Retail density and category overlap condition street-level shop survival near large commercial complexes: evidence from Zhengzhou, China

Abstract A planning authority must rule on a large commercial complex before it exists, and the evidence points both ways: complexes are held both to crowd out and to anchor nearby small shops. Much of that disagreement reflects conditions never estimated. We estimate two of them, and ask whether either can be observed when permission is sought. Following 45,558 street-level retail units in Zhengzhou, China, from 2019 to 2025 across three contrasting case areas containing four complexes, we estimate how survival varies with street-network distance to the nearest complex. Its direction depends on the retail intensity of the location, reversing in the low hundreds of shops within 500 metres, at a turning point the estimates place between 287 and 398. Its steepness depends on the overlap between what a shop sells and what the complexes sell: the survival gradient is about three percentage points per kilometre steeper for shops in categories a complex carries than for the rest. Only one condition is available when permission is granted: surrounding retail can be counted from open data, but what a complex will sell is not fixed until it leases. Category shares can be written into land transfer conditions, as one Chinese parcel shows, and would close that gap. We estimate conditional gradients rather than an average effect, comparing shops at different distances from the same complex. Where earlier studies assign category similarity by judgement, we compute overlap from a complete enumeration of the 1,914 tenant records inside the complexes.

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Publication Details

Journal
Research Square
Published
2026-11-04
DOI
https://doi.org/10.21203/rs.3.rs-11403954/v1
Primary Topic
Agglomeration and Urban Systems
Type
preprint
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preprint

Retail density and category overlap condition street-level shop survival near large commercial complexes: evidence from Zhengzhou, China

Keqing Tantai
Research Square
Agglomeration and Urban Systems
preprint

Retail density and category overlap condition street-level shop survival near large commercial complexes: evidence from Zhengzhou, China

Keqing Tantai
preprint en

Abstract

Abstract A planning authority must rule on a large commercial complex before it exists, and the evidence points both ways: complexes are held both to crowd out and to anchor nearby small shops. Much of that disagreement reflects conditions never estimated. We estimate two of them, and ask whether either can be observed when permission is sought. Following 45,558 street-level retail units in Zhengzhou, China, from 2019 to 2025 across three contrasting case areas containing four complexes, we estimate how survival varies with street-network distance to the nearest complex. Its direction depends on the retail intensity of the location, reversing in the low hundreds of shops within 500 metres, at a turning point the estimates place between 287 and 398. Its steepness depends on the overlap between what a shop sells and what the complexes sell: the survival gradient is about three percentage points per kilometre steeper for shops in categories a complex carries than for the rest. Only one condition is available when permission is granted: surrounding retail can be counted from open data, but what a complex will sell is not fixed until it leases. Category shares can be written into land transfer conditions, as one Chinese parcel shows, and would close that gap. We estimate conditional gradients rather than an average effect, comparing shops at different distances from the same complex. Where earlier studies assign category similarity by judgement, we compute overlap from a complete enumeration of the 1,914 tenant records inside the complexes.

Research Square
University of Nottingham Ningbo China (CN)
Agglomeration and Urban Systems
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Retail density and category overlap condition street-level shop survival near large commercial complexes: evidence from Zhengzhou, China — Keqing Tantai · Research Square (2026) | TGRS Research Map | TGRS