Integrated Environmental Perception and Civic Engagement: The Mediating Role of Residential Satisfaction in Urban Migrants’ Community Participation Intention

Abstract

With the rapid advancement of urbanization, urban migrants’ willingness to participate in community affairs plays a vital role in urban social governance. However, existing studies have paid insufficient attention to the psychological mechanisms through which urban migrants translate perceptions of their residential environment into participation intentions, particularly lacking systematic examinations of the mediating role of residential satisfaction. Drawing on Social Exchange Theory, this study develops a mediation model of “environmental perception → residential satisfaction → community participation intention” to explore how urban migrants’ perceptions of their living environment shape their intention to participation in community affairs via residential satisfaction. A questionnaire survey was conducted among 315 urban migrants in Nanjing, China, and the data were analyzed using structural equation modeling. The results reveal that (1) housing conditions, supporting facilities, property management, and the humanistic environment significantly enhance residents’ residential satisfaction, thereby stimulating their intention to participate in community affairs; (2) while location attributes and transportation have no significant direct effects on community participation intention, they can promote participation indirectly through residential satisfaction; and (3) policy perception neither directly influences community participation intention nor indirectly affects it via residential satisfaction. This study uncovers the underlying mechanisms of urban migrants’ community participation, offering both theoretical insights and practical implications for improving the effectiveness of community governance.

1. Introduction

With the acceleration of globalization and urbanization, large-scale population mobility has become a defining trend of the contemporary era. The migration of individuals—particularly from rural or smaller cities to urban areas—not only reshapes urban demographics but also fuels urban growth in emerging economies [1]. As a result, migrants’ community participation has emerged as a critical factor for urban management efficiency, sustainable development, and social integration in these diverse and rapidly changing contexts [2].

Urban migrants bring renewed dynamism to city development—contributing notably to infrastructure construction and service sectors. However, their integration remains a universal challenge. Materially, issues like insufficient infrastructure, basic living conditions, and environmental resources persist [3]. Socio-culturally, migrants often face exclusion and identity crises, weakening their social belonging and dampening their intention to participate in community affairs [4].

Community participation is recognized as a critical pathway for migrant integration. It enhances cultural adaptability [5], strengthens social capital [6], and improves psychological well-being [7]. Beyond these immediate benefits, fostering active community engagement is fundamental to achieving socially sustainable cities. Social sustainability necessitates the development of inclusive, cohesive, and participatory communities where all residents, including migrants, can thrive. Residential satisfaction plays a key role in this process, influencing individuals’ perceptions and behaviors [8], which in turn reinforces social cohesion and sustainable urban governance. Migrants who are more satisfied with their living environment are more likely to engage in community participation [9]. Prior studies have demonstrated links between residential satisfaction and quality of life [10], sense of belonging [11], social integration [12], and the development of social capital [13].

Nevertheless, existing research presents three key gaps. First, environmental perception has been narrowly defined, focusing mainly on physical elements while neglecting socio-cultural dimensions. Second, limited attention has been paid to migrants’ perceptions of public policies, such as rental subsidies and household registration reforms, which may influence their behavioral decisions. Third, the mediating role of residential satisfaction in the relationship between environmental perception and community participation intention remains underexplored, particularly in rapidly urbanizing contexts where understanding these mechanisms is essential for sustainable development.

In this context, several research questions arise.

• What are the constituent dimensions of environmental perception for urban migrants, and how can a comprehensive assessment framework be constructed?
• What are the current levels of residential satisfaction and community participation intention among urban migrants, and what obstacles and preferred forms of participation do they report?
• To what extent does residential satisfaction mediate the relationship between environmental perception and community participation intention?

To address these questions, this study makes three primary contributions, each corresponding directly to the research questions above. First, it develops and validates a multidimensional framework for environmental perception, integrating fundamental, security, and socio-cultural ties to address the first research question and overcome the narrow definitions prevalent in existing literature. Second, it employs a rigorous empirical approach to diagnose the current state of residential satisfaction and community participation intention among urban migrants. Third, and most significantly, it introduces and empirically tests a mediation model that clarifies the mechanism through which environmental perception influences participation intention, precisely quantifying the mediating role of residential satisfaction to resolve the third research question.

Through these contributions, this study not only bridges identified research gaps but also offers actionable insights for policymakers aiming to foster more inclusive and sustainable urban communities.

2. Theoretical Foundation and Hypothesis Development

2.1. Theoretical Foundation and Conceptual Model

Social Exchange Theory (SET) provides a vital framework for understanding migrants’ participation in community affairs. It suggests that individuals engage in behaviors based on rational evaluations of “resource acquisition” and “reciprocity” [14,15]. In China, this reciprocity is culturally expressed through “renqing” (denoting reciprocal obligation) and “guanxi” (denoting interpersonal networks). Migrants’ community participation can thus be viewed as a form of social exchange. Empirical studies confirm that resource provision—such as organizational support or public services—promotes engagement [16,17]. When migrants perceive adequate environmental resources, they are more likely to reciprocate through community participation [18]. This exchange operates through three progressive resource tiers.

• The Fundamental Tier, comprising housing conditions and supporting facilities, forms the material foundation for urban life.
• The Security Tier, encompassing property management and the humanistic environment, provides stability and psychosocial well-being.
• The socio-emotional tier, consisting of location attributes & transportation and policy perception, facilitates social opportunities and institutional trust.

The specific dimensions within each tier and their hypothesized relationships are detailed in Section 2.2.

These three resource tiers are interconnected and progressive, jointly explaining participation behaviors. Central to this process is residents’ overall evaluation of their environment. Conceptualized as the summary affective evaluation of the overall exchange relationship between a migrant and their community, residential satisfaction (RS) provides a structured framework for this evaluation [19]. Studies show that migrants with positive perceptions of community conditions—like cleanliness, safety, and neighbor relations—report higher residential satisfaction [9,20]. More importantly, satisfaction is not a passive state but transforms into participation through three mechanisms: (1) Psychological drive: Satisfaction strengthens belonging and reduces identity anxiety tied to outsider status [21]; (2) Behavioral incentive: Emotional attachment to the environment spurs motivation for civic engagement [22]; and (3) Resource conversion: A positive living experience motivates migrants to build social networks [23].

Within the SET framework, these mechanisms establish the pathway from environmental perception to residential satisfaction and ultimately to participation intention. The comprehensive conceptual model illustrating this mediating role is presented in Figure 1.

Based on this integrated reasoning, the following core hypothesis is proposed:

H1. 

Residential satisfaction positively influences urban migrants’ community participation intention.

Furthermore, it is hypothesized that environmental perception promotes community participation intention through the mediating effect of residential satisfaction.

The subsequent sections detail the six dimensions that constitute the three tiers and develop specific hypotheses regarding their relationships.

2.2. Hypothesis Development: The Three Tiers and Their Dimensions

Building upon the tiered model of environmental perception grounded in Social Exchange Theory (Section 2.1), this section details the six dimensions that constitute the three resource tiers and develops the specific hypotheses (H2a–H7b) linking them to residential satisfaction and participation intention.

2.2.1. The Fundamental Tier: Housing Conditions and Supporting Facilities

As the most fundamental level of resource provision, housing conditions and supporting facilities form the essential foundation for migrants’ cost–benefit evaluation in the urban social exchange process.

Housing conditions encompass the physical attributes of a residence, including size [9,24], structural quality [25], layout [26], sound insulation [27,28], and utility systems (e.g., water, electricity, heating) [24]. These are fundamental determinants of residential satisfaction. Housing costs, such as rent and management fees, also play a critical role. High housing costs can force households to cut essential expenses (e.g., healthcare, education, food), lowering quality of life and satisfaction [29]. Low-income migrants often face disproportionate housing cost burdens, leading to substandard living conditions and heightened dissatisfaction [30]. Conversely, quality housing facilitates social connections with local residents, providing channels for community participation [31].

Closely complementing housing conditions are supporting facilities, including education, healthcare, commercial, and recreational services, which significantly impact migrants’ living experiences, well-being, and satisfaction [32,33]. In community governance, access to quality healthcare reduces health risks and alleviates pressure on community resources [34], while also enhancing participation by increasing satisfaction with services [35]. Well-developed commercial facilities boost social capital, further improving governance efficacy [36]. Facilities also serve as platforms for interaction and resource access, fostering participation. For instance, studies in Canada’s prairie regions show that robust public services enhance cultural engagement and social cohesion [37], while facility shortages increase dissatisfaction and migration intentions [38]. This aligns with established research confirming that objective community characteristics, such as housing conditions and access to services, are fundamental determinants of residential satisfaction and sense of belonging [39].

Thus, the following hypotheses are proposed:

H2a. 

Housing conditions positively influence urban migrants’ residential satisfaction.

H2b. 

Housing conditions positively influence urban migrants’ community participation intention.

H3a. 

Supporting facilities positively influence urban migrants’ residential satisfaction.

H3b. 

Supporting facilities positively influence urban migrants’ community participation intention.

2.2.2. The Security Tier: Community Property Management and Humanistic Environment

Building upon fundamental resources, the security tier encompasses those factors that provide stability, trust, and psychosocial well-being, representing a higher level in the social exchange relationship.

Community property management ensures the efficient operation, maintenance, and value maximization of community assets [40]. Effective maintenance of public facilities [41], green spaces [42], and high safety standards [43] enhance living comfort, while poor management, such as disorganized parking, breeds dissatisfaction and weakens belonging [44]. Research indicates that property management boosts satisfaction and participation by optimizing resource allocation [45], fostering community identity [46], and providing tailored support for vulnerable groups [47]. Transparent and standardized management practices further encourage participation [48].

Working in concert with formal management systems is the humanistic environment, which refers to the social, cultural, and psychological fabric of a community, shaped by activities, neighborly ties, and cultural initiatives [49]. These elements foster belonging and satisfaction [50,51]. In low-density suburban areas, neighbor relations and community cohesion are key predictors of satisfaction [52]. For migrants, who often feel like outsiders, psychological attachment and belonging significantly influence participation behaviors [53]. Culture, as a carrier of social capital, permeates community activities like facility management and decision-making, enhancing place attachment and civic engagement [54,55]. Diverse cultural environments facilitate social networks, enabling participation, while exclusionary attitudes or cultural conflicts suppress it [56,57].

Thus, the following hypotheses are proposed:

H4a. 

Community property management positively influences urban migrants’ residential satisfaction.

H4b. 

Community property management positively influences urban migrants’ community participation intention.

H5a. 

The humanistic environment positively influences urban migrants’ residential satisfaction.

H5b. 

The humanistic environment positively influences urban migrants’ community participation intention.

2.2.3. The Socio-Emotional Tier: Location Attributes & Transportation and Policy Perception

Representing the highest level of social exchange, the socio-emotional tier encompasses resources that facilitate full social integration, opportunity access, and a sense of institutional fairness, ultimately shaping migrants’ long-term stakes in the community.

Location attributes and transportation refer to the interplay of transportation networks and spatial layouts [58], influencing travel time [59], accessibility [58], costs [60], and proximity to workplaces [60,61]. Efficient transportation enhances daily mobility, community accessibility, and social integration, indirectly boosting satisfaction [62]. It also serves as a medium for community engagement by facilitating access to resources and public affairs [63,64].

Complementing the physical accessibility afforded by transportation is policy perception, which encompasses understanding and evaluating policy content, objectives, implementation, and impacts [65]. It significantly shapes behavioral responses and participation [66]. When citizens clearly understand and identify with local policies, they are more likely to experience a sense of security and satisfaction [67].

For migrants, the perception of receiving tangible benefits from policy measures leads to improved satisfaction with their living environment [68]. Conversely, policy uncertainty or restrictive measures exacerbate living challenges, lowering satisfaction. Empirical evidence from Bengaluru, India, confirms that a lack of affordable formal housing policies directly leads to the proliferation of informal, substandard settlements, severely undermining migrants’ residential satisfaction and well-being [69].

Globally, governments strive to create more satisfactory, inclusive, and participatory living environments for residents by providing affordable housing for middle- and low-income groups and implementing spatial planning strategies [70,71]. The core of policy lies not only in providing shelter but also in enhancing residents’ sense of community integration and life satisfaction by promoting mixed-income living in well-resourced areas. This, in turn, strengthens social participation and contributes to the development of more inclusive and equitable society [70]. Furthermore, within the Chinese context, the household registration system (hukou) and the urban–rural binary structure profoundly influence the allocation of housing resources and access to public services.

Thus, the following hypotheses are proposed:

H6a. 

Location attributes and transportation positively influence urban migrants’ residential satisfaction.

H6b. 

Location attributes and transportation positively influence urban migrants’ community participation intention.

H7a. 

Policy perception positively influences urban migrants’ residential satisfaction.

H7b. 

Policy perception positively influences urban migrants’ community participation intention.

Based on this analysis, a hypothesized theoretical model is established (see Figure 2).

3. Materials and Methods

3.1. Measurement Tool

This study, grounded in social exchange theory (SET), identifies six key dimensions of environmental perception that influence urban migrants’ community participation intention (CPI). The corresponding latent variables and their abbreviations are as follows: (1) housing conditions (HC); (2) supporting facilities (SF); (3) community property management (CPM); (4) humanistic environment (HE); (5) location attributes and transportation (LT); and (6) policy perception (PP).

These six latent variables are measured using 26 observed indicators, as detailed in

Table 1. Operationalization of the multi-dimensional environmental perception construct and its sources.

Abbreviations	Variables	Source
HC	Housing Conditions
HC1	Dwelling area	[9] *, [24] *, [25] *
HC2	Housing affordability	[29] *, [30] *
HC3	Building quality	[25] *, [32,33] *
HC4	Daylighting and ventilation	[24] *, [26] *, [33] *
HC5	Wall sound insulation performance	[27] *, [28] *
HC6	Utility infrastructure	[24] *, [26] *
SF	Supporting Facilities
SF1	Educational facilities	[32,33] *, [38] ***
SF2	Healthcare facilities	[32] *, [34] *, [35] ***
SF3	Recreational facilities	[32,33] *, [38] ***
SF4	Neighborhood commercial facilities	[33] *, [36] **
CPM	Community Property Management
CPM1	Property management fees	[48] **
CPM2	Facilities maintenance	[33] *, [41] *
CPM3	Parking management	[44] *
CPM4	Landscape maintenance	[38] ***, [42] *
CPM5	Neighborhood safety	[43] *
HE	Humanistic Environment
HE1	Community events	[50] **
HE2	Cultural promotion	[54] **
HE3	Neighborhood relations	[52] *, [56] **
HE4	Resident participation level	[55] **
HE5	Community belonging	[55] **, [57] **
LT	Location Attributes and Transportation
LT1	Travel time	[59] *
LT2	Transportation accessibility	[32,58] *
LT3	Transportation cost	[60] *
LT4	Job accessibility	[60,61] *
PP	Policy Perception
PP1	Policy awareness	[65] **, [67] *
PP2	Policy efficacy	[65] **, [68] ***

Note: * Citations related to residential satisfaction; ** citations related to community participation; *** citations related to both residential satisfaction and community participation.

.

The survey instrument is composed of three main sections, aiming to capture a comprehensive picture of urban migrants’ demographic characteristics, community participation intention, and levels of residential satisfaction.

(1) Personal Characteristics of Respondents

This section includes 11 questions pertaining to the individual background of urban migrants, covering variables such as gender, age, occupation, marital status, hukou status (household registration), years of residence in Nanjing, duration of social security contributions, education level, housing tenure, and average monthly income.

(2) Intention and Actual Behavior in Community Governance

This section investigates both the current engagement of urban migrants in community governance and their intention to participate. It also explores reasons for non-participation and preferences regarding community public affairs. A total of six items are included.

(3) Residential Satisfaction Scale for Urban Migrants

A Likert-scale instrument was developed to evaluate urban migrants’ residential satisfaction. The instrument encompasses three core constructs: overall residential satisfaction, six dimensions influencing satisfaction—housing conditions, supporting facilities, community property management, humanistic environment, location attributes and transportation, and policy perception. Respondents rated the corresponding measurement items on a five-point scale, where 1 = very dissatisfied, 2 = dissatisfied, 3 = neutral, 4 = satisfied, and 5 = very satisfied.

3.2. Research Area and Data Collection

This study focuses on Nanjing, the capital of Jiangsu Province, as a quintessential major Chinese city experiencing rapid urbanization—with a rate projected to reach 87.3% by 2024 [72]. Its status as a living laboratory for migrant integration is driven by large-scale inward migration, a relaxation of household registration (hukou) policies, and the aggregation of high-quality public services. As shown in the geographical and socio-demographic context of Figure 3 and

Table 2. Summary of socio-demographic characteristics for the surveyed urban migrant sample (N = 315).

Item	Category	Quantity	%	Item	Category	Quantity	%
Gender	Male	163	51.7	Nanjing household registration	true	38	12.1
	Female	152	48.3		false	277	87.9
Age	≤18	0	0.0	Industry (Occupation)	Public institution	18	5.7
	18–35	196	62.2		Professionals	22	7.0
	36–50	106	33.7		Freelancer	73	23.2
	51–60	13	4.1		Individual business	57	18.1
	≥60	0	0.0		Services	60	19.0
Education level	Junior school and below	40	12.7		Non-employed	79	25.1
	High school	65	20.6		Other	6	1.9
	Junior college	93	29.5	Ownership of housing	Rental	131	41.6
	Undergraduate	105	33.3		Employer-provided	127	40.3
	Master’s and above	12	3.8		Owner-Occupied	57	18.1
Length of residence	1–3 years	186	59.0		<3000 CNY	94	29.8
	3–5 years	95	30.2	Average monthly income	3001–5000 CNY	107	34
	≥6 years	34	10.8		5001–8000 CNY	81	25.7
					>8000 CNY	33	10.5

, these factors have created distinct socio-spatial patterns and intensified real-world concerns among migrants. Consequently, the multidimensional indicators of environmental perception outlined in Table 1—spanning housing conditions, supporting facilities, community property management, etc.—are highly relevant in this setting. Nanjing’s ongoing expansion and policy innovations thus offer a representative context to examine how environmental perceptions shape migrants’ residential satisfaction and civic engagement. To empirically investigate this relationship, a structured questionnaire was developed based on the multidimensional indicators mentioned above. A pilot survey conducted in a Nanjing community was used to refine the questionnaire prior to the formal study.

The formal survey then employed a stratified sampling strategy to ensure representativeness, resulting in the selection of four representative residential communities across the Jiangning, Qixia, and Yuhuatai districts (as shown in Figure 3). These communities were chosen from typical areas with high concentrations of migrant residents, such as affordable housing complexes, youth apartments, and older rental-dense neighborhoods. These areas are primarily inhabited by recent graduates, startup employees, families relocating for children’s education, and low- to middle-income workers in the construction, catering, and service sectors—closely aligning with the study’s target population. All respondents were informed of the study’s purpose, anonymity, and data confidentiality. Participation was entirely voluntary.

A total of 376 questionnaires were collected. To ensure sample validity, 61 responses were excluded based on the following criteria: residence in Nanjing for less than one year, holding local hukou for more than three years, or contributing to local social security for less than one year (or not at all). This yielded 315 valid responses for analysis.

Demographically, the sample was gender-balanced (51.7% male, 48.3% female). Most respondents (62.2%) were aged 18–35, and 33.7% were 36–50. Regarding education, 87.3% had at least completed high school, with bachelor’s degree holders comprising the largest group (33.3%). The vast majority (87.9%) were non-local hukou holders, and over half had lived in Nanjing for one to three years.

In terms of employment, 25.1% were non-working (students, retirees, or unemployed), followed by freelancers (23.2%) and service workers (19%). Monthly income was generally low, with 63.8% earning under 5000 RMB. Housing conditions showed that only 18.1% owned property in Nanjing, while 41.3% rented and 40.3% lived in employer-provided housing or dormitories. Detailed demographic data are presented in Table 2.

3.3. Validation of Questionnaire Data and Statistical Analysis

To verify the quality of the questionnaire data and conduct statistical analysis, this study employed SPSS 26.0 and AMOS 22.0 software. The analysis included reliability testing, validity testing, and structural equation modeling (SEM).

3.3.1. Reliability Testing

Reliability testing is a statistical approach used to assess the consistency, stability, and dependability of measurement results obtained through questionnaires. In this study, Cronbach’s alpha coefficient was used to evaluate the internal consistency of each dimension of the questionnaire. Cronbach’s alpha is a widely accepted metric that estimates the internal reliability of a scale based on a specific formula:

$$\mathsf{\alpha } = {\displaystyle \frac{\mathrm{K}}{\mathrm{K} - 1}}\left(1 - {\displaystyle \frac{\sum {\mathrm{S}}_{\mathrm{i}}^2}{{\mathrm{S}}_{\mathrm{x}}^2}}\right)$$

(1)

where $\mathsf{\alpha }$ denotes the reliability coefficient; K represents the number of test items; ${\mathrm{S}}_{\mathrm{i}}^2$ is the variance of scores for item i across all respondents; and ${\mathrm{S}}_{\mathrm{x}}^2$ is the total variance of the summed scores.

Cronbach’s alpha values range from 0 to 1, with higher values indicating stronger reliability. Typically, values between 0.7 and 0.8 suggest acceptable reliability, values between 0.8 and 0.9 reflect good reliability, and values above 0.9 indicate excellent reliability. In this study, the Cronbach’s alpha values for all dimensions exceeded 0.8, as calculated using SPSS 26.0. This demonstrates a high level of internal consistency across the questionnaire items, indicating that the data are sufficiently reliable for subsequent analysis and modeling (see

Table 3. Reliability analysis demonstrating high internal consistency for all multi-item constructs in the measurement model.

Latent Variable	Code	Description	Cronbach’s Alpha
Housing conditions	HC1	Dwelling area	0.938
	HC2	Housing affordability
	HC3	Building quality
	HC4	Daylighting and ventilation
	HC5	Wall sound insulation performance
	HC6	Utility infrastructure
Supporting facilities	SF1	Educational facilities	0.911
	SF2	Healthcare facilities
	SF3	Recreational facilities
	SF4	Neighborhood commercial facilities
Community property management	CPM1	Property management fees	0.924
	CPM2	Facilities maintenance
	CPM3	Parking management
	CPM4	Landscape maintenance
	CPM5	Neighborhood safety
Humanistic environment	HE1	Community events	0.920
	HE2	Cultural promotion
	HE3	Neighborhood relations
	HE4	Resident participation level
	HE5	Community belonging
Location attributes and transportation	LT1	Travel time	0.918
	LT2	Transportation accessibility
	LT3	Transportation cost
	LT4	Job accessibility
Policy perception	PP1	Policy coverage	0.829
	PP2	Public services
Residential satisfaction	RS1	Overall residential satisfaction	0.878
	RS2	Cost-effectiveness of housing
	RS3	The living and cultural atmosphere of Nanjing
Community participation intention	CPI1	Do you think residents’ community participation is important for improving the community environment?	0.920
	CPI2	Are you willing to contribute your time and energy to community participation?
	CPI3	If conditions permit, do you have the intention to participate in discussions or decision-making regarding community public affairs?
Overall reliability	0.934

).

3.3.2. Validity Testing

Validity testing is a statistical and empirical process used to evaluate whether a measurement instrument accurately and effectively measures the intended constructs or variables. In this study, two key components of construct validity were assessed: convergent validity and discriminant validity.

For convergent validity, the Average Variance Extracted (AVE) and Composite Reliability (CR) were calculated for each latent construct in the model. The formulas for AVE and CR are shown in Equation (2) and Equation (3), respectively:

$$\mathrm{AVE} = {\displaystyle \frac{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathsf{\lambda }}_{\mathrm{i}}^2}{\mathrm{n}}}$$

(2)

$$\mathrm{CR}={\displaystyle \frac{{\left({\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathsf{\lambda }}_{\mathrm{i}}\right)}^2}{{\left({\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathsf{\lambda }}_{\mathrm{i}}\right)}^2+{\sum }_{\mathrm{i}=1}^{\mathrm{n}}\left(1-{\mathsf{\lambda }}_{\mathrm{i}}^2\right)}}$$

(3)

where ${\mathsf{\lambda }}_i$ represents the standardized factor loading of indicator i, n is the number of indicators, and $1-{\mathsf{\lambda }}_i^2$ represents the measurement error variance of each indicator.

As shown in

Table 4. Assessment of convergent validity: factor loadings (Std.), composite reliability (CR), and average variance extracted (AVE) meet established thresholds for all constructs.

Dimensions	Item	Significance Estimation				Std.	SMC	CR	AVE
		UnStd.	S.E.	t-Value	p
Housing conditions	HC6	1.000				0.869	0.755	0.938	0.718
	HC5	1.014	0.053	19.126	***	0.827	0.684
	HC4	1.023	0.049	20.856	***	0.867	0.751
	HC3	0.964	0.049	19.524	***	0.837	0.700
	HC2	1.012	0.05	20.148	***	0.851	0.725
	HC1	1.016	0.053	19.266	***	0.831	0.69
Supporting facilities	SF4	1.000				0.859	0.737	0.911	0.719
	SF3	0.928	0.052	17.739	***	0.818	0.668
	SF2	1.054	0.054	19.479	***	0.868	0.753
	SF1	0.991	0.053	18.745	***	0.846	0.716
Community property management	CPM5	1.000				0.834	0.695	0.924	0.710
	CPM4	1.000	0.058	17.160	***	0.812	0.659
	CPM3	1.005	0.056	18.100	***	0.841	0.707
	CPM2	1.059	0.056	19.004	***	0.867	0.752
	CPM1	1.017	0.054	18.688	***	0.858	0.736
Humanistic environment	HE5	1.000				0.751	0.564	0.921	0.700
	HE4	1.137	0.070	16.323	***	0.881	0.776
	HE3	1.049	0.067	15.653	***	0.849	0.720
	HE2	1.005	0.067	15.075	***	0.821	0.674
	HE1	1.084	0.067	16.177	***	0.847	0.764
Location attributes and transportation	LT4	1.000				0.834	0.695	0.918	0.738
	LT3	0.991	0.054	18.225	***	0.848	0.718
	LT2	0.975	0.053	18.395	***	0.853	0.727
	LT1	1.134	0.057	19.902	***	0.899	0.809
Policy perception	PP2	1.000				0.889	0.790	0.832	0.713
	PP1	0.903	0.130	6.950	***	0.797	0.634
Residential satisfaction	RS1	1.000				0.859	0.732	0.879	0.709
	RS2	0.876	0.051	17.213	***	0.830	0.689
	RS3	0.926	0.053	17.450	***	0.839	0.704
Community participation intention	CPI1	1.000				0.879	0.772	0.921	0.795
	CPI2	1.002	0.043	23.281	***	0.926	0.858
	CPI3	0.889	0.043	20.985	***	0.868	0.754

Note: SMC—Squared Multiple Correlation; CR—Construct Reliability; AVE—Average Variance Extracted; *** Significance level is p < 0.001.

, all constructs met the recommended thresholds for convergent validity (AVE ≥ 0.50 and CR ≥ 0.70), indicating that the observed indicators reliably reflect the latent constructs and that the internal structure of the model aligns with theoretical expectations.

For discriminant validity, the square roots of the AVE values for each construct were compared against the inter-construct correlation coefficients. As presented in

Table 5. Confirmed discriminant validity among all constructs.

	AVE	HC	SF	CPM	HE	LT	PP	RS	CPI
HC	0.718	0.847
SF	0.719	0.254	0.848
CPM	0.710	0.340	0.223	0.843
HE	0.700	0.361	0.296	0.432	0.837
LT	0.738	0.295	0.256	0.292	0.392	0.859
PP	0.713	0.313	0.241	0.205	0.148	0.138	0.844
RS	0.709	0.434	0.413	0.459	0.561	0.464	0.236	0.842
CPI	0.795	0.465	0.379	0.451	0.485	0.369	0.231	0.554	0.891

Note: Bolded type is the square root of the AVE value.

, the square root of each AVE exceeded the corresponding inter-construct correlations, confirming a high level of distinctiveness among the constructs. This suggests that each latent variable captures unique aspects of the respondents’ perceptions, further supporting the model’s overall validity.

3.3.3. Structural Equation Modeling and Model Fit Evaluation

Given that the Structural Equation Modeling (SEM) approach has been successfully applied in previous studies investigating satisfaction mechanisms in similar urban contexts in China [73], this study employs it to empirically test and analyze the hypothesized relationships proposed in the research framework.

A complete SEM typically consists of two parts: a measurement model and a structural model. The measurement model defines the relationships between latent variables and their corresponding observed indicators, while the structural model captures the relationships among latent variables. For example, in a simplified measurement model with four observed indicators (as illustrated in Figure 4), the system of equations includes:

• Measurement equation

  $$\mathrm{X}={ \mathsf{\Lambda }}_{\mathrm{x}}\mathsf{\xi }+\mathsf{\sigma }$$

  (4)

  $$\mathrm{Y}={ \mathsf{\Lambda }}_{\mathrm{y}}\mathsf{\eta }+\mathsf{\epsilon }$$

  (5)

Measurement equations are sets of equations used to represent the relationship between observed variables $\mathrm{X}$ and $\mathrm{Y}$ and latent variables $\mathsf{\xi }$ and $\mathsf{\eta }$.

2.

Structural equation

$$\mathsf{\eta }=\mathsf{\beta }\mathsf{\eta }+\mathsf{\tau }\mathsf{\xi }+\mathsf{\zeta }$$

(6)

Structural equations are sets of equations that represent the relationship between latent variables $\mathsf{\xi }$ and latent variables $\mathsf{\eta }$.

Based on these two sets of equations and the specified model structure, an iterative estimation process is used to derive the model parameters.

Before proceeding to analyze the parameter estimates, the model fit of the overall model must be evaluated. Model fit refers to the degree to which the hypothesized theoretical model aligns with the observed data. AMOS 22.0 provides a range of fit indices that assess model fit from various perspectives (see

Table 6. Excellent goodness-of-fit indices for the structural equation model, indicating a strong match between the proposed model and the observed data.

Model Fit Measure	Recommended Level of Model Fit Measure	Score	Results
CMIN/DF	1–3	1.159	Good
GFI	>0.8 acceptable; >0.9 goodness of fit	0.911	Good
AGFI	>0.8 acceptable; >0.9 goodness of fit	0.893	Good
IFI	>0.9	0.991	Good
TLI(NNFI)	>0.9	0.989	Good
CFI	>0.9	0.991	Good
RMSEA	<0.08 acceptable; <0.05 goodness of fit	0.022	Good

). The chi-square to degrees of freedom ratio (CMIN/DF) is 1.159, which falls within the ideal range of 1 to 3. The Tucker–Lewis Index (TLI), Incremental Fit Index (IFI), and Comparative Fit Index (CFI) all exceed 0.90, indicating a good fit. Additionally, the Goodness-of-Fit Index (GFI) and Adjusted Goodness-of-Fit Index (AGFI) are 0.911 and 0.893, respectively, both meeting the acceptable minimum threshold of 0.80. The Root Mean Square Error of Approximation (RMSEA) value is 0.022, well below the maximum acceptable cutoff of 0.08, further confirming the model’s excellent fit to the data.

4. Results

4.1. Residential Satisfaction and Community Participation Among Urban Migrants

By calculating the average scores of respondents across various survey items, this study provides a straightforward assessment of urban migrants’ satisfaction with their residential environment and their attitudes toward community participation.

The overall satisfaction scores for the six dimensions—housing conditions, supporting facilities, community property management, humanistic environment, location attributes and transportation, and policy perception—were 3.55, 3.53, 3.54, 3.69, 3.76, and 3.70, respectively. These results indicate that urban migrants’ satisfaction with their living environment generally falls in the upper-middle range. While not particularly high, these values suggest a moderately favorable perception of the community experience. A detailed breakdown of satisfaction levels across each dimension and their associated indicators is illustrated in Figure 5.

The average score for community participation intention was 3.36, also reflecting a moderately positive attitude. However, when asked whether they had actually taken part in community public affairs, more than 50% of respondents reported either no participation or only occasional involvement. This reveals a gap between migrants’ subjective intention to engage and their actual participation, which remains limited. The primary reasons cited for this discrepancy include “time and energy constraints”, “distrust in decision-making processes or outcomes of Community participation”, and “perceived limited efficacy of individual participation” (see Figure 6).

Regarding preferences for types of public affairs, urban migrants expressed the highest interest in participating in “cultural-recreational and educational activities”, followed by “public facility improvement and maintenance” and “environmental protection and greening enhancement” (see Figure 7).

4.2. Hypothesis Testing of Urban Migrants’ Community Participation Intention

The research model treats urban migrants’ community participation intention as the dependent variable, with housing conditions, supporting facilities, community property management, humanistic environment, location attributes and transportation, and policy perception as latent variables. Residential satisfaction is introduced as a mediating variable. Structural Equation Modeling (SEM) is employed to explore how these latent variables influence the dependent variable through the mediating role of satisfaction.

Using AMOS 22.0, a structural model was constructed to estimate standardized path coefficients and the relationships among variables. The results of significance testing are shown in

Table 7. Results of testing the research hypotheses.

Hypotheses	Impact Paths	Standardized Estimate	S.E.	C.R.	p	Results
H1	RS → CPI	0.214	0.092	2.916	0.004 **	Support
H2a	HC → RS	0.150	0.055	2.678	0.007 **	Support
H3a	SF → RS	0.189	0.052	3.523	***	Support
H4a	CPM → RS	0.174	0.057	3.065	0.002 **	Support
H5a	HE → RS	0.292	0.064	4.744	***	Support
H6a	LT → RS	0.201	0.056	3.624	***	Support
H7a	PP → RS	0.036	0.055	0.661	0.509	Not support
H2b	HC → CPI	0.201	0.07	3.522	***	Support
H3b	SF → CPI	0.136	0.067	2.481	0.013 *	Support
H4b	CPM → CPI	0.165	0.073	2.863	0.004 **	Support
H5b	HE → CPI	0.152	0.083	2.406	0.016 *	Support
H6b	LT → CPI	0.065	0.071	1.16	0.246	Not support
H7b	PP → CPI	0.019	0.068	0.351	0.726	Not support

Note: *** indicates significance at the 1‰ level; ** indicates significance at the 1% level; * indicates significance at the 5% level.

. Among the proposed hypotheses, H7a (policy perception → residential satisfaction), H6b (location attributes and transportation → community participation intention), and H7b (policy perception → community participation intention) were not supported by the data, while all other hypotheses were validated. A simplified visualization of the significant paths is presented in Figure 8.

4.3. Mediating Effect of Residential Satisfaction

Residential satisfaction plays a crucial mediating role in influencing urban migrants’ community participation intention, particularly in relation to housing conditions, supporting facilities, community property management, humanistic environment, and location attributes & transportation.

Based on the analysis results from AMOS 22.0, the findings indicate that—except for policy perception—housing conditions, supporting facilities, community property management, humanistic environment, and location and transportation all exert indirect influences on migrants’ intention to participate in governance through the mediating effect of residential satisfaction (see

Table 8. Mediating effects of residential satisfaction by predictor.

Relationship	Estimate	Lower	Upper	p
HC → RS → CPI	0.039	0.006	0.113	0.016 *
SF → RS → CPI	0.050	0.008	0.131	0.011 *
CPM → RS → CPI	0.047	0.007	0.129	0.016 *
HE → RS → CPI	0.082	0.022	0.186	0.008 **
LT → RS → CPI	0.054	0.012	0.136	0.010 *
PP → RS → CPI	0.010	−0.020	0.070	0.458

Note: ** indicates significance at the 1% level; * indicates significance at the 5% level.

).

5. Discussions and Implications

5.1. Analysis of Multidimensional Satisfaction Evaluation

In the housing conditions dimension, urban migrants rated the indicator of wall soundproofing the lowest (mean = 3.48; see Figure 5). According to the survey, 81.9% of respondents live in rental units or employer-provided dormitories (see Table 2), and their dissatisfaction with sound insulation reflects a common privacy issue in high-density residential housing such as apartments and shared accommodations [28].

In the dimension of supporting facilities, commercial services (3.57) and basic education facilities (3.56) received relatively favorable evaluations. In contrast, healthcare facilities (3.50) and recreational amenities (3.50) were rated below the overall average (3.53), indicating that while the “survival needs” of urban migrants are generally met, the “developmental needs” are insufficiently addressed. Future policies should better respond to the diverse needs of migrants by providing a broader range of healthcare options, reducing medical costs, and enhancing mental health support [34]. Furthermore, developing multifunctional public spaces and integrating green infrastructure can help accommodate people of different ages and cultural backgrounds [74], thereby promoting the social integration of migrants into the community.

Regarding community property management, urban migrants gave higher ratings to facilities maintenance (3.57) and community security (3.67), but rated the rationality of property fees (3.44) and parking management (3.46) relatively low. Property fees lacking transparency, or service quality misaligned with costs, may trigger a trust crisis [48]. Unfair parking allocation and poor management also contribute significantly to dissatisfaction. In migrant communities, the scarcity of parking resources, combined with relatively closed social networks, intensifies resource competition [75]. Additionally, inadequate management of underground and roadside parking spaces further exacerbates the sense of inequity [44].

In terms of the humanistic environment, the sense of community belonging (3.59) was the only indicator rated below the overall average. This reflects a persistent weakness in the emotional integration of migrants. Due to limited interaction with local residents, migrants often struggle to form emotional connections [56], and may also lack a sense of identity with the physical and cultural aspects of the residential environment, thus diminishing their sense of belonging [57].

In the location and transportation dimension, proximity to the workplace (3.68) was the only indicator scoring below the overall mean, highlighting a severe job–housing mismatch among urban migrants. This problem is especially acute among low-income groups, who are often marginalized in urban systems and face limited access to quality housing and employment opportunities [76]. Moreover, public transportation networks in suburban and non-central areas are significantly less accessible than in central districts [60], exacerbating the spatial mismatch.

In the policy perception dimension, scores for policy awareness (3.71) and perceived policy efficacy (3.68) suggest that migrants have a basic understanding of relevant policies but do not demonstrate high levels of recognition or active engagement. This may result from limitations in the coverage and depth of policy communication, indicating the need for more effective policy dissemination strategies that not only convey information but also build trust and inspire action within migrant communities [77]. The relatively high awareness scores imply that although migrants are aware of policies, they may not perceive them as directly relevant or beneficial. Enhancing perceived policy efficacy could involve emphasizing tangible benefits such as improved access to healthcare and social services, and demonstrating how policies address migrants’ unique challenges [78].

5.2. Barriers and Preferences in Migrants’ Community Participation

Work-related stress and time constraints significantly reduce individuals’ opportunities to engage in community activities [79]. In a study on Latino communities, 17.2% of respondents identified limited time as their primary barrier to participation [80].

“I work six days a week, often overtime. By Sunday, I’m too tired to even think about a community event.”

(Respondent A)

A study in Sweden’s forensic psychiatric sector found that decision-making processes can be influenced by irrelevant biases, undermining the fairness and credibility of decisions [81]. This lack of trust may extend to community participation, where migrants question the effectiveness of their participation. In healthcare contexts, patients’ intention to participate in decision-making is directly influenced by the transparency of information and trust in the process [82], suggesting that opaque and unfair governance processes can suppress participation motivation among urban migrants.

“We give suggestions, but the decisions are already made. Our voices are just for show.”

(Respondent B)

Moreover, many migrants may perceive their individual efforts as having limited impact on community participation outcomes. In the aforementioned study of Latino communities, while many individuals volunteered, their motivation was more about collective improvement than personal influence [80]. This perception may lead migrants to believe that their participation would not bring about meaningful change, thus discouraging involvement.

“I’m just one person. What change can I possibly bring to the whole community?”

(Respondent C)

In terms of preferred public affairs, participating in cultural and educational activities helps migrants cope with migration-related stress, improves quality of life, and facilitates social network development, enhancing connections with local residents and reducing social isolation [83].

Interest in environmental protection and green space improvements stems from a desire for high-quality living environments. Urban greening projects not only improve physical surroundings but also foster community belonging and civic engagement through collective action [84].

Migrants also show considerable concern for the improvement and maintenance of public facilities, which directly affect their quality of life and social inclusion. Despite large-scale urbanization, many still face limited access to healthcare, education, and housing due to institutional barriers. This inequity drives migrants’ demand for better public facilities to meet basic needs. For instance, residents in rural Western China showed strong intention to pay for and participate in sanitation improvements, reflecting urgent infrastructure needs [85]. These findings underscore the critical role of the humanistic environment and supporting facilities in encouraging migrant participation in community participation.

5.3. Influencing Factors of Migrants’ Community Participation Intention

Housing conditions, supporting facilities, community property management, and the humanistic environment were found to have direct positive effects on residential satisfaction and community participation intention. These factors also indirectly influence community participation intention through the mediating effect of satisfaction.

The primary function of location and transportation is to improve commuting efficiency and spatial accessibility [62]. However, improvements in the physical environment do not directly motivate community participation. According to social exchange theory [14], effective social interaction requires reciprocal exchanges. Transportation convenience constitutes a one-way resource flow from the community to residents, lacking the reciprocal mechanism necessary to stimulate return actions. Time saved through better transport is often reallocated to work or household duties rather than social or leisure activities [86]. In migrant communities, residents prioritize employment and social networks [87], further weakening the direct impact of transportation on civic engagement. Migrants often occupy demanding jobs with long or irregular hours (an institutional economic reality), leaving little leisure time for community engagement. The cultural imperative to prioritize economic stability further reinforces this behavior. Thus, the time savings from improved transportation are effectively absorbed by the pressures of socioeconomic adaptation, leaving no surplus for participatory activities.

From a governance perspective, transportation is typically provided as a public utility without embedded mechanisms for fostering community reciprocity. It is a one-way governmental or commercial provision that does not inherently create social obligations or opportunities for interaction necessary to stimulate direct participation intention.

Transportation’s influence on community participation intention mainly occurs via residential satisfaction. Improved transport enhances personal utility—e.g., time savings and reduced stress [88]—which contributes to a better daily experience and emotional attachment to the community [62], ultimately leading to participatory behavior [64]. This finding highlights the importance of aligning transportation improvements with overall living quality to foster intrinsic motivation for participation.

Policy perception demonstrated no significant effect on either residential satisfaction or participation intention. This ineffectiveness stems from a fundamental institutional misalignment: top-down policy designs frequently overlook the bottom-up lived realities of migrants, whose primary concerns revolve around immediate livelihood security and employment [87,89]. This creates a core disconnect between policy content and migrant needs. Furthermore, cultural and governance barriers, such as language obstacles, complex bureaucracy, and implicitly discriminatory provisions, hinder policy comprehension and accessibility, eroding trust and neutralizing potential positive effects [90,91].

The failure of policy perception to translate into action underscores a priority of concrete exigencies over abstract knowledge. Migrant behavior is more influenced by immediate factors like cultural adaptation—the complex process of navigating new social norms, building trust, and securing a stable livelihood. This adaptive struggle often takes precedence over, and renders irrelevant, awareness of formal policies [92,93]. This pattern is cross-culturally consistent: for instance, Arab migrants’ health management is guided more by cultural adaptation than policy knowledge [92], and elderly migrants’ participation is affected more by risk of abuse than policy understanding [93]. This universal principle confirms that the practical socio-cultural and economic challenges inherent in the adaptation process consistently outweigh the perceived relevance of formal policies, explaining the non-significant pathways in our model. Consequently, a policy’s practical relevance is drastically diminished if it fails to align with the cultural backgrounds and socio-economic realities of migrants. As demonstrated in risk management and age-friendly communities research, interventions that are culturally sensitive and address immediate needs are significantly more effective at engendering participation [94,95].

Beyond this calculus of immediate priorities, the null effect of policy perception is further explained by two overarching contextual factors. First, structural and capability barriers—including language limitations, informational gaps, and socioeconomic constraints—likely prevent migrants from acting upon their policy awareness, even if present [90,96]. Second, and perhaps more critically, the influence of formal policy is often eclipsed by robust informal institutions. By relying on kinship networks and trusted community leaders for guidance, migrant communities create alternative pathways for information and decision-making. This dependence actively reinforces informal social networks, which become primary capital for adaptation and problem-solving, thereby diminishing the perceived need and relevance of top-down policy knowledge [97,98].

5.4. Implications

In the housing dimension, lighting, ventilation, and the availability of basic utilities (water, electricity, gas, heating) were found to contribute most to satisfaction—especially for late-working or co-renting migrants. Local housing authorities and planning departments should incorporate mandatory guidelines into building codes that prioritize north–south orientation and mandate minimum daylighting standards for new affordable rental housing projects. Comprehensive coverage and regular maintenance of utilities are also essential. To this end, local governments should establish a dedicated, publicly accountable task force for migrant-concentrated neighborhoods to conduct quarterly utility infrastructure inspections and mandate a 24-h response time for critical outages. Dissatisfaction with noise insulation highlights the privacy issues in dense housing. Spatial design should ensure a clear separation between private and shared areas, and incorporate movable partitions or modular layouts for flexible space use. Property developers and managers, incentivized by tax credits from municipal governments, should be encouraged to use soundproofing materials in new constructions and retrofits.

In terms of supporting facilities, healthcare and nearby commercial services have the strongest impact. Municipal urban planning bureaus should prioritize accessible medical and commercial infrastructure. For example, migrant communities can be equipped with community health centers offering basic medical care, health consultations, and chronic disease management. Real estate developers and planning authorities should also include convenient markets, 24-h convenience stores, and neighborhood supermarkets to reduce living costs. For education, nearby access to kindergartens, primary and secondary schools, and adult education should be ensured. Public leisure spaces can be enhanced by community organizations, in partnership with cultural and sports bureaus, repurposing idle buildings or parks for sports and cultural activities.

In community property management, migrants place high value on the maintenance of public facilities and the transparency of service charges. Efficient, transparent management builds trust and enhances participation intention. Housing authorities should mandate that property management companies in large migrant communities hold quarterly open forums, presenting simplified, multi-lingual financial reports and allowing residents to vote on the allocation of a portion of the service fee budget. Furthermore, property companies should be required to adopt a centralized digital management platform (e.g., WeChat mini-program) for maintenance requests, payment, and communication, ensuring transparency and trackability.

The humanistic environment (β = 0.082) plays the most critical role in enhancing participation intention, as evidenced by its strongest mediating effect in the structural model. As shown in Section 5.2, participation in cultural and educational activities—which received the highest selection rate (67.62%) among all participation preferences—not only enriches leisure time and cultural literacy but also promotes neighborhood interaction and reduces social barriers. However, these initiatives must account for the fact that “time and energy constraints” was the primary barrier, cited in 69.21% of all responses. Community initiatives should therefore focus on environmental protection and greening—which improve living conditions and foster a sense of belonging without imposing significant time burdens.

6. Conclusions

Grounded in social exchange theory, this study employed structural equation modeling to explore the pathways through which multidimensional environmental factors influence community participation intention via residential satisfaction. The findings not only confirm that housing conditions, public service facilities, community property management, and the humanistic environment significantly enhance residential satisfaction—which in turn strengthens participation intention—but also highlight the particular importance of the humanistic environment, underscoring the critical role of social and cultural factors in motivating civic engagement. This provides empirical support for the theoretical framework of “environmental perception → residential satisfaction → community participation intention”.

The study challenges conventional assumptions by revealing that location attributes and transportation and policy perception do not directly affect participation intention. This underscores the need for a more holistic understanding of the factors that drive civic engagement. Transportation improvements must be coordinated with overall living condition enhancements to leverage residential satisfaction’s mediating role, while participation strategies should address migrants’ actual needs through eliminating cultural–structural barriers and acknowledging informal networks.

Empirically, urban migrants reported a upper-middle overall level of participation intention. Key obstacles included work-time constraints, perceived inefficacy of participation, and institutional exclusion. Their participation preferences centered on activities offering tangible life improvements—such as cultural–educational events, environmental greening, and public facility maintenance—which directly enhance quality of life and facilitate social integration.

Limitations of this study are also acknowledged. First, the generalizability of the findings is constrained by the single-city (Nanjing) sampling strategy and the predominantly young, low-income demographic profile of respondents, which may not fully represent the diversity of migrant populations. Second, the cross-sectional design captures intention rather than actual behavior, limiting causal inference. Third, the non-significant effect of policy perception may stem from its measurement with a limited two-item scale. Future research should expand to multiple cities and respondents, employ longitudinal designs to track actual behavior, and develop more comprehensive measures of policy perception. Advancing these research directions will help build a more nuanced, dynamic framework for community participation and provide a scientific basis for inclusive, sustainable urban governance and migrant integration.