A connectivity-based methodology for new air route identification

被引:1
|
作者
Wong, Collin W. H. [1 ]
Cheung, Tommy King Yin [2 ]
Zhang, Anming [3 ]
机构
[1] Hang Seng Univ Hong Kong, Sch Decis Sci, Dept Supply Chain & Informat Management, Shatin, Hong Kong, Peoples R China
[2] Swinburne Univ Technol, Sch Engn, Dept Aviat, Hawthorn, Vic 3122, Australia
[3] Univ British Columbia, Sauder Sch Business, 2053 Main Mall, Vancouver, BC V6T 1Z2, Canada
关键词
Air Network Analysis; Route Prediction; Air Transport Demand Planning; Spatial Methodology; PASSENGER DEMAND; NETWORK; MODEL; TRANSPORTATION; DEREGULATION; AIRPORTS; GROWTH;
D O I
10.1016/j.tra.2023.103715
中图分类号
F [经济];
学科分类号
02 ;
摘要
The change of routes at an airport has a huge impact on airlines' revenue and city economy where the airport is located. Planning a successful route is a complicated decision-making process that involves considerations beyond the origin and destination. Past studies rarely consider how the addition of new routes or revision of existing routes affects the global aviation network and consequently impacts direct and transfer demands. A new data analytic approach is proposed to identify new and long-lasting routes and to assess connection quality from the global network perspective. It includes a comprehensive methodology for analysing the aviation network, evaluating potential route quality, deciding which routes warrant the selection, and estimating the long-and-short term traffic volume forecasts of the selected new routes. Seven attributes have been developed for route selection, covering growth, volume and connectivity-potential. Assessing connectivity potential permits the evaluation of the importance of a potential destination airport by considering the changes in competitive position that other airports connected to the same destination can expect when that new route is added to the network. This approach exploits the geographical relationships between airports and combines the network route supply data over a 9-year period to make assessment decisions on new destinations. A list of promising new destinations is created that can enhance the origin airport's connectivity-potential and improve the competitive advantage of airports. Managerial implications are also proposed for different aviation stakeholders to facilitate their strategic planning on airport facility and capacity expansion, airline competition, multi-airport region collaboration and air service agreements.
引用
收藏
页数:16
相关论文
共 50 条
  • [31] Author Correction: Connectivity-based parcellation of the amygdala and identification of its main white matter connections
    Josue M. Avecillas-Chasin
    Simon Levinson
    Taylor Kuhn
    Mahmoud Omidbeigi
    Jean-Philippe Langevin
    Nader Pouratian
    Ausaf Bari
    Scientific Reports, 13
  • [32] An iterative connectivity-based localization algorithm for sensor networks
    Xiang Mantian
    Shi Haoshan
    Li Lihong
    ICEMI 2007: PROCEEDINGS OF 2007 8TH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOL IV, 2007, : 81 - +
  • [33] CBPtools: a Python package for regional connectivity-based parcellation
    Niels Reuter
    Sarah Genon
    Shahrzad Kharabian Masouleh
    Felix Hoffstaedter
    Xiaojin Liu
    Tobias Kalenscher
    Simon B. Eickhoff
    Kaustubh R. Patil
    Brain Structure and Function, 2020, 225 : 1261 - 1275
  • [34] Functional connectivity-based parcellation of the human sensorimotor cortex
    Long, Xiangyu
    Goltz, Dominique
    Margulies, Daniel S.
    Nierhaus, Till
    Villringer, Arno
    EUROPEAN JOURNAL OF NEUROSCIENCE, 2014, 39 (08) : 1332 - 1342
  • [35] Connectivity-Based Brain Parcellation for Parkinson's Disease
    Li, Yu
    Liu, Aiping
    Li, Liangyong
    Wu, Yunhu
    McKeown, Martin J.
    Chen, Xun
    Wu, Feng
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2023, 70 (05) : 1539 - 1552
  • [36] From innovation to entrepreneurship: Connectivity-based regional development
    Adler, Patrick
    REGIONAL STUDIES, 2021, 55 (02) : 370 - 371
  • [37] Connectivity-Based Accessibility for Public Bicycle Sharing Systems
    Wang, Lei
    Li, Chanying
    Chen, Michael Z. Q.
    Wang, Qing-Guo
    Tao, Fei
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2018, 15 (04) : 1521 - 1532
  • [38] Local Connectivity-Based Density Estimation for Face Clustering
    Shin, Junho
    Lee, Hyo-Jun
    Kim, Hyunseop
    Baek, Jong-Hyeon
    Kim, Daehyun
    Koh, Yeong Jun
    2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2023, : 13621 - 13629
  • [39] A Connectivity-Based Popularity Prediction Approach for Social Networks
    Quan, Huangmao
    Milicic, Ana
    Vucetic, Slobodan
    Wu, Jie
    2012 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2012, : 2098 - 2102
  • [40] Connectivity-Based Optimal Scheduling for Maintenance of Bridge Networks
    Bocchini, Paolo
    Frangopol, Dan M.
    JOURNAL OF ENGINEERING MECHANICS-ASCE, 2013, 139 (06): : 760 - 769