Ports and Shipping
International shipping is an essential part of trade. Countries must have port infrastructure and capacity to allow companies to ship their products to consumers worldwide. Countries with good port infrastructure will attract foreign investment and enable local companies to produce and ship to international markets more efficiently. Read this overview of a study of 91 countries with seaports that examined seaborne trade's economic effects, and how port infrastructure quality and logistics capacity affected trade efficiency.
Empirical analysis and findings
Structural equation model
As the measurement model and reliability tests have confirmed validity and reliability, the structural equation model is proceeded. The parameter estimations, model fit indices, and the results of hypotheses proposed in Section 2.2 are presented and discussed.
The SEM, including estimated standardised factor loadings and regression coefficients, is presented Fig. 2, along with their respective paths. All 10 factors loadings are above the recommended level of 0.70 and are statistically significant. The structural model has a good fit with chi-square (χ2) of 73.78, and the ratio of χ2 and degrees of freedom (that is, 73.78/30 = 2.46 < 3) is within the required level recommended by Bollen and Long (1993). The Adjusted Goodness of Fit Index (AGFI) is 0.99, meaning the estimated model predicted 99% of the variances and co-variances in the observed data. Moreover, other fit index measures, such as CFI (0.98) and TLI (0.97), are well above the minimum requirements. Finally, the root mean-square error of approximation (RMSEA = 0.08), as well as the standardised root mean square residual (SRMR = 0.02), confirmed a good fit of the SEM.
Structural Equation Model.
*p < 0.05, **p < 0.01, ***p < 0.001;
Model –fit: χ2 (30) = 73.78, AGFI = 0.99, CFI = 0.98, TLI = 0.97, RMSEA = 0.08, SRMR = 0.02;
Note that the correlation curve between LPIEC and LPIQT represents correlation among their error terms.
After confirming the fitness of the proposed SEM, we estimated the hypothesised relationships between the latent constructs. The estimates of
the hypothesised relationships and their significance are presented in Table 4. Before establishing the mediation relationship among the variables (that is in H1d, H1e, H1f and H2c), the direct association between independent and
dependent variable as well as its association with the mediation variable was confirmed.
Table 4 Results of Structural Equation Modelling
| Hypotheses | Regression paths | Std. Estimates | S.E. | C.R. | Remarks |
|---|---|---|---|---|---|
| H1 (a) | QPI → LP | 0.66*** | 0.04 | 12.93 | Supported |
| H1 (b) | QPI → ST | −0.10 | 0.40 | −1.60 | Not supported |
| H1 (c) | QPI → NE | 0.17** | 0.25 | 2.80 | Supported |
| H1 (d) | QPI → LP → NE | 0.45*** | 0.20 | 9.31 | Supported |
| H1 (e) | QPI → ST → NE | 0.01 | 0.04 | 1.06 | Not supported |
| H1 (f) | QPI → LP → ST → NE | −0.04 | 0.10 | −1.83 | Not supported |
| H2 (a) | LP → ST | 0.66*** | 0.65 | 8.99 | Supported |
| H2 (b) | LP → NE | 0.67*** | 0.38 | 10.53 | Supported |
| H2 (c) | LP → ST → NE | −0.06 | 0.21 | −1.81 | Not supported |
| H3 | ST → NE | − 0.09 | 0.03 | − 1.95 | Not supported |
Std. Estimate standardized estimates, S.E. standard error, C.R. critical ratio
*p < 0.05, **p < 0.01, ***p < 0.001