Analysis and Optimization of Residential Elements from the Perspective of Multi-Child Families in the Yangtze River Delta Region

Abstract

Over the last few decades, policy changes have resulted in changes in family structure and cyclical changes within families. The structure of multi-child families will have a significant influence on housing demand and supply, necessitating a thorough demand study. This study examines the requirements of 739 multi-child families in the Yangtze River Delta (YRD) region at different stages and graphically displays the variables influencing their level of housing satisfaction, offering a scientific reference for the design and optimization of housing. Firstly, the residential elements that impact families with multiple children were categorized into 3 categories, 14 subcategories, and 65 influencing elements based on expert consultation and word frequency data. Secondly, 739 families in the YRD region were chosen for investigation, and importance–performance analysis (IPA) was employed to study and assess the residential elements of multi-child families. The IPA study findings were compared to those obtained from on-site surveys and network data crawling. Finally, the residential elements to be optimized were quantitatively determined, and the relevant optimization techniques were provided in conjunction with door-to-door interviewing. This study examines the needs of multi-child families at various phases, as well as the factors that impact their residential satisfaction, and provides optimization solutions for the long-term use and renewal of residential structures.

1. Introduction

China’s family structures have undergone a series of changes over the last two decades. The shift in the policy has led to transformations in family structure and intra-family cyclical changes, resulting in new demands. After experiencing a population surge following the establishment of the People’s Republic of China, the birth rate has dropped dramatically in the last decade. According to the data of the seventh census, the number of newborns in China was 9.56 million in 2022, which is 53.5% lower than that in 2016 when the two-child policy was liberalized. The birth rate and infant population will be at their lowest points since New China’s foundation in 2022. In light of this, the Political Bureau of the Central Committee of the Communist Party of China (PBC CCPC) met in 2021 to discuss the “decision on optimizing the fertility policy to promote the long-term balanced development of the population”, and it put forward the multi-child policy and supporting measures. As the population policy has shifted from family planning to promoting population fertility [1,2], commercial residential buildings, which are closely related to families, face many changes and challenges. Changes in fertility policies have led to a shift in family demographics. The residential space associated with family life faces numerous challenges, and this phenomenon is especially visible in multi-child families. However, previous research has mostly focused on spatial concerns related to this phenomenon, neglecting to investigate users’ demands in the context of shifting family structure. From the perspective of the transformation of the family structure, this study attempts to propose corresponding strategies to promote the sustainable development of houses and residential areas, which are quite relevant to the flexible utilization of the functional spaces of their components.

2. Literature Review

Demands for residential aspects alter throughout the family cycle, and changes in the population structure of multi-child families have resulted in a variety of adaptable housing needs. The family is an evolving and changing entity, principally defined by variations in family composition. Therefore, it is essential to assess the living conditions of multi-child families in terms of adaptability, child-friendliness, and satisfaction. Firstly, the demands for residential elements vary throughout the family cycle, and changes in the population structure of multi-child families have resulted in various adaptive housing requirements. Adaptable design seeks to build a flexible and adaptable ecosystem that can respond to the needs of various populations and changing socioeconomic conditions. Secondly, each family is interwoven and impacted by its parents and children as it evolves, showing intergenerational inheritance and the long-term continuity of Chinese family features. It is critical to incorporate pertinent research on child-friendly design into residential demand studies since there is a stage in the family life cycle when parents must care for young children. Finally, as satisfaction-related research expands, quantitative analysis tools can be used to conduct systematic analyses of residential aspects.

2.1. Adaptive Design of Multi-Child Housing

Adaptable design aims to create a flexible ecosystem that can meet the needs of diverse populations and shifting socioeconomic conditions. The study of residential adaptability began in the 1920s, when Corbusier’s “domino house” was presented, and a significant advance in housing adaption was made [3]. This marked the first time structural and non-structural components have been separated. Later, Mies presented his plan for a four-story residential apartment at the Stuttgart Weissenhof Housing Exhibition in 1927. The house was quite adaptable and had the possibility for future modifications thanks to the use of a steel-framed load-bearing structure [4]. Habricken developed the SAR theory in 1961. Residents can rearrange or replace “detachable components” according to changes in demographic composition, economic situation, and living habits during the use of the house, making the residents the creators of their own living environment [5]. The theory of SAR is still active in architectural circles. The superloft shared community designed by MKA is also developed on the basis of SAR, in which the designer assigns various functions to each basic module according to the living habits and requirements of the users. Residents have the flexibility to arrange the functional layout of the interior, allowing the overall lifestyle to seamlessly align with their unique characteristics. After the 1990s, based on the SAR system, the KSI housing system was developed in Japan [6], which gives the filler body more renewability while guaranteeing the durability of the skeleton. In addition to room layouts that can be changed at will, kitchen and bathroom plumbing and electrical wiring can also be altered to increase adaptability, and the KSI housing system greatly saves on energy loss, which complements modern society’s demand for energy efficiency and sustainability. China soon assimilated many theories and borrowed from Japan’s experience to create its own CSI (China Skeleton Infil) housing system, which continues to this day. The examination of this series of residential systems provides effective techniques for establishing residential diversification, but the core of its research has not yet concentrated on adaptive demands in the context of changes in family structure.

In recent years, a number of Chinese real-estate organizations and scholars have come to recognize the significant impact of changing family structures on housing and have attempted to address this shift from a variety of perspectives. Beisi Jia proposed the idea of adaptive housing design, which means that a room’s purpose can be changed in accordance with current needs while maintaining the home’s primary framework. The concept put forward in this work, which is helpful for directing the construction of housing for families with multiple kids, is the foundation for the adaptive housing concept advanced by later scholars [7]. Zhimin Zeng dedicated efforts to maximize space utilization and enhance people’s living quality through a comprehensive study of elements within small and medium-sized suites. This involved analyzing and identifying key design points and methods for each element. Simultaneously, Zeng introduced design strategies focusing on both modularity and flexibility of space [8]. Xiaozheng Qu supplemented and improved the theory and methodology of residential design from the perspective of adapting to the family life cycle [9]. In Adaptive Design of Interior Living Spaces, Qiaoqin Lin focuses on how changes in family demographics can change the needs of existing living environments and analyzes how adaptive design can be used to meet the needs of different dynamics of the residents in interior design solutions [10]. Huili Chen pointed out that by combining the limited indoor space, scientific and technological design can be applied to the space; therefore, the adaptive design of the indoor environment can effectively improve the quality of life of the residents so that life is comfortable and healthy [11]. However, all of these studies concentrated on the solution and design of housing problems, leaving out the “analysis design” linkage study in the context of dynamic changes in family structure.

Since there is no restriction of birth policy in foreign countries, they have had multi-children households for a long time. Residential adaptive design for different periods of the family can cope well with the complex and changing spatial needs of multi-children families, so it has great reference significance for China’s current commercial residential buildings design. At the same time, our country has a strong urgency for research due to the different basic national conditions and policies and the relatively large change in the population ratio. Most of the related studies in China focus on adapting to the structural changes of multi-child families through modularization, flexibility, technology, and other technical means, while the main structural form remains unchanged. There is a lack of in-depth excavation of the changing needs of multi-child families. This study establishes a demand–satisfaction correlation study of residential elements in the context of dynamic family structure development, and quantitative evaluation analysis was introduced to provide scientific reference for optimizing residential elements, which has some practical significance.

2.2. Child-Friendly Design of Residential Areas

The focus on children’s well-being dates back to the early 20th century. Australian scholars, including Sipe and others, assert that the 1911 “Chicago Children’s Exposition” marked the first academic consideration of urban parks and playground design. This event laid the foundation for the development of diverse spaces catering to children’s lives and set the stage for subsequent explorations in design [12]. In the 1920s, academics broadened their research to include metropolitan settings and started investigating how the environment affects children and how children perceive the environment from a sociological perspective. British psychologist Heft established a connection between children’s conduct and environmental availability and proposed 10 prototypes of features that could be available to children [13]. Multidisciplinary research techniques were created in the 1960s as a result of increased interest in children across a variety of disciplines. Kevin Lynch’s project, “Growing Up in the City”, focuses on studying how children organically use space, such as cafés and stairways. By looking into the everyday ways in which children interact with space, it reveals the differences in how children navigate and understand the urban environment compared to adults [14]. In the 1990s, children’s health concerns garnered attention in a range of industries. Gascon et al. thoroughly examined the association between environmental characteristics such as street connectivity, residential density, walkability, green space, food environment, and children’s health [15]. With the rise in popularity of child-friendly design, an increasing number of residential elements encompass children’s demands and behavioral traits.

Residential public spaces are crucial for family life and for fostering emotional ties between family members since they are the most easily accessible and often-used places in children’s everyday lives. It is crucial to investigate design solutions for children according to their physical and psychological demands as well as their activity requirements. At present, relevant research mainly focuses on the following aspects. Xiaoluan Huang and Shuping Deng mentioned the types, principles, and design methods of children’s playgrounds in their books on residential areas [16,17]. Le Zhang et al. developed an indicator system for evaluating the kid-friendliness of urban pocket parks using the entropy-based TOPSIS method, and they subsequently suggested optimization techniques [18]. From the perspective of children’s behavioral activities and the spatial environment, for example, Rui Ji conducted a thorough investigation into children’s outdoor play in Hangzhou, looked at the relationship between play and the natural world, and offered fresh suggestions for improving kids’ outdoor play in their neighborhoods [19]. In-depth research on the connection between physical activity and environmental factors was conducted by Xili Han, Wei Zhu, and Lingling He et al. The resulting findings included systematic reviews, theoretical models, and empirical studies [20,21,22]. From the perspective of research and practice related to child-friendly environments, the practical outcomes in terms of child-friendly areas and transport routes in the Netherlands were summed up by Peng Zeng et al. [23]. Yu Pei et al. conducted an evidence-based study on the child health friendliness of urban settings, using Boston as an example [24]. Tian Chen et al. investigated the topic of creating child-friendly public areas using Zhongxin Eco-city as an example [25]. With the change in fertility policy, the relationship between children and the urban environment has become more important to a certain extent, and a good residential spatial environment can help to eliminate social concerns about fertility, promote the birth and rearing of newborns, and guarantee the sustainable development capacity of society. However, due to birth policy modifications [26,27], the proportion of multi-child families has shifted significantly over the last decade. Previous research is frequently inapplicable to contemporary national conditions and family structure, and there is a lack of comprehensive study on the demand and satisfaction of multi-child families with residential elements in up-to-date living conditions.

In general, research and practice focus more on the issue-solving side of a problem; the above initiatives focus on analyzing how housing and residential areas have changed in order to adapt to future changes in family structure. Therefore, before recommending techniques, we need first to undertake a thorough analysis of the demand for multi-child families to reside in China at the moment. This study introduces the importance–performance analysis method, selects families with multiple children in the Yangtze Delta Region as the research object, and evaluates the demand for residential elements of families with multiple children based on questionnaire data analysis, with the goal of proposing optimization strategies and guidelines for residential design for families with multiple children.

2.3. Importance–Performance Analysis (IPA)

The concept of satisfaction originated from psychology and has been widely applied in the fields of economics, sociology, and housing as research continues to deepen. It is the psychological perception that people have when comparing their expectations of a product, service, or environment with their actual feelings. Carzodo (1965) introduced the notion of customer satisfaction and applied it to the realm of marketing. He felt that customer pleasure would encourage customers to make repeat purchases [28]. Martilla and James developed the IPA approach in 1977 to enhance the service system of businesses and boost customer satisfaction [29]. In 1978, Pizam introduced the satisfaction theory, which laid the groundwork for subsequent studies [30].

The IPA technique investigates how customers assess the value and performance of a supplier’s products and services. It is extensively utilized in the service sector and has the benefits of simplicity, intuitiveness, and high operability. The IPA approach was originally used in the tourism business in 1989 by Evans and Chon K [31]. The IPA technique is still primarily used in tourism research today, with a focus on visitor satisfaction surveys and perceptions of the industry’s image and components. This approach was subsequently progressively extended to the domains of landscape architecture, planning, and architecture. Using IPA, Yu Bingqin (2013) investigated how satisfied locals were with the leisure options available in Shanghai’s urban community parks [32]. It was utilized in the study and optimization of the supply–demand connection of cultural ecosystem services in waterfront environments by Wang Min et al. [33]. Currently, the majority of study subjects are tourists and urban dwellers, along with studies on senior people and rural inhabitants. The substance of the research also focuses mostly on how satisfied elderly people are with their ability to enjoy recreation in urban parks and green areas. Research on residential spaces and community environment regeneration is still in its infancy with regard to application. The research on residence satisfaction has not yet delved into the systematic segmentation of residential elements at the spatial level, nor has it included different family cycles within the study’s time frame.

It is necessary to analyze the benefits and drawbacks of the research object, assess the significance and satisfaction performance of various indicators or dimensions of indicators, and then provide more scientific optimization methods. IPA analysis is crucial for the development of people-oriented settings since it disrupts the unidirectional design mechanism and fosters close communication between designers and users [34]. An IPA analysis often uses a four-quadrant analysis graphic to show the relative value and satisfaction of different metrics. To evaluate analysis results, examine difficulties, and get ready to provide appropriate optimization solutions, one might combine the Excel 2021 scatter plot tool [35].

3. Background of Family Structure in China

3.1. The Changing Trend of Multi-Child Family Structure in China

Influenced by China’s demographic changes and national conditions, the family structure of married and childbearing households has undergone a series of transformations. These changes occurred after the significant development following the founding of the People’s Republic of China and were further shaped by the guidance of the birth policy in the 1980s. Currently, the prevalent family structure in China tends to be a “2 + 1” core household structure, comprising a couple and a single child. According to China’s urban planning, the average number of people in a household is 3.2 [36], and many cities take 90 m² as the dividing line to determine the deed, loan, and other home-purchasing policies based on the structure of only-child families [37].

The fertility policy in China has steadily modified since 2016, transitioning from the universal two-child policy to the three-child policy, from restricting fertility to optimizing fertility, and finally to boosting fertility, in response to the current trend in population structure change. The urban family structure is changing, along with attitudes toward marriage and having children. On the one hand, the population of single and infertile individuals continues to increase annually, while on the other hand, the size and composition of married and conceiving families remain uncertain. The traditional fixed “2 (couples) + 1 (child)” or “2 (couples) + 2 (grandparents) + 1 (child)” model has been replaced by the flexible “2 + 2”, “2 + 3”, and “2 + 2 + 3” models in many married households. Families have a longer parenting cycle than single-child households, which necessitates the involvement of grandparents or nannies for a longer length of time. This results in a more diverse and complicated family size and structure.

The diversified and complex family structure brings complex needs, which the original space finds difficult to meet. For example, the residential layout should ensure both children’s activity space and adults’ privacy space, and the per capita area after population increase should be able to meet daily use. Another example is that with the increase in the number of children, higher requirements are put forward for the design of related supporting facilities, including the richness and safety of activity space. Therefore, this study conducts in-depth research on its complex needs from a scientific perspective, hoping to propose corresponding design optimization strategies in turn.

3.2. The Change Cycle of Multi-Child Family Structure

According to the research of Zhen Li and Shengzhi Gu, the family life cycle is split into six stages: no child after marriage, childbearing in the middle stage, children leaving home, parents in the latter stage, and widowhood [38]. It may be split into five stages when combined with the growing cycle of children in multi-child families: family formation, period I; children feeding, period II; children growth, period III; couple home, period IV; and home care, period V (

Table 1. List of residential features during the family life cycle.

		Multi-Child Family Dwelling Life Cycle
Stage		Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ
Period		Family formation	Children nurturing	Children growth	Parents home	Elderly home care
Characteristics		Couple getting married and buying a house, preparing for pregnancy or getting pregnant	Birth of a child until childcare	Children from kindergarten to high school home-schooling	Children have left home for school or employment, leaving the family with only a couple	Couple moving into old age, aging in place
Stage Year	Only child	1+ year	3 years	15 years 1	18 years 2,3	Average of 13 years from retirement 4
	Two children		6 years 3	18 years 1,3	15 years 2,3
	Three children		9 years 3	21 years 1,3	9 years 2,3
Number of family generations		1 generation	2–3 generations	2–3 generations	1–2 generation(s)	1 generation
Family Composition		Couple	Couple, young children, grandparents (nannies)	Couple, young children	Couple, grandparents in need of care	Elderly couple
Number of family members		2	5–7	4–5	2–4 (+Temporary 2–3 5)	2

¹ 3 years of preschool, 9 years of compulsory education, plus 3 years of day school or vocational school. ² Calculated at the future delayed retirement age of 65. ³ The national average age of childbearing in 2022 is 29.13 years, with children leaving home at approximately 18 years of age, and the World Health Organization recommends an appropriate gestational interval of 2 to 5 years after a live birth. ⁴ The average life expectancy of urban and rural residents in China will be 78.3 years in 2025 (14th Five-Year Plan for Public Services). ⁵ Temporary home stay of children.

). With the increase in the number of children in the family, the period of children’s feeding and growth is multiplied, especially the superposition of children nurturing, children growth, and parent’s home period, which complicates the demand for living and raises the bar for flat design and residential planning.

The period of family formation refers to the stage in which a couple just got married and bought a house to prepare for pregnancy. At this time, the living demand is mainly to meet basic living needs, and the area requirement is not high. However, it is necessary to consider the growth demand for new functions and the adaptability of existing functions in advance.

The period of child nurturing refers to the stage in which family members mainly consist of parents, children, and grandparents or nannies who take care of the children. At this time, facing the increase in family population, it is necessary to consider the rationality of the number of bedrooms and storage spaces. At the same time, it is necessary to consider the layout of the flat around the living environment of mothers and infants.

The period of children’s growth refers to the stage in which the main family members are couples and children, and the growth of children becomes the core concern of the family. At this time, as children grow up, they need an independent rest and learning environment. At the same time, as the children’s social circle forms, the whole family also needs to integrate into the community of families with school-age children.

The period of the parents living at home refers to the stage in which children leave the family to live alone, and the core of the family returns to the couple. As the couple ages, their requirements for living quality also increase, with more emphasis on the comfort and convenience of various spatial elements and also a further pursuit of the quality of the living space.

During the period of elderly home-based care, the physical skills of the occupants decline greatly, and the center of living is on the convenience, safety, and comfort of life.

4. Method

As shown in Figure 1, this paper establishes an extraction process of residential elements for multi-child families and distinguishes the residential elements into 3 major categories and 14 subcategories. Then, the study introduces the importance–performance analysis to distinguish each residential element into four quadrants: to maintain, of over-supply, needs no priority, or to improve. Finally, the study compares the findings of IPA with on-site surveys and network data crawling. Based on this, the residential elements to be optimized are quantitatively determined, and the relevant optimization techniques are provided in conjunction with door-to-door interviewing.

4.1. Sample and Evaluation Framework

The study chose multi-child families in the Yangtze Delta Region as the sample area to minimize the effect of external influences. Its jurisdiction comprises Shanghai, Jiangsu, Zhejiang, and Anhui, with a total of 41 cities and 1 municipality in the 3 provinces. According to the data of the seventh census, as of the end of 2020, the total resident population of the Yangtze Delta Region reached 235 million, accounting for 16.7% of the mainland population, up from 16.1% in 2010. The rate of multiple births showed a rising trend year by year. Taking Shanghai as an example, according to the “2022 Annual Population Monitoring Statistics of Shanghai”, the rate of multiple births reached 4.53%, up 1.15 percentage points year-on-year compared with 2019 [39]. After a long period of development, the region has formed a relatively similar economic level, cultural customs, and housing patterns, so selecting household samples in the region is both universal and typical. The background components in the obtained samples have less interference, making statistical analysis of live elements easier.

Using word frequency screening, interviews, expert consultation, clustering techniques, and other methods, this study further screened the residential elements that impact the life of multi-child families in order to thoroughly analyze the root problems encountered by multi-child families (Figure 2). To start with, this study draws on the consensus reached by Changlian Zhu, Hao Long [40], Renlu Hu, Zhou Yanmin [41], Fang Xianfu, and Yao Shizhang [42] as the basic framework. Next, the study conducted online interviews with 95 multi-child families for the purpose of its preliminary research, identified the factors influencing their housing, and conducted the first round of expert consultation (15 experts) to summarize their characteristics, categorizing residential elements into three major categories: flat layout, flat public areas, and residential areas. Then, in the perspective of multi-child family members’ perception and experience, “flat layout”, “flat public area”, “residential area”, “multi-child”, and “child-friendly” were used as a condition for the research in the CNKI database and the Web of Science core collection database. The residential elements and characteristics that influence multi-child families were extracted from 132 primary journals published within the past decade. Using techniques for clustering and integrating, 65 residential elements were obtained. Finally, a second round of expert interviews was conducted, and residential elements were ultimately divided into 3 categories, with 65 elements in 14 subcategories.

Residential elements can be classified into three main categories, as illustrated in

Table 2. Three levels of Residential Elements.

Major Categories	Subcategories	Elements
Flat layout	A Bedroom	A1	Number
		A2	Area
		A3	Ventilation and lighting
		A4	Sound insulation
		A5	Storage capacity
		A6	Subsidiary space
	B Living room	B1	Area
		B2	Ventilation and lighting
		B3	Variable furniture
		B4	Storage capacity
	C Bathroom	C1	Number
		C2	Area
		C3	Ventilation and lighting
		C4	Wet and dry separation
		C5	Storage capacity
		C6	Equipment
	D Dining room and kitchen	D1	Area
		D2	Ventilation and lighting
		D3	Storage capacity
		D4	Visibility
		D5	Equipment
Flat public area	E Entrance lobby	E1	Activity space
		E2	Service function
		E3	Landscape quality
		E4	Path design
	F Vertical traffic	F1	Elevator waiting time
		F2	Elevator car size
		F3	Resting platform
		F4	Waiting room
		F5	Quick and safe evacuation
	G Corridors space	G1	Ventilation and lighting
		G2	Interference reduction
		G3	Entry transition space
		G4	Outdoor storage
	H Roof space	H1	Roof accessibility
		H2	Activity diversity
		H3	Climate adaptability
		H4	Activity safety
Residential area	I Recreation	I1	Site accessibility
		I2	Facility all-age
		I3	Facility diversity
		I4	Site security
		I5	Resting place
	J Traveling	J1	Road plans
		J2	Walking environment
		J3	Sidewalk facilities
		J4	Street crossing facilities
		J5	Architectural interface
	K Facilities	K1	Facility refinement
		K2	Facility accessibility
		K3	Business facilities
		K4	Medical facilities
		K5	Cultural and sports facilities
	L Neighborhood	L1	Neighborhood
		L2	Inter-generational activities
		L3	Security perception
		L4	Environmental Safety
	M Landscape	M1	Road pavement
		M2	Vegetation species
		M3	Landscape water
		M4	Architectural sketches
	N Parking	N1	Number of parking
		N2	Parking efficiency
		N3	New energy parking
		N4	Electric bicycle parking

: flat layout, flat public section, and residential area. The flat’s layout consists of four main components: bedroom, living room, bathroom, and dining room and kitchen, which are affected by factors such as number, area, ventilation and lighting, and storage capacity. The residential public area consists of four main components: entrance lobby, vertical traffic, corridors and entrance space, and roof activity space, which are mainly affected by factors such as activity space, service function, resting platform, and entrance transition space. The residential area consists of six main components: recreation, traveling, facilities, neighborhood, landscape, and parking, which are mainly affected by factors such as site accessibility, road plans, facility refinement, neighborhood relations, and road pavement.

4.2. Data Acquisition

Comprehensive techniques, including semi-structured interviews, online and offline questionnaire surveys, and network data crawling, were employed in the data-acquiring phase of this study. Semi-structured interviews were carried out on a family basis to obtain firsthand information; this allows participants to respond to questions in a relaxed setting and guarantee accurate responses to pertinent issues with the assistance of other family members. To ensure uniform coverage of study samples, survey questionnaires were distributed using a combination of online and offline techniques. In order to indirectly validate the previously mentioned evaluation method, Python was utilized to crawl real estate transaction data from the network at the same time.

• Semi-structured interviews: From September to November 2022, the research team conducted an initial survey on the residential elements of multi-child families in the Yangtze Delta Region using methods such as door-to-door interviews and group interviews. The interview outline is shown in

  Table 3. Interview outline.

  Topics	Content Outline
  Basic Information	Gender, age, occupation, annual household income, flat layout, family structure
  Spatial Perception	Where do you spend the most time with your child?
  	Which living space do you consider the most lacking in the current living environment?
  Satisfaction Expression	In contrast to your current residence, what are the most crucial features that your next home must have?
  	Do you encounter any inconvenient situations when bringing your children home?
  	Are there any drawbacks or disadvantages associated with the use of the public areas within the flat?
  	Are there available services for community day care, health, and hygiene, and how would you rate the quality of these services?
  	Are there enough recreational facilities, and are there a variety of activities to choose from?
  	Is the pedestrian environment safe for travel, and are there specific areas that need improvement?
  	Are there an adequate number of parking spaces, or have you experienced challenges with parking?
  	Are there any security issues, or do you have concerns about environmental safety?

  ; it is mainly to gather basic information about multi-child families, as well as their space perception and satisfaction with their flats and residential areas.

• Questionnaire survey online/offline: From February to April 2023, a questionnaire survey on the evaluation of elements for multi-child families was conducted both online and offline. The questionnaire focused on elements affecting the lives of multi-child families, using a Likert five-level scale to evaluate its importance and performance. As shown in

  Table 4. Distribution of the number of survey questionnaires.

  Age Range	Jiangsu				Zhejiang				Anhui				Shanghai
  	OL 1	OFF 2	TOT 3	R 4	OL	OFF	TOT	R	OL	OFF	TOT	R	OL	OFF	TOT	R
  ≤30	51	11	62	30	52	19	71	31	49	19	68	36	54	21	75	27
  30–44	27	10	37	23	28	12	40	24	26	15	41	20	31	7	38	27
  45–60	34	8	42	25	40	14	54	25	35	9	44	25	32	12	44	21
  >60	13	20	33	21	9	22	31	18	9	19	28	18	22	9	31	23
  Total	125	49	174	101	129	67	196	93	119	62	181	99	140	48	188	98

  ¹ OL is an abbreviation for online, which refers to questionnaires collected online. ² OFF is an abbreviation for offline, which refers to questionnaires collected offline. ³ TOT is an abbreviation for total, which refers to the total number of questionnaires collected online and offline. ⁴ R is an abbreviation for random, which refers to the number of questionnaires randomly selected in proportion to the age of the population.

  , the research team distributed 739 questionnaires in Jiangsu, Zhejiang, Anhui, and Shanghai, of which 695 were valid. Then, based on the proportional relationship of the population age structure in various regions of the Yangtze Delta region in 2022, a random selection was conducted, and finally, 391 questionnaires were screened out to conduct relevant data analysis and evaluation.

• Data crawling: Network data were used in the study to validate and support fieldwork. Python was used to crawl relevant data from real-estate websites, investigate and collect details about new and used homes for sale, understand relevant details like design and location in the various home types for sale, and determine how buyers balance their personal preferences, their family’s needs, and their financial situation. It is demonstrated that multi-child households concentrate on housing components in a manner akin to field research, which indirectly confirms the validity of the study’s assessment method. The main code is as follows (Supplementary Materials has the complete code):

for page in range(1, 100):
time.sleep(1)
url = ‘https://su.lianjia.com/ershoufang/pg{page}’
Headers = {‘User-Agent’: ‘Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36 Edg/114.0.1823.79’}
response = requests.get(url = url, headers = headers)

(1)

4.3. Importance–Performance Analysis

The digital platform creates optimal circumstances for the programmatic study of urban spatial challenges, allowing for the stratification and analysis of complex urban spatial problems, as well as the establishment of a cognitive, analytical, simulation, evaluation, and feedback process on cities and architecture [43,44]. The modular approach explores many options and solutions while offering reference solutions for urban issues [45,46]. IPA is rather specialized when it comes to studies on the demand side of urban housing. Importance–performance analysis (IPA) was used to assess the outcomes of multi-child families’ evaluations of residential aspects. The evaluation structure is critical to the IPA method, as it is based on the principle of using importance as the horizontal axis X and performance as the vertical axis Y (Figure 3), with the mean importance score and mean performance score forming the horizontal and vertical coordinates of the origin. The elements in the first quadrant are of high importance and high performance and need to be “maintained”. The elements in the second quadrant are of low importance but high performance, belonging to the “oversupplied” category, and the residential elements in this quadrant are in a redundant state. The elements in the third quadrant are of low importance and low performance, belonging to the “no priority” category, and the resources and strategy allocation do not need to consider the elements and characteristics of this area [47,48]. The elements in the fourth quadrant are of high importance but low performance and need to “focus on improving”, and positive measures should be taken. This method helps to understand the satisfaction level of multi-child families with multiple residential elements and distinguish the elements that need improvement. The method helps to understand the level of satisfaction of families with multiple children with regard to a number of residential elements and to distinguish those that need to be improved. Its principles and methods are simple, and the results are intuitive.

5. Results

The findings are assessed in two aspects using the aforementioned method. On the one hand, the expected importance and realistic performance evaluation of various residential elements are analyzed as a whole. On the other hand, the differences and effects of influencing factors under different conditions are analyzed by city type, age of occupants, flat layout, flat area, and household income.

5.1. Overall IPA Results

According to the results of the questionnaire, the mean value of importance for each type of residential element was 2.27, and the mean value of performance was 3.91. The top five items of importance were B1 (2.99), B2 (3.54), G2 (2.93), M2 (2.99), and N1 (3.32). The last five items of performance were A4 (3.65), C4 (3.74), C5 (3.71), I2 (3.73), and N3 (3.71) (Figure 4 and Figure 5). B1, B4, D3, D4, E2, H1, H2, H3, J2, J3, L1, L2, N2, and N3 were in quadrant IV. The mean values of each part from flat layout (I = 2.29, p = 3.89), flat public area (I = 2.35, p = 3.92), and residential area (I = 2.21, p = 3.92) were used as the basis for quadrant division, and then the evaluation results were subdivided into city type, flat area, and age of residents with different perspectives.

5.2. IPA Results According to City Type

In the flat layout aspect, the majority of the samples had B3, B4, C3, C4, D1, and D3 in quadrant IV. The findings show that in a multi-child family structure, the flat layout should prioritize storage space, wet and dry segregated bathrooms, and efficient space use. The findings of C1 show that there is a sizable unmet demand for restrooms in the sample of first-tier cities.

In the flat public area aspect, E1, E2, E3, H1, H2, H3, and G2 are located in quadrant IV in most of the samples, and the design of the flat public area should focus on the roof activity space, ground floor space, and on reducing the interference of corridors. However, the performance of p-values is also higher than the average in first-tier cities despite the I values of E1, E2, and E3 being higher than the average, demonstrating the high level of landscape design and construction of flat public areas in first-tier cities. In the samples of the fourth and fifth-tier cities, the I values of H1, H2, and H3 are lower than the average, indicating that the use of rooftop activity space is not particularly important when there are other options.

In the residential area aspect, only L1, L2, N1, and N3 are in the fourth quadrant, which indicates that neighborhoods need to be improved regardless of city type. In the sample of fourth- and fifth-tier cities, N1 and N3 are not in the fourth quadrant, indicating that parking and new energy vehicle charging issues are not significant in these cities (

Table 5. IPA evaluation results based on city type.

	Flat Layout	Flat Public Area	Residential Area
1st-tier cities
New 1st-tier cities
2nd- and 3rd-tier cities
4th- and 5th-tier cities
Postscript

).

5.3. IPA Results According to Flat Area

In the flat layout aspect, there are 10 residential elements such as A2, B1, B3, C3, and C4 in the sample below 90 m², while there are only 3 and 1 in the residences of 90–144 m² and above 144 m², respectively. The elements that require modification rapidly decline as residential set area increases, demonstrating that flat space is the key determinant of living quality.

The same performance can be found in the aspects of flat public areas and residential areas because the residential area of a small flat area is economically oriented, and the flat public area is generally small in order to control the pool area and the supporting facilities, landscape, and greenery the residential area are all poorly configured, which inevitably affects the comfort. Due to the limited internal space, small households in Hong Kong, Japan, and other locations are increasingly reliant on public space outside their homes (

Table 6. IPA evaluation results based on flat area.

	Flat Layout	Flat Public Area	Residential Area
<90 m2
90–144 m2
>144 m2
Postscript

).

5.4. IPA Results According to Age of Residents

In the aspect of flat layout, the storage capacity of each room, such as A5, B4, C5, and D3, are aspects that need to be improved in every age sample. C4 is in the “focused on improving” area only in the sample under 30 years old, while the p-value of C4 is lower than the average in the rest of the samples, which still needs to be paid attention to. D5 (equipment and facilities) in the 60+ sample appears in quadrant IV, demonstrating that there is a high demand for aging-friendly equipment but insufficient supply.

In the aspect of flat public areas, rooftop activity space and ground floor entry space are still the key targets for improvement. All age samples pay great attention to the convenience of the ground floor living service function, while the 30–45 and 46–60 age samples have higher requirements for the quality of the ground floor landscaping. The I values of H1, H2, and H3 related to the rooftop activity space are lower than the average value among the 60+ age samples, indicating that the group is uninterested in rooftop activities and prefers ground activities.

In the aspect of residential areas, recreation space, neighborhoods, and parking issues are still in the main improvement areas. In the samples under 30 years old and 30–45 years old, J2 is in quadrant IV, which shows more concerns about the creation of a walking environment. While in the samples 46–60 years old and over 60 years old, I4 appears in the “focused on improving” area, which reflects that this group pays more attention to the safety of recreation sites. Meanwhile, L1 and L2, which frequently appear in the “focused on improving” area in other samples, have p-values higher than the average in the samples over 60 years old, indicating that other age groups have higher requirements for the design related to neighborhood relations and inter-generational activities (

Table 7. IPA evaluation results based on age of residents.

	Flat Layout	Flat Public Area	Residential Area
<30
30–45
46–60
>60
Postscript

).

6. Discussion and Optimization

6.1. Discussion

The ultimate goal of the IPA model analysis is to propose optimization strategies for flat design and residential planning for multi-child family structures. Based on the principle of the IPA model, we should focus on the elements in quadrant IV, “priority improvement”, and take into account some special elements in quadrant III, “no priority”. Then, we should calculate the I and p-values of the screened elements and their interrelationships to distinguish the optimized ranking. The residential elements are selected and pooled from three major categories: flat lay out, flat public area, and residential area. Based on the aggregated IPA analysis, the differences of each subcategory are considered comprehensively, and the pool of residential elements to be optimized in each aspect is obtained through frequency statistics, supplemented by the field survey situation. The screening results are shown in

Table 8. Screening of residential elements to be optimized based on IPA analysis.

Type Classification		Set of Residential Elements in IPA Quadrant IV
Major Category	Subcategory	Flat Layout	Flat Public Area	Residential Area
Aggregation		D3, B4, D1, A2, B1	H3, E2, H1	I2, I3, L1, N2, L2, N3
City Type	1st-tier cities	D3, C4, C1, B3, D1, B4	G2, H3, H1, H2	M3, N3, L2, L3, N2
	New 1st-tier cities	B4, D3, D1, C3, B3	H3, H2, H1, G2, E2, E1	L2, N2, I2, L1, J2, J1, K2, N3
	2nd and 3rd-tier cities	D1, D3, C4, B3, C3, B4	H2, E2, H3, G3, F2, E1, H1, G2, E3	N2, N3, L2, J2, M2, I4, K3
	4th and 5th-tier cities	D1, C4, C3, B3, B4	H3,G2,E1	L2
Flat area	<90 m2	C4, B3, B4, D3, C3, B1, A2	F2, H2, G2, E1, H3, E2	M3, N1, N3, N2, M2, I3
	90–144 m2	B4, B3, C3, C4	H2, G3, H3, E1, H1, G2	M3, L2, N2, J2, N3
	>144 m2	C4, B3	H2, H3, E2	N3, I3, L2
Age of residents	<30	C4, B3, B4	H2, H3, G2, H1	J2, L1, L2, M2, M3, N1, N3
	30–45	D3, B3, B4	H2, E2, G2, E3, H3	N3, K2, N2, J2, L2, M2
	45–60	B4, B3, C3	H2, H3, G3, H4, E2, E3, H1, G2	L2, N2, N3, I4, J2, K1
	>60	D4, D5, B4	G3, E2	K4, I4, N3, L3, I3, N1
Post-Screening Collection		D3, B4, D1, A2, B1, C4	H2, H3, E2, H1, E1, G2, G1	I2, J3, I3, L1, N2, L2, N3, J2

.

If there is a difference in the priority ranking of each residential element in the set to be optimized, it is necessary to further rank the importance ranking of each element and divide it into high, medium, and low ranks. The method of differentiation takes into account the I value, p-value, and the difference between I and P. The higher the I value and the lower the p-value, the higher the priority level of optimization of residential elements, and vice versa. In addition, it is also necessary to eliminate the influence brought by too high or too low deviation of a single value of I or P. The points near the line based on the coordinate map Y = −X function in similar conditions are more in demand of optimization, as detailed in Equation (2):

$$S=\frac{\left(\mathrm{I}-\overline{\mathrm{I}}\right)\times \left(\overline{\mathrm{P}}-\mathrm{P}\right)}{\left|\left(\mathrm{I}-\overline{\mathrm{I}}\right)-\left(\overline{\mathrm{P}}-\mathrm{P}\right)\right|}$$

(2)

By calculating and ranking the above filtered residential elements one by one, we can obtain the optimization rank of each element in the three categories (

Table 9. Priority ranking for optimization of living elements based on IPA analysis.

	Priority Ranking of Optimization
	High	Medium	Low
S-value interval	(1, +∞)	[0, 1]	(−∞, 0)
Flat layout	D3, B4, D1	A2, B1	C4
Flat public area	H2, H3	E2, H1	E1, G1, G2
Residential area	I2	J3, I3, L1, N2, L2, N3	J2
Comprehensive evaluation	I2, H2, D3, B4, H3, D1	J3, I3, A2, L1, B1, N2, E2, L2, H1, N3	E1, C4, J2, G2, G1

).

Based on the IPA results, the residential elements to be optimized are quantitatively selected, and the corresponding optimization strategies are given in combination with door-to-door interviews. As shown in

Table 10. Optimization strategies based on IPA evaluation results.

	Focus on Improving the Residential Elements		Improvement Demand	Optimization Strategy	Priority
Flat layout	A2	Area of bedroom	Enlarge the living area and enlarge the size of the living room	Master bedroom area ≥ 14 m2, size ≥ 3.6 × 3.9 m	Medium
	B1	Area of living room		Living room area ≥14 m2, size ≥ 3.6 × 3.9 m	Medium
	D1	Area of dining room and kitchen		Dining area ≥ 9 m2, size ≥ 3.0 × 3.0 m	High
	B4	Storage capacity of living room	Increase storage space and equipment	Dedicated storage room, wall cabinets	High
	D3	Storage capacity of dining room and kitchen		Cabinetry kitchen appliances integration, increase the western kitchen operating table	High
	C4	Wet and dry separation in the bathroom		Avoid nesting design in master bathroom and introduce triple separation bathroom	High
Flat public area	E1	Ground floor activity space	Increase residential ground floor activity space and landscaping	The building is elevated on the ground floor to provide landscaping and event space	Low
	E2	Ground floor service Function	Integration of various life service functions	Expand the entrance foyer and increase various service equipment and facilities	Medium
	H1	Roof accessibility	Expanding rooftop activity space	Strengthen the orientation of roof space, arrange diversified activities, and focus on climate-adaptive design	Medium
	H2	Diversity of roof activities			High
	H3	Climate adaptation for roof activities			High
Residential area	I2	All-age recreation facilities in residential areas	Construction of mixed recreational facilities	Design all-age activity space to accommodate elderly caregiver–child behavior	High
	I3	Diversity of facilities in residential areas			Medium
	J2	Walking environment in residential areas	Improve the pedestrian environment of the residential area	Expand the width of pedestrian paths, improve barrier-free design, improve lighting and greening	Low
	J3	Sidewalk facilities in residential areas			Medium
	L1	Neighborhoods in residential areas	Reshaping and repairing neighborhoods	Expand the space for interaction activities	Medium
	L2	Inter-generational interaction in residential areas	Promote inter-generational interaction	Increase the content of inter-generational activities	Medium
	N2	Parking efficiency in residential areas	Increase the number of parking	Raise residential parking standards, add temporary parking spaces around residential areas	Medium
	N3	New energy parking in residential areas	Additional new energy vehicle parking and charging facilities	The proportion of new energy vehicle charging parking spaces increased to 20% and reserved for additional conditions	Medium

, each residential aspect is categorized using this method into one of four categories: to maintain, to oversupply, need no priority, or to upgrade. D3, B4, D1, A2, B1 in the residential suite, H2, H3 in the public part of the residential area, and I2, J3, I3, and L1 in the residential area are all prioritized for optimization. Corresponding design solutions have been proposed, informed by practical design experience.

6.2. Optimization Strategy for Flat Layout

The results of on-site research reflect that many existing residential units have problems such as insufficient space, ventilation, and lighting, insufficient storage, lack of functionality, insufficient area, and inflexible quantity. Through Python data crawling, it was found that during the process of family structure transformation, homebuyers are more inclined to have more rooms and larger living areas to meet diverse family usage needs. Three-bedroom, four-bedroom, and even more bedroom layouts, as well as larger areas, such as 90~144 m² and above, can better meet the housing needs of families with multiple children. Considering the existing housing standards in China, it is necessary to improve in D3, B4, D1, A2, B1. The following factors can be used to assist the optimization of design: increasing the size and area of rooms, more storage capacity, and a separate bathroom design (

Table 11. Flat layout elements derivation based on IPA analysis.

Type	Flat Layout Derivation
Entryway
	Width = 1.4 m Reserved storage cabinet space: 0.6 m × 1.6 m	Width = 1.2 m Reserved storage cabinet space: 0.4 m × 1.6 m	Width = 1.4 m Reserved storage cabinet space: 1.9 m × 1.4 m	Width = 1.2 m Reserved storage cabinet space: 0.4 m × 1.9 m, 0.6 m × 1.2 m
Living room and dining room
	7.4 m × 5 m Horizontal layout	3.6 m × 6.8 m Vertical layout	6.9 m × 10.8 m Vertical layout	7 m × 7.7 m L-shaped layout
Kitchen
	2.7 m × 3 m (U-shaped layout)	3.8 m × 2.3 m (L-shaped layout)	2.3 m × 5.3 m (L-shaped layout)	3.3 m × 3.9 m (Island layout)
Master Bedroom
	3.2 m × 5 m L-shaped coatroom	3.5 m × 6.7 m Parallel coatroom	5.9 m × 4.5 m L-shaped coatroom	6 m × 6.3 m U-shaped coatroom
Bedroom (Children)
	3.6 m × 3 m Bunk bed design	3.3 m × 3.6 m Semi-loft bed and ready-made bed design	3.3 m × 4.0 m Parallel design	3.3 m × 3.6 m Staggered high and low bed design
Bedroom (Parents)
	3.3 m × 3.9 m Crib can be placed		3.8 m × 3 m High and low beds designed to be shared with children
Master Bathroom
	2.4 m × 2.7 m 3-piece master bath set	2.2 m × 2.8 m 3-piece master bath set	3.5 m × 1.9 m 4-piece master bathroom set	2.5 m × 2.9 m 4-piece master bathroom set
Bathroom (Guest)
	1.8 m × 3.9 m Three-piece guest bath set	1.8 m × 2.9 m Three-piece guest bath set	2 m × 1.8 m Two-piece guest bath set	3 m × 1.7 m Triple Separate guest bath Bath with set

):

• Entryway: Providing for the storage needs of multi-child families should get special attention when handling the transition of areas while maintaining household privacy. It is recommended that the net width be at least 1.2 m, with some room for modest width increases to allow for transitions.
• Living room and dining room: In order to maximize the use of natural light and ventilation, the integrated design of the dining room and living room is usually adopted, and the area can be controlled between 20 and 25 m². To effectively meet the needs of children’s home care, a space of 30 to 40 m² is advised when dividing separate living and dining rooms. It is possible to increase storage capacity by employing built-in furniture, walls, and partitions. It is also beneficial to take into account furniture that can be expanded or contracted as needed. Basic functional requirements can be met with a compact layout measuring 3.6 m in width, whereas standard-sized families are generally advised to be between 3.6 and 4.5 m.
• Kitchen: By using integrated design techniques, a range of layout configurations, such as single-row, double-row, L-shape, U-shape, and island-type arrangements, can be used to maximize space utilization efficiency. To maximize functionality and safety in the kitchen, it is essential to have a sensible distance between kitchen appliances and between tall buildings.
• Bedroom: The number of bedrooms and their functional requirements change depending on the stage of family life. With flexible furniture or spatial partitioning, the number and arrangement of bedrooms can be readily changed to suit changes in family size and guarantee that every member has enough living space. A double bedroom should preferably have a minimum space of 9 m². Bedrooms in small to medium-sized homes usually have a useful area of 12~15 m², whereas master bedrooms in larger homes could have a 15~20 m² useable area.
• Bathroom: To create a safe and convenient environment, the master bathroom can be designed as an integral part of the master suite, taking into account potential future accessibility requirements. Features like accessible doors and anti-slip designs are crucial. Furthermore, guest bathrooms should address specific temporal needs, such as providing adequate space for baby toiletries during the child’s nurturing phase, hence boosting safety and cleanliness in the space.

6.3. Optimization Strategy for Flat Public Area

The results of on-site research reflect that homebuyers will consider family needs, economic conditions, and personal preferences when making choices, and the overall result shows this trend of diversification. Through data crawling, this study has identified the particular focus of multi-child families on specific residential elements during the selection process. Considering the existing housing standards in China, it is necessary to improve H2 and H3 in the public part of the residential area.

• Enrich the ground floor space and add activity space on the roof

In multi-child families, the younger children, in particular, exhibit a pressing need for outdoor activities. The ground floor elevated space and rooftop area stand out as the outdoor spaces most intimately linked to the residence. These areas are less influenced by weather conditions and, in practice, often serve as spaces where grandparents engage with their grandchildren. To foster this dynamic, regulations and policies should be strategically directed to encourage residential buildings to prioritize ground-floor elevated design whenever feasible. Additionally, there should be provisions for additional rooftop activity spaces equipped with corresponding facilities for activities, leisure, and safety, further enhancing the overall living experience.

• Optimize entry space

The entry space outside the flat serves as a transitional zone between the interior and exterior, with a tangible, functional demand for families with multiple children. This space frequently accommodates various strollers and sports equipment. Consequently, it is essential to secure ample room for these domestic conversions, striving to incorporate natural lighting and ventilation. To support this, policies should be tailored to provide specific preferences, such as halving the calculation of the pool area. Moreover, vigilant management and key supervision are crucial to prevent the unauthorized construction of miscellaneous piles in this area.

6.4. Optimization Strategy for Residential Area

Field research revealed that, while residential neighborhoods contain activity venues, they lack a variety of designs and are unable to promote community connection. Some age groups lack specifically devoted activity locations, which might pose safety risks due to location selection and floor design, as well as a lack of accessibility. In terms of landscape, while certain water bodies and architectural decorations have improved environmental quality, many pools are unused, and recreational amenities are inadequate. Insufficient parking ratios, chaotic charging facilities for motor vehicles, and rising demand for parking have resulted in arbitrary parking taking up road space. The results of Python data crawling are compatible with field research. Currently, multi-child families prioritize the environmental quality of residential regions, and newly developed residential areas with complete services and adequate parking spaces are frequently preferred. Given the high significance of I2, J3, I3, and L1 in the IPA evaluation, the following points can be stressed to influence the planning and design of residential areas.

• Supplementation and renovation of all-age recreation sites

Preschool children in multi-child families commonly engage in outdoor activities within the residential area, often accompanied by couples, grandparents, or caregivers. Currently, residential landscape spaces are designed based on functional divisions, including children’s playgrounds, senior activity fields, community squares, and fitness areas. To better address the diverse outdoor activity needs of young children, adults, and the elderly, it is imperative to transcend the traditional functional boundaries of these sites. The design should incorporate an interspersed approach, blending elements from each functional area to create an all-age activity field.

• Neighborhood atmosphere reshaping

A well-organized space not only fosters neighborhood interaction but also yields positive and healthy effects on children’s physical and mental health [49]. Firstly, the establishment of community facilities that seamlessly integrate activities for residents of different generations facilitates potential communication between these inter-generational groups. Illustratively, Germany’s “Multi-generational house” project amalgamates early childhood education, youth counseling, and other functions, creating a comprehensive multi-generational shared facility. This enables residents of varying ages to acquaint themselves and provide mutual assistance [50]. Secondly, the incorporation of inter-generational activities into neighborhood events enriches the overall content. For instance, community planting activities leverage inter-residential green spaces and rooftops to enhance contact opportunities for people of all ages. This approach not only fosters mutual trust but also strengthens neighborhood connections [51].

• Parking problem alleviation

According to the findings from the living demand survey, motor vehicles remain a primary mode of transportation for families with young children, particularly infants and toddlers. The demand for cars in multi-child families is robust, often necessitating the possession of two motor vehicles. Presently, residential areas lack sufficient parking spaces, and in new residential areas in Jiangsu Province, the design standard is one car per 100 m², falling short of accommodating two cars per family. Consequently, the second vehicle in many families lacks a designated parking space, and with a high adoption rate of new energy vehicles for the second purchase, a challenging parking and charging dilemma arises. To address this issue, it is advisable to enhance the parking ratio in newly built residential areas, aiming for an allocation of two cars per family. Additionally, established residential areas could consider implementing social parking spaces or providing night parking along roadways. The incorporation of charging facilities in these areas would help alleviate the challenges associated with both parking and charging.

7. Limitations of the Study

Although this study distributed questionnaires using a combination of online and offline methods while accounting for the influence of age structure, the geographical scope of the Yangtze River Delta region is vast, and data analysis results are inevitably limited by sample size, which may lead to certain errors.

It should be noted that the IPA has certain intrinsic limitations. IPA presupposes independence and linear correlation between variables on the dimensions of significance and satisfaction in terms of respondents’ overall assessment. Respondent ratings are often subjective in practical surveys, making it difficult to establish impartiality across estimates of the relevance and satisfaction of residential elements. This has two consequences; on the one hand, the prominence of residential elements is obviously determined by customer satisfaction ratings. On the other hand, when there is a non-linear connection between specific residential aspects and overall satisfaction, this relationship has a direct impact on consumers’ assessments of the importance of elements. The quality of evaluation in subsequent specific procedures can be improved by incorporating a partial correlation coefficient between the satisfaction of an individual residential element and overall satisfaction.

Additionally, this study used network crawling data to compare the IPA outcomes prior to developing the method. However, the optimization plan derived from analysis and evaluation must be applied in engineering practice to ensure the plan’s feasibility and reasonableness, as well as to make further adjustments.

8. Conclusions

The recent changes in China’s family structure have imposed several limitations on the construction of commercial housing. Much research has focused on this shift, launching a series of explorations for spatial development and augmentation. Contemporary research in this field predominantly centers on solutions, including the design of multi-child family flat layouts, equipment design, and variable adaptive housing design. To promote the long-term sustainable use of commercial housing and inform the optimization and design of commercial residential buildings, research identifying the root causes of inhabitants’ requirements is desperately needed. In order to provide guidance for real-estate development and residential design, this study examines and evaluates the current state of the real-estate supply in the YRD region in relation to the housing demand under the multi-child family structure, assesses the degree of response, and suggests appropriate improvement measures.

The study includes residential demand in the context of dynamic development in the family life cycle, and it employs a variety of approaches to ensure that the analysis and evaluation framework are rational. The scientific and systematic nature of housing demand research has been improved by employing semi-structured interviews, expert consultations, word frequency screening, and other methods to identify the influencing factors of housing for multi-child families, as well as Python data crawling to compare and interpret the analysis. It employs mixed methods to develop a three-tiered evaluation system for the residential elements of multi-child families. The system’s impact criteria are scientific and broad, making them relevant to a variety of resident satisfaction rating scenarios.

The study broadens the scope of traditional research on family housing needs by including residential units, public areas, and residential areas in the composition of residential elements, in contrast to the current situation where most research on family structure and housing is restricted to the interior space of residential units. In this study, 3 major categories, 14 subcategories, and 65 residential aspects make up the IPA evaluation framework. A total of 739 households in the YRD region are included in the study, which takes into account various factors such as city type, flat area, and age of residents. This study effectively illustrates the housing requirements of YRD region multi-child families.

IPA analysis based on importance and satisfaction evaluation can help decision-makers avoid the wasteful use of resources that arises from the limitations of traditional methods by supporting them in accurately identifying priorities and combining field research and network data for verification during the actual construction and optimization of residential communities. It is also essential for the early evaluation of such restorations and offers a scientific basis for the “precision” implementation of extensive upgrades in residential communities. It reveals residential factors that need renovation from the user’s perspective, as well as their priority order. This provides a systematic reference for flat layouts, flat public areas, and residential areas, paving the way for optimal residential development, which is crucial for SDGs 2030 in infrastructure and buildings.