Residential Space Planning Reflecting User Preferences Utilizing Big Data -focused on Newlywed Households

Abstract

Background/Objectives: This study intends to propose a residential space planning approach that reflects user preferences focused on newlywed households, utilizing big data

Methods/Statistical Analysis: This study develops a methodology to derive user-customized residential planning by collecting and analyzing big data. Through precedent research and theoretical consideration, this paper analyzes the characteristics of newlywed households and residential space planning factors according to their preferences. Then, by collecting big data, users’ life styles and preferred space types are analyzed and user preference categories are derived. In the conclusion, user-customized housing models are proposed.

Findings: Based on the analysis of the characteristics of newlywed households and user preferences according to life style and life cycle, a system is configured comprising parameters that can be combined according to the user preferences of newlywed households. The prototypes are developed for three stages: a newlywed couple, a couple with an infant, and a couple with a toddler. The user-customized housing prototypes are suggested according to the life style and life cycle of residents. Much research has been published on the topic of housing for newlywed households, but there have been few integrated studies that propose flexible housing plans that adapt to their life types. This study is distinct from previous studies as it presents residential space models reflecting user preferences according to the life style and life cycle of newlywed households.

Improvements/Applications: It is expected that the results of this study can be expanded, and prototypes customized for other users such as young people will be suggested in the future.