Identifying the characteristics of China’s maritime trading partners on the basis of bilateral shipping connectivity: a cluster analysis

Abstract

China is ranked as the number one maritime connected country in the world. This study attempts to analyse the characteristics of its 155 maritime trading partners. Five components of maritime connectivity have been used for the analysis. A hierarchical clustering technique is applied to group the trading partners into distinct meaningful clusters. As China's main maritime competitors within the East Asian region, the analysis is also applied to Singapore and Hong Kong. The clustering technique produces three distinct clusters for China and Singapore and two for Hong Kong. The results reveal the importance of direct maritime connectivity, with China having the highest number of trading partners with zero transhipment (including its top 15 trading partners), compared to Singapore and Hong Kong. The analysis is further extended by applying ordered logistic regression. The results show that the logistic performance index (LPI) and exports/imports have a positive and significant influence on clusters. Conclusions are drawn as to the potential for implementing strategies and policy interventions on the basis of the emergent clusters, particularly the need for Hong Kong to improve all five components of maritime connectivity in order to compete with China and Singapore.

Maritime Bilateral Connectivity Analysis for Sustainable Maritime Growth: Case of Morocco

“…The third component is the level of competition for services connecting two countries, which is reflected in the number of maritime carriers providing a maritime connection between two countries. The competition is beneficial for shipping routes as it reduces costs and promotes innovation [32]. In addition, Wilmsmeier and Hoffman, 2006 [15], have proved in previous studies that the more links there are, the more intense is the competition [15].…”

“…A good logistics performance increases a country's integration into the international market. The logistic was a part of the contributions of several researchers; it has been demonstrated in the Chinese context that the LPI increases bilateral connectivity [32]. Another researcher affirmed that the logistics performance index (LPI) has a strong impact on trade costs compared to the maritime distance and that the effect is important, especially for bilateral trade in the south coast [17].…”

Spatiotemporal analysis of global grain trade multilayer networks considering topological clustering

“…Spatial scales are mainly divided into global, regional, and national scales, with the global scale studies analyzing trade flows between different countries and the impact of globalization on agriculture (Gutiérrez‐Moya et al., 2023; Lun et al., 2021; Niu et al., 2020), while the regional scale studies focus on trade relations within specific regions such as Europe or Asia and regional integration (Guan et al., 2022), while the national scale studies focus on individual countries' trade policies, market structures, and their role in global trade (Kulkarni et al., 2023). In terms of research methods, existing studies commonly employ complex network analyses (Hou et al., 2018; Wang et al., 2019; Yang et al., 2015), gravity models (Sartori et al., 2017; Zhou, 2011), clustering analyses (Baron et al., 2020; Saeed & Cullinane, 2023), and factor analyses (Zhang et al., 2019). However, these methods have limitations, complex network analysis and gravity models oversimplify the complexity of trade flows, neglecting regional topological relationships and diversity of data shapes, while clustering and factor analyses may oversimplify multidimensional trade data, thereby restricting a precise understanding of the actual relationships.…”

Framework for liner shipping connectivity data analytics and research

“…Information contained in shipping services will also include the number of vessels deployed, type of vessel, size of vessel, shipping lines involved and port of rotation (Yap and Ho, 2021). This information allows shipping connectivity to be determined, quantified and analysed using pairings between origin and destination ports or countries (Wang et al ., 2017; Saeed and Cullinane, 2021). Shipping connectivity can be differentiated into those operated as mainline or feeder services.…”

“…(2010) proposed that shipping connectivity must be viewed in the context of supply chain networks that extend beyond the maritime leg. Important determinants of port competitiveness and competition in relation to shipping connectivity also included influences exercised by transport infrastructure, location of consumption and production centres, efficiency of port operations, position of ports in trade flows, size of transhipment activities and investments in container terminals by shipping lines (Jiang et al ., 2015; Notteboom et al ., 2017; Saeed and Cullinane, 2021). The studies suggest the important role of shipping connectivity in affecting preference of users when determining port choice.…”