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Article

Exploration of Resident Satisfaction and Willingness in the Renovation of a Typical Old Neighborhood

by
Wenjun Peng
1,2,
Yanyan Huang
1,2,*,
Changquan Li
1 and
Yilin Wang
1
1
School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China
2
Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes, Hubei University of Technology, Wuhan 430068, China
*
Author to whom correspondence should be addressed.
Buildings 2025, 15(2), 293; https://doi.org/10.3390/buildings15020293
Submission received: 26 October 2024 / Revised: 10 January 2025 / Accepted: 14 January 2025 / Published: 20 January 2025
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
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Abstract

:
The reconstruction of old communities makes an outstanding contribution to, and holds practical significance for, livelihoods and ecological civilization in the urban renewal context. Clarifying the renovation intentions of residents is conducive to the effective implementation of reconstruction projects. This paper takes a typical old neighborhood in Wuhan as an example to survey residents’ living satisfaction and renovation intention. Multiple linear regression analysis, factor analysis, and correlation analysis were used to quantitatively screen, judge, and process sample data. The results show that residents’ living satisfaction and willingness to renovate were different under the dimensions of resident age and property rights, respectively. Most residents were dissatisfied with the living state of the neighborhood. Residents over 61 years old or those who held real estate certificates had a strong willingness to renovate and tended to accept a unified management manner after the renovation of the old neighborhood. Moreover, resident satisfaction with the internal road traffic, infrastructure, and building state significantly affected the residents’ overall satisfaction with the living environment in the old neighborhood, which should be given more attention to improve the residents’ willingness to support the renovation items. Furthermore, it was found that resident satisfaction with building conditions, infrastructure, internal road traffic, and public environment significantly impacted their agreement with the renovation in the old neighborhood. This investigation could provide a basis and guidance for the reconstruction and design of old communities.

1. Introduction

Renovating old residential areas is important in promoting organic and progressive urban renewal to enhance residents’ well-being. In China, 170,000 old housing complexes in cities and towns were built mostly before the 1990s [1]. As China’s urbanization and economic development enter a new era, these old settlements exhibit significant gaps in meeting modern living requirements in terms of construction standards, public services, facilities, community governance, etc. [2,3]. There is a pressing need for reconstruction in these traditional communities. It is estimated that the renovation of old urban residential communities involves more than 42 million households and about 4 × 109 m2 of renovated floor area [4]. In the face of such a large-scale livelihood project, Chinese governments and departments attach great importance to it. A total of 15 pilot cities began to reconstruct old neighborhoods in 2017. The nationwide renovation has been promoted since 2020. The 14th Five-Year Plan and the Outline of Visionary Targets for 2035 both proposed to accelerate urban renewal, involving the functional improvement of old blocks and the renovation of old buildings. Currently, China’s old neighborhood renewal is developing from the stage of large-scale demolition and construction to the stage of composite rectification, which integrates functional changes, additions and expansions, and partial demolition and construction [5]. Residents, as the core stakeholders in the renovation of old neighborhoods, are both participants and basic accountability units in the community governance system [6]. Maximum efforts should be made to stimulate residents’ awareness of and participation in the improvement of the living environment. Therefore, having a clear understanding of residents’ will is an important prerequisite for advancing the renovation of old residential areas [7]. Paying attention to the residents’ needs, such as residential comfort and quality, can facilitate their motivation and enthusiasm for the improvement and governance of old communities for targeted environment reconstruction.
Wuhan is a national historical and cultural city and has many old blocks. These old districts generally suffer from aging buildings, disorderly private construction, serious safety hazards, space congestion, pluralistic construction subjects, unsound property services, lagging supporting infrastructure, and a prominent aging population. The poor environmental quality and inconvenient living conditions in old neighborhoods do not meet residents’ residential demands [8]. Approaches such as ancillary facility renewal, environmental improvement, and property management service upgrades have been vigorously promoted in the early stages of old neighborhood renovations. Although many old communities have been significantly improved, inhabitants there remain generally dissatisfied with the transformation results in the context of rapid economic development. Thus, the government is strongly expected to strengthen special renovations for old communities. In response to the apparent contradiction between the current state of the human environment in old neighborhoods and residents’ high requirements for living conditions, the Wuhan Municipal Government launched an action plan for renovating old neighborhoods in 2019. The plan focuses on the renovation of 760 districts built before 2000 that lack adequate supporting facilities or public service functions. The renovation focuses on six aspects, consisting of buildings, infrastructure, road access, fire safety, environmental health, and public service upgrading [9]. As the renovation project involves complex problems, including resident interests, reconstruction strategies of public spaces, and diversified and scattered demands, it is necessary to assess dwellers’ willingness to effectively implement the reconstruction. This study contributes to improving residents’ living quality and accelerating the renewal of urban old neighborhoods.
The renovation of old residential areas, belonging to the scope of urban renewal, is carried out mainly by addressing governance dilemmas, reconstruction modes, and contents and strategies. First, the dilemmas existing in old communities are mainly reflected in cluttered spatial environments, insufficient industrial vitality, and disorderly governance [10]. For example, Wang (2023) [11] studied the technical, management, and operational issues in greening, drainage, and roads. The current practice of urban renewal and construction emphasizes environmental improvement and residence enhancement. Organic renewal of old communities involves energy-saving and cost-reducing buildings, construction quality and security, standard property management, and upgrades for sustainable development [12,13]. Secondly, old residential areas experienced renewal including large-scale demolition and reconstruction led by developers, functional restoration-oriented modes such as the repair and retention of internal facilities, and comprehensive remediation-oriented modes such as the adjustment of land spatial layouts [5,14,15,16,17,18]. China’s urban renewal started in 1978, and comprehensive research from multiple perspectives appeared after 1990 for the reconstruction of dilapidated residential districts. For example, Zhang et al. (2022) proposed that progressive renovation in an orderly manner could better protect the history and culture of old districts than large-scale demolition and construction and suggested making full use of existing land and public facilities [19]. Influenced by Jane Jacobs, who pursued small, gradual, and fine renovation [20], most countries have started sustainable and eco-friendly residential renewal from small-scale old residences using discreet modifications. Renovation support mainly covers the welfare led by governments, multi-subject participation with market domination and operation, and civil organization-led government support and owners’ initiatives [3,21,22,23]. Third, the renovation contents and strategies of old communities mainly consist of spatial remediation, functional transformation, and humanistic enhancement (Zhu and González Martínez, 2021 [24]; Dong et al., 2023 [25]). For instance, Japan proposed implementation programs such as “infrastructure maintenance, renovation and management” [26], the comprehensive Danchi environment preparation program [27], etc. Botta (2005) [28] considered technologies, social and natural environments, and occupants and proposed renovation strategies including residential differentiation, road accessibility, functional diversity and expansion, insulation, and energy efficiency to enhance the livability of old residences. Salat (2006, 2009) [29,30] and Swilling et al. (2018) [31] proposed retrofitting initiatives from individual housing blocks, housing interior space, peripheral protective structures, energy conservation and heat preservation, appearance beautification, lighting, etc. Lu (2020) [32] and Lin et al. (2024) [33] put forward governance and management measures such as upgrading architectures and service facilities, improving property management, integrating public space, optimizing organizational structures, and accelerating the coordination efficiency for reconstruction to improve residential suitability.
Based on the above, reconstruction has mainly been considered based on material renewal, without considering the exploitation of old neighborhoods’ advantages and residents’ real demands. Influenced by the idea proposed by Lewis Murnford that urban planning, construction, and renovation should be human-centered and pay attention to people’s basic, social, and spiritual needs [34], multi-subject cooperation, payment preferences, and resident support were identified as the basis for residential renewal [35]. In particular, residents’ support and participation were considered economically significant to improve the living conditions when renovating old communities [36]. Many scholars have carried out relevant studies. For example, Zhang et al. (2015) [37] conducted a questionnaire survey and found that urban residents’ economic status, education, and understanding of green information affected their choice of green buildings. Yang et al. (2018) [38] concluded that policy, publicity, market, and information feedback as incentive measures for joint decision-making by residents significantly impact urban households’ participation in greening renovation. Li et al. (2020) [6] suggested that governance channels and neighborhood relations should be utilized to improve resident awareness of enhancing renewals. Though retrofitting decisions by residents should be recognized and cooperated with [39], few people tend to engage in the renewal process, which seriously constrains the governance [3,40]. The demands of housing owners and tenants were identified as major barriers restricting the sustainable renovation market of buildings in the United States [41]. Tuominen et al. (2012) [42] found that energy efficiency benefits, which mainly influenced homeowners’ interests, could not be properly felt after renovation, based on an analysis of residents’ behavioral willingness and demands. Weinsziehr et al. (2017) [43] stated that factors such as household income constraints, the number of elderly people at home, and the renovation costs of buildings impeded the green retrofitting of aging buildings. Abass and Kucukmehmetoglu (2021) [44] found that there was a significant relationship between the propensity to support or oppose urban renewal implementation and group affiliation. A fundamental aspect of formulating reconstruction programs is to fully consider residents’ opinions, which is a challenge when optimizing a community renewal project in a new round of reconstruction of old residential areas. Thus, scholars began to investigate residents’ willingness and satisfaction to involve more residents in the renovation or regeneration process of old residential areas and analyzed data with methods such as factor analysis, logistic regression analysis, and descriptive and correlational analyses. For example, Ding et al. (2022) [45] proposed that residents should fully express their wishes and needs, based on which the renovation project can be adjusted with real-time feedback. Chen et al. (2022) [46] revealed the main factors influencing subjects’ reforming intention and proposed corresponding countermeasures for urban renewal projects. Xu et al. (2024) [47] found that residents’ perception of the quality of the reconstruction of old residential areas was the decisive factor affecting their satisfaction. In summary, most research on reconstruction in old residential areas has focused on residents’ feelings about the retrofitting performance. There are few studies on residents’ acceptance, demands, or expectations of reconstruction, which may be direct and crucial factors in determining residents’ subsequent satisfaction in the districts. Therefore, it is necessary to investigate residents’ satisfaction and renovation willingness before implementing renovation items.
In this paper, we selected the Changqing (CQ) neighborhood as a case study, which is a representative old settlement in Wuhan, China. To effectively implement renovation items for residents, a field investigation was carried out there before implementing renovation work for the old districts in Wuhan by sampling respondents and categorizing them into groups. The connection between residents’ satisfaction with renovations and overall community living satisfaction was examined to understand how residents prefer the neighborhood. Meanwhile, the impact of resident satisfaction on their willingness to approve renovations was discussed. The investigation helps to clarify the focus areas for carrying out future renovation of old residential communities and promote the realization of reconstruction in a targeted way. As renovation facilitates in the improvement of community residents’ living satisfaction, this study could provide directional and practical guidance for sustainable transformation programs for old neighborhoods. Based on literature research and an empirical investigation, this paper proposes the following conceptual framework (as shown in Figure 1).

2. Materials and Methods

2.1. Study Area

The location of the studied neighborhood is shown in Figure 2 below. The Changqing (CQ) neighborhood was built in the early 1990s, with a total of 2592 households in 54 buildings and a gross floor area of 180,000 m2. The houses in the neighborhood are all 6-storey brick-concrete structures. Problems exist in different aspects of the current community conditions in the neighborhood (seen in Figure 3). Firstly, the housing problems mainly include deteriorating structures, peeling calcimine, unauthorized and illegal buildings, leaky balconies and exterior walls, clogged underground drainage, poor supply of water, public stairs without anti-slip strips, broken banisters, and falling steps. Secondly, the infrastructure is severely lacking in configuration and poorly managed. Specifically, the problems mainly include aging pipelines and networks, blocked sewer pipes, damaged electricity and water meters, mixed rain and sewage flow, serious pollution by cleaning septic tanks, a short supply of public drying facilities, and disorderly waste classification facilities. Thirdly, the problems existing in road traffic are mainly reflected in two aspects: seriously aged and damaged roads that have no street lights and limit the driving speed, and the coexistence of people and vehicles, leading to safety risks. Fourthly, the problems in the public environment mainly include little greening and maintenance, unsightly trees without maintenance, limited and overgrown green spaces mixed with garbage and encroached by piles of debris, a chaotic layout, and simple landscape sketches. Fifthly, the lack of fire-fighting facilities coupled with low design standards and serious natural damage as well as the lack of intelligent monitoring systems lead to the problem of fire safety risks. Lastly, the problems in public services are mainly reflected in the lack of public activity places or public green spaces for leisure, lack of parking lots and indiscriminate parking of vehicles, unsatisfactory supporting facilities for living needs, and imperfect services with old management facilities. Furthermore, with reforms in the housing system, homeownership comes in various forms in this old neighborhood. The real estate types include purchased public housing, low-rent housing, relocation housing, commercial housing, etc. Some property rights belong to individuals, some to their former employers, and others to government departments, etc. Even a small number of ownership units have disappeared. All of the above has led to the coexistence of multiple housing ownership structures and a blurring of the definition of homeownership. Additionally, the complex has a wide age range, with residents who have lived there for 30 years alongside newer inhabitants.

2.2. Questionnaire Design and Survey Conduction

2.2.1. Questionnaire Design and Variable Setting

Questionnaires were used to survey residents’ renovation tendencies and support for implementing the renovation project in the old neighborhood. The questionnaire was designed based on the characteristics of the respondents and related research topics of community renovation by referring to previous research results and combining the experience of the research group. There were 13 single-choice items in the questionnaire, and different response options were set for each item. The questionnaire was designed with factors divided into three sections. The first section included objective factors consisting of residents’ socio-demographic conditions such as age, dwelling type, employment status, occupation, and real estate ownership. The second section consisted of subjective factors such as residents’ overall satisfaction with the community living facilities and environment and interviewees’ evaluations of the community state related to the items in the renovation project on a 5-point Likert-type scale ranging from “very dissatisfied” to “very satisfied”. The “very dissatisfied” option was set to the highest score, which was 5, and the “very satisfied” option was set to the lowest score, which was 1. Rating scores were derived from respondents’ assessments of six different aspects of the neighborhood. The third section included two questions about residents’ willingness to renovate—that is, whether the residents agreed to the renovation in the old neighborhood, and whether they accepted unified management after the renovation. The structure of the designed questionnaire can be seen in Table 1 below.
Furthermore, the variables were defined according to the designed items in the questionnaire. To effectively analyze the data collected from the surveyed community, quantitative statistical analysis methods commonly used in sociology were chosen in this study. The setting of variables corresponded to the setting of the questionnaire items, and a total of 13 variables were obtained. Among them, the variables of residents’ residence type and renovation willingness were divided into two dimensions. Demographic variables such as residents’ age, employment status, and property rights were divided into three dimensions. The remaining variables concerning the residential experiences of the residents were divided into five dimensions. The variables selected in this paper and their classified descriptions are shown in Table 1.

2.2.2. Survey Conduction

This survey was primarily conducted using quantitative research methods, such as distributing questionnaires. Before this survey, the regional government had carried out a publicity campaign on the content of the old neighborhood renovation in CQ. Immediately, both online surveys through a micro-neighborhood app and offline surveys were conducted to gather public opinions on the renovation of the old neighborhood. Meanwhile, the collected data were supplemented or revised with interview methods as needed. The flow chart of the implementation process of the questionnaire survey is shown in Figure 4 below.
The specific implementation of the questionnaire survey was as follows. Firstly, the purpose and objects of the survey were defined. The survey aimed to gather information about residents’ basic attributes, living experiences, renovation willingness, and preferences. The survey covered all residents in the typical old neighborhood. Then, the survey methods were determined. A questionnaire survey was conducted by combining online and offline responses. Initially, to ensure the scientific nature of the survey data, the questionnaire survey was divided into two stages: pre-survey and formal survey. By reviewing and synthesizing relevant literature and combining the basic information about this typical community collected online, the content of the pre-survey questionnaire was designed to focus on the three aspects mentioned above. In June 2021, a pre-survey questionnaire was conducted on some residents, and 50 questionnaires were collected. Based on the actual feedback of respondents, items that were difficult to understand, contained unclear semantic expressions, or were repeated were modified or deleted to form the final questionnaire. Subsequently, questionnaires were distributed to community residents to carry out a formal investigation. During the investigation, we assumed homogeneity within the community sample, and the questionnaire was distributed by simple random sampling. Participants were informed in advance that the questionnaire would be anonymous and that all responses would be kept confidential. This was done to encourage residents to complete the questionnaire, ensure smooth execution of the survey, and facilitate the collection of reliable data. For the distribution and filling of questionnaires, this survey was carried out in two ways: an online questionnaire survey with the help of mini programs and a traditional offline paper questionnaire survey. The offline paper questionnaire survey was carried out by randomly distributing questionnaires on the spot. Community residents were invited to fill out paper questionnaires, which were collected on site. Most of the questionnaires were filled in by residents independently, and a few residents who were limited by physical or cultural factors were assisted by investigators on-site. Meanwhile, online questionnaire distribution was also carried out. Considering practical reasons such as convenience in questionnaire filling, accuracy of statistical results, and inconvenience during epidemic prevention and control, questionnaires were distributed to community residents through the Internet to assist in this investigation. The online survey used a mini program to distribute an electronic version of the designed questionnaire, which residents could access via a link. Recipients of the online questionnaire would be linked to the mini program and could respond anonymously based on the prompts provided. Through the introduction of the residents’ committee, the surveyors enlisted community residents and property management personnel to send the questionnaire links to different virtual communities through online channels such as WeChat and QQ. Residents who did not participate in the offline survey were encouraged to fill out the questionnaire online. Additionally, to make the community reconstruction assessment more representative, a small number of key residents were selected, including excellent practitioners in the community, representative members of the neighborhood committee, and permanent residents who participated in community reconstruction through government organizations or voluntarily. These representative residents were invited to complete the questionnaire by telephone or household survey as a supplement to the random sample.
Moreover, considering the urgent need to understand residents’ reactions to community renovation, a formal questionnaire survey was conducted from July to September 2021. During the formal investigation, the arrangements of residents’ work and living hours were also taken into account, and the survey was carried out during their leisure time. Considering the number of items in the designed questionnaire as well as the goal of broad participation to ensure the representativeness of the questionnaire data, we planned to distribute 3200 questionnaires. Questionnaires were distributed throughout the community. Most residents had begun to pay attention to the community renovation based on previous publicity and were willing to be involved in the survey. Overall, a total of 3104 questionnaires were collected, and 779 invalid questionnaires with incomplete responses, obvious contradictions in item selection, or an overly long or short online response time were excluded. Thus, 2325 valid questionnaires were retained, with a recovery rate of 74.9%. The survey samples included a diverse range of age groups, personnel types, and occupations, and the data collected were accurate, effective, and representative.
Furthermore, the reliability and validity of the questionnaire design and survey data were analyzed using Statistical Product and Service Solutions (SPSS) software (version 26). For the reliability test, Cronbach’s alpha coefficient was used to analyze the internal consistency of the samples to ensure that the returned questionnaires could truly reflect the intended objectives and make the collected data analytically valuable. When Cronbach’s alpha coefficient is greater than 0.7, the reliability of the data is acceptable [5]. For the validity test, the KMO (Kaiser–Meyer–Olkin) test combined with Bartlett’s spherical test was employed to measure the sample adequacy. The validity analysis directly reflects the targeted design of the research questions in the questionnaire. A KMO value greater than 0.5 and a mean p-value in Bartlett’s spherical test of less than 0.05 indicate a satisfactory structure of the questionnaire [48]. In this study, Cronbach’s α values for the overall variable and each latent variable were above 0.8. The KMO values of the overall variable and the latent variables were above 0.5. The significance probability of the p-value was 0.000, indicating a statistically significant confidence level and high reliability. The questionnaire design was appropriate, and both the internal consistency and construct validity of the data were strong, meeting the statistical methods’ requirements.

2.3. Analysis Methods

Based on the statistical data from the samples, various methods were used to analyze the factors influencing residents’ living experience and understand residents’ willingness and demands for community reconstruction. In this way, constructive and rational recommendations can be made to assist the government in formulating effective and targeted strategies by identifying priority areas for community reconstruction. Based on the variable settings in Table 1, this paper mainly used SPSS software to conduct one-way analysis of variance (ANOVA), Pearson correlation analysis, and regression analysis on the survey data. The schematic diagram of the research methods used is shown in Figure 5.
ANOVA is a statistical technique that is used to compare the means of multiple populations and judge the effect of categorical independent variables on dependent variables [49,50]. One-way ANOVA only considers the influence of one characteristic parameter on the target variable [51,52]. Firstly, the normality and homogeneity of variance of the data in each dimension are tested. Then, descriptive statistics and test values, including mean ± standard deviation, F-values, and significance probability, are analyzed to determine whether the group differences in each indicator are significant. If the p-value is less than 0.05, it indicates that there is a significant difference in the characteristic parameter under different grades [53]. Otherwise, it indicates that there is no difference between the data groups. There are two reasons why one-way ANOVA was suitable for detecting significant differences in the impact of residents’ age and property rights on their satisfaction with living conditions in the community renovation. On the one hand, since the two selected independent variables are multi-categorical, discontinuous, and inter-group factors, where each participant is assigned only one level of the factor, one-way ANOVA is suitable for separate testing. On the other hand, because the dependent variable, i.e., residents’ satisfaction evaluation score, is continuous, one-way ANOVA is appropriate for testing differences among groups [50].
Correlation analysis is a statistical method to study the correlation between random variables by studying whether there is a certain dependence between phenomena. Pearson correlation analysis refers to the analysis of two continuous variables to measure the closeness of their linear correlation, including correlation degree and correlation coefficient [54]. Correlation degree helps to judge whether there is a significant difference between two variables, which is usually expressed by a p-value. A p-value of 0.05 or less indicates a significant difference or correlation between variables [55]. A p-value above 0.05 indicates that the difference is not significant [56]. The Pearson correlation coefficient is widely used to measure the direction and strength of linear correlations between two random variables, with a value of [−1, 1] [56]. The closer the correlation coefficient is to ±1, the stronger the correlation between the two variables is and the closer the correlation degree is [57]. Positive and negative signs indicate the correlation direction between the variables. When the correlation coefficient approaches or is equal to 0, it means that the two variables are weakly correlated or uncorrelated [58]. Indicators with a p-value of less than 0.05 would be selected and arranged in descending order according to the coefficients. It was appropriate to use Pearson correlation analysis here to judge the correlation between residents’ satisfaction with the six aspects of the community renovation project and their overall residential satisfaction in this paper for the following reasons. (1) Considering that correlation analysis can eliminate parameter variables with low correlations and optimize the mapping relationships, correlation coefficients were used here between variables to compare the impact of residents’ perception evaluations. (2) The results of the KMO and Bartlett spherical tests above showed that Pearson correlation analysis is suitable for measuring the relationships between the variables. (3) The indicators of residents’ satisfaction with their living experience in this paper are equally spaced variables, making them suitable for Pearson correlation analysis, which is effective for assessing correlations between continuous numerical variables or equally spaced variables.
Regression analysis describes the quantitative functional relationship between variables by establishing a mathematical model, and the rationality and explanatory power of the model can be assessed by testing the regression coefficients [59,60]. A regression equation performs the attribution to explicitly describe the extent to which the explanatory variables act on an explained variable. Multiple regression analysis refers to a statistical analysis method to establish a linear or nonlinear mathematical model [50]. Multiple linear regression analysis involves quantitatively describing the linear relationship between one dependent variable and multiple independent variables through a regression equation [61,62,63]. Multiple linear regression analysis can quantify the influence of a single factor and the interaction effect between multiple factors and is widely used in empirical analysis and research. The fitting coefficients of the multiple regression equation are obtained by performing multiple linear regression on the explained variables. The model of multiple linear regression analysis is expressed as follows: y = β0 + β1X1 + β2X2 + … βkXk + ε, where y represents the dependent variable; X1, X2, …, Xk represent independent variables; β0 is called the regression constant; β1, β2, …, βk are the regression coefficients; and ε~N(0, σ2) is the random error [61]. This paper used residents’ willingness to renovate as the dependent variable, while residents’ satisfaction with the current community situation served as the independent variable, establishing a model for the multiple linear regression analysis. Multiple linear regression analysis is favored for the following reasons. (1) This model can simultaneously consider the influence of multiple explanatory factors on one response factor, providing a clear explanation of the causal relationship of the data and allowing to understand the relationship between variables more comprehensively. (2) It can effectively identify the factors influencing residents’ willingness to renovate and quantify their impact, providing scientific data to support community transformation. (3) It is convenient to operate in practical applications and helps objectively understand whether residents’ renovation willingness matches the contents of community transformation implemented by the government with a methodological tool. Thus, this regression analysis method has advantages in judging the key areas of community reconstruction according to the regression coefficients.

3. Results and Discussion

3.1. Descriptive Statistical Analysis of the Dataset

The descriptive characteristics of the community residents were obtained from the questionnaire survey data. A total of 2325 questionnaires were obtained in this survey, with a coverage rate of 89.7%. The interview content was subjected to the statistics summarized in Table 1. The demographic results of the respondents show that this neighborhood has a complex personnel structure (seen in Table 2), with 11.7% of respondents aged 20 years and below, 69.9% aged between 21 and 60 years, and 18.4% aged 61 years and above. Moreover, 50.0% of the surveyed residents were employed (involving civil servants), 45.0% were retired, and 5.0% were unemployed (including self-employed people and students). Furthermore, 97.0% of the respondents were original residents, with tenants accounting for 3.0%. In terms of residents’ property rights, 63.2% of the residents held land certificates, 28.7% held real estate certificates, and 8.0% had no property rights in the neighborhood.
Furthermore, according to the respondents’ evaluation of the project items and scoring statistics on the renovation items, we obtained the overall evaluation of the residential facilities and living environment in the neighborhood, as shown in Figure 6 and Figure 7 below. Specifically, the interviewees’ satisfaction with the neighborhood is shown in Figure 6. Out of 2325 respondents, 3.4% were very satisfied with the overall living environment of the community at present, 5.6% were satisfied, 30.6% were neutral, 31.9% were dissatisfied, and 28.4% were very dissatisfied, indicating that the majority of residents were unsatisfied. Further, most residents were not satisfied with the state of buildings, infrastructure, and road transportation. Additionally, 91.7% supported the community renovation, and 95% accepted unified community management (seen in Figure 7).

3.2. Differences in Residents’ Satisfaction and Willingness Under Dimensions

A one-way analysis of variance (ANOVA) was performed to examine the differences in residents’ satisfaction scores and their willingness to renovate under the dimensions of age or housing rights after checking the reliability and validity of the questionnaires with respondent data. Significant differences between groups were determined using the F-test, with a specified significance level. Table 3 shows the residents’ satisfaction with renovation items and their renovation intention under the dimensions of age and certificate of house property. Firstly, under the age dimension, variance analysis was conducted on the subsets of residents’ satisfaction with the community items to be renovated and their renewal intention. The results show significant age differences at the 0.05 level in residents’ satisfaction with the community items to be renovated and their remodeling intentions in terms of building condition, road traffic, public environment, fire safety, public services, and agreement on renovation and unified management. Specifically, the F-test values for residents’ satisfaction with the neighborhood items to be renovated such as building state, road traffic inside, public environment, fire safety, and public service were 5.282, 10.888, 10.319, 6.47, and 8.032, respectively. Their corresponding significance values were 0.005, 0.000, 0.000, 0.002, and 0.000, respectively, which are all less than 0.05, indicating significance. Thus, there were significant differences in resident satisfaction with building conditions, road traffic, public environment, fire safety, and public services under different age groups. However, the F-test value for the infrastructure group was 1.18, corresponding to a significance value of 0.308, which is greater than 0.05 and does not reach the significance level. Thus, there was no age-related difference in opinion on public infrastructure. Furthermore, according to the mean statistical results, residents aged 61 years old and above were more likely to approve the renovation of buildings, road traffic, and fire safety. By contrast, residents aged 21–60 were more likely to approve of renovation projects related to road traffic, public environment, fire safety, and public services. Moreover, according to the results of residents’ renovation willingness, the F-values for the factors of agreement with the remodeling and the implementation of unified management were 5.87 and 3.803, respectively. The corresponding significance values were 0.003 and 0.023, respectively, both of which are less than 0.05 and reach the significance level. Therefore, there was a significant difference in residents’ acceptance of renovation and unified management between age groups. Moreover, according to the mean statistics, residents aged 61 and above had high scores, indicating that they have a strong willingness to renovate and accept unified management after the renovation. Secondly, under the dimension of residents’ property rights, there were significant differences in resident satisfaction with community items related to the renovation project and willingness to renovate. Specifically, the F-values for residents’ satisfaction with building conditions, infrastructure, fire safety, and public services were 14.416, 74.094, 3.039, and 6.019, corresponding to significance values of 0.000, 0.000, 0.048, and 0.002, which are all less than 0.05 and reach the significance level. By contrast, the F-values of resident satisfaction with road traffic and the public environment were 0.745 and 1.609, corresponding to significance values of 0.475 and 0.200, which are both greater than 0.05 and do not reach the significance level. Therefore, there was no significant difference in the satisfaction of residents with different residential property rights in terms of road traffic and public environment. Furthermore, according to the mean value statistics, residents who held real estate certificates for their properties were more likely to approve of projects relating to building repair and infrastructure renovation. Residents who held land certificates were also more likely to approve of programs for improvements in buildings and public services. Additionally, in terms of agreement on remodeling of the neighborhood, the F-value was 5.0, corresponding to a significance value of 0.007, which is less than 0.05, thus reaching significance. The F-value of residents’ acceptance of unified management was 5.068, corresponding to a significance value of 0.006, which is less than 0.05, indicating significance. Using mean value statistics, the impact of property rights on residents’ intentions to renovate and their satisfaction with the renovation items was explored. Residents who held real estate certificates had a high mean score of willingness to unify management and were more willing to accept unified management. Residents who held real estate certificates also showed willingness to transform, with a strong renovation intention. Meanwhile, residents who had no property rights in the neighborhood were more supportive of renovation projects for fire prevention.
It can be seen from the above that residents in the CQ neighborhood have a wide age span, complex property ownership rights, and diverse demands for renovation. Residents’ satisfaction with living conditions related to the retrofitting of old residential areas differed under the dimensions of age and housing property rights. The following conclusions can be drawn. First, residents over 61 years old in this community strongly supported reconstruction, with a focus on building repairs, internal road traffic improvement, and fire safety. Moreover, they tended to accept management unification of the community after reconstruction. By contrast, residents aged 21–60 years old were concerned about the public environment, public services, fire safety, and internal road traffic. Secondly, residents who held real estate certificates had the strongest willingness to renovate the old neighborhood for building repairs and tended to accept unified management after renovation of the neighborhood. By contrast, land certificate holders were more likely to expect improved public services. Additionally, non-homeowners had more expectations for remodeling related to fire safety.

3.3. Analysis of Factors’ Influence on Residents’ Willingness to Renovate

3.3.1. Correlations Among Indicators of Residents’ Satisfaction with the Living State

The factors influencing residents’ overall satisfaction with their residence were derived from the completed questionnaire data. Pearson linear correlation analysis was used to quantitatively describe the direction and closeness between the reconstruction variables and residents’ willingness to renovate. The closeness of the linear relationship between the variables is shown in Table 4. According to the detailed results, the building state, internal road traffic, and infrastructure significantly affected residents’ overall satisfaction with the living environment in the old district, followed by the public environment and public services. Fire safety had little impact on the residents’ overall satisfaction. Specifically, there were significant positive correlations between satisfaction with the housing status quo, community infrastructure, or internal road traffic and overall satisfaction with the neighborhood. Their correlation degrees were 0.141, 0.163, and 0.183, respectively. The correlation coefficients between residents’ satisfaction with the community environment and public services and their overall satisfaction with the community were 0.113 and 0.130, respectively. The two correlations are relatively smaller. These indicate that the residents’ satisfaction with the public environment or public services was not significantly related to their overall satisfaction with the neighborhood. By comparison, the significance value of the relationship between residents’ satisfaction with fire safety and their overall satisfaction was 0.654, which is greater than 0.05 and does not reach the significance level, suggesting that residents place little emphasis on fire safety. Visibly, the dissatisfaction of the residents with housing, infrastructure, or internal road traffic contributed greatly to their overall dissatisfaction. Additionally, residents’ satisfaction with fire safety had little influence on their overall satisfaction, indicating a weak willingness for fire safety reform. This is closely related to the fact that the neighborhood is in the city center and has sound public service facilities such as fire safety around the neighborhood.

3.3.2. Determinants of Residents’ Satisfaction with Their Consent to Renovation

Based on the above correlation analysis, residents’ satisfaction levels with the housing status quo, community infrastructure, internal road traffic, public environment, and public services were taken as the independent variables, and their agreement with the renovation was set as the control variable to explore the relationships between them. The premise of regression analysis is that there is no multicollinearity among variables. In this paper, the overall adjusted R2 of the regression model is 0.447, and the results of variance analysis and coefficients in the multiple linear regression analysis are shown in Table 5. Referring to the variance analysis and the regression model, the F-value was 8.305, with a corresponding significance probability of 0.004, which is less than 0.05 and reaches the significance level. Therefore, the fitted model with valid regression results is statistically significant, and this multivariate linear equation is meaningful. Moreover, this study is applied research rather than theoretical, focusing on observing the correlation between variables. Therefore, although the explanatory power of the regression model established in this paper needs to be further improved, it still has practical value. A model was extracted to explore the influence between variables according to the results of the SPSS-based multivariate regression stratification analysis. Multiple linear regression equations were established according to the regression coefficients: Residents’ consent to community renovation = 0.398 + Building conditions × 0.039 + Infrastructure × 0.027 + Internal road traffic × 0.026 + Public environment × 0.022.
According to the regression equation above, the factors that significantly affected residents’ consent to community renovation mainly included building renovation, infrastructure, road traffic, and the public environment. Specifically, the standard regression coefficients for building conditions, infrastructure, road traffic, and public environment were 0.173, 0.119, 0.114, and 0.100, respectively, all with significance values of 0.000, reaching the significance level. The most critical factor affecting whether residents agreed to the renovation was residents’ satisfaction with the building conditions in the old neighborhood, followed by their satisfaction with infrastructure, road traffic, and the public environment. However, the standardized regression coefficient for public services was 0.021, with a significance value of 0.432, which is greater than 0.05 and does not reach the significance level. Hence, residents’ satisfaction with public services does not affect whether they agree to renovation inside the neighborhood. This may be because it is preferred to use the sporadic land around the old residential area to increase public spaces, public service facilities, and infrastructure, thus increasing the overall level of the community’s urban service functions.
From the above, greater resident dissatisfaction with current building conditions was associated with a higher willingness to agree to community renovation, followed by dissatisfaction with infrastructure, internal road traffic, and the public environment. Fire prevention and public services did not significantly influence residents’ willingness to consent to community renovation. This study has the following similarities and differences with other studies. In terms of research direction, other studies have also focused on factors affecting residents’ willingness to participate in community renovation or the difficulties existing in the renovation of old communities [64,65]. However, in the typical old community studied in this paper, residents’ willingness to participate in community reconstruction was high, and the research focused on the areas in which residents expect community reconstruction to be carried out. In terms of research methods, most existing studies used methods such as data envelopment analysis, fuzzy-DEMATEL, the Kano model, and other statistical analysis methods [1,3,65,66,67]. Meanwhile, based on the wide coverage of residents involved in the questionnaire survey and data representativeness, this paper combines qualitative and quantitative methods and adopts multiple types of statistical analysis methods for different research purposes. In terms of research conclusions, both this study and existing studies have found that most old communities have a complex personnel composition and poor building conditions and facilities. Based on surveys and analyses of resident satisfaction, the focus areas of renovation in old communities include housing infrastructure, property management, neighborhood facilities, and the environment [67,68]. However, most of the resident satisfaction research studies on community renovation do not consider the important influence of community residents’ housing property rights, which is considered in this study. Based on the above results and analyses, practical implications can be provided. Firstly, elderly residents who are active in community reconstruction usually show high enthusiasm for neighborhood renewal and contribute their insights in the pre-survey and post-supervision phases, making them an important consideration. Secondly, it is necessary to make full use of the Internet, perform frequent household visits, and utilize multiple communication methods to publicize the objectives, contents, and implementation plans of old community renovation for residents aged 60 and below, especially those who do not own the property they live in, to enhance public participation.

4. Conclusions

Promoting the transformation of old communities in an orderly manner could enhance residents’ living satisfaction. As renovation work is often multifaceted and involves a wide range of residents, it is necessary to investigate their willingness to renovate ahead of time. To effectively implement such renovation, we conducted a study in a pilot neighborhood as part of the old community renovation project in Wuhan. The survey in the old neighborhood tried to clarify residents’ agreement with the implementation of the renovation project and their renovation intention. The differential impact of demographic variables on residents’ perceptions of community living conditions was analyzed first. The evaluations of the renovation items, as well as the overall living environment, were analyzed based on residents’ feedback. Residents’ inclinations and willingness to implement renewal projects were explored to understand whether they supported the reconstruction in the old neighborhood and their renovation demands. The results showed that the residents’ overall satisfaction with the old neighborhood was significantly affected by their evaluation of the building conditions, internal road traffic, and infrastructure. Moreover, residents over 61 years old or residents who held real estate certificates had a strong willingness to renovate and tended to accept unified management after renovation. Focus should therefore be placed on improving the building conditions, infrastructure, internal road traffic, and public environment, which are significantly related to residents’ willingness to renovate in the old community renovation project.
The study provides reference guidelines and optimization suggestions for the renovation of old neighborhoods and provides theoretical support for promoting urban community governance and the formulation of high-quality development policies to enhance the effectiveness of old neighborhood transformation projects in cities. Despite some limitations in this study, future research prospects are proposed. The first is to further explore and improve the explanatory power of the model in the regression analysis by adding independent variables. Further, the accuracy of the questionnaire data can be enhanced by incorporating trap items. Secondly, this paper targeted a typical community, but the demands of residents in other old neighborhoods require specific analysis. When optimizing resident satisfaction after remodeling for other renovation practices, the strategies for solutions and factors influencing residents’ willingness must be tailored to local conditions. Additionally, the application and development of intelligent technology in the transformation of old neighborhoods must evolve to keep pace with the times. Thus, future research should appropriately incorporate technical indicators related to intelligence.

Author Contributions

Conceptualization, W.P. and Y.H.; methodology, W.P.; software, C.L.; validation, W.P., Y.H. and C.L.; formal analysis, C.L.; investigation, Y.W.; resources, Y.W.; data curation, C.L.; writing—original draft preparation, C.L.; writing—review and editing, W.P.; visualization, W.P.; supervision, Y.H.; project administration, Y.H.; funding acquisition, Y.H. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the research project on the influence mechanism of green space landscape on residents’ health in urban high-density residential areas (23Q106); the Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes (2020EJB004); and the project undertaken by HBUT and the project department of China Railway 18th Bureau Group Co., Ltd. on Xinsheng Road, Wuhan, China (8-JF-2022-Xinsheng Road in Wuhan-0-001).

Institutional Review Board Statement

The study does not require IRB approval as it was waived under the law of Measures for Ethical Review of Life Science and Medical Research Involving Human Beings (2023).

Informed Consent Statement

Informed consent was obtained from all subjects participating in the questionnaire survey. The survey purpose, confidentiality measures, and voluntary nature of participation were explained before starting to fill out the questionnaire.

Data Availability Statement

The data used in the study are included in the article; any further requests can be directed to the corresponding author.

Conflicts of Interest

The authors declare that this study received funding from China Railway 18th Bureau Group Co., Ltd. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.

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Buildings 15 00293 g001
Figure 1. Research framework.
Figure 1. Research framework.
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Figure 2. Geographical location of the research object.
Figure 2. Geographical location of the research object.
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Figure 3. The problem situation of the typical old neighborhood under study.
Figure 3. The problem situation of the typical old neighborhood under study.
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Figure 4. Flow chart of the implementation process of the questionnaire survey.
Figure 4. Flow chart of the implementation process of the questionnaire survey.
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Figure 5. Schematic diagram of the research methods used.
Figure 5. Schematic diagram of the research methods used.
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Figure 6. Residents’ satisfaction with the overall living environment and with the situations in six aspects related to the renovation project in the neighborhood.
Figure 6. Residents’ satisfaction with the overall living environment and with the situations in six aspects related to the renovation project in the neighborhood.
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Figure 7. Residents’ willingness to agree on the neighborhood renovation and accept unified management afterward.
Figure 7. Residents’ willingness to agree on the neighborhood renovation and accept unified management afterward.
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Table 1. Descriptive statistics and definitions of the variables used in the analysis.
Table 1. Descriptive statistics and definitions of the variables used in the analysis.
VariablesDescriptive
Demographic characteristics of respondents
Age1 = 20 yrs. and below, 2 = 21–60 yrs., 3 = 61 yrs. and above
Occupation1 = Employed, 2 = Unemployed, 3 = Retired
Dwelling type1 = Migrant, 2 = Local resident
Property ownership certificate1 = Holding the certificate of land property rights, 2 = Holding the housing-ownership certificate, 3 = Holding neither certificate above
Evaluation of the residential environment related to the specific renovation items in the neighborhood
Overall satisfaction with the residential facilities and living environment in the neighborhood1 = Very satisfied, 2 = Satisfied, 3 = Neutral, 4 = Dissatisfied, 5 = Very dissatisfied
How satisfied are you with the housing conditions in the community?1 = Very satisfied, 2 = Satisfied, 3 = Neutral, 4 = Dissatisfied, 5 = Very dissatisfied
How satisfied are you with the community infrastructure at present?1 = Very satisfied, 2 = Satisfied, 3 = Neutral, 4 = Dissatisfied, 5 = Very dissatisfied
How satisfied are you with the road traffic in the community at present?1 = Very satisfied, 2 = Satisfied, 3 = Neutral, 4 = Dissatisfied, 5 = Very dissatisfied
How satisfied are you with the public environment in the community at present?1 = Very satisfied, 2 = Satisfied, 3 = Neutral, 4 = Dissatisfied, 5 = Very dissatisfied
How satisfied are you with the fire safety in the community at present?1 = Very satisfied, 2 = Satisfied, 3 = Neutral, 4 = Dissatisfied, 5 = Very dissatisfied
How satisfied are you with the public services in the community at present?1 = Very satisfied, 2 = Satisfied, 3 = Neutral, 4 = Dissatisfied, 5 = Very dissatisfied
Residents’ willingness to renovate the old neighborhood
Do you agree to renovate this old neighborhood?1 = Yes, 2 = No
Do you accept unified management after the renovation of this neighborhood?1 = Yes, 2 = No
Table 2. Demographic results of the residents interviewed (N = 2325).
Table 2. Demographic results of the residents interviewed (N = 2325).
VariablesDetailsNumbersProportion (%)
Age20 yrs and below27211.7%
21–60 yrs162569.9%
61 yrs and above42818.4%
OccupationUnemployed1165.0%
Employed116350.0%
Retired104645.0%
Dwelling typeTenants703.0%
Original residents225597.0%
Certificate of house propertyHolding a certificate of land property rights147063.2%
Holding the certificate of real estate ownership66828.7%
Holding neither certificate above1878.0%
Note: Data in parentheses are percentages of the total response for the specific renovation.
Table 3. Differences between residents’ satisfaction and renovation intentions among different social groups.
Table 3. Differences between residents’ satisfaction and renovation intentions among different social groups.
VariablesEvaluation Elements Related to the Renovation Items ( x ¯ ± s)Willingness to Transform ( x ¯ ± s)
Building Condition (BC)Infrastructure (INF)Internal Road Traffic (IRT)Public Environment (PE)Fire Safety (FS)Public Service (PS)Consent to Renovation or NotConsent to Unified Management or Not
Age
≤20 yrs3.05 ± 1.7833.32 ± 1.6852.68 ± 1.7592.61 ± 1.7342.86 ± 1.7102.66 ± 1.7300.75 ± 0.4370.86 ± 0.353
21–60 yrs3.75 ± 1.5273.64 ± 1.5343.70 ± 1.4833.61 ± 1.5063.69 ± 1.5953.59 ± 1.5760.89 ± 0.3140.94 ± 0.232
≥61 yrs3.82 ± 1.4743.70 ± 1.5473.52 ± 1.4853.52 ± 1.4783.53 ± 1.5613.48 ± 1.6120.93 ± 0.2540.97 ± 0.183
F5.2821.18010.88810.3196.4708.0325.8703.803
p0.0050.3080.0000.0000.0020.0000.0030.023
Housing equity holding
Holding a certificate of land property rights4.43 ± 1.2104.46 ± 1.1724.35 ± 1.2314.31 ± 1.2784.33 ± 1.2884.38 ± 1.2270.91 ± 0.2850.95 ± 0.223
Holding a certificate of real estate ownership4.46 ± 1.1184.44 ± 1.0484.39 ± 1.1794.41 ± 1.1694.36 ± 1.2274.37 ± 1.2670.94 ± 0.2350.97 ± 0.182
Holding neither certificate above3.94 ± 1.5183.35 ± 1.6674.27 ± 1.3174.28 ± 1.2574.57 ± 0.9564.04 ± 1.4250.88 ± 0.3290.91 ± 0.288
F14.41674.0940.7451.6093.0396.0195.0005.068
p0.0000.0000.4750.2000.0480.0020.0070.006
Table 4. Correlations among residents’ satisfaction with the state of the neighborhood.
Table 4. Correlations among residents’ satisfaction with the state of the neighborhood.
VariableOSBCINFIRTPEFSPS
Overall satisfaction (OS)1
Building condition (BC)0.141 **1
Infrastructure (INF)0.163 **0.569 **1
Internal road traffic (IRT)0.183 **0.495 **0.575 **1
Public environment (PE)0.113 **0.520 **0.522 **0.611 **1
Fire safety (FS)0.0090.507 **0.518 **0.538 **0.629 **1
Public service (PS)0.130 **0.528 **0.529 **0.544 **0.578 **0.611 **1
Note: ** indicates a significant correlation at the 0.01 level (2-tailed).
Table 5. Effect of resident satisfaction on residents’ consent to renovation.
Table 5. Effect of resident satisfaction on residents’ consent to renovation.
ModelBStd. ErrorBetatSig.FSignificance (ANOVA)
Constant0.3980.024 16.4710.0008.3050.004
Building condition0.0390.0060.1736.9300.000
Infrastructure0.0270.0060.1194.5950.000
Internal road traffic0.0260.0060.1144.2990.000
Public environment0.0220.0060.1003.6120.000
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Peng, W.; Huang, Y.; Li, C.; Wang, Y. Exploration of Resident Satisfaction and Willingness in the Renovation of a Typical Old Neighborhood. Buildings 2025, 15, 293. https://doi.org/10.3390/buildings15020293

AMA Style

Peng W, Huang Y, Li C, Wang Y. Exploration of Resident Satisfaction and Willingness in the Renovation of a Typical Old Neighborhood. Buildings. 2025; 15(2):293. https://doi.org/10.3390/buildings15020293

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Peng, Wenjun, Yanyan Huang, Changquan Li, and Yilin Wang. 2025. "Exploration of Resident Satisfaction and Willingness in the Renovation of a Typical Old Neighborhood" Buildings 15, no. 2: 293. https://doi.org/10.3390/buildings15020293

APA Style

Peng, W., Huang, Y., Li, C., & Wang, Y. (2025). Exploration of Resident Satisfaction and Willingness in the Renovation of a Typical Old Neighborhood. Buildings, 15(2), 293. https://doi.org/10.3390/buildings15020293

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