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Research on Spatial Differentiation of Housing Prices Along the Rail Transit Lines in Qingdao City Based on Multi-Scale Geographically Weighted Regression (MGWR) Analysis

Author

Listed:
  • Yanjun Wang

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

  • Zixuan Liu

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

  • Yawen Wang

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

  • Peng Dai

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

Abstract

Urban sprawl and excessive reliance on motorization have led to many urban problems. The balance of supply and demand in the real estate market, as well as price fluctuations, also face many challenges. Urban rail transit not only alleviates traffic congestion and air pollution, but also significantly reduces residents’ commuting time, broadens urban accessibility, and reshapes the decision-making basis for residents when choosing residential locations. This study takes the 1st, 2nd, 3rd, 4th, 8th, 11th, and 13th metro lines that have been opened in Qingdao City as examples. It selects 12,924 residential samples within a 2 km radius along the rail transit lines. By using GIS spatial analysis tools and the multi-scale geographically weighted regression (MGWR) model, it analyzes the spatial differentiation characteristics of housing prices along the rail transit lines and the reasons and mechanisms behind them. The empirical results show that housing prices decrease to varying degrees with the increase in the distance from the rail transit. For every additional 1 km from the rail transit station, the housing price increases by 0.246%. Through model comparison, it was found that MGWR has a better fitting degree than the traditional ordinary least squares method (OLS) and the previous geographically weighted regression model (GWR), and reveals the spatial heterogeneity of the influence of urban rail transit on housing prices. Different indicator elements have different effects on housing prices along these lines. The urban rail transit factor in the location characteristics has a positive impact on housing prices, and has a significant negative correlation in some areas. The significant influence range of the distance to the nearest metro station on housing prices is concentrated within a radius of 373 m, and the effect decays beyond this range. The total floors, building area, green coverage rate, property management fee, and the distance to hospitals and parks in the neighborhood and structural characteristics have spatial heterogeneity. Analyzing the areas affected by the urban rail transit factor, it was found that the double location superposition effect, the networked transportation system, and the agglomeration of urban functional axes are important reasons for the significant phenomena in some local areas. This research provides a scientific basis for optimizing the sustainable development of rail transit in Qingdao and formulating differentiated housing policies. Meanwhile, it expands the application of the MGWR model in sustainable urban spatial governance and has practical significance for other cities to achieve sustainable urban development.

Suggested Citation

  • Yanjun Wang & Zixuan Liu & Yawen Wang & Peng Dai, 2025. "Research on Spatial Differentiation of Housing Prices Along the Rail Transit Lines in Qingdao City Based on Multi-Scale Geographically Weighted Regression (MGWR) Analysis," Sustainability, MDPI, vol. 17(9), pages 1-21, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:9:p:4203-:d:1650298
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    1. repec:eme:jpvi00:14635789810212913 is not listed on IDEAS
    2. repec:osf:socarx:95zsc_v1 is not listed on IDEAS
    3. Insu Hong & Changsok Yoo, 2020. "Analyzing Spatial Variance of Airbnb Pricing Determinants Using Multiscale GWR Approach," Sustainability, MDPI, vol. 12(11), pages 1-18, June.
    4. Torill Nyseth & Abdelillah Hamdouch, 2019. "The Transformative Power of Social Innovation in Urban Planning and Local Development," Urban Planning, Cogitatio Press, vol. 4(1), pages 1-6.
    5. Welch, Timothy F. & Gehrke, Steven R. & Wang, Fangru, 2016. "Long-term impact of network access to bike facilities and public transit stations on housing sales prices in Portland, Oregon," Journal of Transport Geography, Elsevier, vol. 54(C), pages 264-272.
    6. Wagner, Gary A. & Komarek, Timothy & Martin, Julia, 2017. "Is the light rail “Tide” lifting property values? Evidence from Hampton Roads, VA," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 25-37.
    7. Qisheng Pan, 2013. "The impacts of an urban light rail system on residential property values: a case study of the Houston METRORail transit line," Transportation Planning and Technology, Taylor & Francis Journals, vol. 36(2), pages 145-169, April.
    8. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    9. Jin Rui & Frank Othengrafen, 2023. "Examining the Role of Innovative Streets in Enhancing Urban Mobility and Livability for Sustainable Urban Transition: A Review," Sustainability, MDPI, vol. 15(7), pages 1-21, March.
    10. Daniel P. McMillen, 2004. "Geographically Weighted Regression: The Analysis of Spatially Varying Relationships," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 554-556.
    11. Le Galès, Patrick & Vitale, Tommaso Prof, 2013. "Governing the large metropolis. A research agenda," SocArXiv 95zsc, Center for Open Science.
    12. Landis, John & Guhathakurta, Subhrajit & Huang, William & Zhang, Ming, 1995. "Rail Transit Investments, Real Estate Values, and Land Use Change: A Comparative Analysis of Five California Rail Transit Systems," University of California Transportation Center, Working Papers qt2hf9s9sr, University of California Transportation Center.
    13. 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.
    14. Torill Nyseth & Abdelillah Hamdouch, 2019. "The Transformative Power of Social Innovation in Urban Planning and Local Development," Urban Planning, Cogitatio Press, vol. 4(1), pages 1-6.
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