TY - JOUR
T1 - A step in time
T2 - a sequence analysis and choice modelling approach to examine time allocation in individual activities and the role of neighbourhood crime
AU - Lu, Ying
AU - Keel, Chloe
AU - Wickes, Rebecca
AU - Reynald, Danielle
AU - Corcoran, Jonathan
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Australian Research Council; DP200100830.
Publisher Copyright:
© The Author(s) 2024.
PY - 2024
Y1 - 2024
N2 - The Space-Time Budget (STB) method is used to collect spatial and temporal features of an individual’s activities and is an important technique to explore relationships between the environment and crime. This spatial and temporal approach to the study of everyday activity spaces reveals much about victimisation experiences, the relationship between place, time, and perceptions of safety, and where and when offending may occur. Few studies, however, consider the relationship between living in a criminogenic place (neighbourhood crime) and people’s daily activity patterns. Drawing on disaggregate app-based data for 50 participants tracked over a 7-day period, we use sequence analysis to first delineate time allocation to each activity on a minute-by-minute basis. Next, using result from the sequence analysis we introduce the multiple discrete-continuous extreme value (MDCEV) model to understand how neighbourhood crime and socio-demographic characteristics influence individuals’ time allocation to discrete daily activities. Results reveal that neighbourhood drug and violent incidents exert restrictions on an individual’s propensity to spend time outside the home. Females and older people appear more likely to be constrained by the presence of neighbourhood crime (in particular drug and property incidents) as they allocate less time to outdoor activities. The principal utility of the current study is its methodological advancement and the practical insights for urban planning regarding the design of crime prevention strategies to increase guardianship in public places.
AB - The Space-Time Budget (STB) method is used to collect spatial and temporal features of an individual’s activities and is an important technique to explore relationships between the environment and crime. This spatial and temporal approach to the study of everyday activity spaces reveals much about victimisation experiences, the relationship between place, time, and perceptions of safety, and where and when offending may occur. Few studies, however, consider the relationship between living in a criminogenic place (neighbourhood crime) and people’s daily activity patterns. Drawing on disaggregate app-based data for 50 participants tracked over a 7-day period, we use sequence analysis to first delineate time allocation to each activity on a minute-by-minute basis. Next, using result from the sequence analysis we introduce the multiple discrete-continuous extreme value (MDCEV) model to understand how neighbourhood crime and socio-demographic characteristics influence individuals’ time allocation to discrete daily activities. Results reveal that neighbourhood drug and violent incidents exert restrictions on an individual’s propensity to spend time outside the home. Females and older people appear more likely to be constrained by the presence of neighbourhood crime (in particular drug and property incidents) as they allocate less time to outdoor activities. The principal utility of the current study is its methodological advancement and the practical insights for urban planning regarding the design of crime prevention strategies to increase guardianship in public places.
KW - daily activity patterns
KW - multiple discrete-continuous extreme value model
KW - neighbourhood crime
KW - sequence analysis
KW - Space-Time Budget
KW - Time allocation choice
UR - http://www.scopus.com/inward/record.url?scp=85193828459&partnerID=8YFLogxK
U2 - 10.1177/23998083241255491
DO - 10.1177/23998083241255491
M3 - Article
AN - SCOPUS:85193828459
SN - 2399-8083
JO - Environment and Planning B: Urban Analytics and City Science
JF - Environment and Planning B: Urban Analytics and City Science
ER -