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The objective of this paper is to simultaneously analyse the complex relationships between bilateral maritime connectivity, bilateral trade and domestic production as measured by gross domestic product (GDP) per capita. This is achieved by applying non-recursive models and Path Analysis (PA). The top ten best maritime connected countries and their 155 trading partners are selected for the analysis. The components of maritime connectivity, maritime distance, and gravity variables are selected as instrumental variables to analyse the reciprocal relationship between export/import of ten countries and the GDP per capita of their 155 trading partners. The results confirm the reciprocal relationship between export values (that are the import values of trading partners) and GDP per capita, whereas a reciprocal relationship between import values (that are the export values of trading partners) and GDP per capita does not exist. The results also confirm the complexity of the relationships between maritime connectivity, trade and economic growth and that, compared to components of maritime connectivity, none of the gravity variables have a positive impact on bilateral trade. The results suggest that economic policy and trade policy at the global, regional, and national level should recognize the need for, and foster, better maritime connectivity.

This paper presents the results of an empirical study conducted by distributing questionnaires to shipping agents working for foreign principals in Karachi, Pakistan. In Part A of the questionnaire, respondents gave a score reflecting the importance of 13 factors affecting terminal selection. Their responses indicate that service quality, loading/discharging rate and handling charges are the most important selection factors. A linear model is developed in which the dependent variable is total stay (in hours). The independent variables are vessel type, vessel size, total TEUs (twenty-foot equivalent units), vessel frequency and past visits of the shipping line. All the coefficients are significant. In the second section (that is, Part B of the questionnaire), respondents gave scores reflecting the quality of different attributes and how they affect the attractiveness of four specific container terminals. One-way ANOVA was used to test whether respondents have significant opinion differences. The result indicated that respondents do differ in opinions. Moreover, factor analysis of the aggregate data produced two factors with strong loading of six attributes in one factor and two attributes in the second. Maritime Economics & Logistics (2009) 11, 270–288. doi:10.1057/mel.2009.8