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Article

How Can Public Spaces Contribute to Increased Incomes for Urban Residents—A Social Capital Perspective

by
Yiqing Su
1,2,
Huan Xu
2 and
**aoting Zhang
3,*
1
Regional Social Governance Innovation Research Center, Guangxi University, Nanning 530004, China
2
School of Public Policy and Management, Guangxi University, Nanning 530004, China
3
School of Public Health, Fudan University, Shanghai 200032, China
*
Author to whom correspondence should be addressed.
Land 2024, 13(7), 945; https://doi.org/10.3390/land13070945
Submission received: 12 May 2024 / Revised: 20 June 2024 / Accepted: 26 June 2024 / Published: 28 June 2024
(This article belongs to the Special Issue A Livable City: Rational Land Use and Sustainable Urban Space)
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Abstract

:
The recovery of the global economy in the aftermath of COVID-19 faces enormous challenges. Ensuring stable income growth of the population has become an important means for develo** countries to ensure sustained economic development. Raising the overall income of the population is a public initiative that benefits all citizens; therefore, governments of develo** countries should promote the implementation of relevant public policies and the provision of public goods to ensure that existing economic instruments can benefit the entire population. In this regard, public space, as a typical form of public good, may play an important role in promoting the benefits of existing economic policies for all residents. This paper examines how residents’ use of public space contributes to their income growth through social capital. Hypotheses are tested based on an econometric analysis of 1565 questionnaires received from Chinese workers. The results show that residents’ use of public space can indeed be an important way to increase their income, which is realized through the enhancement of social capital. The research presented in this paper provides a new influence variable of public space to improve residents’ income. Further, it improves people’s understanding of the three classical concepts—public space, social capital, and income—by establishing the logical connection and theoretical explanation of physical space, emotional space, and value space in human society. The conclusions of this paper highlight the important role of public space in urban and rural development planning.

1. Introduction

The recovery of the global economy is facing enormous challenges as a result of COVID-19. Under these circumstances, ensuring that the population has stable income growth has become an important way for many countries around the world, especially develo** countries, to ensure the sustained development of their economies. However, for most develo** countries, efforts to increase residents’ income often encounter challenges such as economic recession, regional differences, diseases, natural disasters, and environmental pollution [1,2,3,4,5]. To address the question of how to enhance the income of residents in develo** countries, most existing policy options focus on the effects of economic factors. These include the promotion of the upgrading of the consumption structure and industrial structure, the optimization of human capital, and the transformation of the economic development mode [6,7,8]. However, judging from the currently available theoretical and practical results, promoting the increase in residents’ income is a systematic project. Excessive reliance on economic instruments will likely render economic policies ineffective, which further widens the income gap [9,10,11]. Therefore, how to combine economic policies with other means to avoid falling into the trap of increasing residents’ income deserves further attention.
From a public goods governance perspective, raising the overall income of the population is a public initiative that benefits all citizens. Therefore, governments in develo** countries need to ensure that the effects of already established economic instruments indeed reach the entire population by promoting the implementation of public policies and the provision of public goods [12]. In this regard, public space—a typical public good—may play a key role in facilitating existing economic policies to reach all residents and promote their income growth. Further, this paper finds that public spaces are important places for the cultivation of social capital, which can promote the formation of residents’ relationship networks, interpersonal trust, and reciprocal support. These three dimensions of social capital positively impact the increase in residents’ income. Based on the above background analysis, this paper explores how public space can be a new way to promote the growth of residents’ income in develo** countries. By analyzing the relationship between public space and social capital, new perspectives and strategies for increasing residents’ income can be provided.
Existing research on public space has focused on urban planning and governance, urban green space and residents’ well-being, as well as urban climate. For example, the use of artificial light sources in public spaces can meet the needs of pedestrians with various forms of visual impairments who are walking at night [13], the expansion of the area of urban public green spaces and the improvement of outdoor connectivity can help to improve local residents’ sense of security [14], and the establishment of shelters surrounded by trees and climbing plants can improve the comfort levels of residents during summer and effectively mitigate the urban heat island effect by reducing temperature differences in the surrounding environment [15]. Among the many studies on public space, the relationship between public space and social capital has received particular attention. Related studies have shown that urban streets can provide physical connectivity for social interactions, while the perceptual attributes of urban green space are conducive to facilitating communication among residents, thereby fostering higher levels of social capital [16,17,18]. Thus, through the layout and design of physical space, public space can provide a place where residents can interact socially, thereby promoting the cultivation of social capital.
With regard to the factors influencing the income of residents, relevant studies have emphasized the importance of factors such as educational attainment, family background, and professional skills. For example, the higher the level of education of the people, the more their incomes increase, and the income effect of receiving a higher level of education is more pronounced [19,20,21]; through their familial social connections, children from affluent families are more competitive in the labor market and are therefore more likely to enter the elite class [22]; plus, individuals with professional certificates and proficiency in their specific industry are more likely to be invited to job interviews and are more likely to obtain high-income positions [23]. Moreover, the relationship between social capital and residents’ income has also gradually received increasing scholarly attention. Research showed that residents can obtain effective information and resources and can promote income increase by expanding the size of their relationship network and strengthening social ties with others [24]. By building trusting relationships with friends, conflicts can be reduced, and thus, improvements in household poverty can be realized [25]. The positive role of social capital as a resource and support individual residents obtain in the social network to improve their income should not be ignored.
Further, a review of the literature showed that certain scholars have already conducted preliminary discussions on the effects of public spaces on income. For example, people can economize by growing their own produce in community gardens, thus lowering personal spending on household groceries and expanding their budgets [26]. Improvement and construction of sidewalks and roads provide opportunities for local residents to set up stores or stalls, thus generating and increasing their economic income [27]. Finally, residents can reduce the financial burden imposed by chronic diseases by using community green spaces to fulfill their recreational needs and achieve a longer and healthier life [28].
Despite the substantial progress of previous research in the areas of public space and social capital as well as social capital and residents’ income (several studies have also suggested that public space can increase residents’ income), there are still shortcomings in the existing research: Firstly, although existing research has found a possible relationship between public space and residents’ income, the specific mechanisms involved have rarely been explored. Secondly, although existing studies have found a possible relationship between social capital and residents’ income, how social capital is generated is rarely explored. This lack of exploration makes it impossible for people to find a concrete way to increase their income by promoting social capital in practice. Considering the important role of public space in promoting social interactions among residents and their accumulation of social capital, as well as the positive impact of social capital on residents’ income, based on the above analysis, this paper poses the following research questions: (1) Can public space contribute to increasing residents’ income? (2) Will residents realize an increase in personal income through the enhancement of social capital in the process of their use of public space? This paper provides systematic answers to these two questions by theoretically integrating public space, social capital, and residents’ income based on a web-based questionnaire survey conducted in China.
The possible contributions of this paper are as follows: Firstly, the new influencing variable of public space for raising residents’ income is identified, and a new perspective on how to raise residents’ income is provided. Secondly, this paper discusses the issue of how people’s use of public space can promote their increase in income, identifies the income effect of public space, and expands the available understanding of the importance of public space for human society. Thirdly, this paper systematically discusses the relationship between public space, social capital, and income increase, thus establishing a logical connection and theoretical explanation of physical space, emotional space, and value space in human society. This connection can improve people’s understanding of these three classical concepts.

2. Theoretical Analysis and Research Hypotheses

A glance at various types of literature and scholars’ views clearly shows that there are many definitions of public space. For example, Arendt (2013) [29] argued that public space is a place where citizens can freely express their opinions and participate in both political activities and social decision-making. However, Jacobs (2010) [30] argued that public space is a central place for people’s daily life and social interactions in the city, and it should be diverse and vibrant. In his theory of public sphere, Habermas (1991) [31] defined public space as the place where public opinion can form and where the public can freely discuss and communicate through media such as newspapers, periodicals, radio, and television. Although the definitions for public space vary among different scholars, they all share common features. This paper focuses on these common features of public space and specifically defines public space as a place where residents can engage in socialization, leisure, recreation, and political participation, including streets, squares, and parks.
Based on the research of Putnam (1994) [32], this paper uses the three dimensions of social capital—interpersonal trust, relational networks, and norms of reciprocity—to analyze how the use of urban public space contributes to the increase in residents’ income through the cultivation of social capital. Among these three dimensions, interpersonal trust forms the core of social capital, reflecting the relational attribute of mutual trust between people. This mutual trust is the prerequisite for the formation of social capital and the basis for enhancing interactions among residents. The relationship network is the carrier of social capital, which can connect different residents, promote communication among residents in public spaces, and provide the necessary conditions for residents to cultivate trust and mutual assistance. Reciprocal norms are a vital form of social capital, as these norms not only direct more available resources to residents to broaden their opportunities for upward mobility but also help residents obtain timely and effective economic information to reduce transaction costs. In this way, residents cultivate social capital through activities in public spaces, gain interpersonal trust, broaden their relationship networks, and collaborate for mutual benefit and mutual assistance, thereby increasing their income and improving their overall economic situation. Therefore, based on the above three dimensions of social capital, this paper proposes the analytical framework as shown in Figure 1.

2.1. Impact of the Use of Public Space on Residents’ Income

As an important part of urban space, public space provides an open place for urban and rural residents to carry out social activities associated with daily life, social interaction, leisure and recreation, and physical exercise. This paper argues that public space can also promote residents’ incomes for the following reasons: First, by moving around in public spaces, residents can get to know people of different economic statuses, obtain valuable resources from them, and learn about the economic effects of the space they live in; further, the housing costs and economic pressures of low-income people can be reduced [33]. Secondly, public space can provide residents with places for business exchange and production transactions. For example, in neighborhood parks, certain residents take advantage of the opportunities provided by public space and set up stalls in front of parks to improve their income [27]. Third, the amenities and types of facilities offered by public spaces also impact residents’ incomes. One study found that residents living in affordable housing neighborhoods with low accessibility to external public space amenities can reduce their economic costs associated with the use of external public space amenities by upgrading amenities such as pedestrian systems, commercial services, and parking lots [34]. Finally, during the empirical survey conducted for this study, some of the respondents’ answers also reflected the fact that the use of public space promotes an increase in income. Examples of this are the following: “I go to the side of the nearby square to set up a stall on weekends, mainly to sell some fruits to subsidize my family”. “I met a neighbor in the community when I was playing with my kids in the park, and later he introduced me to work in an organization, and the salary is still higher than what I had”. Therefore, based on the analysis of the above theoretical and practical surveys, this paper proposes Hypothesis (H1):
Hypothesis 1 (H1):
The use of public space will contribute to the promotion of residents’ incomes.

2.2. Relationship between Public Space and Social Capital

As an important place for social interaction, public space is the carrier of both the activities and social relations of residents. Relevant studies clearly show that public space plays an important role in the cultivation of social capital. First, the use of public space can promote interpersonal trust among residents. In practice, public space carries people’s exchanges and interactions, promotes their relationships and trust, and thus has a clear effect on the overall enhancement of community social capital. At the same time, the structure of public space also affects the level of trust between residents. Shared housing in cities can rebuild local social capital and establish interpersonal trust by designing structures that encourage high levels of social interaction among the members of the community [35]. Second, as a typical social space in urban life, public space is an important place for people to interact and expand their social networks. People are more willing to interact in public spaces with better facilities (e.g., laundry rooms, childcare centers, and public parking lots). As a result, in these public spaces with better amenities, people also develop a richer and closer network of relationships [36]. Third, engaging in socialization through the use of public spaces can promote the development of reciprocal norms among residents. It is precisely in public spaces that reciprocal norms among residents often emerge from their engagement in multiple reciprocal activities, which tend to be reciprocal and informal in nature. Related studies have also confirmed that the activity space factor in urban communities is significantly positively related to reciprocal trust in neighborhood social capital [37]. Finally, during the empirical survey for this study, some of the respondents’ answers also reflected that their use of public space could lead to the cultivation of social capital. Examples of this are “Like inside our neighborhood, the hygiene level is relatively good, because everyone abides by the norms in the neighborhood, and when they see anyone indiscriminately disposing garbage, they basically go to stop him”. “I usually like to sing and dance, and I have met many friends with whom to sing and dance together in the park, and we always help each other”. Therefore, based on the analysis of the above theories and actual survey responses, this paper proposes Hypothesis (H2):
Hypothesis 2 (H2):
The use of public space will enhance the social capital of residents.

2.3. Impact of Social Capital on Residents’ Income

The relationship between social capital and residents’ income has been confirmed by many studies. Individual residents can broaden their opportunities for advancement in the workplace by accumulating social capital, which positively affects their income. The concentration of social capital by residents of low-income neighborhoods has a significant impact on their income [24]. Therefore, based on relevant studies, this paper considers that social capital has a significant impact on the growth of residents’ individual incomes, which is mainly manifested in the following three points: Firstly, interpersonal trust in social capital—the basis of residents’ interpersonal interactions—can improve individuals’ access to social resources and reduce the economic cost imposed by information gaps. For example, by building cohesive interpersonal trust relationships outside the neighborhoods in which they live, families in low-income neighborhoods can unlock more social resources, satisfy their own daily needs, and reduce family poverty to a certain extent [38,39]. Secondly, the relationship network in social capital also has a positive impact on the increase in residents’ income. Relevant studies showed that the network size and network level in the relationship network positively affect the income growth of the urban low-income class. As urbanization continues to accelerate, more and more farmers are entering cities in pursuit of work; for them, the use of “human resources” in their social capital network can help to expand their channels of income sources. Thirdly, the norm of reciprocity in social capital plays an important role in increasing residents’ income. When residents interact with their neighbors in the urban community, they can help each other with resources, thus alleviating their economic pressure to a certain extent [25]. In terms of improving the income increase in the low-income class, the norms of mutual aid are clearly effective in improving the current status quo of the low-income class in the city. Fourthly, during the empirical survey of this paper, some respondents’ answers also reflected the positive impact of social capital on residents’ income. Examples of this are “I remember when I was small, basically every family would grow rice, at that time everyone was poor, when rice harvesting could not afford to hire machines to harvest, it was all relatives and friends in the village who helped together”. “I had stayed in the countryside before, it was only in the past few years that I went to the city to work, and during the New Year I heard a friend of mine say that their factories were well-paid, and that as long as I was down-to-earth and willing to work, he would find a way to help me get into the factories, and I was very thankful to him, ah”. Therefore, based on the analysis of the above theoretical and practical deliberations, this paper proposes Hypothesis (H3):
Hypothesis 3 (H3):
An increase in social capital will contribute to boosting the income of the population.
The possible mechanisms by which the use of public space affects the income of residents is summarized as Hypothesis (H4):
Hypothesis 4 (H4):
The use of public space will contribute to an increase in the income of residents through the enhancement of social capital.

3. Data, Variable Selection, and Empirical Methods

3.1. Data Sources, Survey Methods, and Descriptive Statistical Analysis

The data used in this study originate from the online survey project “Survey on the Current Situation of Social Capital and Income of Chinese Residents” conducted by the School of Public Administration of Guangxi University in October 2023. Drawing on the survey methodology of Wang and Han (2021) [40] and Wang and Lu (2021) [41], the project team conducted an anonymous online cross-sectional survey using Questionnaire Star (China Co., Ltd., Shanghai, China). The survey lasted from 7 October 2023 to 7 December 2023 and followed the international methodology of recruiting respondents based on the principles of voluntary participation and reimbursement. Sample information was obtained through stratified random sampling. Questionnaire Star is equivalent to Qualtrics Seattle, WA, USA), SurveyMonkey (San Mateo, CA, USA), or CloudResearch (New York, NY, USA); it provides online questionnaire design and survey functions for research organizations, enterprises, and individuals. The target population of this study is working adults living in mainland China. A random sampling procedure stratified by age and location was used to match relevant Chinese adults in the QuestionStar sample database. The survey covered four aspects: respondents’ basic characteristics, basic income level, use of urban public space, and social capital.
It should be noted that when respondents filled out the questionnaire online, they were influenced by subjective motives and personal emotions, making them prone to answer irrationally, which may bias the source data. To control and reduce the generation of the above problems, this study selected two methods in the process of data collection: On the one hand, by filling out the questionnaire anonymously, the respondents’ personal privacy was strictly protected, and their resistance towards the research project was reduced. On the other hand, drawing on the relevant studies of Gao et al., (2016) [42,43] and Jones et al., (2015) [44], this questionnaire set up several “trap questions” to determine whether the respondents replied truthfully and accurately when filling out the questionnaire. Samples that did not pass the trap questions were eventually screened out to improve the reliability and credibility of the data source.
A total of 1857 questionnaires were retrieved from this survey, and non-compliant samples were excluded according to the following principles: (1) wrong answers to trap questions; (2) apparent regularity in the selection of questions (e.g., consecutively filling in obliquely); (3) abnormal answering time, either too short or too long (the normal response time is usually four to six minutes); and (4) incoherence in the answers to questions before and after the questions, as well as apparent logical errors. Ultimately, this survey obtained 1565 valid questionnaires, representing a validity rate of 84.28%. A breakdown of the regional distribution of respondents in this survey is shown in Figure 2.
The organization and statistics of valid questionnaires indicated that this sample has the following characteristics: From the perspective of the gender of respondents, the proportion of men is 46.24%, and the proportion of women is 53.76%. In terms of age composition, nearly 90% of respondents were aged between 25 and 45 years, with an average age of about 33 years. This age distribution is roughly in line with the average age of 38 years of working staff in China, according to the Ninth National Survey on the Status of the Workforce conducted by the All-China Federation of Trade Unions from January to September 2022. Young and middle-aged people predominate in this sample overall. In terms of the education level of the respondents, more than 90% of respondents in the sample have a high school education or above, which is roughly in line with the results of the Ninth National Survey on the Status of the Workforce. The education level of China’s working people is relatively high, with more than 85% having a high school education or above. In terms of the respondents’ occupations, 81.21% were employed by enterprises, and 10.45% were civil servants working for public organizations. This is generally consistent with the results of the Ninth National Survey on the Status of the Workforce, showing that there were more employees in enterprises than in state-owned units. In terms of the respondents’ vocational skills, 81.1% of respondents possessed skill certificates for their occupations, indicating that the majority of the working people in the sample possessed basic vocational literacy. In terms of the distribution of public spaces where respondents live, parks, squares, and community activity centers account for the majority within 1 km of their neighborhoods, as shown in Table 1.

3.2. Selection of Variables

3.2.1. Dependent Variables

This paper focuses on the impact of residents’ use of public space on their income; therefore, residents’ income is the dependent variable. According to Li et al., (2023) [45] and Zhao et al., (2023) [3] regarding residents’ income, this paper specifically adopts the respondents’ annual income in 2022 (INCOME) as a measure of the income level of residents.

3.2.2. Core Independent Variables

Through in-depth research on public space, scholars have found that public squares concentrate both economic resources and cultural details. Public space has been identified as the place where material culture and social behavior intersect [46], acting as places for commerce and community [47]. Through rational community design and an increase in the thermal comfort of community squares provided in different seasons, residents can be encouraged to visit public squares for social activities [48,49], thus providing an important place for the accumulation of social capital. Based on this, this paper uses the question “Do you visit public squares frequently?” (WTS) to measure residents’ use of public space.

3.2.3. Mediating Variables

Based on the hypotheses (H2–H4), social capital is the mediating variable in this paper, which is used to explore how the use of public space affects residents’ income. Social capital is a latent variable that cannot be directly observed, and further observational variables are therefore needed to measure it. This paper uses exploratory factor analysis to determine the specific dimensions of measuring social capital and the corresponding observational variables.
Based on the classic dimensions of social capital proposed by Putnam (1994) [32] as well as the exploratory analysis conducted in the data processing for this paper, two dimensions are finally chosen to measure the social capital of residents after their use of public spaces. Specifically, on the one hand, this paper chooses the three dimensions of “People you meet in public space are trustworthy” (T1), “You are willing to give more help to people you meet in public space when they are in trouble” (T2), and “Would you be willing to lend money to a person you met in a public space activity who asks you to borrow money and promises to return it within a certain period of time?” (T3). These three dimensions are used to measure the degree of trust between residents and people they met in public spaces and the degree of compliance with behavioral norms among each other. On the other hand, this paper chooses three questions, namely, “In public space activities, you can meet people with higher incomes than you” (N1), “In public space activities, you can meet people with higher education than you” (N2), and “In public space activities, you can meet people who may help you to achieve promotion” (N3), to measure the level of trust between residents and the people they meet in public space as well as their compliance with behavioral norms. Three questions were asked to measure the network of relationships residents have built through their activities in public spaces.
In the questionnaire of this paper, the data were collected through the use of a five-point Likert scale (ranging from 1 = strongly disagree to 5 = strongly agree) to measure the level of trust and the relationship network. The test of combined reliability and mean extracted value variance for the above two sets of observed variables are shown in Table 2.

3.2.4. Control Variables

The control variables in this paper encompass the five main categories of factors affecting residents’ income, which have also been summarized by existing research: age, gender, education level, work occupation, and health status. This enables this paper to analyze the impact of public space use on residents’ income while controlling all conditions to be constant. First, Yang et al., (2022) [50] found that age and gender have a moderating effect on personal income by affecting self-control, where men and relatively older individuals are more likely to increase their own income. Therefore, age (AGE) and gender (GENDER)—the most basic characteristics of resident status—need to be controlled for. Second, according to Turner et al., (2020) [19], educational attainment is also an important variable that affects residents’ income. Therefore, in this paper, the respondents’ educational attainment (EDU) has been used as a control for the educational level variable. This variable has options that include common educational levels such as elementary school, junior high school, senior high school, bachelor’s degree, graduate school, and above. As pointed out above, different occupational backgrounds have an important impact on residents’ income. According to Liang et al., (2014) [51], Gao et al., (2015) [52], and Kifle et al., (2019) [53], whether the respondent is a civil servant (PC) and whether the respondent is an employee of an enterprise (EE) are used as a measure of the occupational background of residents. Fourth, health status is an important indicator of a person’s physical condition; if their physical function is impaired, their ability to work will be greatly affected, which in turn will also affect their access to income. According to Wei et al., (2020) [54] and Mair et al., (2020) [55], to measure the respondent’s health status, this paper selects whether the respondent suffers from chronic diseases (ILL), whether the respondent smokes cigarettes regularly (SMOKE), and whether the respondent drinks alcohol regularly (DRINK). In addition, this paper includes control variables such as province of residence, personal residency status, and household size in the model to control for possible regional differences as well as the effects of differences in other demographic factors on the estimation results. Table 3 shows the variable descriptions and descriptive statistics of this study.

3.3. Model

3.3.1. Instrumental Variables Regression

The dependent variable in this study is a continuous real number; therefore, this paper first tests whether a boost of income originates from residents’ use of public space through ordinary least squares (OLS). However, OLS regression may be biased because of endogeneity problems such as omitted variables. For example, climate change affects people’s income, and according to ** countries and thus narrow the global and regional economic gap is a topic of widespread concern. Using 1565 survey data from China, this paper analyzes the relationship between the use of public space and residents’ income by taking the annual income of Chinese residents in 2022 as a research object and using social capital as a mediating variable. The main conclusion of this paper is that the use of public space contributes to the increase in residents’ income through the trust and network dimensions of social capital. Residents cultivate social capital through activities in public spaces and then increase their income with the help of that cultivated social capital. Based on this conclusion, this paper explores the mechanism and realization path of public space use → social capital → residents’ annual income, which provides new perspectives and ways to increase the income of residents.
Therefore, this paper calls on the government to reserve a sufficient quantity and quality of public space for residents in urban planning, especially public spaces conducive to the cultivation of residents’ social capital, as this helps to promote the increase in residents’ income. In China, for example, as urbanization continues to expand, economic interests often drive urban planners to excessively convert public land into construction land, thus encroaching on and squeezing out a large amount of community public space. Such a development is detrimental to the development of residents’ leisure activities and their cultivation of social capital. Therefore, it is particularly important to rationally plan the layout and distribution of public space in Chinese cities based on this reality. This paper proposes the following suggestions: On the one hand, for public spaces closer to where people live, such as neighborhood communities, the comfort of sidewalks and resting chairs can be optimized, and fitness venues and parent–child recreational facilities can be increased. Consequently, a space for residents to communicate with one another is created, and cohesion between neighbors is increased, which achieves mutual benefit and trust. On the other hand, public spaces that are farther away from where people live, such as parks and squares, can be improved by increasing the density of green lawns, improving children’s playground facilities and sports equipment, as well as improving the friendliness of park staff. These measures can encourage residents to visit public spaces for social interaction, enhance their well-being, and cultivate a wider range of social capital. At the same time, interventions in public spaces may also have a series of negative impacts. On the one hand, as a result of the beautification of public spaces, the number of public users will continue to increase, which may impose increased pressure on hygiene and cleanliness and increase the management costs of public spaces. On the other hand, this large number of people will lead to an increase in environmental noise, which may induce negative and even stressful feelings among residents, especially female visitors. In addition, public space interventions may also produce problems such as air pollution, ecological damage, and reduced biodiversity. Therefore, urban planners should give full consideration to the emergence of the problems mentioned above when renovating public spaces; they should strengthen the management of public spaces by promoting the rationalization and design of public spaces to better serve urban development.
The research in this paper also has several shortcomings. For example, the selected public space focuses on squares and parks, and therefore, the income effect of other types of public space has not been examined. The selection of public space focuses on the vicinity of the place of residence, and there is a lack of in-depth discussion on the income effect of public spaces near the place of work. Moreover, the type of income that is affected by the increase in residents’ income via public space was also not examined closely. At the same time, because this paper mainly explores whether the use of public space has an income effect on residents, focusing on the presence or absence of an income effect, this paper lacks a detailed analysis of the geographic environment in which the public space is located. Also, different types of public spaces are not distinguished, and an in-depth exploration of the differences between the two external environments mentioned above and the resulting impact on the extent of residents’ income is also missing. Future research needs to improve and supplement the above-mentioned aspects based on the conclusions of this paper, with the goal of obtaining a more complete theoretical elaboration on the relationship between public space and residents’ income.

Author Contributions

Conceptualization, Y.S. and X.Z.; Methodology, X.Z.; Software, H.X. and X.Z.; Validation, X.Z.; Formal analysis, Y.S. and H.X.; Investigation, H.X.; Resources, Y.S.; Data curation, H.X.; Writing—original draft, H.X. and X.Z.; Writing—review & editing, Y.S. and X.Z.; Visualization, Y.S. and H.X.; Supervision, X.Z.; Project administration, H.X. and X.Z.; Funding acquisition, Y.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by Medical Ethics Committee of Guangxi University (protocol code: Gxu-2024-039; date of approval: 13 June 2024) for studies involving humans.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A. The Statistical Principles of Propensity Score Matching

From a statistical perspective, let the dependent variable values for members of the experimental and control groups be represented by Y 1 and Y 0 , respectively, and let w be a binary variable, where w = 1 represents individuals in the experimental group, and w = 0 represents individuals in the control group. Therefore, when an individual belongs to the experimental group, the value of E Y 1 w = 1 is observable as a factual event, while the value of E Y 0 w = 1 is a counterfactual event that cannot be observed. For instance, the impact of a university education on an individual who has received it cannot be observed under a hypothetical scenario where he had not received a university education. Similarly, for the control group, the value of E Y 0 w = 0 is observable as a factual event, while the value of E Y 1 w = 0 is counterfactual and, therefore, unobservable. Thus, our objective is to determine the causal relationship between the differences in “fact” and “counterfactual” elements among individuals in the experimental group, which can be calculated as a weighted average.
T = π E Y 1 w = 1 − E Y 0 w = 1 + 1 − π E Y 1 w = 0 − E Y 0 w = 0
The symbol π signifies the proportion of all individuals surveyed who belong to the experimental group.
Since counterfactuals are unobservable and the same group of people can only belong to either the experimental or control group, it is imperative to fulfill the following non-confounding assumption when making causal inferences:
E Y 1 w = 0 = E Y 1 w = 1
E Y 0 w = 0 = E Y 0 w = 1
The notion here is that a separate group of individuals in the control group can act as a representative for the counterfactual state of individuals in the experimental group. Therefore, it is possible to simplify Equation (A1) as follows:
T = E Y 1 w = 1 − E Y 0 w = 0
In the context of a randomized experiment, the assumptions presented in equations E Y 1 w = 0 = E Y 1 w = 1 and E Y 0 w = 0 = E Y 0 w = 1 hold since experimental individuals are assigned to the experimental and control groups in a random manner. However, it is worth noting that when relying on observational data, the fact of randomization cannot be guaranteed. Thus, it becomes imperative to control for confounding variables as much as possible to maintain the independence between variable w and variables Y 1 and Y 0 , i.e.,
E Y 1 w = 0 , x = E Y 1 w = 1 , x
E Y 0 w = 0 , x = E Y 0 w = 1 , x
The variable x represents a confounding variable. As long as the confounding variable can be identified and controlled, w can be approximated to be independent of Y 1 and Y 0 [60], i.e.,
Y 0 , Y 1 ⊥ w x
At this stage, a specific propensity score of P for the confounding variable x is obtained through logistic regression, leading to the following relationship:
E Y 1 w = 0 , P = E Y 1 w = 1 , P
E Y 0 w = 0 , P = E Y 0 w = 1 , P
In summary, it is possible to obtain an “approximate” fulfillment of the non-confounding assumption, thereby obtaining the desired causal inference.

Appendix B. The Principle of Mediation Effect Model

We hypothesize that WTS affects INCOME through possible mediating mechanisms. Following Baron and Kenny (1986) [79], we use the following econometric model:
I N C O M E = β 0 + β 1 W T S + ∑ k θ k X k + ε
M = a 0 + a 1 W T S + μ
I N C O M E = c 0 + c 1 W T S + b 1 M + ∑ k λ k X k + η
I N C O M E = c 0 + b 1 a 0 + c 1 W T S + a b 1 W T S + ∑ k λ k X k + b 1 μ + η
In Equations (A10)–(A12), INCOME is the annual income of residents, WTS is the core independent variable measured by whether to go to the square, M i is the set of mediating variables, and X i represents the control variables. Equation (A10) gives the total effect of WTS on INCOME, with magnitude β 1 . Equations (A11) and (A12) show how the effect of WTS is mediated by other variables; the coefficient a 1 measures the effect of WTS on the mediator, and b 1 measures the effect of the mediator on INCOME. Substituting Equation (A11) into Equation (A12) gives Equation (A13), where c1 measures the direct effect of WTS on INCOME, and a 1 b 1 measures how much WTS affects INCOME through the mediating mechanisms.

References

  1. Gou, S.Y.; Liu, X.D. Evaluation of Mexican poverty reduction policies under the COVID-19 pandemic impacts. Front. Public Health 2022, 10, 978991. [Google Scholar]
  2. Nakamura, S.; Harati, R.; Lall, S.V.; Dikhanov, Y.M.; Hamadeh, N.; Oliver, W.V.; Rissanen, M.O.; Yamanaka, M. Is living in African cities expensive? Appl. Econ. Lett. 2019, 26, 1007–1012. [Google Scholar] [CrossRef]
  3. Zhao, P.J.; Li, K.; Coyte, P.C. The impact of non-communicable chronic diseases on the earned income of working age Chinese residents. Humanit. Soc. Sci. Commun. 2023, 10, 476. [Google Scholar] [CrossRef]
  4. Huang, L. Effect of Natural Hazards on the Income and Sense of Subjective Well-Being of Rural Residents: Evidence from Rural China. Front. Ecol. Evol. 2022, 10, 898557. [Google Scholar] [CrossRef]
  5. Xu, P.; Li, S.W.; Yang, X.A.; Li, Y.F. Research on the Relationship between Urban Agricultural Nonpoint Source Pollution and Rural Residents’ Income Growth. J. Environ. Public Health 2022, 2022, 4133245. [Google Scholar] [CrossRef]
  6. Pascual, G.S. Mexico, the Middle-Income Trap and the Trap and the Structural Reforms. Tla-melaua 2019, 13, 50–74. [Google Scholar] [CrossRef]
  7. Goto, K.; Endo, T. Labor-intensive industries in middle-income countries: Traps, challenges, and the local garment market in Thailand. J. Asia Pac. Econ. 2014, 19, 369–386. [Google Scholar] [CrossRef]
  8. Glawe, L.; Wagner, H. The middle-income trap 2.0: The increasing role of human capital in the age of automation and implications for develo** Asia. Asian Econ. Pap. 2020, 19, 40–58. [Google Scholar] [CrossRef]
  9. Hung, N.T.; Yen, N.T.H.; Duc, L.D.M.; Thuy, V.H.N.; Vu, N.T. Relationship between government quality, economic growth and income inequality: Evidence from Vietnam. Cogent Bus. Manag. 2020, 7, 1736847. [Google Scholar] [CrossRef]
  10. Banna, H.; Masud, M.M.; Rodrigo, S.K.A. How does economic growth impact on income inequality across ethnic groups in Malaysia? Poverty Public Policy 2020, 12, 397–420. [Google Scholar] [CrossRef]
  11. Vo, D.H.; Pham, A.T.; Tran, Q.; Vu, N.T. The long-run effects of financial development on income inequality: Evidence from the Asia-Pacific countries. Heliyon 2023, 9, e19000. [Google Scholar] [CrossRef]
  12. Su, Y.; Chen, X.; Li, Y.; Wang, Y. The robustness mechanism of the rural social-ecological system in response to the impact of urbanization—Evidence from irrigation commons in China. World Dev. 2024, 178, 106565. [Google Scholar] [CrossRef]
  13. Radicchi, A.; Henckel, D. Planning Artificial Light at Night for Pedestrian Visual Diversity in Public Spaces. Sustainability 2023, 15, 1488. [Google Scholar] [CrossRef]
  14. Reyes-Riveros, R.; Altamirano, A.; De la Barrera, F.; Rozas-Vasquez, D.; Vieli, L.; Meli, P. Linking public urban green spaces and human well-being: A systematic review. Urban For. Urban Green. 2021, 61, 127105. [Google Scholar] [CrossRef]
  15. Mosca, F.; Sani, G.M.D.; Giachetta, A.; Perini, K. Nature-Based Solutions: Thermal Comfort Improvement and Psychological Wellbeing, a Case Study in Genoa, Italy. Sustainability 2021, 13, 11638. [Google Scholar] [CrossRef]
  16. Samsudin, R.; Yok, T.P.; Chua, V. Social capital formation in high density urban environments: Perceived attributes of neighborhood green space shape social capital more directly than physical ones. Landsc. Urban Plan. 2022, 227, 104527. [Google Scholar] [CrossRef]
  17. Habibi, K.; Taoshih, N.; Pira, M. Assessing Social Capital Indicators in Public Spaces in Central streets of the City of Sanandaj, Iran. J. Reg. City Plan. 2022, 33, 1–13. [Google Scholar] [CrossRef]
  18. Su, Y.; Zhang, X.; Xuan, Y. Linking neighborhood green spaces to loneliness among elderly residents—A path analysis of social capital. Cities 2024, 149, 104952. [Google Scholar] [CrossRef]
  19. Turner, T.; Cross, C.; Murphy, C. Occupations, age and gender: Men and women’s earnings in the Irish labour market. Econ. Ind. Democr. 2020, 41, 276–295. [Google Scholar] [CrossRef]
  20. Lavrinovicha, I.; Lavrinenko, O.; Teivans-Treinovskis, J. Influence of education on unemployment rate and incomes of residents. Procedia-Soc. Behav. Sci. 2015, 174, 3824–3831. [Google Scholar] [CrossRef]
  21. Lu, H.; Zhao, P.; Hu, H.; Zeng, L.; Wu, K.S.; Lv, D. Transport infrastructure and urban-rural income disparity: A municipal-level analysis in China. J. Transp. Geogr. 2022, 99, 103292. [Google Scholar] [CrossRef]
  22. Jiang, S.; Qi, L.; Lin, X. The Impacts of COVID-19 Shock on Intergenerational Income Mobility: Evidence from China. Int. J. Environ. Res. Public Health 2022, 19, 11546. [Google Scholar] [CrossRef]
  23. Hao, X.; Yang, X.; Kou, K.; Zhang, Y.; Guo, C. Research on the Contribution Mechanism of Vocational Human Capital Characteristics to Income. Educ. Sci. 2023, 13, 246. [Google Scholar] [CrossRef]
  24. Kovacs, A.J.; Juhasz, S.; Bokanyi, E.; Lengyel, B. Income-related spatial concentration of individual social capital in cities. Environ. Plan. B-Urban Anal. City Sci. 2023, 50, 1072–1086. [Google Scholar] [CrossRef]
  25. Curley, A.M. Relocating the poor: Social capital and neighborhood resources. J. Urban Aff. 2010, 32, 79–103. [Google Scholar] [CrossRef]
  26. Delshad, A.B. Community gardens: An investment in social cohesion, public health, economic sustainability, and the urban environment. Urban For. Urban Green. 2022, 70, 127549. [Google Scholar] [CrossRef]
  27. Bonilla, M.H. The significance and meanings of public space improvement in low-income neighbourhoods’ colonias populares’ in Xalapa-Mexico. Habitat Int. 2013, 38, 34–46. [Google Scholar] [CrossRef]
  28. Astell-Burt, T.; Feng, X.; Mavoa, S.; Badland, H.M.; Giles-Corti, B. Do low-income neighbourhoods have the least green space? A cross-sectional study of Australia’s most populous cities. BMC Public Health 2014, 14, 292. [Google Scholar] [CrossRef]
  29. Arendt, H. The Human Condition; University of Chicago Press: Chicago, IL, USA, 2013. [Google Scholar]
  30. Jacobs, J. Dark Age Ahead; Vintage: Toronto, ON, Canada, 2010. [Google Scholar]
  31. Habermas, J. The Structural Transformation of the Public Sphere: An Inquiry into A category of Bourgeois Society; MIT Press: Cambridge, MA, USA, 1991. [Google Scholar]
  32. Putnam, R.D. Making Democracy Work: Civic Traditions in Modern Italy; Princeton University Press: Princeton, NJ, USA, 1994. [Google Scholar]
  33. Wu, J.J.; Plantinga, A.J. The influence of public open space on urban spatial structure. J. Environ. Econ. Manag. 2003, 46, 288–309. [Google Scholar] [CrossRef]
  34. Zhao, J.; Peng, Z.; Liu, L.; Yu, Y.; Yu, Y. Evaluation on the Internal Public Space Quality in Affordable Housing Based on Multi-Source Data and IPA Analysis. Land 2021, 10, 1000. [Google Scholar] [CrossRef]
  35. Guan, S.; Wang, J. Research on the Optimal Design of Community Public Space from the Perspective of Social Capital. Sustainability 2023, 15, 9767. [Google Scholar] [CrossRef]
  36. Alhusban, S.A.; Alhusban, A.A.; AlBetawi, Y.N. Suggesting theoretical urban neighborhood design concept by adopting the changing discourse of social capital. J. Enterp. Communities People Places Glob. Econ. 2019, 13, 391–411. [Google Scholar] [CrossRef]
  37. Yan, Y.; Shahraki, A.A. Exploring the Mutual Relationships between Public Space and Social Satisfaction with Case Studies. Sustainability 2023, 15, 7710. [Google Scholar] [CrossRef]
  38. Brisson, D.S.; Usher, C.L. Bonding social capital in low-income neighborhoods. Fam. Relat. 2005, 54, 644–653. [Google Scholar] [CrossRef]
  39. Su, Y.; Zhang, S.; Li, Y.; Yu, H. How does social capital promote consumer participation in food safety governance? Evidence from online food consumers in China. Humanit. Soc. Sci. Commun. 2024, 11, 1–12. [Google Scholar] [CrossRef]
  40. Wang, C.; Han, B.; Zhao, T.; Liu, H.; Liu, B.; Chen, L.; ** Review of How Income Affects Accessing Local Green Space to Engage in Outdoor Physical Activity to Improve Well-Being: Implications for Post-COVID-19. Int. J. Environ. Res. Public Health 2020, 17, 9313. [Google Scholar] [CrossRef]
  41. Jiang, Y.; Long, H.; Tang, Y.; Deng, W.; Chen, K.; Zheng, Y. The impact of land consolidation on rural vitalization at village level: A case study of a Chinese village. J. Rural. Stud. 2021, 86, 485–496. [Google Scholar] [CrossRef]
  42. Baron, R.M.; Kenny, D.A. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Personal. Soc. Psychol. 1986, 51, 1173. [Google Scholar] [CrossRef] [PubMed]
Land 13 00945 g001
Figure 1. Theoretical framework diagram.
Figure 1. Theoretical framework diagram.
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Figure 2. Regional distribution of respondents.
Figure 2. Regional distribution of respondents.
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Figure 3. Mediated effect pathway.
Figure 3. Mediated effect pathway.
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Figure 4. Overlap in testing results.
Figure 4. Overlap in testing results.
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Table 1. Distribution of public space within 1 km of residential neighborhoods.
Table 1. Distribution of public space within 1 km of residential neighborhoods.
Distribution of Public SpaceSample SizePercentage of Distribution
Parks (for public recreation)124879.49%
Squares112671.72%
Public playgrounds88556.37%
Community center115073.25%
Other types of public space20913.31%
No public space in the vicinity of the place of residence332.1%
Table 2. Observed variables: composite reliability and average variance extracted values.
Table 2. Observed variables: composite reliability and average variance extracted values.
Latent VariableObserved VariableStandardization
Factor Loading		Composite ReliabilityAverage Value ExtractedStandardization
Cronbach’s α
Trust and behavioral normsT10.7600.7620.5170.725
T20.722
T30.672
NetworkN10.7780.7410.4890.808
N20.669
N30.644
Table 3. Description of variables and descriptive statistics.
Table 3. Description of variables and descriptive statistics.
Variable NameDescriptiveSample SizeMeanStd. Dev.Min.Max.
Dependent variable
INCOME (ln)Annual income of residents (Unit: 10.000 yuan)15652.6520.686−1.6096.908
Core independent variable
WTSWhether to go to the square (Yes = 1, No = 0)15650.7020.45801
Control variables
GENDERGender (M = 1, F = 0)15650.4630.449901
AGEA person’s age156532.7486.6331773
EDUBelow elementary school = 1, elementary school = 2, middle school = 3, high school = 4, bachelor’s degree = 5, master’s degree = 6, doctorate = 715655.0630.41117
PCOccupation is civil servant (Yes = 1, No = 0)15650.1040.30601
EEOccupation is enterprise employee (Yes = 1, No = 0)15650.8130.39001
SMOKETobacco use (1 = Never to 5 = Frequently)15651.7511.18215
DRINKAlcohol consumption (1 = Never to 5 = Frequently)15652.3760.95415
ILLPresence of a chronic disease (Yes = 1, No = 0)15650.4750.50001
FAMILYNUMNumber of persons in the household15653.8171.18219
LIVETIMELength of residence in current location (Unit: year)156519.35012.858170
WITHMEWhether respondents are living alone (Yes = 1, No = 0)15650.0490.21501
TRUSTT1Do you think that people you meet in public spaces are trustworthy (1 = Completely disagree to 5 = Completely agree)15653.1131.12115
T2Are you willing to raise help for people you meet at public space events when they are in trouble (1 = Completely disagree to 5 = Completely agree)15653.3220.99215
T3When someone you met at a public space event asks you to borrow money, are you willing to lend it to them (1 = Completely disagree to 5 = Completely agree)15652.7451.24615
NET (Internet)N1Are you able to meet people with higher incomes than you by moving around in public spaces (1 = Totally disagree to 5 = Totally agree)15653.4681.05815
N2Are you able to meet people with more education than you by moving around in public spaces (1 = Completely disagree to 5 = Completely agree)15653.4491.09015
N3Are you able to meet people who may help you to achieve promotion at events in public spaces (1 = Completely disagree to 5 = Completely agree)15653.3831.10715
Table 4. Baseline regression and instrumental variable regression results.
Table 4. Baseline regression and instrumental variable regression results.
VariablesModel 1Model 2Model 3Model 4Model 5Model 6
OLSOLSOLSOLSOLSIV-OLS
WTS0.087 *0.081 *0.079 *0.074 *0.084 *0.064 *
(2.23)(2.20)(2.15)(2.04)(2.29)(1.71)
GENDER 0.189 ***0.190 ***0.137 ***0.138 ***0.137 ***
(5.44)(5.48)(3.51)(3.55)(3.63)
AGE 0.0070.0070.0070.0060.006 **
(1.80)(1.92)(1.82)(1.54)(2.06)
EDU 0.341 ***0.346 ***0.351 ***0.346 ***0.346 ***
(3.78)(3.81)(3.82)(3.74)(8.35)
DANGYUAN 0.174 ***0.190 ***0.184 ***0.181 ***0.182 ***
(4.46)(4.85)(4.66)(4.62)(4.55)
FAMILYNUM 0.0030.003−0.0010.0030.003
(0.19)(0.19)(−0.05)(0.22)(0.24)
WITHME −0.109−0.104−0.107−0.123−0.122
(−1.37)(−1.33)(−1.35)(−1.51)(−1.55)
LIVETIME −0.001−0.001−0.001−0.002−0.002
(−0.65)(−0.63)(−0.57)(−1.10)(−1.27)
PC −0.045−0.042−0.039−0.038
(−0.55)(−0.53)(−0.49)(−0.52)
EE 0.0730.0720.0580.060
(1.08)(1.07)(0.87)(1.07)
SMOKE 0.048 **0.048 **0.049 ***
(2.81)(2.81)(3.01)
SLEEP −0.005−0.000−0.001
(−0.23)(−0.01)(−0.04)
ILL −0.020−0.014−0.014
(−0.60)(−0.44)(−0.41)
ProvinceUncontrolledUncontrolledUncontrolledUncontrolledControlledControlled
_cons2.591 ***0.5270.4300.4000.4470.460 *
(78.17)(1.10)(0.90)(0.81)(0.89)(1.80)
N156515651565156515651565
R20.0030.0920.0950.1010.1130.113
F4.99414.39712.4889.9427.4288.43
p0.0260.0000.0000.0000.0000.000
t statistics in parentheses; * p < 0.05, ** p < 0.01, *** p < 0.001.
Table 5. Overall sample balance test for each matching method.
Table 5. Overall sample balance test for each matching method.
Matching MethodSample SituationPs R2LR Chi2p > Chi2Mean Bias
Neighbor matchingUnmatched0.01528.730.1215.2
Matched0.00411.240.9852.6
Radius matchingUnmatched0.01528.730.1215.2
Matched0.0013.361.0001.4
Kernel matchingUnmatched0.01528.730.1215.2
Matched0.0026.870.9982.0
Table 6. Treatment effects of the impact of whether residents go to the public space on income.
Table 6. Treatment effects of the impact of whether residents go to the public space on income.
Matching MethodTreatedControlsATT DiffT-StatSig
1:2 nearest neighbor matching2.6782.5910.1222.64***
Radius matching2.6782.5910.0962.38***
Kernel matching2.6782.5910.1002.51***
Note: 1. *** represents significance at the 1% level. 2. Samples’ 0.25 σ ^ ≈ 0.063 , the chosen caliper range = 0.06, which represents one-to-two matching and radius matching among the observed values with a 6% difference in the tendency score.
Table 7. Results of robustness tests.
Table 7. Results of robustness tests.
Model 7 Model 8
OLS Heckman Selection Model
Frequency of residents going to the public space0.054 ***Length of time residents spend in the public space0.118 ***
(4.13) (4.16)
Control variablesControlledControl variablesControlled
ProvinceControlledProvinceControlled
N1123N1565
R20.127R2-
p0.000p0.000
Notes: *** p < 0.001.
Table 8. Mediating effect path coefficients.
Table 8. Mediating effect path coefficients.
FormRatioBootstrap Bias-Corrected 95%
Confidence Interval (Math.)
Model path: a
Use of public space → Interpersonal trust0.065(0.019, 0.113)
Use of public space → Network of relationships0.099(0.051, 0.145)
Model path: b
Interpersonal trust → Residents’ income0.056(−0.003, 0.117)
Networks of relationships → Residents’ income0.181(0.117, 0.237)
Mediating effects: a × b
Use of public space → Interpersonal trust → Residents’ income0.006(0.001, 0.014)
Use of public space → Network of relationships → Residents’ income0.012(0.004, 0.023)
Direct effect: c′
Use of public space → Residents’ income0.039(0.001, 0.080)
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Su, Y.; Xu, H.; Zhang, X. How Can Public Spaces Contribute to Increased Incomes for Urban Residents—A Social Capital Perspective. Land 2024, 13, 945. https://doi.org/10.3390/land13070945

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Su Y, Xu H, Zhang X. How Can Public Spaces Contribute to Increased Incomes for Urban Residents—A Social Capital Perspective. Land. 2024; 13(7):945. https://doi.org/10.3390/land13070945

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Su, Yiqing, Huan Xu, and **aoting Zhang. 2024. "How Can Public Spaces Contribute to Increased Incomes for Urban Residents—A Social Capital Perspective" Land 13, no. 7: 945. https://doi.org/10.3390/land13070945

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