| Literature DB >> 35917071 |
Lijie Du1,2, Asif Razzaq3, Muhammad Waqas4.
Abstract
Small- and medium-sized enterprises (SMEs) in China have been hit hard by the coronavirus (COVID-19) outbreak, which has jeopardized their going out of business altogether. As a result, this research will shed light on the long-term impacts of COVID-19 lockdown on small businesses worldwide. The information was gathered through a survey questionnaire that 313 people completed. Analyzing the model was accomplished through the use of SEM in this investigation. Management and staff at SMEs worldwide provided the study's data sources. Research shows that COVID-19 has a significantly bad influence on profitability, operational, economic, and access to finance. In the study's findings, outside funding aids have played an important role in SMEs' skill to persist and succeed through technological novelty than in their real output. SME businesses, administrations, and policymakers need to understand the implications of this study's results.Entities:
Keywords: Access to finance; COVID-19; SME; Sustainable business practices; Technology innovation
Year: 2022 PMID: 35917071 PMCID: PMC9344445 DOI: 10.1007/s11356-022-22221-7
Source DB: PubMed Journal: Environ Sci Pollut Res Int ISSN: 0944-1344 Impact factor: 5.190
Fig. 1Flow diagram
Enterprise profile
| Characterization | Frequency | Percent | |
|---|---|---|---|
| SME size | 5–10 employees | 29 | 35.5 |
| 11–20 employees | 24.5 | 24.5 | |
| 21–50 employees | 36.5 | 29 | |
| 51–99 employees | 10 | 11 | |
| SME age | Less than 10 | 47 | 54 |
| 11 to less than 20 | 18 | 15 | |
| 21 to less than 30 | 22 | 8.7 | |
| 31 to less than 50 | 21 | 13.3 | |
| 51 and more | 12 | 9 | |
Fig. 2Path diagram
Respondent profile
| Item | Characterization | Frequency | Percent |
|---|---|---|---|
| Gender | Female | 218.4 | 32.655 |
| Male | 484.05 | 72.345 | |
| Employee type (domestic and global) | Local | 542.85 | 81.165 |
| Global | 159.6 | 23.835 | |
| Employees work in local or global companies | Domestic industry | 672 | 100.485 |
| Global companies | 30.45 | 4.515 | |
| Specialization | HRM department | 178.5 | 26.67 |
| Marketing department | 166.95 | 24.99 | |
| Bookkeeping/funding division/section | 137.55 | 20.58 | |
| Information technology department | 115.5 | 17.22 | |
| Cusomer care center | 78.75 | 11.76 | |
| Operations department | 25.2 | 3.78 | |
| Position level | Top level managers | 300.3 | 44.94 |
| Middle level managers | 139.65 | 20.895 | |
| Lower middle level management | 177.45 | 26.565 | |
| Lower level managers | 85.05 | 12.705 |
Measurement assessment results
| Variable | Item | Alpha | CR | AVE | Loadings |
|---|---|---|---|---|---|
| COVID-19 | COVID1 | 0.843 | 0.889 | 0.615 | 0.778 |
| COVID2 | 0.755 | ||||
| COVID3 | 0.812 | ||||
| COVID4 | 0.787 | ||||
| Green innovation | GIN1 | 0.877 | 0.907 | 0.620 | 0.787 |
| GIN2 | 0.769 | ||||
| GIN3 | 0.773 | ||||
| GIN4 | 0.821 | ||||
| Green marketing | GMK1 | 0.868 | 0.901 | 0.603 | 0.816 |
| GMK2 | 0.797 | ||||
| GMK3 | 0.744 | ||||
| GMK4 | 0.762 | ||||
| Green supply chain | GSCM1 | 0.879 | 0.906 | 0.581 | 0.750 |
| GSCM2 | 0.752 | ||||
| GSCM3 | 0.825 | ||||
| GSCM4 | 0.778 | ||||
| Green HRM | GHRM1 | 0.879 | 0.908 | 0.642 | 0.790 |
| GHRM2 | 0.747 | ||||
| GHRM3 | 0.757 | ||||
| GHRM4 | 0.804 | ||||
| GHRM5 | 0.796 | ||||
| Social awareness | SOCA1 | 0.866 | 0.903 | 0.651 | 0.785 |
| SOCA2 | 0.725 | ||||
| SOCA3 | 0.717 | ||||
| Environmental awareness | ENVA1 | 0.861 | 0.900 | 0.642 | 0.749 |
| ENVA2 | 0.822 | ||||
| ENVA3 | 0.799 | ||||
| ENVA4 | 0.818 | ||||
| Green manufacturing | GRNM1 | 0.828 | 0.879 | 0.593 | 0.806 |
| GRNM2 | 0.740 | ||||
| GRNM3 | 0.796 | ||||
| GRNM4 | 0.787 | ||||
| Green design | GRND1 | 0.860 | 0.898 | 0.618 | 0.842 |
| GRND2 | 0.827 | ||||
| GRND3 | 0.782 | ||||
| GRND4 | 0.780 | ||||
| GRND5 | 0.818 | ||||
| Recycling and remanufacturing | R&R1 | 0.868 | 0.901 | 0.603 | 0.810 |
| R&R2 | 0.811 | ||||
| R&R3 | 0.787 | ||||
| R&R4 | 0.792 | ||||
| Information technology | INFT1 | 0.879 | 0.906 | 0.581 | 0.769 |
| INFT2 | 0.809 | ||||
| INFT3 | 0.771 | ||||
| INFT4 | 0.707 | ||||
| Sustainable business practices | SBP1 | 0.879 | 0.908 | 0.642 | 0.769 |
| SBP2 | 0.809 | ||||
| SBP3 | 0.771 | ||||
| SBP4 | 0.707 |
Square roots of AVE and factor correlation coefficients
| COVID-19 | GIN | GRM | GSCM | GHRM | SOCA | ENVA | GRNM | GRND | R&R | INFT | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| COVID-19 | ||||||||||||
| GIN | 0.45 | |||||||||||
| GRM | 0.36 | 0.45 | ||||||||||
| GSCM | 0.38 | 0.39 | 0.48 | |||||||||
| GHRM | 0.25 | 0.31 | 0.36 | 0.39 | ||||||||
| SOCA | 0.22 | 0.36 | 0.35 | 0.36 | 0.32 | |||||||
| ENVA | 0.44 | 0.52 | 0.46 | 0.44 | 0.40 | 0.45 | ||||||
| GRNM | 0.39 | 0.42 | 0.47 | 0.46 | 0.51 | 0.39 | 0.63 | |||||
| GRND | 0.43 | 0.41 | 0.38 | 0.40 | 0.39 | 0.35 | 0.58 | 0.54 | ||||
| R&R | 0.46 | 0.38 | 0.37 | 0.40 | 0.41 | 0.45 | 0.55 | 0.56 | 0.54 | 0 | ||
| INFT | 0.39 | 0.42 | 0.40 | 0.41 | 0.41 | 0.47 | 0.61 | 0.61 | 0.62 | 0.78 | ||
The bold values in the diagonal line represent the square root of the average variance extracted
Hypothesis test results
| Hypothesis | Path | Result | |||
|---|---|---|---|---|---|
| H1 | COVID-19 → SBP | − 0.371*** | 6.57 | 0 | Support |
| H2 | Green innovation (GIN) → SBP | 0.125** | 2.15 | 0.032 | Support |
| H3 | Green marketing (GMK) → SBP | 0.267*** | 5.29 | 0.001 | Support |
| H4 | Green supply chain (GSCM) → SBP | 0.378*** | 4.72 | 0.001 | Support |
| H5 | Green HRM (GHRM) → SBP | 0.33** | 5.86 | 0.021 | Support |
| H6 | Social awareness → SBP | 0.506*** | 9.07 | 0.002 | Support |
| H7 | Environmental awareness → SBP | 0.175** | 2.98 | 0.001 | Support |
| H8 | Green manufacturing (GRNM) → SBP | 0.227 | 2.91 | 0.401 | Support |
| H9 | Green desing (GRND) → SBP | 0.117** | 1.85 | 0.035 | Reject |
| H10 | Recycling and remanufacturing (R&R) → SBP | 0.22* | 4.22 | 0.051 | Support |
| H11 | Information technology (INFT) → SBP | 0.373*** | 8.67 | 0.001 | Support |