continue to tighten and stakeholder pressures intensify.

AVAILABILITY OF DATA AND MATERIALS

The data will be made available on reasonable request by contacting the corresponding author.

Finding

None.

Conflict of interest

The authors declare no conflicts of interest.

Acknowledgements

Declared None.

Appendix

Survey Questionnaire

Section A: Demographic Profiles

1) Gender

• Male
• Female

2) Age

• 20 – 29 years
• 30 – 39 years
• 40 – 49 years
• 50 years and above

3) Industry/Organisation Type

• Finance
• Energy
• Manufacturing
• Technology

Section B: Digital Accounting Tools

Rate the following based on the 5-point scale as below.

1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree

Section C: ESG (Environmental, Social, Governance) Reporting Accuracy

Rate the following based on the 5-point scale as below.

1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree

Section D: Corporate Sustainability Strategies

Rate the following based on the 5-point scale as below.

1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree

Section E: Regulatory Environment

Rate the following based on the 5-point scale as below.

1 = Strongly Disagree, 2 = Disagree, 3 = Neutral,4 = Agree, 5 = Strongly Agree