Hypermarkets temporal regimes in the pandemic times

March 20, 2021

This post is, more than anything else, a reflection on a specific source of spatio-temporal information. We want to share with you 'live' stream of data showing real-time occupancy of Globus hypermarkets in the Czech Republic. Data comes from hand-held counters that are used to monitor store occupancy to be in compliance with COVID-19 preventive measures (not exceeding the limit of 1 person per 15 square meters of the retail floor). The dataset may not be completely error-free as produced by a manual entry system, but it still quite faithfully captures temporal regimes of particular stores in the pandemic times. So, feel free to explore the simple dashboard or, alternatively, to download data and analyze it in your way. We will be happy to get some feedback from you in return.

Up-to-date status

The system updates data from the stores every half hour. The time of the last update is indicated below. The table shows occupancy of the stores valid for the time of the last update.

Location Occup. [%] Location Occup. [%]
Brno Ostrava
České Budějovice Pardubice
Chomutov Plzeň
Havířov Praha - Čakovice
Karlovy Vary Praha - Černý Most
Liberec Praha - Zličín
Olomouc Trmice
Opava

Plot of occupancy rhythms

The diagram natively captures the frame of three days. Pre-defined frame can be changed interactively in order to look into the past months and identify regular rhythmicities as well as singular events.

The data in the diagram have been collected since 1st December 2020.

The diagram shows the last 2000 records.
You can download the full database (.csv) here.

Here are some questions related to this retail-rhythm data we are thinking about. What kind of spatio-temporal proxy the data represents? Does it, in a narrower interpretation, just reflect individual timings of shopping? Or, does it contain more general information on broader urban rhythms? To what extent are these rhythms specific to the current pandemic situation? There are 15 stores monitored, scattered throughout the country – could we consider different socio-spatial contexts as a variable underlying possible differences between rhythms of particular stores? Hopefully we will have time to provide some answers soon.

References:
Globus (2021). Branch selection. Globus ČR, v.o.s. https://www.globus.cz/#!branch-selection

TIMESPACE.CITY Urban Rhythms Research Group

Add a comment