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Exploring the influencing factors on urban rail transit (URT) ridership is vital for travel demand estimation and urban resources planning. Among various existing ridership modeling methods, direct demand model with ordinary least square (OLS) multiple regression as a representative has considerable advantages over the traditional four-step model. Nevertheless, OLS multiple regression neglects spatial instability and spatial heterogeneity from the magnitude of the coefficients across the urban area. This paper aims to focus on modeling and analyzing the factors influencing metro ridership at the station level.

This paper constructs two novel direct demand models based on geographically weighted regression (GWR) for modeling influencing factors on metro ridership from a local perspective. One is GWR with globally implemented LASSO for feature selection, and the other one is geographically weighted LASSO (GWL) model, which is GWR with locally implemented LASSO for feature selection.

The results of real-world case study of Shenzhen Metro show that the two local models presented perform better than the traditional global model (OLS) in terms of estimation error of ridership and goodness-of-fit. Additionally, the GWL model results in a better fit than GWR with global LASSO model, indicating that the locally implemented LASSO is more effective for the accurate estimation of Shenzhen metro ridership than global LASSO does. Moreover, the information provided by both two local models regarding the spatial varied elasticities demonstrates the strong spatial interpretability of models and potentials in transport planning.

The main contributions are threefold: the approach is based on spatial models considering spatial autocorrelation of variables, which outperform the traditional global regression model – OLS – in terms of model fitting and spatial explanatory power. GWR with global feature selection using LASSO and GWL is compared through a real-world case study on Shenzhen Metro, that is, the difference between global feature selection and local feature selection is discussed. Network structures as a type of factors are quantified with the measurements in the field of complex network.

The Incheon Region has numerous assets that fall within a Pentaport model.' These include the Incheon International Airport, the Port of Incheon, a coastal industrial park, free economic zones, a leisure port, and Songdo new town designed to be the future Silicon Valley of Korea. This paper looks at how Northeast Asia trade flows between China and Korea might be enhanced by application of the Pentaport model in making the Incheon region a North East Asian Hub. It looks also at their trade and logistics systems as well as their water borne commerce. It proposes an integrated transportation system for the Yellow Sea Region being beneficial to the economies of the Northeast Asia. It also stresses that innovative technologies for ships, terminals and cargo handling systems should be introduced to develop a competitive short sea shipping system in the region and cooperation among the regional countries will be essential to achieve the final goal. The potential of methods of container shipping is discussed as it might apply to short sea shipping in the Yellow Sea Region that could greatly facilitate Incheon's situation with respect to the broader region in application of the Pentaport model.

In the 21^st Century, a region 's growth and prosperity will depend upon its intermodal transportation infrastructure and its ability to efficiently move goods, materials, and people within the system whether it be from origin to destination; from supplier to customer through the various levels of the supply-chain; or from point to point within the system. Planning for the future focuses on improving a region 's intermodal transportation system efficiencies and infrastructure, its connection to other economies, and on the development of logistics institutions and facilities.

With China 's rapidly developing economy and society, record numbers of new modern facilities such as airports, ports, highways, logistics parks and warehouses are being built. Along with this, companies have made extensive investments in information technologies and software to support the tremendous growth that has taken place in the logistics industry. The development and improvement of China's historic inland water transport system is essential to their continued future growth and prosperity. In Korea, past and present National Governments have emphasized the importance of developing a North East Asian Logistics and Business Hub in their region and have worked on strategies, which include water transport, as part of an important national agenda to that end.

This article looks at how trade flows in the Yangtze and Yellow Sea Regions and between China and South Korea might be enhanced by application of improved shipping methods in marine commerce that will promote economic growth in the region. The application of logistics practices and use of barges is explored for the movement of containers on inland and coastal waterways as well as in short sea shipping which could greatly facilitate the region 's situation with respect to future economic growth.