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Small-world characteristics on transportation networks: a perspective from network autocorrelation

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  • Zengwang Xu
  • Daniel Sui

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  • Zengwang Xu & Daniel Sui, 2007. "Small-world characteristics on transportation networks: a perspective from network autocorrelation," Journal of Geographical Systems, Springer, vol. 9(2), pages 189-205, June.
    • Handle: RePEc:kap:jgeosy:v:9:y:2007:i:2:p:189-205
    DOI: 10.1007/s10109-007-0045-1
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    References listed on IDEAS

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    1. M. E. J. Newman & D. J. Watts, 1999. "Scaling and Percolation in the Small-World Network Model," Working Papers 99-05-034, Santa Fe Institute.
    2. repec:cor:louvrp:-2168 is not listed on IDEAS
    3. Réka Albert & Hawoong Jeong & Albert-László Barabási, 1999. "Diameter of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 130-131, September.
    4. Latora, Vito & Marchiori, Massimo, 2002. "Is the Boston subway a small-world network?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 109-113.
    5. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    6. PEETERS, Dominique & THOMAS, Isabelle, 2009. "Network autocorrelation," LIDAM Reprints CORE 2168, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. A K M Stoneham, 1977. "The Small-World Problem in a Spatial Context," Environment and Planning A, , vol. 9(2), pages 185-195, February.
    8. M. T. Gastner & M. E.J. Newman, 2006. "The spatial structure of networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 49(2), pages 247-252, January.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Patel Nilanchal & Mukherjee Alok Bhushan, 2015. "Assessment of network traffic congestion through Traffic Congestability Value (TCV): a new index," Bulletin of Geography. Socio-economic Series, Sciendo, vol. 30(30), pages 123-134, December.
    2. Richard Connors & David Watling, 2015. "Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation," Networks and Spatial Economics, Springer, vol. 15(2), pages 367-395, June.
    3. Juanjuan Luo & Teng Fei & Meng Tian & Yifei Liu & Meng Bian, 2023. "Sensitivity metrics of complex network based on co-occurrence truth table: exemplified by a high-speed rail network," Journal of Geographical Systems, Springer, vol. 25(4), pages 519-538, October.
    4. Yingying Xing & Jian Lu & Shengdi Chen & Sunanda Dissanayake, 2017. "Vulnerability analysis of urban rail transit based on complex network theory: a case study of Shanghai Metro," Public Transport, Springer, vol. 9(3), pages 501-525, October.
    5. Sun, Yeran & Mburu, Lucy & Wang, Shaohua, 2016. "Analysis of community properties and node properties to understand the structure of the bus transport network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 523-530.
    6. Tao Cheng & James Haworth & Jiaqiu Wang, 2012. "Spatio-temporal autocorrelation of road network data," Journal of Geographical Systems, Springer, vol. 14(4), pages 389-413, October.
    7. López, Fernando A. & Páez, Antonio & Carrasco, Juan A. & Ruminot, Natalia A., 2017. "Vulnerability of nodes under controlled network topology and flow autocorrelation conditions," Journal of Transport Geography, Elsevier, vol. 59(C), pages 77-87.
    8. Aldrich, Preston R. & El-Zabet, Jermeen & Hassan, Seerat & Briguglio, Joseph & Aliaj, Enela & Radcliffe, Maria & Mirza, Taha & Comar, Timothy & Nadolski, Jeremy & Huebner, Cynthia D., 2015. "Monte Carlo tests of small-world architecture for coarse-grained networks of the United States railroad and highway transportation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 32-39.

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    More about this item

    Keywords

    Small-world network; Network autocorrelation; Spatial autocorrelation; C51;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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