| Literature DB >> 35087454 |
Hanxiao Wang1, Bei Liu2.
Abstract
One Road One Belt has made a drastic change not only to the lives of people but also to their minds and future prospective. This initiative has connected not only countries but has consolidated trading patterns. It has not only impacted physical trade but has also boosted the e-commerce of China. Therefore, this study has tried to find the major patterns of trading across the globe and digital commerce considering the factors of production. China, being the cheapest country for manufacturing, has excelled in the e-commerce as well. The targeted population for this study was contractors, marketers, logistic service providers, and engineers. The sample size in this study was 329. Data collection was done through a survey developed on the Likert scale. The software used for the data analysis was Smart-PLS for structural equation modeling. Findings of the study show that factors of production and international trade have an impact on e-commerce. Moreover, the foreign policy and international relations have also been found to have a significant role in e-commerce (digital entrepreneurship).Entities:
Keywords: OBOR (One Belt One Road); e-commerce; factors of production; foreign policy; international relations; international trade
Year: 2022 PMID: 35087454 PMCID: PMC8787324 DOI: 10.3389/fpsyg.2021.793383
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
FIGURE 1Conceptual model.
Demographic summary.
| Demographic summary | Frequency | % |
|
| ||
| Male | 245 | 74.18 |
| Female | 84 | 25.54 |
|
| ||
| <25 | 32 | 9.72 |
| 25–30 | 41 | 12.46 |
| 31–40 | 102 | 31.00 |
| 41–50 | 114 | 34.65 |
| 50> | 40 | 12.15 |
|
| ||
| Higher secondary | 69 | 20.97 |
| Bachelor | 98 | 29.78 |
| Masters | 80 | 24.31 |
| Doctorate | 40 | 12.15 |
| Others | 42 | 12.76 |
|
| ||
| Construction | 76 | 23.10 |
| Logistics | 85 | 25.83 |
| Marketing | 26 | 7.90 |
| Engineering | 142 | 43.16 |
N = 329.
Measurement model and descriptive statistics.
| Constructs | Code | FD | α | CR | AVE | M | SD |
|
| 0.930 | 0.943 | 0.673 | 0.769 | 0.773 | ||
| DE1 | 0.855 | ||||||
| DE2 | 0.827 | ||||||
| DE3 | 0.830 | ||||||
| DE4 | 0.824 | ||||||
| DE5 | 0.833 | ||||||
| DE6 | 0.778 | ||||||
| DE7 | 0.805 | ||||||
| DE8 | 0.808 | ||||||
|
| 0.873 | 0.898 | 0.595 | ||||
| FOP1 | 0.802 | ||||||
| FOP2 | 0.747 | ||||||
| FOP3 | 0.785 | ||||||
| FOP4 | 0.727 | ||||||
| FOP5 | 0.805 | ||||||
| FOP6 | 0.761 | ||||||
|
| 0.964 | 0.971 | 0.849 | 0.835 | 0.835 | ||
| FP1 | 0.897 | ||||||
| FP2 | 0.907 | ||||||
| FP3 | 0.878 | ||||||
| FP4 | 0.932 | ||||||
| FP5 | 0.937 | ||||||
| FP6 | 0.972 | ||||||
|
| 0.896 | 0.928 | 0.763 | 0.279 | 0.276 | ||
| IR1 | 0.886 | ||||||
| IR2 | 0.859 | ||||||
| IR3 | 0.876 | ||||||
| IR4 | 0.872 | ||||||
|
| 0.833 | 0.877 | 0.555 | 0.691 | 0.696 | ||
| IT1 | 0.753 | ||||||
| IT2 | 0.771 | ||||||
| IT3 | 0.470 | ||||||
| IT4 | 0.583 | ||||||
| IT5 | 0.908 | ||||||
| IT6 | 0.884 |
CR, Construct reliability; AVE, Average variance extracted; α, Cronbach alpha; M, Mean; SD, Standard deviation.
FIGURE 2PLS-algorithm for the measurement model.
Fornell and Larcker criterion.
| Variables | E-com | FOP | FP | IR | IT |
| E-com |
| ||||
| FOP | 0.533 |
| |||
| FP | 0.197 | 0.525 |
| ||
| IR | 0.813 | 0.494 | 0.249 |
| |
| IT | 0.809 | 0.622 | 0.457 | 0.756 |
|
E-com, E-commerce; FP, Foreign policy; IR, International relations; FOP, Factors of production; IT, International trade. Bold values indicate the relationship and significance of test.
HTMT ratio.
| Variables | E-com | FOP | FP | IR | IT |
| E-com | |||||
| FOP | 0.514 | ||||
| FP | 0.204 | 0.661 | |||
| IR | 0.887 | 0.493 | 0.265 | ||
| IT | 0.901 | 0.728 | 0.609 | 0.832 |
E-com, E-commerce; FP, Foreign policy; IR, International relations; FOP, Factors of production; IT, International trade.
FIGURE 3PLS-bootstrapping for the structural model.
Results for the structural model.
| Paths | H | O | M |
| T-Stats |
| Results | |
| FP - > IR | H1 | 0.249 | 0.248 | 0.065 | 3.837 | 0.000 | 0.062 | Supported |
| FP - > E-com | H2 | −0.230 | −0.226 | 0.032 | 7.167 | 0.000 | Not Supported | |
| FOP - > E-com | H3 | 0.076 | 0.076 | 0.038 | 1.971 | 0.025 | 0.836 | Supported |
| FOP - > IT | H4 | 0.622 | 0.624 | 0.041 | 15.004 | 0.000 | 0.387 | Supported |
| IR - > E-com | H5 | 0.327 | 0.329 | 0.039 | 8.312 | 0.000 | Supported | |
| IT - > E-com | H6 | 0.669 | 0.668 | 0.042 | 15.922 | 0.000 | Supported |
Significance level *** = 0.005%, ** = 0.05%. H, Hypothesis; O, Original sample; M, Sample mean; SD, Standard deviation; E-com, E-commerce; FP, Foreign policy; IR, International relations; FOP, Factors of production; IT, International trade.