IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i19p5191-d269586.html
   My bibliography  Save this article

Spatial Correlation Network of Format in the Central Districts of a Megacity: The Case of Shanghai

Author

Listed:
  • Xinyu Hu

    (Department of Urban and Rural Planning, College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China)

  • Huiya Yang

    (Department of Urban and Rural Planning, College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China)

  • Junyan Yang

    (Department of Urban Planning, School of Architecture, Southeast University, Nanjing 210096, China)

  • Zhonghu Zhang

    (Department of Urban and Rural Planning, College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China)

Abstract

The format of different industries within a city is an essential part of a megacity’s development and reflects its central districts’ economic characteristics and development trends. This study takes two central districts in the megacity of Shanghai as its research object and explores the inter-spatial relationships among business format, as well as the mutual spatial relationships within the format network, using the quantitative and qualitative methods of case selection and spatial connectivity. Based on the degree of connectivity, the inter-related formats form a format model association network. Two related characteristics of a format type-related network are hierarchy and stability, and two levels are determined according to the importance of each format in the network: core dominant and non-core dominant. By exploring these relationships, the internal spatial correlation structure of format in the city center, and the hierarchy and systematization of each format, is explained. The results simultaneously contribute to the spatial planning of the central district and provide a valuable policy basis for urban planning managers.

Suggested Citation

  • Xinyu Hu & Huiya Yang & Junyan Yang & Zhonghu Zhang, 2019. "Spatial Correlation Network of Format in the Central Districts of a Megacity: The Case of Shanghai," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5191-:d:269586
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/19/5191/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/19/5191/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. B Hillier, 1999. "The Hidden Geometry of Deformed Grids: Or, Why Space Syntax Works, When it Looks as Though it Shouldn't," Environment and Planning B, , vol. 26(2), pages 169-191, April.
    2. Berman, Barry, 2019. "Flatlined: Combatting the death of retail stores," Business Horizons, Elsevier, vol. 62(1), pages 75-82.
    3. Cardinali, Maria Grazia & Bellini, Silvia, 2014. "Interformat competition in the grocery retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 21(4), pages 438-448.
    4. Xinyu Hu & Zhonghu Zhang & Junyan Yang, 2019. "Spatial Correlation of Formats in the Central Districts of a Megacity: The Case of Shanghai," Sustainability, MDPI, vol. 11(6), pages 1-12, March.
    5. Koschmann, Anthony & Isaac, Mathew S., 2018. "Retailer Categorization: How Store-Format Price Image Influences Expected Prices and Consumer Choices," Journal of Retailing, Elsevier, vol. 94(4), pages 364-379.
    6. Calvo-Porral, Cristina & Lévy-Mangin, Jean-Pierre, 2019. "Profiling shopping mall customers during hard times," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 238-246.
    7. Yoon, Heeyeun, 2018. "Interrelationships between retail clusters in different hierarchies, land value and property development: A panel VAR approach," Land Use Policy, Elsevier, vol. 78(C), pages 245-257.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cai, Ya-Jun & Lo, Chris K.Y., 2020. "Omni-channel management in the new retailing era: A systematic review and future research agenda," International Journal of Production Economics, Elsevier, vol. 229(C).
    2. Gilboa, Shaked & Mitchell, Vince, 2020. "The role of culture and purchasing power parity in shaping mall-shoppers’ profiles," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    3. Hänninen, Mikko & Paavola, Lauri, 2021. "Managing transformations in retail agglomerations:Case Itis shopping center," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    4. Maria Palazzo & Agostino Vollero & Alfonso Siano, 2016. "Identifying new segments from a global branding perspective: a three-country study," Journal of Marketing Analytics, Palgrave Macmillan, vol. 4(4), pages 159-171, December.
    5. Ali, Syed Mithun & Rahman, Md. Hafizur & Tumpa, Tasmia Jannat & Moghul Rifat, Abid Ali & Paul, Sanjoy Kumar, 2018. "Examining price and service competition among retailers in a supply chain under potential demand disruption," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 40-47.
    6. Pillai, Rajasshrie & Sivathanu, Brijesh & Dwivedi, Yogesh K., 2020. "Shopping intention at AI-powered automated retail stores (AIPARS)," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    7. Gilboa, Shaked & Vilnai-Yavetz, Iris & Mitchell, Vince & Borges, Adilson & Frimpong, Kwabena & Belhsen, Nourdine, 2020. "Mall experiences are not universal: The moderating roles of national culture and mall industry age," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    8. Han, Myat Su & Hampson, Daniel Peter & Wang, Yonggui & Wang, Hong, 2022. "Consumer confidence and green purchase intention: An application of the stimulus-organism-response model," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    9. Ameen, Nisreen & Tarhini, Ali & Shah, Mahmood Hussain & Nusair, Khaldoon, 2021. "A cross cultural study of gender differences in omnichannel retailing contexts," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    10. Dongjun Kim & Jinsung Yun & Kijung Kim & Seungil Lee, 2021. "A Comparative Study of the Robustness and Resilience of Retail Areas in Seoul, Korea before and after the COVID-19 Outbreak, Using Big Data," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
    11. Jaeger, Lena-Christin & Höhler Julia, 2020. "Using Word of Mouth Data from Social Media to Identify Asymmetric Competition in Food Retailing," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305609, German Association of Agricultural Economists (GEWISOLA).
    12. Pantano, Eleonora & Dennis, Charles & De Pietro, Michela, 2021. "Shopping centers revisited: The interplay between consumers’ spontaneous online communications and retail planning," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    13. Elshiewy, Ossama & Peschel, Anne O., 2022. "Internal reference price response across store formats," Journal of Retailing, Elsevier, vol. 98(3), pages 496-509.
    14. Terblanche, Nic S. & Kidd, Martin, 2021. "Exploring an in-store customer journey for customers shopping for outdoor apparel," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    15. Marcello Sansone & Roberto Bruni & Annarita Colamatteo & Maria Anna Pagnanelli, 2017. "Dynamic capabilities in retailers? marketing strategies: Defining an analysis model," MERCATI & COMPETITIVIT?, FrancoAngeli Editore, vol. 2017(2), pages 17-42.
    16. Shokouhyar, Sajjad & Shokoohyar, Sina & Safari, Sepehr, 2020. "Research on the influence of after-sales service quality factors on customer satisfaction," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    17. Rosenbaum, Mark S. & Edwards, Karen & Ramirez, Germán Contreras, 2021. "The benefits and pitfalls of contemporary pop-up shops," Business Horizons, Elsevier, vol. 64(1), pages 93-106.
    18. Li, Xi & Dahana, Wirawan Dony & Ye, Qiongwei & Peng, Luluo & Zhou, Jiaying, 2021. "How does shopping duration evolve and influence buying behavior? The role of marketing and shopping environment," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    19. Krey, Nina & Picot-Coupey, Karine & Cliquet, Gérard, 2022. "Shopping mall retailing: A bibliometric analysis and systematic assessment of Chebat's contributions," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    20. Stephan Zielke & Deonir Toni & José Afonso Mazzon, 2023. "Cognitive, emotional and inferential paths from price perception to buying intention in an integrated brand price image model," SN Business & Economics, Springer, vol. 3(1), pages 1-25, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5191-:d:269586. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.