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Influence of Urban Railway Network Centrality on Residential Property Values in Bangkok

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  • Varameth Vichiensan

    (Department of Civil Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand
    Center for Logistics Engineering Technology and Management, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand)

  • Vasinee Wasuntarasook

    (Graduate School, Kasetsart University, Bangkok 10900, Thailand)

  • Titipakorn Prakayaphun

    (Department of Constructional Engineering, Graduate School of Engineering, Chubu University, Kasugai 487-8501, Japan)

  • Masanobu Kii

    (Graduate School of Engineering, Osaka University, Osaka 565-0871, Japan)

  • Yoshitsugu Hayashi

    (Center for Sustainable Development and Global Smart City, Chubu University, Kasugai 487-8501, Japan)

Abstract

In recent decades, Bangkok has experienced substantial investments in its urban railway network, resulting in a profound transformation of the city’s landscape. This study examines the relationship between railway development and property value uplift, particularly focusing on network centrality, which is closely linked to urban structure. Our findings are based on two primary analyses: network centrality and spatial hedonic models. The network centrality analysis reveals that closeness centrality underscores the city’s prevailing monocentric structure, while the betweenness centrality measure envisions the potential emergence of urban subcenters. In our hedonic analysis of condominiums near railway stations, we formulated various regression models with different specifications, incorporating spatial effects and network centrality. With Bangkok’s predominant monocentric structure in mind, we found that the spatial regression model, including a spatial error specification and closeness centrality, outperforms the others. This suggests that the impact of railways on property values extends beyond station proximity and encompasses network centrality, intricately linked with the city’s urban structure. We applied our developed model to estimate the expected increase in property values at major interchange stations with high network centralities. These numerical values indicate a considerable potential for their evolution into urban subcenters. These insights offer valuable policy recommendations for effectively harnessing transit-related premiums and shaping the future development of both the railway system and the city.

Suggested Citation

  • Varameth Vichiensan & Vasinee Wasuntarasook & Titipakorn Prakayaphun & Masanobu Kii & Yoshitsugu Hayashi, 2023. "Influence of Urban Railway Network Centrality on Residential Property Values in Bangkok," Sustainability, MDPI, vol. 15(22), pages 1-25, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:22:p:16013-:d:1281646
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    1. Duy Q. Nguyen-Phuoc & William Young & Graham Currie & Chris Gruyter, 2020. "Traffic congestion relief associated with public transport: state-of-the-art," Public Transport, Springer, vol. 12(2), pages 455-481, June.
    2. Morikawa, So & Aoyama, Miwa & Kato, Hironori, 2023. "Development of railway station plazas: Impact on land prices of surrounding areas," Transport Policy, Elsevier, vol. 142(C), pages 1-14.
    3. Daquan Huang & Xiaoqing Yang & Zhen Liu & Xingshuo Zhao & Fanhao Kong, 2018. "The Dynamic Impacts of Employment Subcenters on Residential Land Price in Transitional China: An Examination of the Beijing Metropolitan Area," Sustainability, MDPI, vol. 10(4), pages 1-22, March.
    4. Sisman, S. & Aydinoglu, A.C., 2022. "A modelling approach with geographically weighted regression methods for determining geographic variation and influencing factors in housing price: A case in Istanbul," Land Use Policy, Elsevier, vol. 119(C).
    5. Chakrabarti, Sandip & Kushari, Triparnee & Mazumder, Taraknath, 2022. "Does transportation network centrality determine housing price?," Journal of Transport Geography, Elsevier, vol. 103(C).
    6. Sebastian Brandt & Wolfgang Maennig, 2012. "The impact of rail access on condominium prices in Hamburg," Transportation, Springer, vol. 39(5), pages 997-1017, September.
    7. Cats, Oded, 2017. "Topological evolution of a metropolitan rail transport network: The case of Stockholm," Journal of Transport Geography, Elsevier, vol. 62(C), pages 172-183.
    8. Zhang, Min, 2023. "Value uplift from transit investment-Property value or land value? A case study of the Gold Coast light rail system in Australia," Transport Policy, Elsevier, vol. 132(C), pages 88-98.
    9. Yuchen Zhou & Yuhong Tian & Chi Yung Jim & Xu Liu & Jingya Luan & Mengxuan Yan, 2022. "Effects of Public Transport Accessibility and Property Attributes on Housing Prices in Polycentric Beijing," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    10. Sheng Wei & Shuqing N Teng & Hui-Jia Li & Jiangang Xu & Haitao Ma & Xia-li Luan & Xuejiao Yang & Da Shen & Maosong Liu & Zheng Y X Huang & Chi Xu, 2019. "Hierarchical structure in the world’s largest high-speed rail network," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-11, February.
    11. Pagliara, Francesca & Papa, Enrica, 2011. "Urban rail systems investments: an analysis of the impacts on property values and residents’ location," Journal of Transport Geography, Elsevier, vol. 19(2), pages 200-211.
    12. Li, Zheng, 2018. "The impact of metro accessibility on residential property values: An empirical analysis," Research in Transportation Economics, Elsevier, vol. 70(C), pages 52-56.
    13. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
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