The analysis of the efficient scores data in the excel sheet is as shown in the descriptive Table 1 below.
Table 1: Descriptive statistics.
The table shows the count, mean, minimum, maximum, and standard deviation values similar to those presented in the research. The results are presented in eight decimal places as compared to the published research’s four decimal places. The analysis of variance (ANOVA) of the significance of firms’ size on their efficiency scores in the dataset is shown in the Table 2 below.
Table 2: ANOVA.
The ANOVA results show a statistically significant effect of a firm’s size on its efficiency. The F value and p-value obtained F(3, 393) = 10.195, p = 0.000 were significant since the p-value was less than the significance level of 0.05. Since the ANOVA test shows a statistically significant difference between the groups, post-hoc analysis was conducted to investigate multiple comparisons between the groups. The post-hoc analysis based on the least-significant difference was conducted, and the results are as shown in Table 3 below.
Table 3: Multiple Comparisons.
The post-hoc analysis results from the analysis of the data are similar to the published research’s results. The results show significant means difference between small, medium, and large shipping firms. The p-values for comparing small, medium, and large shipping firms are all less than 0.05; implying statistically significant mean differences. The P-value of the efficiency mean differences between large firms and significantly large firms is 0.742 which is greater than 0.05. Therefore, the difference between large and significantly large shipping firms are not statistically significant.
The results in Table 1, Table 2, and Table 3 in published research used the Durbin Watson test of autocorrelation between market orientation and firm performance. The analysis in Table 1 showed a single market orientation factor with small statistical significance on firm performance from the test. The test researcher partially accepted the hypothesis which would have rather been rejected. The analysis in Table 2 showed; the firm size was statistically significant to its performance, confirmed by the ANOVA test showing the researcher’s results were correct. The analysis in Table 3 shows hierarchical regression analysis in testing firm size’s effect on market orientation.
The results showed significant p-values that led to the acceptance of the hypothesis. The researcher’s use of Durbin Watson’s tests for testing the hypothesis was effective for testing correlations since similar results were shown in the ANOVA test presented in Table 5 of the published research.