A new connectivity index for container portsJ o h n J B a r t h o l d i I I I a , P i s i t J a r u m a n e e r o j b a n d A m a r R a m u d h i n A b s t r a c t We propose a new index, the Container Port Connectivity Index, to measure the trade connectivity of ports within the network of container shipping. This index is based on both economics and network topology, and a distinctive feature is that the strength of a port is based on its position within the global structure of the shipping network, and not just on local information such as the number of TEUs handled, or direct links to other ports. Furthermore, the index produces separate scores for inbound and outbound container movements and in so doing it supports more detailed analyses. We explore the usefulness of the index by analyzing the global network of scheduled mainline container-shipping services as it existed in September 2011.Keywords: container port; shipping network; connectivityThe online version of this article is available Open Access M e a s u r i n g t h e C o n n e c t i v i t y o f C o n t a i n e r P o r t sWhat makes a container port important? From an operational point of view, it is connectivity: Are there convenient services to and from other important ports? Several measures borrowed from graph theory have been applied to measure connectivity, but these are typically based only weakly on economics.We suggest a new measure of importance with which to compare container ports, which we call the Container Port Connectivity Index (CPCI).

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The COVID-19 pandemic is found to be one of the external stimuli that greatly affects mobility of people, leading to a shift of transportation modes towards private individual ones. To properly explain the change in people’s transport behavior, especially in pre- and post- pandemic periods, a tensor-based framework is herein proposed and applied to Pun Pun–the only public bicycle-sharing system in Bangkok, Thailand–where multidimensional trip data of Pun Pun are decomposed into four different modes related to their spatial and temporal dimensions by a non-negative Tucker decomposition approach. According to our computational results, the first pandemic wave has a sizable influence not only on Pun Pun but also on other modes of transportation. Nonetheless, Pun Pun is relatively more resilient, as it recovers more quickly than other public transportation modes. In terms of trip patterns, we find that, prior to the pandemic, trips made during weekdays are dominated by business trips with two peak periods (morning and evening peaks), while those made during weekends are more related to leisure activities as they involve stations nearby a public park. However, after the first pandemic wave ends, the patterns of weekday trips have been drastically changed, as the number of business trips sharply drops, while that of educational trips connecting metro/subway stations with a major educational institute in the region significantly rises. These findings may be regarded as a reflection of the ever-changing transport behavior of people seeking a sustainable mode of private transport, with a more positive outlook on the use of bicycle-sharing system in Bangkok, Thailand.

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