This study is on investigation of the productivity of Nigerian Shipping Industry, a study of some selected companies. In addressing the specific objectives, four hypotheses were formulated. Data was sourced through primary sources and secondary sources. The collected data were analyzed using Data Envelopment Analysis Model, Principal Component Analysis (PCA), Production Frontier Model (Cobb Douglas Function, Data Envelopment Analysis (DEA) Model, Least Squares Regression–Based Estimation of Frontier. From the analysis Based on the significance of the p value at α = 0.05, the researcher reject the null hypothesis in favour of the alternative hypothesis. Therefore, the productivity of shipping companies was positively affected by capital input resources applied during the study period, in hypothesis two it is also significant at α = 0.05. Therefore, based on this result we again see a positive contribution of labour input with productivity in the case of these shipping companies. In hypothesis three the coefficient of port efficiency is 0.009 with a “t” statistic of 0.430. This is however not significant. The implication is that port efficiency or crane efficiency at the ports of call does not have a significant impact on the productivity of shipping companies and hypothesis four the result suggests that most shipping companies operating in Nigeria’s shipping industry should be encouraged to improve their overall efficiency which will accrue directly to shippers and indirectly to the national economy. The study therefore concludes by recommending that that most shipping companies operating in Nigeria’s shipping industry should be encouraged to improve their overall efficiency which will accrue shippers and indirectly to the national economy and many other recommendations.
This study is on investigation of the productivity of Nigerian Shipping Industry, a study of some selected companies. In addressing the specific objectives, four hypotheses were formulated. Data was sourced through primary sources and secondary sources. The collected data were analyzed using Data Envelopment Analysis Model, Principal Component Analysis (PCA), Production Frontier Model (Cobb Douglas Function, Data Envelopment Analysis (DEA) Model, Least Squares Regression–Based Estimation of Frontier. From the analysis Based on the significance of the p value at α = 0.05, the researcher reject the null hypothesis in favour of the alternative hypothesis. Therefore, the productivity of shipping companies was positively affected by capital input resources applied during the study period, in hypothesis two it is also significant at α = 0.05. Therefore, based on this result we again see a positive contribution of labour input with productivity in the case of these shipping companies. In hypothesis three the coefficient of port efficiency is 0.009 with a “t” statistic of 0.430. This is however not significant. The implication is that port efficiency or crane efficiency at the ports of call does not have a significant impact on the productivity of shipping companies and hypothesis four the result suggests that most shipping companies operating in Nigeria’s shipping industry should be encouraged to improve their overall efficiency which will accrue directly to shippers and indirectly to the national economy. The study therefore concludes by recommending that that most shipping companies operating in Nigeria’s shipping industry should be encouraged to improve their overall efficiency which will accrue shippers and indirectly to the national economy and many other recommendations.