Influence of Digital Accounting System Usage on SMEs Performance: The Moderating Effect of COVID-19
Abstract
:1. Introduction
2. Literature Review
3. Theoretical Understanding and Foundation
4. The Research Model and Hypotheses
4.1. Technological Factors and DAS Usage
4.2. Organizational Factors and DAS Usage
4.3. Environmental Factors and DAS Usage
4.4. DAS Usage and DAS Performance
4.5. Moderating Effect of COVID-19 on the Relationship between DAS Usage and DAS Performance
5. Methodology
6. Data Analysis
7. Results and Interpretation
7.1. Assessment of Measurement Model
7.2. Assessment of the Structural Model
7.2.1. Direct Relationship Model
7.2.2. Moderating Relationship Model
8. Discussion
9. Implications
10. Limitations and Recommendations for Future Studies
11. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Measurement Items | Source |
DAS Usage Our business use DAS Our business intends to use DAS in regular bases in the future. Our business would highly recommend DAS for others to adopt. | [23] |
Relative advantage DAS enables our business to appropriately manage supply chain risks. DAS enables our business to provide useful information to make decisions. DAS would enable our business to respond faster than competitors to changing environments. DAS would enable our business to reduce our operation cost. DAS would enable our business to reduce our operation time. | [47] |
Top Management Support Our top management promotes the use of DAS in the business. Our top management creates support for DAS initiatives within the business. Our top management promotes DAS as a strategic priority within the business. Our top Management is interested in the news about DAS adoption. Our top Management overcome the hurdles present due to natural resistance to technology usage. | [47] |
Organizational Readiness Lacking capital/financial resources has prevented my business from fully exploit BD. Lacking needed IT infrastructure has prevented my business from exploiting BD. Lacking analytics capability prevent the business fully exploit BD. Lacking skilled resources prevent the business fully exploit BD. | [23] |
Government Support The governmental policies encourage our business to adopt new ITs (e.g., BDA). The government provides incentives for adopting BD. Government procurements and contracts such as offering technical support, training, and funding for BD adoption. Standards or laws support adoption of BD technologies. Adequate legal protection supports BD technology adoption. There are some business laws to deal with the security and privacy concerns over the BD technologies. | [47] |
DAS Performance DAS is a processing system to generate information for decision managers. DAS minimize uncertainty in decision-making and improve the ability to plan and control activities. DAS supports our business growth in terms of sales, revenue and customers provide information to internal and external audiences. DAS improve user satisfaction, reduce errors, and improve information availability. DAS reduce costs reduce time, save human resources for businesses to use. DAS is a connection tool for management systems and operational systems. | [47] |
COVID-19 COVID-19 has had an adverse impact on our organization. COVID-19 has made daily work even more challenging. COVID-19 has added to concerns about their future development. COVID-19 has inspired our organization to take the initiative to expand business. COVID-19 has caused me to work longer hours. COVID-19 has made work more demanding. | [100] |
Compatibility Using DAS is compatible with our business culture. Using DAS is compatible with our business values. Using DAS is compatible with our preferred work practices. | [23] |
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Innovations | Innovations Impacts | Author (s) |
---|---|---|
ERP Adoption | ERP performance | [27] |
Mobile Business Use | M-Business Value | [57] |
E-commerce Usage | E-commerce impact | [58] |
AIS Implementation | Business Sustainability | [26] |
E-commerce usage | Business performance | [43] |
Big Data (BD) Adoption | BD Impact | [59] |
Internet usage | Procurement- process performance | [45] |
E-Business (EB) Usage | EB value | [56] |
AIS Usage | AIS Effectiveness | [47] |
Characteristic | Frequency | Percent | |
---|---|---|---|
Position | CEOs | 88 | 48.1% |
Senior managers | 49 | 26.8% | |
Managers | 47 | 25.1% | |
Experience | 3 years or less | 48 | 26.2% |
4–7 years | 42 | 22.9% | |
8–11 years | 49 | 26.8% | |
More than 11 | 44 | 24.1% | |
Gender | Male | 105 | 57.4% |
Female | 78 | 42.6% | |
Age | 20–29 years | 39 | 21.3% |
30–39 years | 46 | 25.1% | |
40–49 years | 66 | 36.1% | |
50 years and above | 32 | 17.5% | |
Education | Diploma or below | 29 | 15.8% |
Bachelor degree | 81 | 44.3% | |
Master’s degree | 59 | 32.2% | |
PhD | 14 | 7.6% | |
Number of Years Using DAS | 2 years or less | 72 | 39.3% |
3–5 years | 62 | 33.9% | |
6–8 years | 33 | 18.1% | |
More than 8 years | 16 | 8.7% |
Latent Construct | Item | Item Loading | Cronbach’s Alpha | Composite Reliability | AVE |
---|---|---|---|---|---|
>0.4 | >0.7 | >0.7 | >0.5 | ||
DAS Performance (DASP) | DASP1 | 0.873 | 0.837 | 0.879 | 0.553 |
DASP2 | 0.799 | ||||
DASP3 | 0.734 | ||||
DASP4 | 0.751 | ||||
DASP5 | 0.692 | ||||
DASP6 | 0.567 | ||||
DAS Use (DASU) | DASU1 | 0.647 | 0.719 | 0.826 | 0.545 |
DASU2 | 0.772 | ||||
DASU3 | 0.698 | ||||
DASU4 | 0.822 | ||||
Relative Advantage (RA) | RA1 | 0.503 | 0.836 | 0.874 | 0.541 |
RA2 | 0.707 | ||||
RA3 | 0.803 | ||||
RA4 | 0.796 | ||||
RA5 | 0.816 | ||||
RA6 | 0.741 | ||||
Compatibility (CO) | CO1 | 0.756 | 0.717 | 0.835 | 0.631 |
CO2 | 0.901 | ||||
CO3 | 0.713 | ||||
Top Management Support (TMS) | TMS 1 | 0.830 | 0.853 | 0.894 | 0.627 |
TMS 2 | 0.844 | ||||
TMS 3 | 0.842 | ||||
TMS 4 | 0.725 | ||||
TMS 5 | 0.709 | ||||
Organizational Readiness (OR) | OR1 | 0.653 | 0.849 | 0.893 | 0.628 |
OR2 | 0.836 | ||||
OR3 | 0.877 | ||||
OR4 | 0.853 | ||||
OR5 | 0.720 | ||||
COVID-19 (COV) | COV1 | 0.455 | 0.767 | 0.845 | 0.538 |
COV2 | 0.511 | ||||
COV4 | 0.801 | ||||
COV5 | 0.888 | ||||
COV6 | 0.889 | ||||
Government Support (GS) | GS1 | 0.719 | 0.810 | 0.866 | 0.523 |
GS2 | 0.605 | ||||
GS3 | 0.838 | ||||
GS4 | 0.825 | ||||
GS5 | 0.734 | ||||
GS6 | 0.576 |
DAS P | DAS U | Co | COV | RA | GS | TMS | OR | |
---|---|---|---|---|---|---|---|---|
DAS P | 0.743 | |||||||
DAS U | 0.383 | 0.738 | ||||||
Co | 0.451 | 0.347 | 0.794 | |||||
COV | 0.288 | 0.386 | 0.317 | 0.733 | ||||
R A | 0.261 | 0.371 | 0.211 | 0.305 | 0.828 | |||
G S | 0.146 | 0.160 | 0.196 | 0.025 | 0.128 | 0.723 | ||
TMS | 0.372 | 0.306 | 0.247 | 0.659 | 0.280 | 0.088 | 0.832 | |
O R | 0.086 | 0.277 | 0.165 | 0.425 | 0.603 | 0.061 | 0.293 | 0.793 |
Hypothesis No. | Relationship | Path Coefficient | T-Value | p-Value | Decision |
---|---|---|---|---|---|
H1 | RA → DAS U | 0.009 | 0.110 | 0.457 | Not Supported |
H2 | CO → DAS U | 0.194 | 2.588 | 0.013 ** | Supported |
H3 | TMS → DAS U | 0.095 | 1.450 | 0.088 * | Supported |
H4 | OR → DAS U | 0.127 | 1.816 | 0.049 ** | Supported |
H5 | GS → DAS U | 0.089 | 1.394 | 0.096 * | Supported |
H6 | DAS U → DAS P | 0.383 | 6.977 | 0.000 *** | Supported |
Hypothesis No. | Relationship | Path Coefficient | T-Value | p-Value | Decision |
---|---|---|---|---|---|
H9 | DASU * COVID-19 → DASP | 0.202 | 2.132 | 0.028 ** | Supported |
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Lutfi, A.; Alkelani, S.N.; Al-Khasawneh, M.A.; Alshira’h, A.F.; Alshirah, M.H.; Almaiah, M.A.; Alrawad, M.; Alsyouf, A.; Saad, M.; Ibrahim, N. Influence of Digital Accounting System Usage on SMEs Performance: The Moderating Effect of COVID-19. Sustainability 2022, 14, 15048. https://doi.org/10.3390/su142215048
Lutfi A, Alkelani SN, Al-Khasawneh MA, Alshira’h AF, Alshirah MH, Almaiah MA, Alrawad M, Alsyouf A, Saad M, Ibrahim N. Influence of Digital Accounting System Usage on SMEs Performance: The Moderating Effect of COVID-19. Sustainability. 2022; 14(22):15048. https://doi.org/10.3390/su142215048
Chicago/Turabian StyleLutfi, Abdalwali, Saleh Nafeth Alkelani, Malak Akif Al-Khasawneh, Ahmad Farhan Alshira’h, Malek Hamed Alshirah, Mohammed Amin Almaiah, Mahmaod Alrawad, Adi Alsyouf, Mohamed Saad, and Nahla Ibrahim. 2022. "Influence of Digital Accounting System Usage on SMEs Performance: The Moderating Effect of COVID-19" Sustainability 14, no. 22: 15048. https://doi.org/10.3390/su142215048
APA StyleLutfi, A., Alkelani, S. N., Al-Khasawneh, M. A., Alshira’h, A. F., Alshirah, M. H., Almaiah, M. A., Alrawad, M., Alsyouf, A., Saad, M., & Ibrahim, N. (2022). Influence of Digital Accounting System Usage on SMEs Performance: The Moderating Effect of COVID-19. Sustainability, 14(22), 15048. https://doi.org/10.3390/su142215048