The Moderating Role of Finance, Accounting, and Digital Disruption in ESG, Financial Reporting, and Auditing: A Triple-Helix Perspective
Abstract
:1. Introduction
2. Literature Review and Hypothesis Development
2.1. Hypotheses Development
2.1.1. Direct Effects
2.1.2. Moderation Effects
3. Materials and Methods
3.1. Purpose of This Paper
3.2. Survey Instrument Development
- ✓
- Expert review: Five academics and five industry practitioners reviewed the questionnaire for content validity, clarity, and relevance.
- ✓
- Pilot study: A small sample of 20 respondents participated in a pilot test. Based on their feedback, minor adjustments were made to item wording to enhance clarity and ensure respondent comprehension.
3.3. Sampling Procedure and Sample Size Justification
3.4. Data Analysis
3.5. Data Collection
3.6. Development and Validation of Key Constructs
4. Results
5. Discussion
6. Conclusions
6.1. Practical Implications
6.2. Directions for Future Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Factors | Role | Interaction | Equation | Moderates | Outcome | Theories |
---|---|---|---|---|---|---|
Auditing and Sustainability (AS) Financial Reporting and ESG Integration (FRESGI) Finance, Accounting, and Digital Disruption (FADD) | IV DV Mod. | Interaction 1 Interaction 2 Interaction 3 Interaction 4 | (AS_1 × FADD_1) (AS_1 × FADD_2) (AS_2 × FADD_1) (AS_2 × FADD_2) | H3a, H3b H3c, H3d H3e, H3f H3g, H3h | FRESGI_2, FRESGI_1 FRESGI_2, FRESGI_1 FRESGI_2, FRESGI_1 FRESGI_2, FRESGI_1 | Triple-Helix Model of Innovation (Etzkowitz & Leydesdorff, 1995) Stakeholder Theory (Freeman, 1984) Legitimacy Theory-Suchman (1995) Agency Theory (Jensen & Meckling, 1976) Signaling Theory (Spence, 1973) Theory of Disruptive Innovation (Christensen, 1997) Institutional Theory (DiMaggio & Powell, 1983) |
Factor 1 Auditing and Sustainability (AS) | ||
Subfactor 1: Corporate Perspective (ASCP) | ||
Item | Constructs | Source |
AS1 | Auditing helps corporates implement fair labor policies and uphold decent work conditions. | Emblen-Perry (2019) Lulaj (2025b) Pumphrey and Crain (2008) Kukalaj et al. (2025) Lulaj et al. (2024b) Avdimetaj et al. (2025) Ruiz-Barbadillo and Martínez-Ferrero (2022) Lulaj et al. (2024a) Gao and Zhang (2006) |
AS2 | Strong internal auditing practices improve corporate governance, sustainability accountability, and risk management. | |
AS3 | The digital transformation of auditing (AI, blockchain, automation) enhances transparency, efficiency, and fraud detection. | |
AS4 | Independent auditing helps detect and prevent financial misstatements, fraud, and ESG violations. | |
AS5 | Ethical and sustainable auditing practices drive long-term economic growth and responsible business conduct. | |
Subfactor 2: Government and Academia Perspectives (ASGAP) | ||
AS6 | Government regulations play a critical role in ensuring ethical, transparent, and sustainable auditing practices. | |
AS7 | Auditing contributes to financial stability and reduces the risk of economic and labor market crises. | |
AS8 | Public sector audits strengthen fiscal accountability, ensuring effective use of resources for economic development. | |
AS9 | Auditing standards should evolve to integrate ESG (environmental, social, and governance) factors into financial oversight. | |
AS10 | Collaborations between corporates, the government, and academia advance research and innovation in sustainable auditing. | |
Factor 2 Financial Reporting and ESG Integration (FRESGI) | ||
Subfactor 1: Corporate Perspective (FRESGICP) | De Silva et al. (2025) N. M. Nguyen et al. (2025) Rani et al. (2025) Jamaludin et al. (2025) Liudmyla and Maria (2022) D’Aquila (1998) | |
FRESGI1 | Transparent financial reporting enhances investor confidence and supports sustainable economic growth. | |
FRESGI2 | Real-time and digital financial reporting systems improve decision-making and risk assessment. | |
FRESGI3 | Reliable and verifiable financial statements improve corporate creditworthiness and long-term financial stability. | |
FRESGI4 | Corporate fiscal transparency enhances responsible governance, risk management, and equitable economic policies. | |
FRESGI5 | The integration of sustainability metrics into financial reports supports long-term business profitability and economic resilience. | |
Subfactor 2: Government and Academia Perspectives (FRESGIGAP) | ||
FRESGI6 | ESG and sustainability disclosures should be mandatory for corporate reporting and investor decision-making. | |
FRESGI7 | International financial reporting standards (IFRS) improve global trade, cross-border investments, and sustainability compliance. | |
FRESGI8 | Third-party verification of financial and ESG reports enhances corporate credibility and stakeholder trust. | |
FRESGI9 | Effective financial reporting reduces economic inequality by promoting fair wages, job creation, and inclusive growth. | |
FRESGI10 | The use of AI and blockchain in financial reporting has increased accuracy, efficiency, and fraud prevention. | |
Factor 3 Finance, Accounting, and Digital Disruption (FADD) | ||
Subfactor 1: Corporate Perspective (FADDCP) | Lulaj et al. (2024c) Thakur et al. (2023) Zimand-Sheiner and Earon (2019) Lulaj (2021) Fauzel et al. (2024) Wawak et al. (2024) Ayalew and Zhang (2025) Alsughayer (2025) Hiew et al. (2025) Lulaj and Iseni (2018). Sutton (2010) Inder (2023) | |
FADD1 | Responsible financial management is essential for corporate sustainability, job security, and economic stability. | |
FADD2 | The adoption of fintech (AI, blockchain, digital banking) expands financial accessibility and promotes economic participation. | |
FADD3 | Corporate financial planning and responsible investment strategies drive sustainable national economic development. | |
FADD4 | Ethical financial decision-making supports fair employment, decent wages, and long-term job creation. | |
FADD5 | Investment in human capital strengthens financial stability, innovation, and sustainable business growth. | |
Subfactor 2: Government and Academia Perspectives (FADDGAP) | ||
FADD6 | Risk management strategies, including ESG risk assessment, are crucial for corporate resilience in uncertain economic environments. | |
FADD7 | Corporate financial policies and tax strategies influence employment, wages, and sustainable business growth. | |
FADD8 | Corporate financial regulations should align with sustainability goals, responsible investments, and green financing. | |
FADD9 | Access to financial education and digital literacy enhances workforce productivity and financial inclusion. | |
FADD10 | Accounting innovations, including automation and AI-driven analytics, improve corporate financial decision-making and sustainability reporting. |
Category | Variable | Freq. | % | |
---|---|---|---|---|
Gen. | G A C | Male | 100 | 50.0 |
Female | 78 | 39.0 | ||
Prefer not to answer | 22 | 11.0 | ||
Age | G A C | 18–25 years | 12 | 6.0 |
26–35 years | 65 | 32.5 | ||
36–45 years | 64 | 32.0 | ||
46–55 years | 36 | 18.0 | ||
Over 56 years | 23 | 11.5 | ||
Edu. | G A C | Bachelor’s degree | 76 | 38.0 |
Master’s degree | 91 | 45.5 | ||
PhD | 33 | 16.5 | ||
Pos. | G | Ministry Official (ME, MFLT) | 2 | 1.0 |
A | Academic Staff | 33 | 16.5 | |
C | Financial Manager | 27 | 13.5 | |
General Manager | 38 | 19.0 | ||
Accountant | 50 | 25.0 | ||
Business Owner | 21 | 10.5 | ||
Internal Auditor | 15 | 7.5 | ||
Director | 14 | 7.0 | ||
WE | G A C | 1–5 years | 10 | 5.0 |
6–10 years | 91 | 45.5 | ||
Over 10 years | 99 | 49.5 | ||
ES | G A C | Public | 33 | 16.5 |
Private | 167 | 83.5 | ||
DIAD | G A C | Yes | 195 | 97.5 |
No | 0 | 0.0 | ||
Don’t know | 5 | 2.5 | ||
CPFRS | G A C | Yes | 199 | 99.5 |
No | 0 | 0.0 | ||
Don’t know | 1 | 0.5 | ||
UATFMA | G A C | Yes | 191 | 95.5 |
No | 2 | 1.0 | ||
Don’t know | 7 | 3.5 |
Variable | Mean | Std. Dev. | Gen. | Age. | Edu. | Pos. | WE | ES | AS | FRESGI | FADD | DIAD | CPFRS | UATEMA |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Gen | 1.61 | 0.69 | 1 | |||||||||||
Age | 2.97 | 1.11 | −0.01 | 1 | ||||||||||
Edu | 2.79 | 0.71 | −0.06 | −0.10 | 1 | |||||||||
Pos. | 4.64 | 2.03 | −0.01 | 0.11 | 0.15 * | 1 | ||||||||
WE | 2.46 | 0.60 | −0.00 | −0.01 | −0.02 | 0.00 | 1 | |||||||
ES | 1.84 | 0.37 | 0.00 | −0.05 | −0.04 | 0.13 | −0.10 | 1 | ||||||
AS | 4.34 | 0.39 | −0.13 | −0.06 | 0.06 | 0.06 | −0.10 | 0.08 | 1 | |||||
FRESGI | 4.31 | 0.37 | −0.10 | −0.09 | 0.07 | 0.03 | −0.10 | 0.10 | 0.88 ** | 1 | ||||
FADD | 4.31 | 0.38 | −0.12 | −0.13 | 0.08 | 0.08 | −0.09 | 0.07 | 0.81 ** | 0.85 ** | 1 | |||
DIAD | 1.05 | 0.31 | −0.10 | 0.18 * | −0.04 | 0.06 | −0.01 | −0.01 | −0.00 | −0.03 | −0.02 | 1 | ||
CPFRS | 1.01 | 0.14 | 0.04 | 0.00 | 0.02 | −0.02 | −0.05 | −0.16 * | −0.11 | −0.06 | −0.06 | −0.01 | 1 | |
UATFMA | 1.08 | 0.38 | 0.04 | 0.07 | 0.12 | 0.04 | 0.11 | −0.05 | −0.18 * | −0.17 * | −0.19 ** | 0.05 | −0.02 | 1 |
Component Matrix | KMO | TVE | α | ||||
---|---|---|---|---|---|---|---|
Factors | Subfactors | AS | FADD | FRESGI | |||
AS_1 | AS1 | 0.99 | 0.74 | 0.88 | |||
AS2 | 0.80 | ||||||
AS3 | 0.78 | ||||||
AS4 | 0.73 | ||||||
AS5 | 0.79 | ||||||
AS_2 | AS6 | 0.73 | 0.79 | 54.67 | 0.79 | ||
AS7 | 0.73 | ||||||
AS8 | 0.74 | ||||||
AS9 | 0.67 | ||||||
AS10 | 0.81 | ||||||
FADD_1 | FADD1 | 0.73 | 0.79 | 53.04 | 0.78 | ||
FADD2 | 0.75 | ||||||
FADD3 | 0.73 | ||||||
FADD4 | 0.75 | ||||||
FADD5 | 0.68 | ||||||
FADD_2 | FADD6 | 0.73 | 0.79 | 56.68 | 0.81 | ||
FADD7 | 0.80 | ||||||
FADD8 | 0.70 | ||||||
FADD9 | 0.75 | ||||||
FADD10 | 0.78 | ||||||
FRESGI_1 | FRESGI1 | 0.79 | 0.76 | 52.10 | 0.77 | ||
FRESGI2 | 0.72 | ||||||
FRESGI3 | 0.75 | ||||||
FRESGI4 | 0.68 | ||||||
FRESGI5 | 0.66 | ||||||
FRESGI_2 | FRESGI6 | 0.79 | 0.80 | 55.29 | 0.80 | ||
FRESGI7 | 0.83 | ||||||
FRESGI8 | 0.76 | ||||||
FRESGI9 | 0.57 | ||||||
FRESGI10 | 0.75 |
Path | B | β | S.E. | C.R. | p-Value | Direct Effects | Significance Level |
---|---|---|---|---|---|---|---|
FADD → FRESGI | 0.401 | 0.401 | 0.050 | 7.958 | *** | 0.013 | Highly Significant (p < 0.001) |
AS → FRESGI | 0.553 | 0.553 | 0.050 | 10.970 | *** | 0.009 | Highly Significant (p < 0.001) |
Path | B | β | S.E. | C.R. | p-Value | Significance Level |
---|---|---|---|---|---|---|
FADD_2 → FRESGI_2 | 0.281 | 0.281 | 0.067 | 4.181 | *** | Highly Significant (p < 0.001) |
FADD_1 → FRESGI_2 | 0.143 | 0.143 | 0.071 | 2.025 | 0.043 | Significant (p < 0.05) |
AS_2 → FRESGI_2 | 0.296 | 0.296 | 0.070 | 4.242 | *** | Highly Significant (p < 0.001) |
AS_1 → FRESGI_2 | 0.252 | 0.252 | 0.066 | 3.822 | *** | Highly Significant (p < 0.001) |
Interaction1 → FRESGI_2 | 0.090 | 0.080 | 0.063 | 1.428 | 0.153 | Not Significant (p > 0.05) |
Interaction1 → FRESGI_1 | −0.016 | −0.014 | 0.058 | −0.276 | 0.783 | Not Significant (p > 0.05) |
Interaction2 → FRESGI_2 | −0.179 | −0.170 | 0.069 | −2.600 | 0.009 | Significant (p < 0.01) |
Interaction3 → FRESGI_2 | 0.015 | 0.015 | 0.057 | 0.257 | 0.797 | Not Significant (p > 0.05) |
Interaction4 → FRESGI_2 | 0.053 | 0.048 | 0.073 | 0.725 | 0.468 | Not Significant (p > 0.05) |
FADD_2 → FRESGI_1 | 0.246 | 0.246 | 0.062 | 3.979 | *** | Highly Significant (p < 0.001) |
FADD_1 → FRESGI_1 | 0.259 | 0.259 | 0.065 | 3.990 | *** | Highly Significant (p < 0.001) |
AS_2 → FRESGI_1 | 0.278 | 0.278 | 0.064 | 4.342 | *** | Highly Significant (p < 0.001) |
AS_1 → FRESGI_1 | 0.218 | 0.218 | 0.061 | 3.606 | *** | Highly Significant (p < 0.001) |
Interaction2 → FRESGI_1 | −0.125 | −0.118 | 0.063 | −1.970 | 0.049 | Significant (p < 0.05) |
Interaction3 → FRESGI_1 | −0.015 | −0.015 | 0.052 | −0.297 | 0.767 | Not Significant (p > 0.05) |
Interaction4 → FRESGI_1 | 0.119 | 0.108 | 0.067 | 1.779 | 0.075 | Not Significant (p > 0.05) |
Path | Estimate | Interpretation |
---|---|---|
AS_2 ↔ AS_1 | 0.766 | Strong positive correlation |
AS_1 ↔ FADD_1 | 0.686 | Strong positive correlation |
AS_1 ↔ FADD_2 | 0.703 | Strong positive correlation |
AS_1 ↔ Interaction1 | 0.296 | Moderate positive correlation |
AS_1 ↔ Interaction2 | 0.237 | Moderate positive correlation |
AS_1 ↔ Interaction3 | 0.249 | Moderate positive correlation |
AS_1 ↔ Interaction4 | 0.307 | Moderate positive correlation |
AS_2 ↔ FADD_1 | 0.790 | Very strong positive correlation |
AS_2 ↔ FADD_2 | 0.652 | Strong positive correlation |
AS_2 ↔ Interaction1 | 0.281 | Moderate positive correlation |
AS_2 ↔ Interaction2 | 0.295 | Moderate positive correlation |
AS_2 ↔ Interaction3 | 0.163 | Weak positive correlation |
AS_2 ↔ Interaction4 | 0.276 | Moderate positive correlation |
FADD_1 ↔ FADD_2 | 0.731 | Strong positive correlation |
FADD_1 ↔ Interaction1 | 0.394 | Moderate positive correlation |
FADD_1 ↔ Interaction2 | 0.410 | Moderate positive correlation |
FADD_1 ↔ Interaction3 | 0.123 | Weak positive correlation |
FADD_1 ↔ Interaction4 | 0.309 | Moderate positive correlation |
FADD_2 ↔ Interaction1 | 0.438 | Moderate positive correlation |
FADD_2 ↔ Interaction2 | 0.544 | Moderate to strong positive correlation |
FADD_2 ↔ Interaction3 | 0.282 | Moderate positive correlation |
FADD_2 ↔ Interaction4 | 0.498 | Moderate positive correlation |
Interaction1 ↔ Interaction2 | 0.655 | Strong positive correlation |
Interaction1 ↔ Interaction3 | 0.511 | Moderate to strong positive correlation |
Interaction1 ↔ Interaction4 | 0.520 | Moderate to strong positive correlation |
Interaction2 ↔ Interaction3 | 0.329 | Moderate positive correlation |
Interaction2 ↔ Interaction4 | 0.672 | Strong positive correlation |
Interaction3 ↔ Interaction4 | 0.664 | Strong positive correlation |
Variable | Estimate | S.E. | C.R. | p | Significance |
---|---|---|---|---|---|
AS_2 | 0.995 | 0.100 | 9.975 | *** | Significant |
AS_1 | 0.995 | 0.100 | 9.975 | *** | Significant |
FADD_1 | 0.995 | 0.100 | 9.975 | *** | Significant |
FADD_2 | 0.995 | 0.100 | 9.975 | *** | Significant |
Interaction1 | 0.781 | 0.078 | 9.975 | *** | Significant |
Interaction2 | 0.890 | 0.089 | 9.975 | *** | Significant |
Interaction3 | 0.991 | 0.099 | 9.975 | *** | Significant |
Interaction4 | 0.822 | 0.082 | 9.975 | *** | Significant |
Test | Value | Threshold | Interpretation |
---|---|---|---|
RMR | 0.007 | <0.05 | Good fit |
GFI | 0.992 | >0.90 | Excellent fit |
NFI | 0.995 | >0.90 | Excellent fit |
CFI | 0.995 | >0.90 | Excellent fit |
Hypothesis | Path | Supported/Not Supported | |
---|---|---|---|
Direct Effects | |||
H1 (Effect of FADD on FRESGI) | FADD → FRESGI | Supported (p = 0.013) | |
H1a | FADD_1 → FRESGI_2 | Supported (p = 0.043) | |
H1b | FADD_2 → FRESGI_2 | Supported (p < 0.001) | |
H1c | FADD_1 → FRESGI_1 | Supported (p < 0.001) | |
H1d | FADD_2 → FRESGI_1 | Supported (p < 0.001) | |
H2 (Effect of AS on FRESGI) | AS → FRESGI | Supported (p = 0.009) | |
H2a | AS_1 → FRESGI_2 | Supported (p < 0.001) | |
H2b | AS_2 → FRESGI_2 | Supported (p < 0.001) | |
H2c | AS_1 → FRESGI_1 | Supported (p < 0.001) | |
H2d | AS_2 → FRESGI_1 | Supported (p < 0.001) | |
Moderation Effects | |||
H3a | Interaction1 | (AS_1 × FADD_1) → FRESGI_2 | Not Supported (p = 0.153) |
H3b | (AS_1 × FADD_1) → FRESGI_1 | Not Supported (p = 0.783) | |
H3c | Interaction2 | (AS_1 × FADD_2) → FRESGI_2 | Supported (Negative Moderation) (p = 0.009) |
H3d | (AS_1 × FADD_2) → FRESGI_1 | Supported (Negative Moderation) (p = 0.049) | |
H3e | Interaction3 | (AS_2 × FADD_1) → FRESGI_2 | Not Supported (p = 0.797) |
H3f | (AS_2 × FADD_1) → FRESGI_1 | Not Supported (p = 0.767) | |
H3g | Interaction4 | (AS_2 × FADD_2) → FRESGI_2 | Not Supported (p = 0.468) |
H3h | (AS_2 × FADD_2) → FRESGI_1 | Not Supported (p = 0.075) |
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Lulaj, E.; Brajković, M. The Moderating Role of Finance, Accounting, and Digital Disruption in ESG, Financial Reporting, and Auditing: A Triple-Helix Perspective. J. Risk Financial Manag. 2025, 18, 245. https://doi.org/10.3390/jrfm18050245
Lulaj E, Brajković M. The Moderating Role of Finance, Accounting, and Digital Disruption in ESG, Financial Reporting, and Auditing: A Triple-Helix Perspective. Journal of Risk and Financial Management. 2025; 18(5):245. https://doi.org/10.3390/jrfm18050245
Chicago/Turabian StyleLulaj, Enkeleda, and Mileta Brajković. 2025. "The Moderating Role of Finance, Accounting, and Digital Disruption in ESG, Financial Reporting, and Auditing: A Triple-Helix Perspective" Journal of Risk and Financial Management 18, no. 5: 245. https://doi.org/10.3390/jrfm18050245
APA StyleLulaj, E., & Brajković, M. (2025). The Moderating Role of Finance, Accounting, and Digital Disruption in ESG, Financial Reporting, and Auditing: A Triple-Helix Perspective. Journal of Risk and Financial Management, 18(5), 245. https://doi.org/10.3390/jrfm18050245