Q-methodological exploration of environmental characteristics affecting residential security in hybrid blocks: a focus on Beijing

Chinese cities have experienced rapid expansion in recent years, resulting in the emergence of hybrid neighborhoods characterized by buildings of varying ages, functions, and resident demographics. The distinctive environmental features hold significant research value for understanding their impact on residents’ perceptions of safety. However, research on the security of such neighborhoods remains limited. Q-methodology combines quantitative and qualitative research methods and is suitable for the study of hybrid blocks with complex factors affecting residents’ safety assessment. Three typical hybrid blocks were selected for the experiment. The findings point to six key environmental characteristics affecting residents’ sense of security within the scope of the study. Additionally, different social groups and living environments shape distinct perceptions and standards of security. This work contributes to the study of residential safety under hybrid blocks in China, enriching the existing crime prevention theory and improving its applicability and effectiveness. It can also help urban planners and policymakers reduce the tendency to overemphasize complex external environmental factors and provide a valuable reference to residential safety awareness in hybrid blocks.

Authors

Institutions

Publication Details

Journal
Humanities and Social Sciences Communications
Published
2025-11-26
DOI
https://doi.org/10.1057/s41599-025-06293-7
Primary Topic
Q Methodology Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Q-methodological exploration of environmental characteristics affecting residential security in hybrid blocks: a focus on Beijing

Xiangguo Peng, Yu Xia, Junming Zhao, Jiaxin Liu et al.
Humanities and Social Sciences Communications
Q Methodology Applications
article

Q-methodological exploration of environmental characteristics affecting residential security in hybrid blocks: a focus on Beijing

Xiangguo Peng, Yu Xia, Junming Zhao, Jiaxin Liu, Y. An
article en

Abstract

Chinese cities have experienced rapid expansion in recent years, resulting in the emergence of hybrid neighborhoods characterized by buildings of varying ages, functions, and resident demographics. The distinctive environmental features hold significant research value for understanding their impact on residents’ perceptions of safety. However, research on the security of such neighborhoods remains limited. Q-methodology combines quantitative and qualitative research methods and is suitable for the study of hybrid blocks with complex factors affecting residents’ safety assessment. Three typical hybrid blocks were selected for the experiment. The findings point to six key environmental characteristics affecting residents’ sense of security within the scope of the study. Additionally, different social groups and living environments shape distinct perceptions and standards of security. This work contributes to the study of residential safety under hybrid blocks in China, enriching the existing crime prevention theory and improving its applicability and effectiveness. It can also help urban planners and policymakers reduce the tendency to overemphasize complex external environmental factors and provide a valuable reference to residential safety awareness in hybrid blocks.

Humanities and Social Sciences CommunicationsVol. 12(1)
Chinese Academy of Sciences (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 58%
Q Methodology Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.