Shopping Centre Spatial Complexity, Management Efficiency and Tenant Mix Variety
Tony ShunTe Yuo,
Yu-Cheng Lin,
Jou-Hsuan Wu and
Kuan-Yu Huang
ERES from European Real Estate Society (ERES)
Abstract:
Spatial complexity is not only one of the crucial sources of wayfinding problem within a shopping facility; it is also a significant determinant for space usage efficiency. The distribution of total floor area for a shopping mall is basically finding the optimum solution for tenant location/allocation and pedestrian flow plans. Normally, with higher spatial complexity, shoppers are easier to get lost and generate higher shopping costs; however, space usage flexibility could also be increased. Therefore, a good measurement for spatial complexity for shopping areas is needed. This paper compares several measurements for spatial complexity. The intention is to tackle the spatial complexity issue through three dimensions: horizontal complexity, vertical movements and multiple-purposive users in mixed use environment. And the data is collected from the US, UK, Taiwan, Singapore, Hong Kong, Malaysia and Shanghai with more than 100 floorplans to explore the influential factors for spatial complexity within shopping centres. Using GIS, space syntax and other non-spatial techniques, this research suggests some interesting management issues and enhances the understanding of spatial complexity within a shopping environment.
JEL-codes: R3 (search for similar items in EconPapers)
Date: 2013-01-01
New Economics Papers: this item is included in nep-sea and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://eres.architexturez.net/doc/oai-eres-id-eres2013-46 (text/html)
https://eres.architexturez.net/system/files/pdf/eres2013_46.content.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:arz:wpaper:eres2013_46
Access Statistics for this paper
More papers in ERES from European Real Estate Society (ERES) Contact information at EDIRC.
Bibliographic data for series maintained by Architexturez Imprints ().