The Effects of Apartment Meal Service Attributes on Residential Satisfaction, Community Pride, and Continuance Intention: A Multi-Group Analysis by Living Area Type

Recent housing environments increasingly function as lifestyle-oriented spaces, extending the role of apartment meal services beyond basic food provision. While foodservice research has largely focused on institutional or commercial settings, limited attention has been given to apartment meal services as residential-based experiential amenities. This study examines the structural relationships among apartment meal service attributes, residential satisfaction, community pride, and residential continuance intention. Data were collected from 400 residents across four apartment complexes, and structural equation modeling with multi-group analysis was employed to explore these relationships and contextual differences. The findings indicate that meal service attributes are significantly associated with residential satisfaction and community pride, and both variables show significant positive relationships with continuance intention. Multi-group analysis further suggests that the strength of certain structural paths differs between central and non-central living areas. These results imply that apartment meal services may function as housing-based lifestyle infrastructure and provide an extended perspective for understanding foodservice within a residential experiential context.

Authors

Publication Details

Journal
Culinary Science & Hospitality Research
Published
2026-03-31
DOI
https://doi.org/10.20878/cshr.2026.32.3.013
Primary Topic
Korean Urban and Social Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Effects of Apartment Meal Service Attributes on Residential Satisfaction, Community Pride, and Continuance Intention: A Multi-Group Analysis by Living Area Type

Euijae Yu, Xiaochen Wang
Culinary Science & Hospitality Research
Korean Urban and Social Studies
article

The Effects of Apartment Meal Service Attributes on Residential Satisfaction, Community Pride, and Continuance Intention: A Multi-Group Analysis by Living Area Type

Euijae Yu, Xiaochen Wang
article en

Abstract

Recent housing environments increasingly function as lifestyle-oriented spaces, extending the role of apartment meal services beyond basic food provision. While foodservice research has largely focused on institutional or commercial settings, limited attention has been given to apartment meal services as residential-based experiential amenities. This study examines the structural relationships among apartment meal service attributes, residential satisfaction, community pride, and residential continuance intention. Data were collected from 400 residents across four apartment complexes, and structural equation modeling with multi-group analysis was employed to explore these relationships and contextual differences. The findings indicate that meal service attributes are significantly associated with residential satisfaction and community pride, and both variables show significant positive relationships with continuance intention. Multi-group analysis further suggests that the strength of certain structural paths differs between central and non-central living areas. These results imply that apartment meal services may function as housing-based lifestyle infrastructure and provide an extended perspective for understanding foodservice within a residential experiential context.

Culinary Science & Hospitality ResearchVol. 32(3)
Openalex Percentile: Top 6%
Korean Urban and Social Studies
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.