Port costs: Lower port charges whilst holding other factors constant lead to a more competitive position (Ishii, 2013; Yeo et al., 2011; Tongzon, 2009; Murphy et al., 1989; Slack, 1985). Lower costs achieve a higher level of port competitiveness (Yeo et al., 2011). Commonly, port costs including transport costs per container (PC1), port charges (PC3), and port service costs (PC4) are a significant factor for evaluating port competitiveness. Further, trans-shipment cost (PC2) is a critical element of the cost factor in managing mega port competitiveness because megacontainer ships imply transhipment markets with a feeder-and-hub relationship (Imai et al., 2013)

Service quality: Ports must meet port users’ needs or expectations. Service quality presents the overall quality of service provided to users in a port area (Tongzon, 1994), and good service quality increases the reputation of the port and reliability of its services, thereby strengthening a port’s competitiveness (Yeo et al., 2011; Cho et al., 2010). Further, port service quality positively affects customer satisfaction, loyalty, and referral intentions (Cho et al., 2010). Reliability of service performance (SQ1), shipment safety and security (SQ2), application of IT and EDI in operations (SQ3), quick response to port user’s needs (SQ4) and low congestion in a port (SQ5) are categorised into the construct of service quality in managing port competitiveness as a regional gateway

Fig. 2. Structure of port competitiveness among hub ports

Source: Author

4.2. Comparison among the target ports

The significance of the relative importance of each dimension is presented in relation to the overall competitiveness of target ports, based on the results of EFA in a two-step process. Firstly, to reflect the relative importance of sub-dimensions, the value of variance explained (%) was employed to assess the average absolute value of each factor (xi) (formula 1).

1st step: xi = (% of Variance) / (Total varience explained) * m           (1)

where m = Mean values of each dimension.

Thereafter, to calculate the overall competitiveness of each port, these were summed over all ports. The set of average absolute values was used to evaluate overall competitiveness (see Formula 2). Table 4 presents the results of the evaluation of competitiveness amongst the target ports.

2nd step:∑_(i=1)^n▒x=x_1+x_2⋯+x_n = Overall port competitiveness          (2)

Comparisons of the mean value of each dimension show that Shanghai has the highest value in availability (4.3), followed by efficiency (3.5), costs (3.5), and service quality (2.7). Hong Kong shows the highest value in efficiency (4.1) and service quality (4.2). In addition, Busan shows comparatively well distributed values in all dimensions (Model 1). Firstly we calculated overall competitiveness without considering the relative importance of each dimension. The results showed that Shanghai takes first place followed consecutively by Busan (2nd) and Hong Kong (3rd). However, by considering the relative importance of each dimension, the ranking in comparison was different between Busan and Hong Kong (Model 2). Results indicate that the ranking of competitiveness with multiple-determinants can reflect the relative importance of each dimension.

Table 4

Comparison amongst the target ports

Model 1* Model 2**

Shanghai Hong Kong Busan Shanghai Hong Kong Busan

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