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How to Measure the Impact of Walking Accessibility of Suburban Rail Station Catchment Areas on the Commercial Premium Benefits of Joint Development

Author

Listed:
  • Yuchen Qin

    (School of Architecture, Huaqiao University, Xiamen 361021, China
    These authors contributed equally to this work.)

  • Yikang Zhang

    (School of Architecture, Huaqiao University, Xiamen 361021, China
    These authors contributed equally to this work.)

  • Minfeng Yao

    (School of Architecture, Huaqiao University, Xiamen 361021, China)

  • Qiwei Chen

    (School of Architecture, Huaqiao University, Xiamen 361021, China)

Abstract

As the primary solution to the issue of high passenger traffic in urban areas, rail transit has a significant impact on the structural form of cities and regional development. Additionally, it has varying degrees of a premium effect on land value around stations. Current research on the factors influencing the premium effect of rail transit station areas mainly focuses on the macro level of the station area circle, with more attention given to the premium caused by distance and functional differences. Most research objects are typically urban center lines or stations. However, this study focuses on the core area of the station and concentrates on the impact of the construction of integrated station–city facilities on the choice of pedestrian routes and the enhancement of pedestrian accessibility. It also explores whether this enhancement is associated with the premium benefits of ancillary commercial development. To achieve this goal, this paper integrates models from several related studies to conduct a comprehensive assessment. Firstly, it uses a spatial panel econometric model to improve the classical characteristic price method model. It then combines the ideas and models of the cost–benefit analysis method, taking the Odakyu Odawara Line of the Japanese suburban railroad as an example. This analysis explores the mechanism and factors influencing the rent premium of commercial facilities in the suburban rail station area and systematically assesses the combined station–city facilities. The study evaluates the social benefits (enhanced walkability) and economic value (premium value added from commercial facilities) of the combined station–city facilities systematically. The results of the study show that (1) the premium benefits of suburban railroad station area commercial facilities are significantly related to the type of station–city combination facilities, combination mode, and walking time and weakly related to the location factor. Additionally, (2) the results of the cost–benefit valuation analysis based on the Ebina Station verify that a reasonable design of station–city combination facilities can effectively enhance the proximity of commercial facilities to the station and improve the walking accessibility, thus promoting the premium benefits. The study demonstrates that a reasonable design of the combined station and city facilities can effectively enhance the proximity of commercial facilities to the station and improve pedestrian accessibility, promoting premium benefits, which can quickly feed the construction cost of the station and achieve positive revenue in the short term. Therefore, the results of the study provide a quantitative reference for the planning and design of suburban stations.

Suggested Citation

  • Yuchen Qin & Yikang Zhang & Minfeng Yao & Qiwei Chen, 2023. "How to Measure the Impact of Walking Accessibility of Suburban Rail Station Catchment Areas on the Commercial Premium Benefits of Joint Development," Sustainability, MDPI, vol. 15(6), pages 1-29, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:4897-:d:1092630
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    1. Jungyeol Hong & Reuben Tamakloe & Soobeom Lee & Dongjoo Park, 2019. "Exploring the Topological Characteristics of Complex Public Transportation Networks: Focus on Variations in Both Single and Integrated Systems in the Seoul Metropolitan Area," Sustainability, MDPI, vol. 11(19), pages 1-26, September.
    2. Hao Wu & Hongzan Jiao & Yang Yu & Zhigang Li & Zhenghong Peng & Lingbo Liu & Zheng Zeng, 2018. "Influence Factors and Regression Model of Urban Housing Prices Based on Internet Open Access Data," Sustainability, MDPI, vol. 10(5), pages 1-17, May.
    3. Murat Celik, H. & Guldmann, Jean-Michel, 2007. "Spatial interaction modeling of interregional commodity flows," Socio-Economic Planning Sciences, Elsevier, vol. 41(2), pages 147-162, June.
    4. Paul K. Asabere & Barrie Harvey, 1985. "Factors Influencing the Value of Urban Land: Evidence from Halifax‐Dartmouth, Canada," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 13(4), pages 361-377, December.
    5. Qingchun Liu & Peixiong Zhao & Yan Xiao & Xin Zhou & Jun Yang, 2022. "Walking Accessibility to the Bus Stop: Does It Affect Residential Rents? The Case of Jinan, China," Land, MDPI, vol. 11(6), pages 1-17, June.
    6. John Matthews & Geoffrey Turnbull, 2007. "Neighborhood Street Layout and Property Value: The Interaction of Accessibility and Land Use Mix," The Journal of Real Estate Finance and Economics, Springer, vol. 35(2), pages 111-141, August.
    7. Haitao Yu & Hao Pang & Ming Zhang, 2018. "Value‐added effects of transit‐oriented development: The impact of urban rail on commercial property values with consideration of spatial heterogeneity," Papers in Regional Science, Wiley Blackwell, vol. 97(4), pages 1375-1396, November.
    8. Kim Dovey & Elek Pafka, 2017. "What is functional mix? An assemblage approach," Planning Theory & Practice, Taylor & Francis Journals, vol. 18(2), pages 249-267, April.
    9. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    10. Kyujin Lee & Woojin Kim & Junghan Baek & Junghwa Kim, 2021. "A Comparison into the Factors Affecting Urban Rail Systems: Local, Express, and High-Speed Rail in Tunnels at a Great Depth in a Metropolitan Area," Sustainability, MDPI, vol. 13(17), pages 1-15, August.
    11. Zhou, Zhengyi & Zhang, Anming, 2021. "High-speed rail and industrial developments: Evidence from house prices and city-level GDP in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 98-113.
    12. Rungpansa Noichan & Bart Dewancker, 2018. "Analysis of Accessibility in an Urban Mass Transit Node: A Case Study in a Bangkok Transit Station," Sustainability, MDPI, vol. 10(12), pages 1-26, December.
    13. Guibo Sun & Chris Webster & Xiaohu Zhang, 2021. "Connecting the city: A three-dimensional pedestrian network of Hong Kong," Environment and Planning B, , vol. 48(1), pages 60-75, January.
    14. Jin Kim & Ming Zhang, 2005. "Determining Transit’s Impact on Seoul Commercial Land Values: An Application of Spatial Econometrics," International Real Estate Review, Global Social Science Institute, vol. 8(1), pages 1-26.
    15. Sangwan Lee & Liming Wang, 2022. "Intermediate Effect of the COVID-19 Pandemic on Prices of Housing near Light Rail Transit: A Case Study of the Portland Metropolitan Area," Sustainability, MDPI, vol. 14(15), pages 1-17, July.
    16. 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.
    17. Zhong, Haotian & Li, Wei, 2016. "Rail transit investment and property values: An old tale retold," Transport Policy, Elsevier, vol. 51(C), pages 33-48.
    18. Balta-Ozkan, Nazmiye & Yildirim, Julide & Connor, Peter M., 2015. "Regional distribution of photovoltaic deployment in the UK and its determinants: A spatial econometric approach," Energy Economics, Elsevier, vol. 51(C), pages 417-429.
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