Evaluation of Residents’ Satisfaction with Cultural Spaces in Historic Districts Based on ERG Theory—A Case Study of Longweiguan Historic and Cultural District in Dali City, China

Abstract

Amid urbanization, historic districts serve as key carriers of urban cultural memory, confronting dual challenges of integrating tradition with modernity and balancing cultural inheritance with spatial renewal. Enhancing residents’ satisfaction with cultural spaces is crucial for improving their quality of life and promoting the sustainable development of urban culture. However, existing research lacks systematic analysis of the intrinsic relationship between residents’ needs and spatial satisfaction, focusing on holistic conservation or spatial design. Using ERG Theory and taking Longweiguan Historic and Cultural District in Dali, China, as the case, this study explores how residents’ needs and cultural space satisfaction interact via theoretical construction and empirical analysis. It establishes a 20-index satisfaction evaluation system, adopting field surveys, in-depth interviews and Structural Equation Modeling (SEM) for quantitative analysis. Findings: (1) Residents reported moderate-to-high overall satisfaction with cultural spaces, where relatedness needs demonstrated the most significant impact on satisfaction, while growth needs scored lowest. (2) Existence needs directly affect satisfaction through basic elements like spatial safety and indirectly strengthen relatedness needs. (3) Cultural industry spaces hinder satisfaction due to disconnected innovation and resident participation. Thus, a “safety–social interaction–innovation” strategy is proposed to support the living conservation and sustainable development of historic districts.

1. Introduction

Historic districts are one of the most important cultural heritages of a city. They record the living patterns, residential development, economic activities, and cultural evolution of the people in the region, preserve precious cultural heritage and traditional crafts, and reflect the development history and characteristics of a region [1]. Among them, cultural spaces with unique material forms and cultural significance are important venues for cultural activities in the district. They carry cultural activities such as belief worship, folk festivals, traditional craft practices, and folk art performances passed down from generation to generation by local residents. Their spatial quality directly affects residents’ quality of life and cultural inheritance.

Current studies on historic districts mostly focus on district conservation and renewal planning [2], as well as building and space conservation strategies [3]. Relevant studies on cultural spaces mainly focus on their spatial characteristics [4], spatial reconstruction, and optimization design [5]. However, due to urban expansion and old city reconstruction, the authenticity of historic districts in China has been damaged, and the overall spatial pattern and texture have been ignored [6]. Cultural spaces also have problems such as low utilization rate, waste of cultural resources, and mismatch between functions and residents’ expectations. The main reason is the neglect of the diverse needs of residents as the main users of the space [7]. Although existing studies have emphasized the importance of residents’ feelings in the conservation of district spatial environments [8,9], systematic research examining resident-centered demand analysis and perceptual evaluations of cultural spaces remains limited. Furthermore, most existing studies rely predominantly on qualitative approaches, lacking support from quantitative evaluation models. In addition, there are certain limitations in in-depth analysis of residents’ complex needs and the characteristics of cultural spaces, making it difficult to accurately grasp the connection between residents’ needs at different levels and the actual situation of cultural spaces. Therefore, in-depth exploration of this relationship is particularly necessary. ERG Theory covers three levels of needs: existence, relatedness, and growth [10], which is highly consistent with the demand levels of residents for cultural spaces in historic districts. It provides a new perspective and theoretical support for the study and is expected to break through the predicament of existing studies and provide more effective ideas and methods for solving practical problems such as cultural inheritance and spatial renewal.

The purpose of this study is to construct an evaluation index system for residents’ satisfaction with cultural spaces in historic districts based on ERG Theory. Taking Longweiguan Historic and Cultural District in Dali, China, as an empirical research object, and using the “need–space–satisfaction” ERG Theory as the application framework, it provides a “safety–social interaction–innovation” trinity optimization direction for the conservation and renewal of cultural spaces in Longweiguan. The study comprises three key components: first, constructing an evaluation index system for cultural space satisfaction based on ERG Theory; subsequently, analyzing residents’ satisfaction with cultural spaces at different need levels and its influencing factors; and ultimately, putting forward strategies and suggestions to improve cultural space satisfaction. This study uses field surveys to analyze the current situation of cultural spaces in Longweiguan Historic and Cultural District, adopts questionnaire surveys to collect data on residents’ satisfaction with cultural spaces and relevant information, and uses interviews to further explore the in-depth needs of residents. At the same time, statistical methods are used to analyze and process the data, including descriptive statistical analysis, Pearson correlation analysis, and Structural Equation Modeling analysis, so as to quantitatively analyze the connection and influence mechanism between residents’ needs and cultural space satisfaction. This study introduces ERG Theory into residents’ satisfaction evaluation, enriches the research perspective of cultural spaces in historic districts, and expands the application field of ERG Theory. The research results can provide a decision-making basis for the conservation and renewal of cultural spaces in Longweiguan and similar historic districts and further promote the sustainable development of the district.

2. Literature Review

The following analyzes the current status of previous studies with the logical framework of “theoretical basis-research content-research methods”.

2.1. ERG Theory and Its Application (Theoretical Basis)

ERG Theory was proposed by Clayton Alderfer of Yale University in the United States. It is a motivation theory formed on the basis of empirical research and revision of Maslow’s Hierarchy of Needs Theory [10]. The theory holds that there are three core dimensions of human needs, namely existence needs, relatedness needs, and growth needs [11]. ERG Theory weakens the sense of hierarchy in Maslow’s Needs Theory, which is more in line with the complexity and dynamics of peoples’ needs in reality.

In the selection of theoretical foundations for urban satisfaction research, place attachment theory, environmental psychology, and ERG Theory each have their distinct focuses. Place attachment theory provides an important reference for understanding the emotional bond between people and space. Sharareh Farhad et al. conducted a questionnaire survey on 300 residents in the historic Aghazaman neighborhood of Sanandaj, Iran, and found a significant positive correlation between the components of architectural identity and residents’ place attachment [12]. By exploring the collective memory of residents in the twin cities of Lviv and Wrocław, Maria Lewicka revealed that place attachment is closely associated with place identity and ethnic memory [13]. Relevant studies in environmental psychology offer a crucial perspective for analyzing the interaction mechanism between people and space. Taking the historic urban area of Dandong as the research object, Ji Xian et al. used Gradient Boosting Decision Trees (GBDT) to analyze the impact of the historic built environment on residents’ satisfaction, and found that more than half of the variance in satisfaction was related to the unique features of the historic environment [14]. Based on cognitive psychology and taking historic neighborhoods as the research scenario, D Zhang et al. analyzed the inherent connection between humanistic needs and satisfaction [15].

Compared with these theories, ERG Theory has a more systematic analytical advantage in the “need–space–satisfaction” framework. Place attachment theory focuses on the emotional connection between residents and the built environment, while environmental psychology emphasizes the one-way path from “environmental characteristics to psychological perception”. Both lack systematic classification and quantitative analysis of residents’ multi-level needs, making it difficult to accurately decompose the dynamic needs of residents in different dimensions and their impact paths on satisfaction.

ERG Theory was initially widely used in the field of psychology. Catherine Cheung and other scholars have used ERG Theory to analyze the changes in the psychological needs of tourists from China, Japan, and South Korea at different stages of the COVID-19 pandemic [16]. ERG Theory has also been widely used in other fields. Deborah McPhee et al. found that ERG can promote employees’ identification with their own culture and at the same time strengthen their connection with the organization, thereby improving employees’ job satisfaction [17]. In recent years, ERG Theory has been used in the research and design of various spaces. Drawing on the ERG Theory and taking the Diaoyutai Historic Block in Nanjing as a case, Wang Jiali et al. investigated the dilemmas in the spatial renewal of residential areas within the historic districts and put forward a people-centered sustainable renewal and governance strategy [18]. Leveraging the Service Scenario-ERG-RIPA Model and taking the Shuangta Market in Suzhou as an example, Liu Mingyuan et al. evaluated the user experience in cultural tourism scenarios from the perspectives of both residents and tourists, analyzed the needs of different user groups, and assessed satisfaction patterns, thus proposing a systematic analytical framework to understand the demand differences in cultural tourism spaces such as traditional markets [19].

These studies are all grounded in the ERG Theory, concentrating on issues like spatial renewal and user experience. They integrate specific case studies to present relevant strategies or analytical frameworks. Nevertheless, the existing research fails to adequately cover the diverse types of cultural spaces in historic urban areas and has not thoroughly explored the intrinsic mechanism between residents’ needs and their satisfaction with cultural spaces within the context of the ERG Theory.

2.2. Need Elements for Satisfaction in Historic Districts (Research Content)

The index elements for the study of satisfaction in historic districts have formed a multi-dimensional system. Abusaada and Elshater took Ibrahim Al-Lakani Street in Heliopolis, Egypt, as the research object, and used social morphological characteristics such as building facades and symbolic elements, as well as multi-sensory responses such as vision, aesthetics, society, and spirit as indicators. They pointed out that the street atmosphere affects tourists’ satisfaction through these elements [20]. Mansouri and Ujang focused on the historic district of Kuala Lumpur and used walking accessibility, connectivity, continuity, and the diversity of street activities such as catering and shopping as indicators. They concluded that the characteristics of the walking network directly affect the experience of residents and tourists [21]. Jiang and Timmermans took the historic districts of Chongqing and Shanghai as cases and proposed social environment elements such as safety and neighborhood interaction, as well as economic elements such as housing costs and family income, and the “expectation-reality gap” will further adjust residents’ satisfaction [22]. Tina Davoodi et al. took the Walled City of Famagusta in Northern Cyprus as the research area and constructed indicators from economic elements such as housing living costs and property rights options, social elements such as infrastructure accessibility, safety and management rules, cultural elements such as the fit between architecture and cultural values and the reflection of historical characteristics, and environmental elements such as housing and neighborhood environment quality and green space. She believed that multi-dimensional elements comprehensively affect the satisfaction of residents and non-residents [23].

N Huete Alcocer et al. used Structural Equation Modeling (SEM) to study the role of destination image in tourist satisfaction at heritage sites, confirming that destination image can effectively predict tourist satisfaction with heritage destinations [24]. TS Pham et al. applied PLS-SEM to analyze 394 domestic tourists in Vietnamese heritage tourism destinations, finding that objective authenticity and existential authenticity positively affect tourists’ place attachment and further influence satisfaction [25]. Ricardo David Hernández-Rojas et al. adopted SEM to study the Citadel of the Catholic King in Córdoba, Spain, revealing that tourists’ perceived value of cultural heritage positively affects satisfaction, and perceived heritage quality moderates this relationship [26].

However, the satisfaction index elements of historic districts mostly focus on material culture, with insufficient quantification of intangible culture and insufficient exploration of differences in residents’ needs.

2.3. Research Methods and Optimization of Historic District Satisfaction (Research Methods)

The existing methods used in the study of satisfaction in historic districts can be summarized into three categories, covering quantitative, qualitative, and mixed research paradigms.

In terms of research based on statistical analysis methods, the main focus is on quantitatively analyzing the influencing factors and dimensions of satisfaction through statistical models. Taking Insadong in South Korea as an example, Yu Wenting et al. used factor analysis and regression analysis to extract six dimensions of tourists’ satisfaction in historic districts and clarified that “the integration of tradition and modernity” has the highest weight [27]. Anfal Al-Ali et al. took the Abu Dhabi community as the research object and explored the impact of the built environment on neighborhood satisfaction and social capital through questionnaire surveys and statistical analysis [28]. In her research on the Walled City of Famagusta in Northern Cyprus, Tina Davoodi employed methods such as the Relative Importance Index (RII) and Exploratory Factor Analysis (EFA) to analyze data. Her aim was to explore the key factors influencing the satisfaction levels of residents in historic districts [23]. Based on the survey data of old communities in Ganzhou, Xu Shuitai et al. constructed a satisfaction model for the renewal of old communities through the Customer Satisfaction Index (CSI) theory and Partial Least Squares Structural Equation Modeling (PLS-SEM) and in-depth analyzed residents’ satisfaction and its main influencing factors [29]. Shafaqat Mehmood et al. used PLS-SEM (instead of traditional CB-SEM) to analyze the relationship between user-generated content (UGC) and travel intentions at heritage sites, verifying the applicability of PLS-SEM in handling complex variable relationships in heritage tourism research [30].

In terms of qualitative research based on evaluation models and tools, the focus is on analyzing the influencing factors by interpreting the characteristics of satisfaction. Taking four communities in different construction periods in the old district of Huanshi East Road in Guangzhou as cases, Chen Tao et al. constructed a residents’ satisfaction evaluation system through Post-Occupancy Evaluation (POE) and Importance-Performance Analysis (IPA) [31]. Based on factor analysis and modified IPA method, Song Yimin et al. analyzed the tourists’ satisfaction of Jinyu Lane in Quanzhou and put forward optimization strategies for the conservation and renewal of historic streets [2]. Taking two high-density communities in Suzhou as examples, Chen Jinliu et al. used Structural Equation Modeling (SEM) to analyze residents’ satisfaction and found the importance of community environment quality, facilities, and social connections [32]. Taking Nantou Ancient City in Shenzhen as an example, Gu Siming et al. constructed an evaluation system based on multi-group satisfaction, and identified core issues such as the richness of business types through IPA [33]. Yue Cai et al. used ArcMap 10.8 to conduct kernel density analysis based on these evaluation results, analyzed the coupling coordination degree between the cultural resource value and the street walking environment of Zhongshan Road Historic and Cultural District in Xiamen, China, and developed cultural visiting routes [34]. Jiang Siyu et al. conducted a public survey based on the ancient city of Zhangzhou, employing nonparametric tests and box plot analysis to investigate differences in the perception of cultural landscape genes (CLGs) among residents and tourists with varying individual characteristics [35]. Norzalita Abd Aziz et al. used purposive sampling to conduct questionnaire surveys on residents around Yogyakarta’s heritage sites in Indonesia and qualitatively analyzed the differences in the impact of different tourism benefits on community life satisfaction, providing a qualitative research reference for international heritage community satisfaction studies [36].

In terms of research based on qualitative and mixed methods, the main focus is on exploring the laws of satisfaction by combining qualitative or mixed methods such as questionnaires and grounded theory. Taking an old community in Wuhan as an example, Peng Wenjun et al. used a variety of data analysis methods (including mixed methods) to explore the impact of factors such as residents’ age and property rights on the willingness to renovate and satisfaction and provided guidance for practice [37]. Based on the 2019 Beijing urban physical examination questionnaire data, Jiang Yazhuo et al. constructed a regression model to analyze the satisfaction of residents in Beijing’s historic districts with their living environment and its impact on subjective well-being [8]. Based on scenario theory, Chu Haifeng et al. combined street view image technology and IPA to construct a tourist satisfaction evaluation system including elements such as space, material structure, and participating subjects [38]. Yao Lu selected three key historical and cultural districts in Suzhou by constructing a model based on multi-source data and the Analytic Hierarchy Process (AHP). Using this model, she calculated the tourism competitiveness of each district and analyzed visitor satisfaction across the three areas [39]. Zeng Yujun used factor analysis and IPA to evaluate the satisfaction of elderly residents and the importance of satisfaction and pointed out that improving the conservation of site elevation differences and barrier-free facilities can significantly improve residents’ satisfaction [40]. Based on space syntax and POI big data, Wu Zhihong evaluated the street vitality of the East Street Historic District in Mengzi, Yunnan, and established a closed-loop tool of “diagnosis–intervention–reassessment”, providing a methodology and work paradigm for the urban renewal of historic districts [41]. S. Mostafa Rasoolimanesh et al. combined PLS-SEM (quantitative) and fuzzy-set qualitative comparative analysis (fsQCA) (qualitative) to analyze tourist data in Kashan, Iran, realizing the complementary application of symmetric and asymmetric methods in exploring the impact of memorable tourism experiences on behavioral intentions [42].

These studies have provided rich results for the study of satisfaction in historic districts, but most of them do not focus on the satisfaction of cultural spaces in historic districts. In terms of research methods, although a variety of analysis methods have been used, such as factor analysis, regression analysis, and Structural Equation Modeling, the construction of a comprehensive framework for satisfaction evaluation and multi-dimensional detailed analysis still needs to be further improved. In addition, the existing studies fail to fully cover the special elements of historic districts in the construction of the index system, such as the functionality of cultural spaces and the inheritance and innovation of historical culture, resulting in the evaluation results unable to comprehensively reflect the comprehensive value of the district.

In view of these shortcomings, this study constructs a satisfaction evaluation system suitable for historic districts based on ERG Theory, comprehensively considers the needs of residents at different levels, and in-depth analyzes the multi-dimensional characteristics of cultural spaces in order to provide more comprehensive and effective theoretical support and practical guidance for the conservation and sustainable development of historic districts.

3. Materials and Methods

3.1. Research Area

As one of the first batch of national historical and cultural cities in China, Dali in Yunnan Province in the southwest of China contains many precious cultural resources and attracts tourists from all over the world all year round. Longweiguan Historic and Cultural District is located in the central part of Dali (Figure 1), backed by Cangshan Mountain in the west, adjacent to Xier River in the south, and facing Erhai Lake in the east. It occupies a commanding position with dangerous terrain, easy to defend and difficult to attack (Figure 2). The district is named after the Longweiguan Ruins. The Longweiguan Ruins, an ancient city site of the Nanzhao Kingdom and a significant military pass of the Dali Kingdom, boast a history spanning over 1200 years. It has long been a strategic stronghold coveted by military forces throughout the ages. Moreover, it served as a vital post-station along both the Ancient Tea-Horse Road and the Southern Silk Road. Later, it developed into a settlement for different ethnic groups such as Bai, Han, and Yi.

At present, there are many cultural heritage sites with high historical and cultural values distributed in Longweiguan District: historical and cultural attractions such as the Shoukang Building, General Temple, Confucian Temple, Mituo Temple, Yulong Academy, and the Tomb of Tang Tianbao Soldiers, as well as traditional residential streets such as Longwei Street and Zhongcheng Street. It is one of the important districts that reflect the long history and distinctive style of Dali, a famous historical and cultural city (Figure 2).

The Longweiguan Historic and Cultural District is a typical residential-type historic district. About 80% of the buildings in the district are for residential purposes, with only a small number of commercial buildings distributed along the frontage of the main street. The overall quality of the buildings is relatively good, with only a few idle spaces resulting from the collapse of some buildings. Moreover, the architectural spatial style is mainly that of traditional folk houses (Figure 3).

The Longweiguan has typical components of cultural spaces in historic districts such as historic buildings, traditional streets and cultural attractions. The functional attributes and residents’ perception logic of its cultural spaces are consistent with most historic districts in China, which can provide a typical research sample for cultural space satisfaction evaluation. In addition, the attributes of military passes and the Ancient Tea-Horse Road in history make its cultural spaces have both the functions of “business culture inheritance + spatial defense memory”. Residents’ needs pay more attention to cultural experience, spatial safety, and cultural living presentation; the diverse architecture and folk customs form a unique regional interaction scenario, which is conducive to revealing the differentiated needs of residents at different levels.

3.2. Definition of Cultural Space Concept

3.2.1. Concept and Type of Cultural Space

Cultural space in historic districts refers to an architectural space and venue that carries local spiritual values, condenses the community’s emotional memories, and serves the cultural life of residents. It is an important space for the dynamic display of local lifestyle, the embodiment of cultural values, and the preservation of historical memories. Traditional manual crafts, folk art, folk literature, even customs, beliefs, and values hidden in the daily life of residents usually take cultural space as the carrier.

In view of the different historical, cultural, public service, and practical inheritance values of the cultural spaces in Longweiguan District, they are divided into three categories: cultural heritage space, cultural facility space, and cultural industry space [7] (

Table 1. Types of Cultural Spaces.

Type	Value	Concept	Representative Form
Cultural Heritage Space	Historical and Cultural Value	Historical and cultural heritages with preservation value and their related spaces	ancient ruins, ancient buildings, former residences of celebrities, temples, churches, etc.
Cultural Facility Space	Public Service Value	Various places and community cultural centers that meet the daily needs of residents’ public cultural life	activity centers, community parks, squares, ancient wells, famous ancient trees
Cultural Industry Space	Practical Inheritance Value	Business and inheritance places led by cultural exploration, inheritance, creativity, and transformation	traditional handicraft workshops, time-honored stores, intangible cultural heritage inheritance venues

). Cultural heritage space takes historical and cultural value as its core attribute, referring to various historical and cultural heritages (such as ancient ruins, ancient buildings, former residences of celebrities, etc.) and their related open spaces (such as pre-temple squares). Guided by public service value, cultural facility space refers to various spaces that meet the daily public cultural life needs of residents and provide cultural experience and leisure interaction, including not only special cultural venues such as community activity centers and cultural squares, but also composite spaces with both living services and cultural exchange functions such as areas around ancient wells and famous ancient trees. With the core attribute of cultural practice and inheritance activities, cultural industry space refers to places that rely on cultural exploration, inheritance, and creative transformation to carry out operation and inheritance, and have economic attributes at the same time. It is a place that integrates cultural value and economic operation, such as traditional handicraft workshops, time-honored stores, and intangible cultural heritage inheritance venues.

3.2.2. Current Situation of Cultural Spaces in Longweiguan

According to data review and field survey statistics, there are about 100 existing cultural spaces in Longweiguan Historic and Cultural District. Among them, cultural heritage spaces account for a large proportion, reaching 40. The architectural style of ancient buildings such as Shoukang Building Gate is well preserved, and the gate passage has become a place for residents to visit and pass through daily; although only the house sites remain at the former residences of celebrities like Ma Chongliu and Zhao Xueping, they are still inhabited by people after restoration by later generations. Religious buildings such as Puji Temple and Mituo Temple still provide a carrier for the cultural beliefs of local residents (Figure 4). There are 39 cultural facility spaces. Water cultural spaces such as Dajing Well and Erjing Well have the dual attributes of daily water source for residents and water cultural belief space; community cultural centers and venues around ancient trees have built a platform for residents’ cultural activities and ideological exchanges, enhancing community cohesion and cultural vitality (Figure 5). There are 21 cultural industry spaces. Some traditional handicraft workshops such as Jufenghao Shoe Store and Wufuxiang Dyeing Workshop have survived to this day as carriers of living inheritance of intangible cultural heritage; although time-honored stores such as Shunchang Bank and Anhuan Hall have stopped their traditional business operations, their former sites are well preserved and have profound historical heritage, and have the potential to be transformed into composite functional spaces such as cultural display and creative offices. The inheritance and display activities of intangible cultural heritage such as Dongjing Music and Bai Nationality Three-Course Tea are quite rich (Figure 6 and

Table 2. Statistics of cultural spaces in Longweiguan District.

Cultural Space	Quantity	Name
Cultural Heritage Space	40	Shoukang Building, Xiaguan Kuixing Building, Former Residence of Ma Chongliu, Parade Ground, Former Residence of Zhao Xueping, Yulong Academy, Guansheng Temple, Assessment Garden, Li Pangen’s Courtyard, Former Residence of Su Jin, Yang Zhanyuan’s Courtyard, Dade Hall, Zhang’s Courtyard, Yikeyin Courtyard, Yang Bingxun’s Residence, Duan Shiyi’s Courtyard, Site of Former Residence of Ma Enpu, Former Residence of Ma Xiang, Former Residence of Ma Dingbang, Former Residence of Zhang Feiran, Dafushi Courtyard, Li’s Courtyard, Shibao Courtyard, Shaoxingxiang, Shijian Courtyard, Former Residence of Wang Lianyuan, Mu’s Courtyard, Zhaojiaying, Liu Da’s Courtyard, Liujia Camp, Wenchang Shrine (3), Christian Church, Xiaguan Confucian Temple, Puji Temple, Mituo Temple, Spirit Pagoda, Sanqing Hall Taoist Temple
Cultural Facility Space	39	Octagonal Pavilion, Dajing Well, Erjing Well, Longquan Well, Dazhongcheng Archway, Cuihua Park, Longquan Village Group 5 Service Center, Longquan Village Group 3 Service Center, Guanyi Community Service Center, Longquan Village Group 1 Service Center, Longquan Village Group 2 Service Center, 28 Ancient Trees
Cultural Industry Space	21	Jufenghao Shoe Store, Wufuxiang Dyeing Workshop, Tengyunhao Paper Binding, Shunchang Bank, Su’s Gold and Silver Treasury, Songhe Hall, Anhuan Hall, Yusheng Store, Fushun Horse Shop, Shayan Shop, Linfahao Tobacco Shreds, Demao Store, Paper Binding Shop, Intangible Cultural Heritage Inheritance and Display Venues (Xiaguan Tuocha Production Technology, Dongjing Music Performance, Bai Nationality Folk Legend Display, Bai Nationality Three-Course Tea, Bai Nationality Paper Cutting and Clay Sculpture, Bai Nationality Painting, Bai Nationality Embroidery, Bai Nationality Raw Skin)

).

3.3. Research Methods and Data Collection

3.3.1. Research Methods

This study collects sample data of residents in Longweiguan Historic and Cultural District through questionnaire surveys, including residents’ background information and residents’ scores on the cultural space satisfaction evaluation scale. It uses frequency analysis of descriptive statistics to calculate the mean and standard deviation, understands the average level and dispersion degree of residents’ satisfaction with the overall and various aspects of cultural spaces, and initially grasps the overall situation of satisfaction.

The research methods used in this study are mainly factor analysis, Pearson correlation analysis, and Structural Equation Modeling.

Factor Analysis: Originated from the correlation analysis idea of Charles Spearman and improved by Louis Thurstone, it is a multivariate statistical method to extract a few potential common factors from multiple observed variables and reveal the internal connection of variables [43]. Its advantages include simplifying data dimensions and identifying potential variables, while its disadvantages include high requirements for data quality, subjective judgment in factor interpretation, and great influence of samples on results. Qi Yingtao et al. used principal component analysis to extract factors with eigenvalues greater than 1 and rotated them by the maximum variance method. Finally, six factors were extracted at the overall level, and common factors under three states were identified to analyze the semantic perception structure and differences in the vending space in the cultural street of Xi’an Baxian Palace [44]. In this study, first, KMO and Bartlett’s sphericity test are used to verify the data adaptability, then potential factors are extracted from satisfaction indicators and dimensionality reduction is carried out to clarify the connotation of common factors, and finally high-loading indicators are selected by rotating factor loading coefficients to verify the explanatory power of common factors to original variables, providing empirical basis for the connection between latent and manifest variables in the subsequent SEM.

Pearson Correlation Analysis: Proposed by British statistician Karl Pearson in 1895 on the basis of Francis Galton’s concept of “correlation”, it is a statistical method to measure the degree and direction of linear correlation between two continuous variables [45]. The core indicator is the Pearson correlation coefficient (r, with a value range of [−1, 1]). The closer |r| is to 1, the stronger the linear correlation. It needs to meet the prerequisites that variables are continuous, bivariate normal distribution, and no outliers. Its advantages are intuitive results, simple calculation, wide application, and accurate quantification of correlation strength. Its disadvantages are that it can only identify linear correlation, is sensitive to outliers, can only explain “correlation” rather than “causality” between variables, is only applicable to continuous variables, and the reliability of results depends on the satisfaction of prerequisites. Taking a typical old community in Wuhan as an example, Peng Wenjun et al. employed Pearson correlation analysis to examine the satisfaction of residents in different dimensions with the overall living satisfaction and renovation approval degree, quantify the direction and tightness of linear correlation between various variables, and lay a foundation for the subsequent exploration of factors affecting residents’ renovation willingness [37]. This study uses Pearson correlation analysis to check the relationship between continuous variables and measure their linear correlation, including correlation coefficient and significance level, and analyze the relationship between evaluation indicators of each type of cultural space, as well as the relationships among the satisfaction of each type of cultural space, the satisfaction of the “existence–relatedness–growth” three dimensions, and the overall satisfaction.

Structural Equation Modeling: This method originates from the integration and development of statistical methods such as factor analysis and path analysis. It is a multivariate statistical analysis method that integrates “measurement model (connecting latent variables and manifest variables)” and “structural model (verifying causal relationship between latent variables)” [46]. Its advantages are that it can handle abstract latent variables such as “satisfaction” and “identity”, verify complex theoretical frameworks, and quantify multi-path effects. Its disadvantages are high requirements for data volume and normality, complex model construction and result interpretation, and dependence on prior theoretical assumptions. Toru Nakayama et al. used Structural Equation Modeling to quantify the positive impact path coefficients of each latent variable on life satisfaction based on four latent variables extracted by exploratory factor analysis: living environment satisfaction, health status satisfaction, social relationship satisfaction, and life rhythm satisfaction [47]. This study uses Structural Equation Modeling (SEM) to analyze the relationship between individual indicators and their impact on overall satisfaction, ensures the reliability and validity of the measurement model through confirmatory factor analysis, clarifies key impact indicators and action paths, and provides quantitative basis for understanding the formation mechanism of residents’ satisfaction.

This study uses “need–space–satisfaction” as the application framework. Through investigation preparation, it understands the practical problems of historic districts and determines residents’ needs; through data collection, it analyzes the characteristics and current situation of cultural spaces, and clarifies the connection path between needs and spaces; finally, through data analysis, the influencing factors of residents’ satisfaction with cultural spaces are obtained, and the relationship between residents’ needs and cultural space satisfaction is explored (Figure 7).

3.3.2. Data Collection

The survey data is divided into two parts. One is the collection of personal background information, that is, the personal basic information of the respondents (gender, age, ethnicity, occupation, etc.). The purpose is to investigate the distribution characteristics of the target group in terms of population structure and social attributes and identify the potential connection between group characteristics and behaviors and attitudes. The other is the collection of residents’ cultural space satisfaction evaluation scale. According to ERG Theory, the scale divides different cultural spaces into three dimensions: existence, relatedness, and growth. A 5-point Likert scale is used for scoring, and satisfaction is divided into five levels: very satisfied, satisfied, general, dissatisfied, and very dissatisfied. A random sampling method was used to distribute questionnaires in areas with a high flow of residents in the district, such as the main streets of Zhongcheng Street and Longwei Street, markets, and community activity centers. Finally, a total of 421 questionnaires were distributed, and 394 valid ones were recovered. The whole survey followed academic ethics: the respondents were clearly informed of the research purpose, questionnaire content, and data usage, and their voluntary participation was confirmed. Personal information was anonymized, and data was encrypted and stored only for this study. At the same time, they were informed they could terminate their participation at any time without negative impact (Figure 8).

3.4. Analysis of Residents’ Needs and Satisfaction Connection Mechanism Based on ERG Theory

3.4.1. Manifestations of Residents’ Needs for Cultural Spaces Under ERG Theory

In the dimension of existence needs (E-Needs), residents’ basic demands for cultural spaces focus on the safety and functionality of the physical environment, including the stability of building structures, the compliance of hygiene conditions, and the completeness of basic service facilities, such as the hardware configuration of rest seats and lighting systems. In the dimension of relatedness needs (R-Needs), residents expect cultural spaces to be carriers of social interaction and enhance emotional connection through neighborhood interaction, community activities, and other forms, such as holding folk gatherings in traditional streets to strengthen community belonging; in the dimension of growth needs (G-Needs), residents pay attention to the educational and developmental value of cultural spaces, which is manifested in the desire for opportunities to learn traditional crafts and understand local historical culture, such as participating in intangible cultural heritage inheritance activities to achieve self-improvement [48].

3.4.2. Applicability of ERG Theory Principles to Residents’ Needs Characteristics

Principle of Need Disorder: ERG Theory points out that human needs do not develop strictly in an order from low to high. Residents’ three types of needs intersecting coexist, and there is no strict hierarchical progressive relationship. For example, elderly residents may pay attention to both the comfort of seats in cultural spaces (existence needs) and neighborhood tea parties (relatedness needs), while young people may pursue intangible cultural heritage experience (growth needs) and Wi-Fi coverage in the venue (existence needs) at the same time, which confirms the non-sequential nature of need development.

Principle of Need Coexistence: Needs at different levels can exist at the same time and stimulate individuals. Residents’ three types of needs often appear simultaneously. For example, for cultural heritage spaces, residents hope that their buildings will be properly protected and repaired (existence needs). They furthermore expect to hold folk activities in these spaces (relatedness needs). They desire to deeply understand the local historical culture and inherit traditional crafts by participating in relevant cultural activities, so as to achieve self-growth and meet growth needs.

Principle of Need Regression: When higher-level needs are not met, residents will shift their attention to lower-level needs. When residents encounter obstacles in pursuing growth and development needs in cultural spaces, such as limited opportunities to learn traditional crafts provided by cultural industry spaces, they may put forward higher requirements for the infrastructure of cultural spaces, such as health facilities and rest places, or have a stronger desire for cultural spaces to strengthen social functions and enhance existence needs and relatedness needs to make up for the lack of growth and development needs.

Principle of Need Enhancement: When a certain need is met, an individual’s pursuit of that need and higher-level needs will be enhanced. For example, when the district repairs and protects a cultural heritage space, improving its safety and display effect and meeting residents’ existence needs and certain growth and development needs, residents may further expect the space to hold more activities related to cultural heritage, such as cultural lectures and traditional craft experience, to deepen the understanding and inheritance of cultural heritage, which is the enhancement of growth and development need (Figure 9).

3.4.3. Connection Path Between Need Satisfaction and Residents’ Satisfaction

Firstly, as the foundation, the satisfaction degree of existence needs constitutes the bottom line of satisfaction. The physical environment quality of cultural spaces, such as building safety, hygiene conditions, and infrastructure status, directly affects the level of satisfaction. Secondly, relatedness needs play an intermediary role through a sense of belonging. Residents’ satisfaction with cultural spaces where folk activities are held regularly is significantly improved, confirming the positive effect of relatedness needs. Thirdly, the satisfaction of growth needs forms a satisfaction premium. Places that provide traditional craft inheritance courses can increase residents’ repeat visit rate and recommendation willingness, reflecting the value-added effect of cultural empowerment. In addition, there is an interaction effect between needs: Existence needs are the premise of relatedness and growth needs. For example, potential safety hazards will inhibit social and learning willingness, while an active social atmosphere can promote the realization of growth needs, such as neighborhood craft exchanges making up for the lack of formal training.

3.5. Construction of Evaluation System

Based on laws, policies, evaluation indicators, the literature materials in the fields of historic district conservation, cultural space construction, and community service facility configuration, combined with field survey data, this study classifies and sorts the cultural space evaluation indicators according to the three-level needs of ERG Theory, and modifies the original indicators through several rounds of expert consultation and indicator screening. The experts who participated in the screening of evaluation indicators and determination of weights mainly have professional backgrounds in architecture and urban-rural planning, and some are from local urban planning management departments and cultural relics protection units, and all possess years of research or practical experience in historic district conservation and cultural space planning. This ensures the professionalism and practical adaptability of the indicator design. Finally, the satisfaction evaluation index system for cultural spaces in historic districts is determined (

Table 3. Satisfaction evaluation index system of cultural spaces in Longweiguan and reference sources.

Type Layer	Criterion Layer	Indicator Layer	Indicator Reference Sources
A Cultural Heritage Space	Existence Needs	A1 Spatial Safety	Chen Jizhou, (2025) [48]; Say-Wah Lee, (2021) [49]; Gu Siming, (2023) [33]; Li Yuhua, (2024) [50]
		A2 Supporting Completeness	Chen Jizhou, (2025) [48]; Ma Yue, (2024) [51]; Liu Mingyuan, (2025) [19]; Say-Wah Lee, (2021) [49]
	Relatedness Needs	A3 Cultural Identity	Ma Yue, (2024) [51]; Chen Zichu, (2024) [52]; Say-Wah Lee, (2021) [49]
		A4 Social Interaction	Chen Jizhou, (2025) [48]; Liu Mingyuan, (2025) [19]; Gu Siming, (2023) [33]
	Growth Needs	A5 Cultural Education	Ma Yue, (2024) [51]; Say-Wah Lee, (2021) [49]; Gu Siming, (2023) [33]
		A6 Cultural Utilization	Ma Yue, (2024) [51]; Davoodi Tina, (2019) [23]
B Cultural Facility Space	Existence Needs	B1 Spatial Practicality	Ma Yue, (2024) [51]; Liu Mingyuan, (2025) [19]; Gong Cong, (2025) [53]; Liu Chenxi, (2025) [54]
		B2 Traffic Accessibility	Chen Jizhou, (2025) [48]; Ma Yue, (2024) [51]; Gong Cong, (2025) [53]; Huang Dongsheng, (2025) [55]
		B3 Spatial Comfort	Chen Jizhou, (2025) [48]; Liu Mingyuan, (2025) [19]; Davoodi Tina, (2019) [23]; She Haoran, (2025) [56]
	Relatedness Needs	B4 Social Diversity	Ma Yue, (2024) [51]; Liu Mingyuan, (2025) [19]; He Jing, (2020) [57]; Say-Wah Lee, (2021) [49]
		B5 Cultural Sharing	Ma Yue, (2024) [51]; Davoodi Tina, (2019) [23]; Ji Xian, (2024) [14]
		B6 Cultural Cohesion	He Jing, (2020) [57]; Ji Xian, (2024) [14]; Zhang Fan, (2025) [58]
	Growth Needs	B7 Cultural Improvement	Liu Mingyuan, (2025) [19]; Gong Cong, (2025) [53]; Davoodi Tina, (2019) [23]; Yang Yue, (2025) [59]
		B8 Cultural Innovation	Liu Mingyuan, (2025) [19]; Say-Wah Lee, (2021) [49]; Gu Siming, (2023) [33]
C Cultural Industry Space	Existence Needs	C1 Economic Effectiveness	Ma Yue, (2024) [51]; Elena Bykowa, (2021) [60]; Gu Siming, (2023) [33]
		C2 Spatial Applicability	Chen Jizhou, (2025) [48]; Liu Mingyuan, (2025) [19]; Elena Bykowa, (2021) [60]
	Relatedness Needs	C3 Cultural Participation	Ma Yue, (2024) [51]; Say-Wah Lee, (2021) [49]
		C4 Cultural Belonging	Liu Mingyuan, (2025) [19]; Chen Zichu, (2024) [52]
	Growth Needs	C5 Cultural Inheritance	Say-Wah Lee, (2021) [49]; Elena Bykowa, (2021) [60]; Gu Siming, (2023) [33]
		C6 Innovative Development	Ma Yue, (2024) [51]; Liu Mingyuan, (2025) [19]; Gong Cong, (2025) [53]

). The cultural heritage space includes six evaluation indicators (A1–A6), the cultural facility space includes eight evaluation indicators (B1–B8), and the cultural industry space includes six evaluation indicators (C1–C6). Explanations of specific indicators are shown in Appendix A 

Table A1. Explanations of evaluation indicators for residents’ satisfaction with cultural spaces in Longweiguan.

Indicator	Indicator Description
A1 Spatial Safety	Sound building structure and complete fire-fighting facilities
A2 Supporting Completeness	Equipped with rest areas, sanitation facilities, barrier-free facilities, etc.
A3 Cultural Identity	Display local historical culture and traditional crafts to enhance residents’ pride and identity in local culture
A4 Social Interaction	Provide venues and opportunities for people to communicate and interact
A5 Cultural Education	Possess educational functions, using new communication technologies to enable people to deeply understand historical and cultural knowledge through exhibitions, explanations, etc.
A6 Cultural Utilization	Innovative utilization of cultural heritage spaces, transformed into venues with modern cultural functions
B1 Spatial Practicality	Reasonable spatial layout, clear division of functional areas, and complete facilities
B2 Traffic Accessibility	Convenient transportation between the space and residents’ residences, easily accessible location, and sufficient parking spaces
B3 Spatial Comfort	A comfortable environment that allows residents to feel physically and mentally pleasant when participating in activities and willing to stay for a long time
B4 Social Diversity	Provide various types of cultural activities to meet the interests and hobbies of different residents
B5 Cultural Sharing	Cultural resources and tools are open to residents with a sound sharing mechanism
B6 Cultural Cohesion	Attract a large number of residents to participate, promote communication and cooperation among residents, and enhance cultural cohesion
B7 Cultural Improvement	Cultural activities can help residents learn new skills, improve personal abilities, and achieve self-growth
B8 Cultural Innovation	Integration of diverse cultures and organization of creative activities
C1 Economic Effectiveness	Provide employment opportunities, increase residents’ income, and drive economic development
C2 Spatial Applicability	Comfortable and safe working environment for traditional handicraft workshops, with good tools and equipment, and workplaces meeting safety standards
C3 Cultural Participation	Residents’ participation in traditional handicraft inheritance activities and cultural popularization activities
C4 Cultural Belonging	Residents are proud of traditional handicraft workshops and intangible cultural heritage inheritance, willing to recommend them to the outside world, and have a strong sense of identity
C5 Cultural Inheritance	Provide inheritance spaces for traditional craftsmen, with organized master–apprentice inheritance activities or skill displays
C6 Innovative Development	Development of cultural and creative products inspired by ethnic culture, transformation of traditional handicraft workshops and time-honored stores

.

In terms of the safety of cultural heritage space, with many ancient buildings in the district, ensuring the stability of building structures and the completeness of fire-fighting facilities can prevent safety risks caused by age or accidents. In terms of supporting completeness, setting up resting seats is convenient for tourists and residents to stop for a break, and improving barrier-free facilities enhances the accessibility of cultural spaces for special groups. In terms of cultural identity, by displaying the historical stories and traditional crafts of Longweiguan, the pride and identity of local residents in their native culture are enhanced. Social interaction is manifested in creating places such as traditional markets and cultural squares to promote communication and interaction between residents and tourists. Cultural education enables people to acquire in-depth knowledge by using multimedia to display the historical changes in the district. Cultural utilization refers to innovatively activating the heritage space by transforming idle ancient houses into cultural studios and folk exhibition halls.

In the cultural facility space, spatial practicality requires the reasonable layout of cultural facilities and the complete allocation of amenities to adapt to the complex functional needs of the district. Traffic accessibility emphasizes the convenient transportation between cultural facilities and residents’ residences, which eases the traffic pressure of the district and facilitates residents’ access. Spatial comfort refers to creating a pleasant environment to enhance residents’ willingness to stay. Social diversity needs to carry out various cultural activities to meet the interests of different residents. Cultural sharing requires opening cultural resources and tools to promote cultural inheritance. Cultural cohesion attracts residents’ participation by holding community activities such as folk festivals and enhances cultural identity. Cultural improvement helps residents learn new skills by holding activities such as traditional craft courses. Cultural innovation integrates local and multi-cultural elements and holds activities such as creative markets.

In the cultural industry space, economic effectiveness means that cultural industries in the district, such as the sale of handcrafts, provide employment opportunities, drive the economy, and help residents increase their income. Spatial applicability is to ensure that the environment of traditional handicraft workshops is comfortable and safe, and the equipment meets the standards, which is conducive to creation. Cultural participation is manifested in people’s participation in the inheritance of crafts such as tie-dyeing and cultural activities, which reflect vitality. Cultural identity means that residents are proud of the district’s crafts and intangible cultural heritage and take the initiative to promote them. Cultural inheritance builds an inheritance space for traditional craftsmen and carries out master–apprentice inheritance. Innovative development uses Bai culture as inspiration to develop cultural and creative products and promote the transformation of traditional workshops.

4. Results and Analysis

Data analysis first validated the authenticity and validity of the data through reliability testing, validity testing, and factor analysis. Subsequently, descriptive statistical methods were employed to clarify residents’ overall satisfaction with cultural spaces and the scores for each indicator. Through correlation analysis and Structural Equation Modeling (SEM), a quantitative analysis was conducted on the current satisfaction status, influencing factors, and the demand–satisfaction linkage mechanism among residents of the Longweiguan Historic Cultural District. This revealed how different levels of demand influence satisfaction levels (Figure 10).

4.1. Data Reliability Verification

Reliability analysis is mainly used to examine the stability and consistency of the results measured by the scale in the questionnaire, that is, to test whether the scale samples in the questionnaire are true and reliable. This paper uses the Cronbach’s Alpha reliability coefficient method to conduct a dimensional reliability analysis of the questionnaire. The value range of Cronbach’s Alpha coefficient is between 0 and 1. The closer it is to 1, the higher the reliability of the questionnaire.

From the test results in the following table, it can be seen that the Cronbach α coefficients of satisfaction with cultural heritage space, cultural facility space, and cultural industry space are 0.855, 0.892, and 0.877, respectively, and the Cronbach α coefficient of the total scale is 0.953, all greater than 0.7 (

Table 4. Dimensional reliability analysis of residents’ satisfaction.

Dimension	Cronbach’s α Coefficient	Standardized Cronbach’s α Coefficient	Number of Items	Sample Size
Cultural heritage space	0.855	0.854	6	394
Cultural facilities space	0.892	0.893	8	394
Cultural industries space	0.877	0.877	6	394
Overall	0.953	0.953	20	394

), indicating that the scale has extremely high internal consistency reliability. The standardized Cronbach α coefficient is also 0.953, indicating that after considering the influence of the variability of each item score, the reliability of the scale remains highly stable. It shows that the questionnaire survey results pass the reliability test and have high reliability.

4.2. Validity and Factor Analysis

Validity analysis is used to test whether the measurement tool can accurately reflect the actual characteristics of the research variables. The core is to verify the adaptability between indicators and theoretical dimensions. In this study, KMO test and Bartlett’s sphericity test are used to verify that the data is suitable for factor analysis. The KMO value is 0.974, which is close to 1. The closer it is to 1, the more effectively the common information between variables can be extracted, indicating that there is a strong common variance between variables, which is suitable for factor analysis. The approximate chi-square value of Bartlett’s sphericity test is 4608.049, df = 190, p = 0.000 ***, which rejects the original hypothesis of variable independence, indicating that the variables are highly correlated and can be reduced by factor analysis to explore the potential structure between various indicator elements (

Table 5. Validity analysis.

KMO Test and Bartlett’s Test
KMO value		0.974
Bartlett’s Test of Sphericity	Approximate Chi-square	4608.049
	df	190
	p	0.000 ***

Note: *** represent significance levels of 1%.

).

Factor analysis is a statistical method to extract potential common factors through dimensionality reduction. The rotated factor loading coefficient table is used to show the strength of the connection between variables and each factor (the higher the loading value, the closer the connection). Generally speaking, when the rotated factor loading value is greater than 0.5, the variable can be expressed by the corresponding common factor; for a more sufficient and reasonable explanation that variables can be well expressed by common factors, it is more ideal that the rotated factor loading value is greater than 0.7. Factor analysis shows that in Factor 1, C4 Cultural Belonging (0.70), B4 Social Diversity (0.649), and A3 Cultural Identity (0.588) show that residents have a strong demand for cultural belonging and social interaction, reflecting the symbiotic relationship between social interaction and cultural identity. In Factor 2, B1 Spatial Practicality (0.711) and B3 Spatial Comfort (0.589) reflect residents’ basic functional needs for the practicality and comfort of cultural spaces. In Factor 3, A4 Social Interaction (0.606) and B2 Traffic Accessibility (0.675) reflect the intersection of social and functional needs in residential historic districts. In Factor 4, A5 Cultural Education (0.823) highlights residents’ strong demand for cultural resources (

Table 6. Factor loading coefficient table of residents’ satisfaction indicators at all levels.

Factor Loading Coefficient Table After Rotation					Communality (Common Factor Variance)
	Factor Loading Coefficients After Rotation
	Factor 1	Factor 2	Factor 3	Factor 4
A1	0.398	0.399	0.451	0.462	0.734
A2	0.245	0.41	0.328	0.46	0.548
A3	0.588	0.362	0.403	−0.018	0.639
A4	0.478	−0.092	0.606	0.4	0.764
A5	0.228	0.184	0.162	0.823	0.789
A6	0.26	0.256	0.709	0.175	0.667
B1	0.306	0.711	0.239	0.168	0.684
B2	0.198	0.425	0.675	0.152	0.698
B3	0.48	0.589	0.194	0.229	0.668
B4	0.649	0.196	0.418	0.102	0.646
B5	0.242	0.562	0.42	0.284	0.631
B6	0.561	0.439	0.147	0.307	0.622
B7	0.578	0.402	0.055	0.328	0.606
B8	0.489	0.356	0.147	0.438	0.579
C1	0.54	0.301	0.313	0.335	0.592
C2	0.623	0.29	0.239	0.233	0.584
C3	0.596	0.202	0.294	0.265	0.553
C4	0.7	0.205	0.2	0.227	0.623
C5	0.574	0.222	0.278	0.38	0.6
C6	0.521	0.265	0.268	0.458	0.623

).

Through cross-analysis of key variables, it is found that C4 Cultural Belonging (Factor 1 loading 0.70) and A3 Cultural Identity (Factor 1 loading 0.588) are both concentrated in the relatedness dimension, indicating that cultural identity has duality. It is not only an emotional link but also the basis for social interaction. The comparison between C6 Innovative Development (Factor 4 loading 0.458) and A5 Cultural Education (Factor 4 loading 0.823) shows that innovative momentum needs to be based on educational resources. Group B variables (such as B1, B3) are distributed between existence and relatedness needs, reflecting that cultural facility spaces need to take into account both functional practicality and social attributes.

4.3. Measurement of Current Satisfaction Status with Cultural Spaces

4.3.1. Statistical Characteristics of Voluntary Samples

According to the questionnaire analysis, the gender distribution of residents in Longweiguan is balanced, with females accounting for 51.5% and males accounting for 48.5%. Residents are mainly middle-aged and young people, and the proportion of dynamic people in the district is high. Long-term residents (over 10 years) account for the highest proportion (38.1%), reflecting the strong stability of residents in the district. Occupations are diversified, with individual operators (24.4%) and freelancers (18.0%) accounting for a relatively high proportion, which is in line with the characteristics of the integration of small businesses and culture in historic districts. The majority are Han nationality (45.7%) and Bai nationality (40.1%), which is in line with the regional cultural characteristics of multi-ethnic settlement in Dali (

Table 7. Statistical characteristics of personal background information.

Information	Option	Frequency	Percentage (%)	Cumulative Percentage (%)
Gender	Female	203	51.523	51.523
	Male	191	48.477	100
Age Group	From 18 to 30 years old	169	42.893	42.893
	From 31 to 50 years old	117	29.695	72.589
	51 years old and over	70	17.766	90.355
	Under 18 years old	38	9.645	100
Residence Duration in Longweiguan	Over 10 years	150	38.071	38.071
	From 6 to 10 years	109	27.665	65.736
	Less than 1 year	73	18.528	84.264
	From 1 to 5 years	62	15.736	100
Occupation	Individual Operator	96	24.365	24.365
	Others	82	20.812	45.178
	Freelancer	71	18.02	63.198
	Enterprise employee	64	16.244	79.442
	Government/Institution Staff	55	13.959	93.401
	Retiree	26	6.599	100
Ethnicity	Han	180	45.685	45.685
	Bai	158	40.102	85.787
	Other Ethnicities	56	14.213	100
Total		394	100.000	100.000

). According to the analysis, it is found that the correlation between residents’ satisfaction and personal differences (such as ethnicity, gender, age, occupation) is not significant, so population differences are not the main factors affecting residents’ satisfaction (Figure 11).

4.3.2. Overall Characterization of Satisfaction

Data show that the satisfaction of residents in Longweiguan, Dali, with the three types of cultural spaces is generally above average (mean 3.09–3.15), among which the overall satisfaction mean is 3.126, the satisfaction with cultural facility space is slightly higher (mean 3.14, CV = 0.257), and the satisfaction with cultural industry space is slightly lower with a slightly larger degree of dispersion (mean 3.09, CV = 0.273). The skewness of all variables is negative (−0.17 to −0.26), indicating that the score distribution is left-skewed, that is, most residents tend to give higher evaluations. The kurtosis is negative (−0.36 to −0.65), reflecting that the data distribution is flatter than the normal distribution. Residents have a good overall recognition of the cultural space in the district, but the satisfaction with the cultural industry space still needs to be improved (

Table 8. Descriptive statistics of residents’ satisfaction with various cultural spaces.

Variable Name	Sample Size	Max	Min	Avg	Sigma	Median	Variance	Kurtosis	Skewness	Coefficient of Variation (CV)
Satisfaction of Cultural heritage space	394	5	1	3.145	0.86	3.167	0.739	−0.648	−0.266	0.273
Satisfaction of Cultural facilities space	394	5	1	3.14	0.808	3.25	0.653	−0.412	−0.179	0.257
Satisfaction of Cultural industries space	394	5	1	3.09	0.845	3.167	0.714	−0.363	−0.264	0.273
Overall satisfaction	394	5	1	3.126	0.792	3.225	0.628	−0.54	−0.251	0.253

).

Among the three dimensions based on ERG Theory, the mean satisfaction of existence needs is 3.167, that of relatedness needs is 3.128, that of growth needs is 3.077, and the mean overall satisfaction is 3.126. The mean satisfaction of growth needs is the lowest and lower than the overall satisfaction, reflecting that residents’ satisfaction with growth needs (cultural improvement, innovative development, etc.) is insufficient, indicating that the supply of growth needs dimension in cultural space construction may not fully meet residents’ expectations (

Table 9. Descriptive statistics of residents’ satisfaction with three dimensions of ERG Theory.

Variable Name	Sample Size	Max	Min	Avg	Sigma	Median	Variance	Kurtosis	Skewness	Coefficient of Variation (CV)
Existence Needs	394	5	1	3.167	0.853	3.286	0.728	−0.677	−0.289	0.269
Relatedness Needs	394	5	1	3.128	0.812	3.143	0.659	−0.387	−0.181	0.260
Growth Needs	394	5	1	3.077	0.827	3.167	0.684	−0.505	−0.106	0.269
Overall Satisfaction	394	5	1	3.126	0.792	3.225	0.628	−0.54	−0.251	0.253

).

According to the survey data, frequency statistical analysis is carried out on the three types of evaluation elements, A, B, and C (Figure 12). Residents’ satisfaction with cultural spaces in Longweiguan shows significant differences. A1 Spatial Safety, B8 Cultural Innovation, and C4 Cultural Belonging have more high scores, indicating that residents have a high recognition of basic safety, cultural innovation, and identity; A5 Cultural Education and A6 Cultural Utilization have low scores, reflecting the insufficient educational transformation and actual utilization efficiency of cultural resources.

4.4. Correlation Analysis of Residents’ Satisfaction

This paper uses Pearson correlation coefficient to analyze the correlation degree between variables. First, test whether there is a statistically significant relationship (p < 0.05) between the X and Y axes, and then analyze the positive and negative directions of the correlation coefficient and the degree of correlation. The analysis results are represented by a heat map, and the color depth reflects the degree of correlation, with red indicating strong positive correlation (Figure 13).

Figure 13a shows that A4 Social Interaction, A5 Cultural Education, and A6 Cultural Utilization are highly correlated. A2 Supporting Completeness has a weak correlation with other variables and a negative correlation with A5 Cultural Education and A6 Cultural Utilization. A3 Cultural Identity is only significantly correlated with A1 Spatial Safety. This indicates that supporting facilities are disconnected from cultural functions, and cultural identity has not been effectively transformed into motivation for educational utilization. It is necessary to strengthen the integrated design of facilities and cultural activities and enhance the synergy between cultural identity and educational utilization.

Figure 13b shows that B6 Cultural Cohesion is highly correlated with B7 Cultural Improvement and B8 Cultural Innovation, but B5 Cultural Sharing has a negative correlation with B7 and B8, and B1 Spatial Practicality has a negative correlation with B2 Traffic Accessibility. This indicates that there is a contradiction between cultural sharing and cultural improvement and innovation, and there is a conflict between traffic accessibility and spatial practicality. It is necessary to optimize the allocation of spatial resources, strengthen sharing and innovative development, and improve the balance between traffic and practicality.

Figure 13c shows that C5 Cultural Inheritance is highly correlated with C6 Innovative Development, but C6 Innovative Development has a weak correlation with C3 Cultural Participation and C2 Spatial Applicability. This indicates that innovative development is disconnected from cultural participation, and spatial applicability provides insufficient support for innovation. It is necessary to strengthen the integration of innovative practices and residents’ participation and optimize spatial design to promote the transformation of innovative momentum.

Figure 13d shows that overall satisfaction has the strongest correlation with cultural industry space and relatedness needs. Growth needs are significantly correlated with overall satisfaction, existence needs have a weak correlation with growth needs, and satisfaction with cultural heritage space has a low correlation with satisfaction with cultural facility space. This indicates that the balance between existence and growth needs is insufficient, and the linkage between cultural heritage and facility space is weak. It is necessary to strengthen the integration of basic functions and cultural development and jointly improve the satisfaction of cultural heritage space and cultural facility space.

4.5. Establishment and Analysis of Structural Equation Modeling (SEM)

4.5.1. Establishment of SEM

According to the preliminary results of Pearson correlation analysis, SEM is used to conduct an in-depth study of the relationship between variables. A conceptual model is proposed based on ERG need hierarchy theory. The model is based on the relationship assumptions of corresponding variables, mainly including the relationship between existence needs, relatedness needs, and growth needs, as well as their relationship structure with the overall satisfaction of cultural spaces.

After several rounds of hypothesis adjustment, combined with the survey of residents’ needs and the analysis of model fitting, the following assumptions are finally determined (

Table 10. Assumptions on the relationship structure between residents’ needs at different levels and satisfaction.

Question Number	Assumption
H1	Existence needs have a significantly positive impact on overall satisfaction.
H2	Relationship needs have a significantly positive impact on overall satisfaction.
H3	Growth needs have a significantly positive impact on overall satisfaction.
H4	Existence needs have a significantly positive impact on relationship needs.
H5	Growth needs have a significantly positive impact on relationship needs.
H6	Relationship needs have a significantly positive impact on growth needs.
H7	Relationship needs have a significantly positive impact on existence needs.

). According to the proposed assumptions, the original path of residents’ satisfaction with cultural spaces is drawn as shown in Figure 14. The conceptual model shows a weighted structural path diagram, which mainly includes the standardized coefficients of the model. Its value and direction indicate the impact degree and path between variables and are used to analyze the impact relationship of structural paths.

4.5.2. Confirmatory Factor Analysis

Confirmatory Factor Analysis (CFA) is used to test whether the factors formed by multiple latent variables are valid and whether the relationship between factors and corresponding latent variables conforms to the theoretical relationship of the hypothetical model. Factor loading coefficients are used to screen the measured variables within the factors. The measured variables that pass the significance test (p < 0.05) and have a standardized loading coefficient greater than 0.6 are selected. The results show (

Table 11. Factor loading coefficient table.

Factor	Variable	Standardized Loading Coefficient	p
Factor 1	Overall Satisfaction Score	0.946	-
Factor 2	A1 B1 B2 B3 A2 C1 C2	0.812 0.697 0.695 0.747 0.695 0.743 0.72	- 0.000 *** 0.000 *** 0.000 *** 0.000 *** 0.000 *** 0.000 ***
Factor 2	A3 A4 B4 B5 B6 C3 C4	0.703 0.695 0.72 0.714 0.728 0.706 0.708	- 0.000 *** 0.000 *** 0.000 *** 0.000 *** 0.000 *** 0.000 ***
Factor 4	A5 A6 B7 B8 C5 C6	0.66 0.677 0.698 0.703 0.725 0.737	- 0.000 *** 0.000 *** 0.000 *** 0.000 *** 0.000 ***

Note: *** represent significance levels of 1%.

) that all factors meet the requirements and can be used for further analysis.

The results of Average Variance Extracted (AVE) and Composite Reliability (CR) can be used to represent the convergent validity of variables within the factor. Generally speaking, it is sufficient to meet either AVE higher than 0.5 or CR higher than 0.7. The model evaluation results all meet the conditions (

Table 12. AVE and CR model evaluation.

Factor	Average Variance Extracted (AVE) Value	Composite Reliability (CR) Value
Factor 1	0.896	0.896
Factor 2	0.544	0.891
Factor 3	0.505	0.877
Factor 4	0.49	0.852

), indicating high convergent validity.

4.5.3. Solution of SEM

The model fitting results are shown in

Table 13. Model fitting results.

χ2	df	p	χ2/df	GFI	RMSEA	RMR	CFI	NFI	NNFI
-	-	>0.05	<3	>0.9	<0.10	<0.05	>0.9	>0.9	>0.9
563.518	182	0.000 ***	3.096	0.913	0.073	14.227	0.939	0.913	0.93
			approach	ideal	ideal	not ideal	ideal	ideal	ideal

Note: *** represent significance levels of 1%.

. The model fitting can be analyzed through its indicators, and it is usually not required to pass all tests. Chi-square (χ²) and degrees of freedom (df) are mainly used for comparing multiple models. A smaller chi-square value is preferable. Degrees of freedom reflect the complexity of the model: the simpler the model, the more degrees of freedom it has; conversely, the more complex the model, the fewer degrees of freedom it possesses. The Goodness of Fit Index (GFI) primarily uses the coefficient of determination and standard error of regression to test the degree of fit between the model and sample observations. Its value ranges from 0 to 1, with a value closer to 0 indicating a poorer fit. A GFI ≥ 0.9 is considered to represent a good model fit. For the Root Mean Square Error of Approximation (RMSEA), an RMSEA value below 0.08 is generally acceptable (the smaller the better). The Root Mean Square Residual (RMR) measures the average residual between predicted correlations and actual observed correlations to assess the model’s fit. An RMR < 0.1 is deemed to indicate a good model fit. The Comparative Fit Index (CFI) is used when comparing the hypothesized model with the independent model. Its value ranges from 0 to 1: a value closer to 0 signifies a poorer fit, while a value closer to 1 indicates a better fit. Typically, a CFI ≥ 0.9 is regarded as a good model fit. For the Non-Normed Fit Index (NNFI) and Normed Fit Index (NFI), higher values are better, indicating superior performance of the fitted model. The fitting indexes are CFI = 0.913, RMSEA = 0.073, RMR = 14.227, GFI = 0.939, NFI = 0.913, and TLI = 0.93. Most of them are within the acceptable range, indicating that the model fits well.

As can be seen from the model path coefficients (

Table 14. Model regression coefficients.

Factor (Latent Variable)	→	Analysis Item (Manifest Variable)	Non-Standardized Coefficient	Standardized Coefficient	SE	Z	p
Existence needs	→	overall satisfaction	1.144	0.08	0.261	4.389	0.000 ***
Relationship needs	→	overall satisfaction	9.446	0.463	0.183	51.587	0.000 ***
Growth needs	→	overall satisfaction	9.701	0.457	0.176	55.173	0.000 ***
Existence needs	→	Relationship needs	1.319	1.878	0.066	19.928	0.000 ***
Growth needs	→	Relationship needs	1.51	1.45	0.045	33.832	0.000 ***
Relationship needs	→	Growth needs	0.96	1	0.074	13.046	0.000 ***
Relationship needs	→	Existence needs	1.424	1	0.086	16.513	0.000 ***

Note: *** represent significance levels of 1%. → represents a path relationship.

), which reflect the paired characteristics of the model, the significance test (p < 0.05) confirms that there are significant relationships among all model variables, indicating the existence of influential relationships between variables. The standardized path coefficients represent the magnitude of the influence effect between variables. By analyzing the influence magnitude between different needs and overall satisfaction, the degree of influence of various factors on residents’ satisfaction with cultural spaces can be determined.

4.5.4. Analysis of Influencing Factors on Residents’ Satisfaction with Cultural Spaces

As illustrated in Figure 14, the conceptual model of residents’ satisfaction with cultural spaces based on ERG Theory, the factors at all levels that influence residents’ satisfaction are analyzed. The key influencing factors of residents’ satisfaction are existence needs (standardized coefficient: 0.08), relatedness needs (standardized coefficient: 0.463), and growth needs (standardized coefficient: 0.457). All of these factors have a significant positive impact on overall satisfaction, with relatedness needs and growth needs exerting a relatively greater influence on satisfaction. There are also significant positive correlations among these three latent variables, particularly between existence needs and relatedness needs (standardized coefficient: 1.878). However, there is no obvious correlation between existence needs and growth needs.

The main factors influencing each latent variable are as follows:

Based on the above analysis, among the existence needs, the impact of A1 Spatial Safety (standardized coefficient: 0.834) is significantly higher than that of other factor variables (all around 0.7). This indicates that residents’ evaluations of spatial safety elements, such as the safety of building structures (e.g., cracks and tilts in walls and beams), the completeness of fire-fighting facilities, and the smoothness of roads, play a decisive role in the satisfaction with existence needs. Meanwhile, this dimension has a strong positive path impact (standardized coefficient: 1.319) on the satisfaction with relatedness needs. This implies that when residents perceive insufficient spatial safety, it will not only directly reduce their satisfaction with existence needs but also weaken their satisfaction at the relatedness needs level (e.g., the willingness to participate in community interactions), forming a transmission mechanism of “safety foundation → social willingness”.

The standardized coefficients of all factor variables under relatedness needs exceed 0.7, among which B6 Cultural Cohesion (0.749) is particularly prominent. This reflects that residents have a strong expectation for the function of cultural spaces in promoting neighborhood communication and enhancing collective identity, and this expectation has a significant impact on residents’ satisfaction at the relatedness needs level. Data shows that relatedness needs have a significant positive path impact (0.96) on the satisfaction with growth needs and a reverse path impact (1.424) on the satisfaction with existence needs. This reveals a two-way feedback mechanism of “basic needs ← social experience → growth needs”: high-quality community interactions may not only stimulate residents’ pursuit of cultural inheritance and innovation but also intensify their anxiety about basic safety guarantees when social interactions are hindered.

Among the growth needs, C6 Innovative Development (0.764) and C5 Cultural Inheritance (0.749) are the core influencing factors. This indicates that residents pay great attention to whether cultural spaces can provide activities for the inheritance of traditional crafts (such as the display of Bai nationality paper-cutting and clay sculpture) to help them achieve self-improvement, and whether traditional handicraft workshops and time-honored stores can achieve the dual functions of innovation and transformation in combination with modern conditions. This dimension has a significant reverse path impact (1.51) on the satisfaction with relatedness needs, forming a feedback loop of “development achievements → social quality”. When cultural spaces demonstrate innovative vitality, they will attract more residents to participate in interactions, thereby strengthening community cohesion. Conversely, if the inheritance of culture stagnates, it may lead to a decline in the quality of social activities and form a cycle of demand attenuation.

5. Discussion

5.1. Research Findings

This study is the first to introduce ERG Theory into the evaluation of residents’ satisfaction with cultural spaces in historic districts. It systematically reveals the dynamic interweaving characteristics of residents’ demand levels for cultural spaces and the mechanism influencing satisfaction. The core research findings are as follows:

(1) Verification of the dynamic applicability of ERG Theory: The study confirms that ERG Theory can effectively explain the characteristics of residents’ spatial needs. This is consistent with the conclusion of Liu Mingyuan’s (2025) research on evaluating user experience in cultural tourism spaces in the Shuangta Market in Suzhou [19]. Both studies jointly confirm the adaptability of this theory in the field of spatial research. However, this study finds that residents’ needs present a two-way feedback path of “existence–relatedness–growth”, and the standardized coefficient of the non-linear relationship between demand levels ranges from 1.319 to 1.51, which clearly defines the intensity and path of the interaction between needs. This reflects the dual attributes of cultural spaces in historic districts as “carriers of life + containers of culture”. As a multi-ethnic residential district, the residents of Longweiguan not only need safety guarantees but also are eager to enhance their cultural identity through social interaction, which provides a basis for the analysis of the demand mechanism. The standardized path coefficients between demand hierarchies (1.319–1.51) indicate that the interaction intensity between existence needs and relatedness needs is the highest, which is closely related to the specific characteristics of Longweiguan’s heritage. As a former military pass and an important node on the Ancient Tea-Horse Road, its historical function of “defense + communication” has shaped residents’ inherent dual demands for spatial safety (Existence Needs) and social connection (Relatedness Needs). From the perspective of cultural policies, Dali’s emphasis on the “living conservation” of historic districts has promoted the integration of basic living security and cultural interaction functions, indirectly strengthening the linkage between these two types of needs. In contrast, there is no obvious direct correlation between existence needs and growth needs (no significant path coefficient), which is affected by the socio-economic conditions of the district. Most residents are individual operators and freelancers, and their demands for cultural education and innovative development (Growth Needs) are restricted by time and economic costs, resulting in a relatively independent development logic of Growth Needs compared with the other two types of needs.

(2) The core role of relatedness needs: The impact coefficient of relatedness needs (cultural cohesion, social diversity) on overall satisfaction is the highest (β = 0.463), and it serves as an intermediary variable between existence needs and growth needs. This echoes the research of Chen Jizhou (2025) who emphasized public social spaces in the study of the Nanhesha Historic Block in Yangzhou [48]. However, this study further finds that relatedness needs are transmitted through two key factors: cultural cohesion (B6) and social diversity (B4), and the transmission mechanism of relatedness needs is clarified through the SEM model. The former strengthens the multi-ethnic cultural identity of Longweiguan, while the latter provides interaction opportunities through street gatherings, intangible cultural heritage experiences, etc. Together, they form the core path for improving satisfaction. Cultural spaces in historic districts are “carriers of social memory”. Residents of Longweiguan have long interacted in spaces such as Shoukang Building and Dajing Well, and these spaces have been integrated into their daily lives. This finding clearly identifies the transmission factors of relatedness needs for the first time, pointing out the direction for optimizing social functions. The highest impact coefficient of Relatedness Needs (β = 0.463) is not only a result of the spatial characteristics of Longweiguan but also influenced by regional cultural policies. Dali’s cultural policy of “ethnic cultural integration” encourages the joint participation of multiple ethnic groups in cultural activities, making cultural cohesion and social diversity (core indicators of relatedness needs) key points for residents to perceive satisfaction. From the perspective of socio-economic conditions, the diversified occupations of residents (individual operators, freelancers, etc.) have given rise to cross-group social demands, and cultural spaces such as traditional streets and community activity centers just meet this demand, further increasing the weight of relatedness needs. Compared with growth needs, relatedness needs have a lower threshold for satisfaction—they do not require residents to have a high educational background or economic investment and can be realized through daily interactions, which also makes relatedness needs more likely to become the core driving factor of overall satisfaction.

(3) The innovation bottleneck of cultural industry spaces: The study shows that the satisfaction with cultural industry spaces is the lowest (mean value: 3.09), and there is a weak correlation (r = 0.268) between innovative development (C6) and cultural participation (C3). This reveals the structural contradiction between innovative practices and residents’ participation. This is consistent with the problem of insufficient dynamic inheritance of the intangible cultural heritage industry proposed by He Chuan (2024) in his research on intangible cultural heritage, spatial structure, and mechanisms in the Dongting Lake Basin [61]. However, this study finds that the root cause of this contradiction is not simply the insufficient inheritance efforts, but the lack of dual support from spatial applicability (C2) and cultural education resources (A5). The working environment of some traditional handicraft workshops in Longweiguan fails to meet the participation needs of residents; in addition, the insufficient cultural education makes it difficult for residents to deeply participate in innovative practices. The root cause lies in the fact that the current transformation of cultural industry spaces in historic districts mostly focuses on morphological renewal, while ignoring functional adaptation and educational empowerment. The phenomenon of the lowest satisfaction with growth needs (mean value: 3.077) and the low correlation between innovative development and cultural participation is closely related to the specific characteristics of Longweiguan’s heritage and socio-economic conditions. Longweiguan’s cultural industry is mainly dominated by traditional handicrafts and time-honored brands, which are restricted by traditional production methods and have a slow pace of innovation. From the perspective of cultural policies, although there are policies supporting the inheritance of ICH, there is a lack of specific measures to link innovation with residents’ participation, leading to innovative practices being divorced from the actual needs of residents. At the socio-economic level, the aging of some traditional craftsmen and the shortage of young inheritors make it difficult to promote innovative development; at the same time, residents’ insufficient access to cultural education resources (such as the lack of systematic training in traditional crafts) limits their ability to participate in innovative activities, forming a bottleneck in the satisfaction of growth needs. Compared with the other two dimensions, growth needs have higher requirements for resource investment and policy guidance, and the current insufficient supply in these aspects directly leads to the weak performance of growth-related indicators.

5.2. Optimization Strategies

Based on the preceding research conclusions that “existence needs are the foundation, relatedness needs are the core, growth needs have shortcomings, and the disconnection of cultural industry spaces is a bottleneck”, and aiming at the pain points in meeting the three types of needs and the core contradictions, a “safety–social interaction–innovation” trinity optimization strategy is proposed as follows:

At the existence needs level (safety): Reinforce and restore the structure of ancient buildings. Implement seismic reinforcement for ancient buildings such as Shoukang Building and Ma Chongliu’s Former Residence and focus on repairing structural problems such as wall cracks and beam-column tilts. Optimize fire-fighting and road traffic. Add micro-fire stations in the areas with dense cultural heritage spaces to establish a “1 min response” fire-fighting network. Widen some narrow sections of Longwei Street and Zhongcheng Street and set up signs for the separation of pedestrians and vehicles.

At the relatedness needs level (social interaction): Create a community cultural IP. Take cultural facility spaces such as Dajing Well and ancient trees as carriers, plan the “Longweiguan Cultural Festival”, integrate intangible cultural heritage projects such as the Bai nationality’s Three-Course Tea and Dongjing Music, and form an annual cultural event. Carry out the composite transformation of social spaces. Transform the former site of Shunchang Bank into an “intangible cultural heritage workshop + community living room” with composite functional spaces such as a shared kitchen and a handicraft experience area.

At the growth needs level (innovation): Transform and upgrade traditional industries. Establish a “time-honored brand revitalization plan”. Stores can develop cultural and creative co-branded products and introduce 3D printing technology to realize the digital innovation of traditional tie-dye patterns. Build an intangible cultural heritage education and inheritance system. Set up a “Bai Nationality Cultural Inheritance College” at the former site of Yulong Academy and Dali Senior Citizens’ University, offer skill courses such as clay sculpture and paper-cutting, and establish a dual-track training system of “intangible cultural heritage inheritors + university tutors”.

5.3. Limitations

This study constructs an application framework guided by ERG Theory, providing a new theoretical tool for understanding the complex needs of historic districts. By analyzing the needs of residents in historic districts and linking them to residents’ satisfaction with cultural spaces, a logical framework of “needs–space–satisfaction” is formed, expanding the research perspective on the conservation of historic districts. However, there are still certain limitations:

(1)

Single-case Analysis of the Study: The research samples are concentrated in the specific area of Longweiguan, making it difficult to cover the differences in needs of districts with different levels of commercial development and historical and cultural accumulation.

(2)

Absence of Longitudinal Data: This study uses cross-sectional data for analysis, which can only capture the demand status of residents in the Longweiguan Historic District at a specific time node and cannot reflect the dynamic evolution process of needs over time.

(3)

Reliance on Self-reported Perceptions: The measurement of some indicators (such as B8 Cultural Innovation) relies on residents’ subjective perceptions, which are affected by factors such as residents’ age and educational level. It is difficult to fully judge residents’ true satisfaction, and there is a lack of quantitative data support for objective innovation achievements.

(4)

Potential Impact of Seasonal or Tourism-related Fluctuations: Longweiguan, as a tourism-oriented historic district, is affected by seasonal tourism fluctuations. The changes in tourist flow, commercial activities, and living environment may influence residents’ demands and satisfaction, which is not considered in this study.

6. Conclusions

This study selects the representative Longweiguan Historic District in Dali City, Yunnan Province, China, as the research object. Based on ERG Theory (existence–relatedness–growth needs), it constructs an evaluation system for residents’ satisfaction with cultural spaces in historic districts and reveals the non-linear relationship between demand levels through the structural equation model. The research findings are as follows:

(1)

Residents’ overall satisfaction with cultural spaces is above average. Among the demand levels, relatedness needs have the strongest driving effect on satisfaction, which is directly related to the social and emotional value carried by historic districts. However, the satisfaction with growth needs is the lowest, exposing the inadequacy of spaces in meeting residents’ demands for self-improvement.

(2)

Existence needs directly affect satisfaction through basic elements such as spatial safety and indirectly strengthen relatedness needs through the path of “safety foundation to social willingness”. This confirms that the demand levels are not isolated but have a linkage effect.

(3)

Cultural industry spaces have become a bottleneck for improving satisfaction due to the disconnection between innovative practices and residents’ participation. Cultural industry spaces should be the core carriers for activating growth needs. However, due to the lack of synergy between innovative initiatives and residents’ engagement, they fail to effectively meet the demands of original residents. This not only reduces the satisfaction with growth needs but also becomes a key obstacle restricting the improvement of overall satisfaction.

This study combines ERG Theory with the structural equation model to quantitatively analyze the complex mechanism of cultural space needs. Based on this, a “safety–social–innovation” trinity optimization strategy is proposed, providing an operable path for the dynamic conservation of historic districts. It addresses the limitations of the traditional hierarchy of needs theory and provides a new theoretical perspective for investigating the residential needs in the space of historical districts. It further lays a foundation for future research in this field.

Future research can establish a needs assessment system based on ERG Theory, track changes in residents’ needs regularly through dynamic needs monitoring, consider the timeliness of data, and combine longitudinal follow-up studies to avoid “one-size-fits-all” planning. In addition, it is necessary to include comparisons of various historic districts, control key variables to verify the commonalities and individualities of needs, and enhance the generalizability of the conclusions. Meanwhile, future studies should incorporate the impact of seasonal or tourism-related factors, select research periods covering different tourism cycles, and analyze how such external fluctuations affect residents’ needs and satisfaction to make the conclusions more comprehensive and practical.