scholarly journals Modeling the Evolutionary Mechanism of China’s Domestic Air Transport Network

2020 ◽  
Vol 12 (16) ◽  
pp. 6295
Author(s):  
Shengrun Zhang ◽  
Yue Hu ◽  
Xiaowei Tang ◽  
Kurt Fuellhart ◽  
Liang Dai ◽  
...  
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Distance Effect ◽  
Transport Network ◽  
Rapid Expansion ◽  
Air Transport ◽  
High Speed Rail ◽  
Systematic Classification ◽  
Endogenous Variables ◽  
Endogenous Covariates

With the rapid expansion of China’s domestic air transport network (CATN), it is fundamental to model which factors and mechanisms impact this development. This paper investigates how the combined endogenous and exogenous factors influencing the evolution of CATN based on longitudinal data by utilizing a more all-encompassing methodology of stochastic actor based-modeling (SABM). Endogenous variables include a density effect, a betweenness effect, a transitivity closure effect, and a ‘number of distances-two’ effect. Exogenous variables incorporate airport hierarchy, a distance effect, presence or absence of low-cost carriers (LCCs) and high-speed rail (HSR). The systematic classification of Chinese airports into more than the typical two or three tiers allows the impacts of the four endogenous covariates to be revealed. Overall, the CATN has tended to evolve into a more compacted and non-concentrated network structure through the creation of non-stop routes and closed triads. The integrated inclusion of low-cost carrier and high-speed rail effects highlights the importance of market presence to the initiation of new routes at initial stages, cultivating potential demand and increasing accessibility. In addition, the construction of HSR to one primary airport within a multi-airport system can raise “shadow effects” for other airports. Our findings provide policy suggestions for airport operators in terms of developing accurate positions in the hierarchy and strengthening transfer ability.

scholarly journals Evolution and Determinants of an Air Transport Network: A Case Study of the Chinese Main Air Transport Network

2019 ◽  
Vol 11 (14) ◽  
pp. 3933 ◽  
Author(s):  
Min Su ◽  
Weixin Luan ◽  
Zeyang Li ◽  
Shulin Wan ◽  
Zhenchao Zhang
Keyword(s):  
Network Structure ◽  
High Speed ◽  
Information Source ◽  
Small World ◽  
Transport Network ◽  
Air Transport ◽  
Promoting Effect ◽  
High Speed Rail ◽  
Path Lengths ◽  
The Impact

The Chinese main air transport network (CMATN) is the framework for air passenger transport in the country. This study uses complex networks and an econometric model to analyze CMATN’s evolution and determinants. In terms of overall network structure, the network has always shown small-world properties, with smaller average path lengths (2.06–2.15) and larger clustering coefficients (0.68–0.77), while its cumulative degree distribution follows an exponential function. City passenger volumes conform to the degree power law function, which means that the more destinations a city connects to, the higher its passenger traffic will be. In major hub cities, such as Beijing, Shanghai, and Guangzhou, control power decreases, while Chengdu, Kunming, Chongqing, Xi’an, Urumqi, and other cities play an increasingly important role in CMATN. In terms of main route passenger volumes and formation, increases in GDP and tourism have had a promoting effect, while high-speed rail (HSR) poses a threat to overlapping routes. CMATN is primarily located in the central and eastern regions, focusing on China’s economy, tourism, and efficient HSR development. Although the competition from HSR affects the overall network structure of CMATN based on its influence on specific routes, we believe that the impact is limited due to the different transport attributes of the two networks. The research results of this study can become an information source for decision makers and provide a reference for air transport to seek sustainable development.

Struttura competitiva dopo la crisi Alitalia: il caso dela tratta Milano-Roma

2009 ◽  
pp. 167-178
Author(s):  
Giovanna Campopiano ◽  
Josip Kotlar ◽  
Andrea Salanti
Keyword(s):  
Price Competition ◽  
High Speed ◽  
Substantial Reduction ◽  
Air Travel ◽  
Air Transport ◽  
High Speed Rail ◽  
Passenger Traffic ◽  
Transport Services ◽  
Real Price

Air travel routes and high speed rail connection between Milan and Rome after the Alitalia crisis This paper analyses the first available data about changes in passenger traffic and air/rail fares after the Alitalia crisis and the substantial reduction of the travel time between Milan and Rome, due to the improvement of high speed rail on this connection. As recently happened in similar cases within Europe, the rail has gained a significant share of traffic previously attracted by air transport services. Apart from that, a real price competition is prevented by a number of inefficiencies which are mainly due to the monopolistic position of the new Alitalia on the route Milan Linate-Rome Fiumicino and problems of accessibility affecting our airports, and partly our rail stations too. The role of the various authorities potentially involved is burdened, in the last instance, by infrastructural deficiencies.

scholarly journals Effects of introducing low-cost high-speed rail on air-rail competition: Modelling and numerical analysis for Paris-Marseille

2020 ◽  
Vol 99 ◽  
pp. 145-162
Author(s):  
Yixiao Wang ◽  
Luoyi Sun ◽  
Ruud H. Teunter ◽  
Jianhong Wu ◽  
Guowei Hua
Keyword(s):  
Numerical Analysis ◽  
High Speed ◽  
Low Cost ◽  
High Speed Rail

scholarly journals A Regression Tree Approach for Investigating the Impact of High Speed Rail on Tourists’ Choices

2020 ◽  
Vol 12 (3) ◽  
pp. 910 ◽  
Author(s):  
Francesca Pagliara ◽  
Filomena Mauriello ◽  
Lucia Russo
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Decision Rules ◽  
Regression Tree ◽  
High Speed Rail ◽  
Explanatory Variables ◽  
Independent Variables ◽  
Italian Provinces ◽  
Tree Methods ◽  
The Impact

This paper provides a contribution to the international literature by applying regression tree methods to the analysis of the expected effects of the High Speed Rail project in Italy on the tourism market. This approach, as far as the author knows, has never been applied in this context. Tourism and transport information have been gathered for 99 Italian provinces during the 2006–2016 period. Tree-structured methods have been chosen as an application of regression models in which some explanatory variables are used as covariates to predict the dependent variable values on the basis of some decision rules. This approach establishes a casual effect between dependent and independent variables. The dependent variables chosen are the Italian and foreign tourists, and the number of overnights spent by Italians and foreigners. Among the independent variables are the presence of HSR, the presence of first-level airport hubs and the number of operating bases of low-cost airlines; among the attractiveness variables are the GDP, the number of attractions in a given province, the presence of the sea, the population and the percentage of unemployment. The main outcome of this study is that HSR affects the tourism market.

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