| Literature DB >> 34899522 |
Tang Xianbin1, Wu Qiong1.
Abstract
The most powerful and crucial concept today is a sustainable digital economy. This research is aimed to investigate the predictors of a sustainable digital economy in China. In addition, the mediating roles of social reforms and economic policies were investigated between good governance and a sustainable digital economy. This cross-sectional research considered partial least square-structural equational modeling (PLS-SEM) as an analysis technique. The data were collected from 317 managerial staff of the e-commerce industry in China via a self-structured questionnaire. A random sampling technique was applied in the data collection process. Results showed that good governance positively impacts the sustainable digital economy, social reforms, and economic policies. Additionally, an increase in social reforms and economic policies led to a sustainable digital economy in China. Social reforms and economic policies partially mediated the relationship between good governance and a sustainable digital economy. This research contributes to the body of knowledge by identifying components of a sustainable digital economy and examining whether good governance may aid in attaining a sustainable digital economy. Nowadays, research on the sustainable digital economy has got attention from policymakers and researchers around the globe. These outcomes suggest several ways to improve the sustainable digital economy in China. This research is not without limitations, such as cross-sectional and based on responses of the respondents. Several research avenues were discussed and can be influenced by many factors for future perspectives.Entities:
Keywords: e-commerce; economic policies; good governance; social reforms; sustainable digital economy
Year: 2021 PMID: 34899522 PMCID: PMC8651544 DOI: 10.3389/fpsyg.2021.773022
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
FIGURE 1Conceptual model.
Demographics of the respondents.
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| Male | 160 | 50.5 |
| Female | 157 | 49.5 |
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| Bachelor and below | 48 | 15.1 |
| Masters | 178 | 56.2 |
| Doctorate | 54 | 17.0 |
| Professional Diploma | 37 | 11.7 |
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| 5 years and less | 43 | 13.6 |
| 6–10 years | 167 | 52.7 |
| 11–15 years | 61 | 19.2 |
| 15–20 years | 37 | 11.7 |
| 21 years and above | 9 | 2.8 |
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| CEO | 28 | 8.8 |
| Functional Manager | 150 | 47.3 |
| General Manager | 139 | 43.8 |
Measurement model and descriptive statistics.
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| Good governance | 0.91 | 0.933 | 0.735 | 3.843 | 1.020 | ||
| GG1 | 0.891 | ||||||
| GG2 | 0.847 | ||||||
| GG3 | 0.872 | ||||||
| GG4 | 0.813 | ||||||
| GG5 | 0.863 | ||||||
| Social reforms | 0.912 | 0.93 | 0.657 | 3.748 | 1.050 | ||
| SR1 | 0.817 | ||||||
| SR2 | 0.802 | ||||||
| SR3 | 0.845 | ||||||
| SR4 | 0.714 | ||||||
| SR5 | 0.877 | ||||||
| SR6 | 0.793 | ||||||
| SR7 | 0.818 | ||||||
| Economic policies | 0.891 | 0.92 | 0.699 | 3.92 | 1.084 | ||
| EP1 | 0.893 | ||||||
| EP2 | 0.83 | ||||||
| EP3 | 0.82 | ||||||
| EP4 | 0.752 | ||||||
| EP5 | 0.877 | ||||||
| Sustainable digital economy | 0.899 | 0.93 | 0.768 | 3.8855 | 1.091 | ||
| SDE1 | 0.879 | ||||||
| SDE2 | 0.879 | ||||||
| SDE3 | 0.865 | ||||||
| SDE4 | 0.882 | ||||||
FD, factor loadings; CR, construct reliability; AVE, average variance extracted; α, Cronbach alpha.
FIGURE 2Measurement model outcomes.
Fornell and Larcker criterion.
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| Economic policy |
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| Good governance | 0.812 |
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| Social reforms | 0.813 | 0.830 |
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| Sustainable digital economy | 0.823 | 0.777 | 0.779 |
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HTML ratio.
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| Economic policy | – | |||
| Good governance | 0.065 | – | ||
| Social reforms | 0.840 | 0.711 | – | |
| Sustainable digital economy | 0.693 | 0.827 | 0.824 | – |
FIGURE 3Structural model outcomes.
Direct and indirect effects.
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| H1 | GG → SR | 0.830 | 0.831 | 0.021 | 38.847 | 0.000 | Supported | 0.449 | 0.689 |
| H2 | GG → SDE | 0.146 | 0.145 | 0.071 | 2.069 | 0.019 | Supported | 0.584 | 0.766 |
| H3 | GG → EP | 0.812 | 0.813 | 0.021 | 38.719 | 0.000 | Supported | 0.457 | 0.659 |
| H4 | SR → SDE | 0.155 | 0.156 | 0.065 | 2.37 | 0.009 | Supported | ||
| H5 | EP → SDE | 0.618 | 0.619 | 0.067 | 9.226 | 0.000 | Supported | ||
| H6 | GG →SR → SDE | 0.502 | 0.503 | 0.059 | 8.577 | 0.000 | Supported | ||
| H7 | GG → EP → SDE | 0.129 | 0.13 | 0.055 | 2.362 | 0.009 | Supported |
O, original sample or beta coefficient; M, sample mean; STDEV, standard deviation; H., hypothesis.
FIGURE 4Predictive relevance of the model.