摘要 :
This study develops a Connectivity Utility Model that can be used to assess the connectivity of an airport, a train station, a city or a region in multi-modal transport networks involving multiple quality dimensions of transport s...
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This study develops a Connectivity Utility Model that can be used to assess the connectivity of an airport, a train station, a city or a region in multi-modal transport networks involving multiple quality dimensions of transport services. This new connectivity measure considers both direct connections, and single- and multi-modal indirect connections. A novel feature of our model is the use of various radiation functions that not only help aggregate the overall connectivity of different transport modes' terminals in a city, but also capture their contribution to neighbouring cities' connectivity. This makes it possible to assess a region's or a country's overall transport connectivity. The methodology of this model is illustrated using the 2016 Chinese air and rail schedule data. The high concentration in transport services at large cities suggests that there exists a certain degree of inertia in the overall geography of China's transport infrastructure.
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This study proposes a series of statistical and regression approaches to investigate city-cluster transport connectivity patterns. Three major city clusters in China are selected for this study, namely, the Beijing-Tianjin-Hebei (...
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This study proposes a series of statistical and regression approaches to investigate city-cluster transport connectivity patterns. Three major city clusters in China are selected for this study, namely, the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) economic zones. Our analyses examine three aspects of city-cluster connectivity patterns: (i) connectivity distribution among cities within the city cluster; (ii) dependence of the non-center city on the center city; and (iii) the impact of improved intra-city-cluster rail con-nectivity on air-connectivity distribution. First, it is found that the BTH has the most con-centrated connectivity among the three city clusters, with Beijing clearly dominating the other cities in every kind of connectivity. The connectivity distributions are more balanced in the YRD and PRD. Second, the calculated "survival connectivity" and regression analyses suggest that non-center cities heavily rely on the center city as the hub to develop their network connectivity. Such a "hub-and-spoke system" helps a non-center city improve total connectivity but reduces its direct connectivity to other cities outside the city cluster. Finally, our regression analysis shows that improved intra-city-cluster rail connectivity further deteriorates the air-connectivity dis-parity within the city cluster, which occurs because the center city benefits more from the up-graded air-HSR (high speed rail) intermodal connectivity because it can attract air passengers from neighboring non-center cities. Relevant policy implications and suggestions are also dis-cussed in the paper. We believe the proposed statistical and regression approaches can be easily applied to examine city-cluster connectivity in other contexts and countries.
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This study calculates the connectivity of 69 Chinese airports and identifies the underlying drivers of the variation in airport connectivity over a period 2005-2016. Our connectivity model incorporates multiple discount factors in...
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This study calculates the connectivity of 69 Chinese airports and identifies the underlying drivers of the variation in airport connectivity over a period 2005-2016. Our connectivity model incorporates multiple discount factors including capacity and velocity penalties to correct for the quality of a connection. We find that Chinese airports experienced a great increase in air connectivity over the study period. Beijing Capital, Shanghai Pudong and Guangzhou Baiyun are far ahead of other airports in terms of overall connectivity and especially so in terms of international connectivity. However, the growth of some tourism cities and small cities has been stagnant and they suffered losses of connectivity at times. Airport competition measured by HHI, average fare, investment in local city's fixed asset investment and airport facilities, macroeconomic conditions, and population are found to be closely associated with an airport's connectivity. We also find that the presence of low-cost carriers is conducive for air connectivity, while HSR has the effect of decreasing airport connectivity. (C) 2017 Elsevier Ltd. All rights reserved.
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This paper proposes a dynamic weighted model to measure the connectivity of intercity passenger transportation in China. We consider both quality and quantity of the connections of two transport modes: air and rail. Among the 23 m...
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This paper proposes a dynamic weighted model to measure the connectivity of intercity passenger transportation in China. We consider both quality and quantity of the connections of two transport modes: air and rail. Among the 23 major cities selected, Shanghai is revealed to have the highest connectivity level, leading in both air and rail connectivity. Hong Kong, Kunming, and Urumqi are the three cities that predominantly rely on air transportation whose contribution to the connectivity exceeds 80%. This research also suggests that the connections between international cities and China's domestic network are highly concentrated on a few cities, namely, Hong Kong, Shanghai, Beijing, and Guangzhou, and that Seoul is the best connected international city in terms of its transport links with China. Shanghai-Nanjing has been found to be the best-connected city pair, primarily due to the significant contribution from high-speed rail (HSR) service. Our study shows that the contribution from train service is more than 80% for 19 of the 20 top-ranking domestic routes measured by connectivity. In addition, HSR has become a preferred and dominant option over air on a number of long-distance routes up to 1,300km. This finding has significant policy implications for transportation infrastructure planning and investment.
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This paper assesses air connectivity between China and Australia for the period 2005-16 using a Connectivity Utility Model. Our direct connectivity measure shows that as a gateway city, Sydney continues to play a key role in facil...
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This paper assesses air connectivity between China and Australia for the period 2005-16 using a Connectivity Utility Model. Our direct connectivity measure shows that as a gateway city, Sydney continues to play a key role in facilitating the movements of people and goods between China and Australia. Guangzhou has become the city best connected with Australia since 2011 as measured by direct connectivity. When indirect connections are considered, the largest increases in overall connectivity from 2005 to 2016 can be observed among Australia's major capital cities, particularly Sydney, Melbourne and Brisbane. Chinese carriers are the key drivers behind the increases. There have been rises and falls for airports serving as a hub between China and Australia. Guangzhou has forged its strong status as a transfer hub between Australia and China thanks to the quick expansion of China Southern. The gaps between Guangzhou and other transfer hubs measured by hub connectivity have widened since 2010.
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