IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i18p7297-d409541.html
   My bibliography  Save this article

Hub-Periphery Hierarchy in Bus Transportation Networks: Gini Coefficients and the Seoul Bus System

Author

Listed:
  • Chansoo Kim

    (AI Lab., Computational Science Center & ESRI, Korea Institute of Science and Technology, Seoul 02792, Korea
    Equal contributions.)

  • Segun Goh

    (Institut für Theoretische Physik II, Heinrich-Heine-Universität Düsseldorf, 40225 Düsseldorf, Germany
    Equal contributions.)

  • Myeong Seon Choi

    (Graduate School of Nanoscience and Technology, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea)

  • Keumsook Lee

    (Department of Geography, Sungshin Women’s University, Seoul 02844, Korea)

  • M. Y. Choi

    (Department of Physics and Astronomy and Center for Theoretical Physics, Seoul National University, Seoul 08826, Korea)

Abstract

Bus transportation networks are characteristically different from other mass transportation systems such as airline or subway networks, and thus the usual approach may not work properly. In this paper, to analyze the bus transportation network, we employ the Gini coefficient, which measures the disparity of weights of bus stops. Applied to the Seoul bus system specifically, the Gini coefficient allows us to classify nodes in the bus network into two distinct types: hub and peripheral nodes. We elucidate the structural properties of the two types in the years 2011 and 2013, and probe the evolution of each type over the two years. It is revealed that the hub type evolves according to the controlled growth process while the peripheral one, displaying a number of new constructions as well as sudden closings of bus stops, is not described by growth dynamics. The Gini coefficient thus provides a key mathematical criterion of decomposing the transportation network into a growing one and the other. It would also help policymakers to deal with the complexity of urban mobility and make more sustainable city planning.

Suggested Citation

  • Chansoo Kim & Segun Goh & Myeong Seon Choi & Keumsook Lee & M. Y. Choi, 2020. "Hub-Periphery Hierarchy in Bus Transportation Networks: Gini Coefficients and the Seoul Bus System," Sustainability, MDPI, vol. 12(18), pages 1-14, September.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7297-:d:409541
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/18/7297/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/18/7297/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lee, Keumsook & Jung, Woo-Sung & Park, Jong Soo & Choi, M.Y., 2008. "Statistical analysis of the Metropolitan Seoul Subway System: Network structure and passenger flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6231-6234.
    2. Lambert, Peter J & Aronson, J Richard, 1993. "Inequality Decomposition Analysis and the Gini Coefficient Revisited," Economic Journal, Royal Economic Society, vol. 103(420), pages 1221-1227, September.
    3. Farahani, Reza Zanjirani & Miandoabchi, Elnaz & Szeto, W.Y. & Rashidi, Hannaneh, 2013. "A review of urban transportation network design problems," European Journal of Operational Research, Elsevier, vol. 229(2), pages 281-302.
    4. Xingjian Liu & Ben Derudder & Kang Wu, 2016. "Measuring Polycentric Urban Development in China: An Intercity Transportation Network Perspective," Regional Studies, Taylor & Francis Journals, vol. 50(8), pages 1302-1315, August.
    5. Dorfman, Robert, 1979. "A Formula for the Gini Coefficient," The Review of Economics and Statistics, MIT Press, vol. 61(1), pages 146-149, February.
    6. Yang, Xu-Hua & Chen, Guang & Sun, Bao & Chen, Sheng-Yong & Wang, Wan-Liang, 2011. "Bus transport network model with ideal n-depth clique network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4660-4672.
    7. Hu, Yihong & Zhu, Daoli, 2009. "Empirical analysis of the worldwide maritime transportation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(10), pages 2061-2071.
    8. repec:ebl:ecbull:v:4:y:2003:i:7:p:1-6 is not listed on IDEAS
    9. Hugo Badia, 2020. "Comparison of Bus Network Structures in Face of Urban Dispersion for a Ring-Radial City," Networks and Spatial Economics, Springer, vol. 20(1), pages 233-271, March.
    10. Jeon, Christy Mihyeon & Amekudzi, Adjo A. & Guensler, Randall L., 2013. "Sustainability assessment at the transportation planning level: Performance measures and indexes," Transport Policy, Elsevier, vol. 25(C), pages 10-21.
    11. Chansoo Kim & Daniel S Kim & Kwangwon Ahn & M Y Choi, 2017. "Dynamics of analyst forecasts and emergence of complexity: Role of information disparity," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-18, May.
    12. Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(2), pages 186-199, June.
    13. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    14. Stéphane Mussard & Michel Terraza & Françoise Seyte, 2003. "Decomposition of Gini and the generalized entropy inequality measures," Economics Bulletin, AccessEcon, vol. 4(7), pages 1-6.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiawei Gui & Qunqi Wu, 2020. "Multiple Utility Analyses for Sustainable Public Transport Planning and Management: Evidence from GPS-Equipped Taxi Data in Haikou," Sustainability, MDPI, vol. 12(19), pages 1-46, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. I. Josa & A. Aguado, 2020. "Measuring Unidimensional Inequality: Practical Framework for the Choice of an Appropriate Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(2), pages 541-570, June.
    2. Rongrong Li & Xue-Ting Jiang, 2017. "Inequality of Carbon Intensity: Empirical Analysis of China 2000–2014," Sustainability, MDPI, vol. 9(5), pages 1-12, April.
    3. Khai X. Chiong & Hyungsik Roger Moon, 2017. "Estimation of Graphical Models using the $L_{1,2}$ Norm," Papers 1709.10038, arXiv.org, revised Oct 2017.
    4. Fagiolo, Giorgio & Santoni, Gianluca, 2015. "Human-mobility networks, country income, and labor productivity," Network Science, Cambridge University Press, vol. 3(3), pages 377-407, September.
    5. Stéphane Mussard & Françoise Seyte & Michel Terraza, 2006. "La décomposition de l’indicateur de Gini en sous-groupes : une revue de la littérature," Cahiers de recherche 06-11, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    6. Cats, Oded & Birch, Nigel, 2021. "Multi-modal network evolution in polycentric regions," Journal of Transport Geography, Elsevier, vol. 96(C).
    7. repec:ebl:ecbull:v:4:y:2003:i:29:p:1-12 is not listed on IDEAS
    8. Louis de Mesnard, 1997. "About the problems caused by the Gini and Kakwani index of inequality measurement [A propos des problèmes causés par les indices de mesure d'inégalité de Gini et de Kakwani]," Working Papers hal-01527267, HAL.
    9. Michele Giammatteo, 2007. "The bidimensional decomposition of inequality: A nested Theil approach," LIS Working papers 466, LIS Cross-National Data Center in Luxembourg.
    10. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    11. Lo Turco, Alessia & Maggioni, Daniela & Zazzaro, Alberto, 2019. "Financial dependence and growth: The role of input-output linkages," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 308-328.
    12. Anja Kukuvec & Harald Oberhofer, 2020. "The Propagation of Business Expectations within the European Union," CESifo Working Paper Series 8198, CESifo.
    13. Andrés César & Guillermo Falcone, 2020. "Heterogeneous Effects of Chinese Import Competition on Chilean Manufacturing Plants," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 1-60, December.
    14. Liu, Duan & Yu, Nizhou & Wan, Hong, 2022. "Does water rights trading affect corporate investment? The role of resource allocation and risk mitigation channels," Economic Modelling, Elsevier, vol. 117(C).
    15. Guo Chen & Amy K Glasmeier & Min Zhang & Yang Shao, 2016. "Urbanization and Income Inequality in Post-Reform China: A Causal Analysis Based on Time Series Data," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-16, July.
    16. Molnárová, Zuzana & Reiter, Michael, 2022. "Technology, demand, and productivity: What an industry model tells us about business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    17. Andrew Foerster & Andreas Hornstein & Pierre-Daniel Sarte & Mark W. Watson, 2019. "Aggregate Implications of Changing Sectoral Trends," NBER Working Papers 25867, National Bureau of Economic Research, Inc.
    18. Peydró, José-Luis & Jiménez, Gabriel & Kenan, Huremovic & Moral-Benito, Enrique & Vega-Redondo, Fernando, 2020. "Production and financial networks in interplay: Crisis evidence from supplier-customer and credit registers," CEPR Discussion Papers 15277, C.E.P.R. Discussion Papers.
    19. Xinghui Wang & Wenjing Geng & Ruidong Han & Qifa Xu, 2023. "Asymptotic Properties of the M-estimation for an AR(1) Process with a General Autoregressive Coefficient," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-23, March.
    20. Bahar, Dany & Rosenow, Samuel & Stein, Ernesto & Wagner, Rodrigo, 2019. "Export take-offs and acceleration: Unpacking cross-sector linkages in the evolution of comparative advantage," World Development, Elsevier, vol. 117(C), pages 48-60.
    21. MIZUNO Takayuki & SOUMA Wataru & WATANABE Tsutomu, 2015. "Buyer-Supplier Networks and Aggregate Volatility," Discussion papers 15056, Research Institute of Economy, Trade and Industry (RIETI).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7297-:d:409541. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.