The impact of socio-demographic indicators on urban shopping trip parameters
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25510%2F24%3A39922547" target="_blank" >RIV/00216275:25510/24:39922547 - isvavai.cz</a>
Result on the web
<a href="https://eforum.lntu.edu.ua/index.php/jurnal-mbf/article/view/1522" target="_blank" >https://eforum.lntu.edu.ua/index.php/jurnal-mbf/article/view/1522</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.36910/automash.v2i23.1522" target="_blank" >10.36910/automash.v2i23.1522</a>
Alternative languages
Result language
angličtina
Original language name
The impact of socio-demographic indicators on urban shopping trip parameters
Original language description
Understanding the factors influencing a user's choice of mode and travel time within an urban transport system is a crucial element of urban mobility research. This study focuses on the characteristics of shopping trips, which are less time-regulated compared to work or school commutes but have a significant impact on urban traffic flows. The aim of the research was to identify the connections between socio-demographic indicators and people's choice of place and time for shopping. An online survey was conducted among residents of Lviv, yielding 152 responses suitable for further analysis. The results indicate that the likelihood of using transport is much higher when shopping at large malls or markets (64.2%) compared to shopping at smaller stores (31.3%). Most shopping trips are made in the afternoon (after 3:00 p.m.). The study of the influence of socio-demographic characteristics on the choice of shopping location and time was carried out using the cross-tabulation method, followed by a χ²-test to verify the hypothesis of variable independence. According to the results, car ownership significantly influences the choice of shopping location, while gender and household income affect the choice of shopping time. A further cluster analysis based on statistically significant indicators, using the k-means method, identified five population clusters with distinct preferences for shopping time and location. These findings are valuable for modeling shopping trip demand and distribution over time and space.
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
20100 - Civil engineering
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Sučasnì tehnologìï v mašinobuduvannì ta transportì
ISSN
2313-5425
e-ISSN
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Volume of the periodical
Neuveden
Issue of the periodical within the volume
2(23)
Country of publishing house
UA - UKRAINE
Number of pages
8
Pages from-to
27-34
UT code for WoS article
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EID of the result in the Scopus database
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