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Café and Restaurant under My Home: Predicting Urban Commercialization through Machine Learning

Author

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  • Seung-Chul Noh

    (Department of Public Administration, Hanshin University, Osan 18101, Korea)

  • Jung-Ho Park

    (SURE Education Research Group, Department of Smart City, Chung-Ang University, Seoul 06974, Korea)

Abstract

The small commercial stores opening in housing structures in Seoul have been soaring since the beginning of this century. While commercialization generally increases urban vitality and achieves land use mix, cafés and restaurants in low-rise residential areas may attract numerous passenger populations, with increased noise and crimes, in the residential area. The urban commercialization is so fast and prevalent that neither urban researchers nor policymakers can respond to it timely without a practical prediction tool. Focusing on cafés and restaurants, we propose an XGBoost machine learning model that can predict commercial store openings in urban residential areas and further play the role of an early warning system. Our findings highlight a large degree of difference in the predictor importance between the variables used in our machine learning model. The most important predictor relates to land price, indicating that economic motivation leads to the conversion of urban housing to small cafés and restaurants. The Mapo neighborhood is predicted to be the most prone to the commercialization of urban housing, therefore, its urgency to be prepared against expected commercialization deserves underscoring. Overall, our results show that the machine learning approach can be applied to predict changes in land uses and contribute to timely policy designs in rapidly changing urban context.

Suggested Citation

  • Seung-Chul Noh & Jung-Ho Park, 2021. "Café and Restaurant under My Home: Predicting Urban Commercialization through Machine Learning," Sustainability, MDPI, vol. 13(10), pages 1-22, May.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5699-:d:557756
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    References listed on IDEAS

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    1. Jonathan Reades & Jordan De Souza & Phil Hubbard, 2019. "Understanding urban gentrification through machine learning," Urban Studies, Urban Studies Journal Limited, vol. 56(5), pages 922-942, April.
    2. Shin, Hyun Bang & Kim, Soo-Hyun, 2016. "The developmental state, speculative urbanisation and the politics of displacement in gentrifying Seoul," LSE Research Online Documents on Economics 60439, London School of Economics and Political Science, LSE Library.
    3. José Carpio-Pinedo & Manuel Benito-Moreno & Patxi J. Lamíquiz-Daudén, 2021. "Beyond land use mix, walkable trips. An approach based on parcel-level land use data and network analysis," Journal of Maps, Taylor & Francis Journals, vol. 17(1), pages 23-30, January.
    4. Benjamin Preis & Aarthi Janakiraman & Alex Bob & Justin Steil, 2021. "Mapping gentrification and displacement pressure: An exploration of four distinct methodologies," Urban Studies, Urban Studies Journal Limited, vol. 58(2), pages 405-424, February.
    5. Keunhyun Park & Reid Ewing & Sadegh Sabouri & Dong-ah Choi & Shima Hamidi & Guang Tian, 2020. "Guidelines for a Polycentric Region to Reduce Vehicle Use and Increase Walking and Transit Use," Journal of the American Planning Association, Taylor & Francis Journals, vol. 86(2), pages 236-249, April.
    6. Jose Carpio-Pinedo & Sonia De Gregorio Hurtado & Inés Sánchez De Madariaga, 2019. "Gender Mainstreaming in Urban Planning: The Potential of Geographic Information Systems and Open Data Sources," Planning Theory & Practice, Taylor & Francis Journals, vol. 20(2), pages 221-240, March.
    7. Sue Easton & Loretta Lees & Phil Hubbard & Nicholas Tate, 2020. "Measuring and mapping displacement: The problem of quantification in the battle against gentrification," Urban Studies, Urban Studies Journal Limited, vol. 57(2), pages 286-306, February.
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