Spatial efficiency evaluation of subway station areas neighboring historic districts: Integrate transportation, culture and place resource

Abstract

Recently, cultural tourism has emerged as a key driver for economic revitalization, and subway stations located near historic districts have become important cultural and economic centers. A pressing challenge now lies in how to better leverage the cultural resources of these areas. Additionally, it's necessary to explore how to integrate transportation, cultural, and environmental resources to enhance overall benefits, particularly within the framework of sustainable development goals. To address this, the study selected subway stations adjacent to historical districts of various cultural types across China as samples. Cultural value was quantified using Value Philosophy (VP) and Cultural Sociology Theory (CST). A spatial efficiency evaluation system was developed, incorporating three key dimensions: transportation, culture, and place and employed an evaluation model combining “CRITIC-VIKOR-GRA.” A range of data, including geographical information, passenger flow, point of interest (POI), and network views, were collected to support objective research. Research indicates that culture and place dimensions exert a more direct influence on spatial efficiency, whereas traffic factors demonstrate greater significance in fostering the cohesion of spatial resources. To enhance spatial efficiency and fully realize resource value, it is essential to promote close interaction and reciprocal feedback mechanisms among the dimensions of transportation culture, and place.

Graphical abstract

Keywords

Subway station areas neighboring historic district / Cultural value / Spatial efficiency / Resource integration

1 Introduction

The construction of subway stations offers a significant opportunity for urban renewal. However, building stations near historic districts presents several challenges. Large-scale, long-term construction and standardized methods can disrupt the intricate urban fabric of historic neighborhoods, leading to the loss of traditional features and cultural characteristics (Shen et al., 2016). At the same time, these districts hold potential for enhancing subway development. The cultural value of historic areas can attract visitors, improve subway efficiency (Li, 2020), enrich station environments, and contribute to the city's overall cultural identity (Zhang et al., 2023). China's urbanization is now transitioning from rapid expansion to more sustainable optimization. In this phase, the focus has shifted toward better coordinating spatial resources, improving spatial quality, and meeting growing urban demands (Zhu et al., 2022). Coordinated construction of subway station area and surrounding blocks can serve as a catalyst for integrating regional resources, such as commerce, public transportation, cultural hubs, and social spaces. This integration involves not only station design and land use but also balancing the commercial-to-residential ratio, public space layouts, and other urban elements. To ensure high-quality environments around transit stations, the China Urban Planning Society has developed the “Guidelines for Spatial Planning and Design of Facilities in the Surrounding Areas of Urban Rail Transit Stations.” These guidelines aim to create a seamless relationship between station facilities and surrounding urban spaces, fostering more integrated and efficient urban environments.

Existing research on the relationship between subway stations and historic districts has mainly focused on the impact of station design on land use, the built environment, and travel behavior. Studies on integrated land use and subway systems show that coordinated planning can yield substantial benefits, such as improved environmental quality and increased vitality (Calvo et al., 2013). Additionally, understanding the social and spatial imbalances in urban areas can provide insights into sustainable development strategies (Hosseini et al., 2022). Micro-optimization of station spaces, tailored to local characteristics, can further promote diversity and regional identity (Rodriguez and Kang, 2020). However, there is a gap in research regarding the spatial efficiency of station areas neighboring historic districts. While previous studies have examined aspects such as cultural value (Hu and Gong, 2019; Yang et al., 2022), traffic dynamics (Qi et al., 2019; Watson, 2021), and group behavior (Chen et al., 2022; Gu et al., 2018), these analyses typically focus on one or two dimensions. This study aims to fill that gap by evaluating spatial efficiency in a holistic manner, integrating historical, cultural, and behavioral factors to promote resource-sharing and enhance the value of complex urban spaces.

This paper aims to enhance the overall value of complex urban spaces by doing up the relationship between traffic, culture, and place (Fig. 1). To achieve this, the theoretical framework draws on spatial production logic, urban geography, Transit-Oriented Development (TOD) theory, VP, CST and other related theories. The study investigates the concept and characteristics of spatial efficiency in subway stations neighboring historic districts, explores the dynamic interactions within these urban spaces, and quantifies efficiency of traffic, cultural and place. In the empirical section, seven distinct national or provincial historic districts are selected as case studies. Subway stations that border the protected areas of these historic districts are identified for further analysis. Data collection includes map data, passenger flow data, POI data, and other relevant indicators aligned with the efficiency quantification index. For the evaluation, The CRITIC method was used to calculate the weights, while the VIKOR method was employed to rank effectiveness, and the GRA method was applied to assess the degree of influence of various factors. These three methods align well with the objectives and characteristics of this study, and their operational logic is consistent. The paper addresses three key research questions:

1) How can cultural value be quantitatively assessed?

2) What is the spatial efficiency level of subway stations neighboring historic districts, considering the dimensions of traffic, culture, and place?

3) How to improve the overall efficiency of the space and the efficiency of each dimension?

This study strengthens the spatial and theoretical connection between historic districts and subway stations, offering an empirical basis for multi-integrated spatial planning at both the medium and micro levels. By addressing social contradictions within complex urban spaces, the research enables objective, quantitative analysis through the disaggregation of dimensions and levels, which is valuable for practical application. The findings of the study can inform the organic renewal and efficiency enhancement of these areas, guiding land planning policies and commercial investment strategies.

2 Theoretical construction

2.1 Spatial efficiency of subway station areas neighboring historic districts

Henri Lefebvre, in his work The Production of Space, contends that “Space is neither subject nor object, but a social reality, a set of social relations and forms” (Henri, 2022). While pragmatism in urban sociology focuses on empirical facts and induction, an exclusive emphasis on the causes of social phenomena may overlook their historical context and temporal relevance (Zhao, 2018). Social phenomena, instead, emerge as the result of the complex interplay of various mechanisms within space. The concept of spatial efficiency remains somewhat ambiguous within academic discourse, as it is interpreted differently across disciplines. From an ecological standpoint, spatial efficiency refers to the impact of urban space production on the balance of the urban ecosystem, which in turn affects people's living and working conditions. In the field of urban spatial economics, economic efficiency in urban space production is concerned with maximizing land output and generating space products that cater to mass consumption (Liu, 2022). In architecture, the development of urban rail transit systems has led to a more stratified definition of spatial efficiency, described as a “comprehensive index that integrates land efficiency, spatial efficiency, spatial quality, and social value.” This broader definition encompasses the usage efficiency, spatial quality, economic benefits, and social value of urban spaces, particularly in architectural and urban planning contexts (Tang and Xu, 2017).

The development of subway station areas can generate long-term, effective value for urban space, spanning various dimensions such as production, life, economy, and culture (Bowes and Ihlanfeldt, 2001; Ibraeva et al., 2020; Kitada and Gao, 2020). The cultural value of historical districts, for instance, is not solely expressed through physical entities or immaterial elements but is also articulated through the relationships formed with the carriers that embody this value. Over time, these relationships become increasingly intertwined with other spatial dimensions, such as economic, environmental, and land considerations (Steven et al., 2006; Xiao et al., 2019). To systematically evaluate the spatial elements and diverse values of subway station areas in historical districts, and to promote a deeper understanding and more efficient utilization of spatial efficiency, we define “spatial efficiency of subway station areas neighboring historical districts” by integrating the theory of space production and urban philosophical logic. Specifically, it refers to “the generation of multiple values and varied outcomes resulting from the continuous and reciprocal interactions among spatial subjects―including material entities, intangible elements, and human actors―within a public TOD framework, shaped by the combined influence of the natural environment, historical culture, and social mechanisms.”

2.2 Mutual driving mechanism of spatial efficiency of subway station areas neighboring historic districts

“Subway Station Areas Neighboring Historic District” does not merely represent the combination of a historical district and a subway station area in geospatial level. Instead, the spatial efficiency cannot be reduced to a simple amalgamation of historical district cultural efficiency and subway station TOD efficiency. Both concepts overlap and complement each other, involving multiple elements at various spatial levels and content dimensions. Within this framework, there are primary and secondary divisions regarding levels, along with overlapping and complementary content, as well as mutual driving forces that contribute to the generation of efficiency.

The primary and secondary levels of this study are as follows. In terms of research scope and content, the subway station area is the primary focus, while historical districts serve as the secondary focus. This study examines the impact of subway stations on historic districts with older characteristics, approaching the analysis from the perspective of new urban performance. In this context, historic districts are seen as a key factor influencing the efficiency of subway stations. In the era of stock development, the primary trend in urban renewal is leveraging rail transit to drive system optimization, enhance quality, and increase land value along transit corridors (Guo et al., 2022).

The overlapping and complementary aspects of historic districts and subway stations lie in their shared elements and differing perspectives within urban space. Common features include the street network, texture elements, urban functions, and green environments. In contrast, differing perspectives focus on how to achieve distinct goals―such as preserving history or enhancing value― through organizational elements. Subways facilitate the movement of people to the streets, which in turn provide cultural symbols that enrich the otherwise monotonous environment of standardized subway construction.

Efficiency in transportation and cultural development is driven by the interaction between historic districts and subway stations (Fig. 2). Subway passenger flow enhances cultural consumption in historic districts, while these districts, in turn, attract passengers, boosting regional traffic volumes. Historic districts provide cultural elements that enrich subway station spaces, while subways disseminate cultural information, extending the reach of the historic district. Furthermore, the development of subway station areas improves and optimizes the built environment of historic districts, while the spatial texture of these districts offers a contextual basis for the construction of station areas. Thus, both are mutually reinforcing and advancing in terms of the external built environment, internal cultural elements, and practical application.

2.3 Quantification logic of TOD efficiency of subway station areas

Based on the theoretical framework of TOD, regional development models focused on public transportation prioritize convenient transit, mixed-use functions, and environmental comfort as their main objectives. The effectiveness of these models is reflected in the comprehensive benefits they bring to urban transportation, society, economy, and the environment. Cervero and Kockelman identified and summarized specific factors affecting TOD efficiency into the “3D Principle,” which includes density, diversity, and design, comprising a total of ten index factors (Cervero and Kockelman, 1997). Subsequent studies on the impact of the built environment on walking and cycling in Bogotá revealed that, in older urban areas initially dominated by nonmotorized vehicles, land attributes such as density and land diversity are not the primary factors influencing walking behavior. Instead, the design of infrastructure―encompassing road facilities, street density, and connectivity―plays a more significant role. Building on this foundation, researchers introduced two additional dimensions: “Distance to Transit” and “Destination Accessibility,” forming the “5D Principle,” which now includes a total of 39 index factors (Cervero et al., 2009).

To date, many scholars continue to analyse TOD efficiency using the “5D Principle” and have developed various dimensions, such as “5D+,” in response to advancements in research levels and the expansion of research topics. Additionally, researchers modify or remove indicators to accommodate regional differences and specific research focuses (Xia and Zhang, 2019; Zhang et al., 2022). In analysing the spatial characteristics of human settlements, key factors that affect social, economic, and environmental values include population density, types and quantities of commercial forms, standardized vegetation index, and walkability. The integration of walking, bus, and subway transit represents a primary mode of low-carbon travel, closely linked to the cultural, traffic, and built environment values of subway station areas. These factors should be considered when evaluating spatial efficiency (Sun and Leng, 2021; Zhang et al., 2022). The analysis of these influencing factors guides the selection of efficiency evaluation indicators throughout the research process.

2.4 Quantification logic of cultural efficacy of historical districts

CST suggests a dualistic relationship between culture and society, where each influences the other. Scholars study the symbols that carry cultural signification and explore their interrelations. Building on the robust framework of CST as exemplified by scholars like Alexander, the symbolic system that distinguishes between the sacred and the secular proves useful in explaining individual behavior. In the context of scholarship, researchers tend to evaluate the value of historical districts qualitatively. This approach stems from the abstract nature of cultural value, which makes it difficult to measure concretely. In the social sciences, for instance, Spanish sociologist Javier G. (Polavieja, 2015) used instrumental variables to assess the direct impact of traditionalist culture on women's labor force participation. Similarly, American sociologist (Pedulla and Thébaud, 2015) employed survey experiments to investigate how restrictive labor market institutions shape “family-work” preferences, which they found to be influenced by traditionalist cultural values. Furthermore, Obukhova et al. (2014) applied a quasi-experimental design to study how changes in the political environment affect cultural dynamics. Together, these studies highlight how culture's applied value can be quantitatively evaluated through the use of tool carriers (e.g., instruments, methodologies) and associated object carriers (e.g., behaviors, institutions).

The renewal of historic districts, when guided by cultural tourism, can effectively balance the extraction of cultural value with the preservation of economic value. Unlike district renewal driven primarily by commercial development, this approach fosters a more diverse spatial atmosphere, encourages innovative business models, and enhances the overall spiritual experience. By focusing on the static objects and environments within the original historical districts, these elements can be leveraged as carriers of efficiency and further quantified. Figure 3 illustrates the quantification framework linking cultural elements to cultural value evaluation indicators, which is structured through three distinct pathways: static element catalysts, dynamic accessibility quantification, and business format-oriented upgrading. For example, static material elements can foster social connections via catalytic dissemination mechanisms, thereby enabling value transformation through online search engagement and offline on-site experiential perception. These processes are measured using two quantitative indicators: online search volume and the number of perceived cultural scenes. The greater the number of searches and application scenarios, the higher the degree of transformation and utilization of cultural elements. Dynamic quantification involves establishing interactive relationships between environmental features and human behaviors. Specifically, the influence of street texture morphology on traffic networks can be quantified by street block scale (Chen et al., 2021), while the impact of the built environment on travel behavior can be assessed through walkability metrics (Long et al., 2018). Finally, business format orientation focuses on evaluating the sociocultural application of intangible heritage and its derivatives, primarily reflected in the quantity and diversity of cultural industries. Throughout the entire research process, cultural elements quantified cultural efficiency indicators in various ways through these channels.

3 Research area and data

3.1 Sample selection

The selection of subway stations within typical historical blocks follows a three-step process. First, the primary criterion is based on the 30 historical and cultural blocks in China identified in the “Notice on the Identification of Chinese Historical and Cultural Blocks,” issued by the government in April 2015. These blocks were chosen for their rich cultural value, well-preserved cultural relics, far-reaching significance, and representativeness. Second, the selection is further refined by considering the principles of typical historical blocks among the seven types of historical and cultural cities. This ensures a diversity of cultural types, as well as the objectivity and universality of the research. Finally, the selected subway stations must meet the basic conditions for existing subway development and operation. In summary, 16 subway stations adjacent to 7 historic districts have been chosen as research samples, as shown in Table 1.

3.2 Research scope

The radiation area of subway stations is typically defined using various methods, including walking radius, functional factors, topographic features, and development boundaries. Among these, the walking radius method is the most commonly used in many studies (Bertolini, 1999). This study adopts the isochronous circle shortest path calculation method from urban geography, using each entrance and exit of the station as a starting point and defining the research scope based on a 10-min walking distance. From a sustainable development perspective, the historic districts' protected area is evolving and integrating with surrounding urban space, similar to the “Buffer Zone” concept in the Valletta Principles. Due to the subway stations' irregular influence area and the complex overlap between urban land divisions and the historic district, this study expands the boundary outward while preserving the integrity of block plots and road networks (Fig. 4).

3.3 Indicator data source

This study systematically collected and processed multi-source data from multiple cities, encompassing web search data, geospatial data, and subway passenger flow data. Web search data were sourced from four major Chinese platforms―Baidu, Toutiao, Rednote, and Tik Tok―to quantify the search volume of cultural element terms within each station area, which were then subjected to statistical analysis. Geospatial data consisted of street network information downloaded from Baidu Maps and categorized POI data collected via web crawlers. These datasets were processed in ArcGIS through proximity analysis, path modelling, and spatial integration. Subway passenger flow data were retrieved from official websites of subway operators in seven cities, while field surveys were conducted to record the number of cultural scenes present in underground spaces around each station. Finally, considering the substantial differences in indicator dimensions and the distinct attributes of positive and negative effects, this study employs either forward or reverse standardization techniques to normalize the data and eliminate dimensional inconsistencies.

(1) Traffic dimension (A). Based on the commonalities identified in existing literature and the spatial characteristics of historical blocks, eight key traffic efficiency evaluation indicators have been summarized (Table 2). These indicators primarily assess the public transportation and pedestrian networks within the station area. They cover various aspects, including traffic capacity, transfer efficiency, infrastructure quality, and other relevant dimensions related to the overall functionality and accessibility of the subway station area.

(2) Culture dimension (B). The evaluation of cultural efficacy in this study diverges from traditional approaches that typically assess cultures' aesthetic and historical value from a macro perspective (Yu and Luan, 2014), or people's perceptions of cultural information within the built environment from a micro perspective (Liu et al., 2023). Instead, this study focuses on the application status and potential of culture within urban spaces from a meso perspective. In other words, the emphasis shifts from the cultural subject itself to the objective value generated by culture through material objects, behavioral subjects, spatial relations, and other influencing factors. As a result, the evaluation indicators for cultural efficacy are grounded in objective and quantifiable data, which helps avoid errors linked to subjective cognition. This evaluation framework consists of six key indicators (Table 3).

(3) Place dimension (C). The place dimension encompasses not only land development aspects related to TOD efficiency but also the derived value of cultural space within these districts. Key factors such as location attributes, economic characteristics, the natural environment, the comfort of the built environment, and the continuity of spatial texture play a crucial role in shaping the coordination and development of regional spatial resources. The specific indicators are shown in Table 4.

4 Research methods

4.1 Weight calculation method – CRITIC

In this study, the CRITIC weight method was selected for several reasons. Alignment with research objectives: This method aligns with the objective perspective of the research. The goal of this study is to develop a comprehensive and universally applicable spatial effectiveness evaluation system. As such, the selection of research samples, evaluation dimensions, indicators, and methods must adhere to objective logic. The CRITIC method, proposed by Greek scholar Diakoulaki, is designed to determine objective weights based on the relative importance of various factors in multi-objective decision-making problems (Diakoulaki et al., 1995). It enables quantitative analysis that is based entirely on actual measurement data from the indicators. Support for in-depth exploration: This weighting method is well-suited for the core purpose of exploring internal correlations within the subway station domain in historic districts. It primarily relies on the intensity of comparison and conflict among the evaluation indicators to determine their objective weights (Guo, 2024).

4.2 Comprehensive effectiveness ranking method – VIKOR

The VIKOR method is a multi-attribute decision-making technique based on ideal solutions, proposed by Serafim Opricovic and Gongzhi Fan in 1998 for complex systems (Papathanasiou and Ploskas, 2018). The solution derived from the VIKOR method represents a compromise solution, being the alternative closest to the optimal solution among all possible options. VIKOR's main benefit is that it creates a ranked compromise solution, making it perfect for cases where decision-makers have trouble comparing options―especially when the criteria don't align, like transit efficiency versus cultural effectiveness in this study.

As shown in Fig. 5, the method begins by assuming there are m samples and n indexes. It establishes the original data matrix, conducts positive and standardized processing, and identifies the maximum and minimum values of each column element as the positive and negative ideal solutions. Following this, formulas (1), (2), and (3) are used to calculate the group effect value S_i, individual regret value R_i, and interest ratio Q_i. A smaller Q_i value indicates a better scheme. The variable V represents the decision coefficient. In this study, it is assumed that the weights of all elements and dimensions are equal, and that the objectives of all groups are the same; thus, v = 0.5, leading to the adoption of a compromise solution. Finally, the optimal scheme is determined according to the following principles: Assume that schemes M₁ and M₂ are the top two alternatives ranked according to the value of Q_i. Scheme M₁ is considered the optimal scheme when the following conditions are met:

Condition 1: Q₂–Q₁≥1/(m–1), where Q₁ represents the highest value of Q for the optimal evaluation object, and Q₂ represents the second highest value of Q for the suboptimal evaluation object. Here, m is the total number of alternatives.

Condition 2: In the ordering of S_i or R_i, Q₁ remains the optimal solution. If both conditions are satisfied simultaneously, then M₁ is the optimal scheme. If only Condition 1 is satisfied, then both schemes M₁ and M₂ are considered ideal compromise schemes. If only Condition 2 is satisfied, Condition 1 is evaluated sequentially based on the ordering of Q_i values. If the Q_t value of the t-th scheme meets Condition 1, then all schemes from the first to the (t-1)-th are deemed ideal compromise schemes.

\begin{array}{}\text{(1)}& S_i={\displaystyle \sum _{j=1}^n\frac{w_j\left(Z_j^{+}-z_{ij}\right)}{\left(Z_j^{+}-Z_j^{-}\right)};}\end{array}

\begin{array}{}\text{(2)}& R_i={{\displaystyle \max }}_i\frac{w_j\left(Z_j^{+}-z_{ij}\right)}{\left(Z_j^{+}-Z_j^{-}\right)};\end{array}

\begin{array}{}\text{(3)}& Q_j=\frac{v(S_i-S^{-})}{S^{+}-S^{-}}+\frac{(1-v)(R_i-R^{-})}{R^{+}-R^{-}}\mathrm{.}\end{array}

In the formula, Z_ij represents the value of the j -th evaluation index of the i-th sample, and w_j is the weight of each index.

4.3 Impact factor ranking method―GRA

Grey System Theory is a mathematical framework designed for situations where there is uncertainty or incomplete information. It is especially useful when data is limited or not fully available. One of its most important methods is GRA, which helps to assess the degree of association between different sequences by examining the geometric similarity between their curves or patterns over time (Liu et al., 2010). The adaptability of GRA can be outlined based on two key characteristics. First, the sample size is small, with spatial overlap and complex correlations among indicators. Second, the aim of the research and analysis is not to extract or identify cause-and-effect relationships through dimensionality reduction, but to conduct factor correlation analysis based on the optimal solution. This analysis seeks to identify the influencing factors of spatial effectiveness for the research samples.

As shown in Fig. 6, the method begins by assuming there are m samples and n evaluation indicators, and it constructs a reference sequence alongside a comparison sequence. The reference sequence represents the optimal value sequence. First, the sample ranked highest in the comprehensive efficiency evaluation is designated as the reference sequence. However, a top ranking does not necessarily imply that the values of each factor are optimal; this may result from a high degree of interaction between the systems. Next, the equalization method is employed for dimensionless processing. Finally, the correlation coefficient is calculated according to Formula (4), and the correlation degree is determined using Formula (5). The closer the correlation degree is to 1, the stronger the correlation.

\begin{array}{}\text{(4)}& {\zeta }_{ij}(k)=\frac{{{\displaystyle \min }}_i{{\displaystyle \min }}_k|x_0(k)-x_i(k)|+\rho \cdot {{\displaystyle \max }}_i{{\displaystyle \max }}_k|x_0(k)-x_i(k)|}{|x_0(k)-x_i(k)|+\rho \cdot {{\displaystyle \max }}_i{{\displaystyle \max }}_k|x_0(k)-x_i(k)|}\mathrm{.}\end{array}

\begin{array}{}\text{(5)}& r_{ij}={\displaystyle \sum _{k=1}^n{\zeta }_{ij}(k)}\mathrm{.}\end{array}

Where |x₀(k)–x_i(k)| is the absolute value of the difference between each data and the reference sequence data of the row, ρ is the resolution coefficient, located between [0, 1], generally 0.5, k = 1, 2, 3, …, n.

5 Results and discussion

5.1 Comprehensive efficiency ranking

The calculation of the overall efficiency weight across the three dimensions is based on the combined effect of all indicators, with the total weight summing to 1. Similarly, within each dimension, the weight of performance is determined by the relative contributions of its indicators, ensuring that the sum of the weights for each dimension also equals 1. The parameter calculation results are summarized in Table 5, with the optimal schemes for each dimension highlighted. The data analysis indicates that Wuyi Square station offers the most effective solution across the comprehensive traffic, cultural, and place dimensions. It has the highest number of subway station entrances and exits among all samples, which enhances spatial connectivity. Figure 7 illustrates the station's traffic network, which integrates a two-tier system of ground vehicles and underground walkways. Additionally, multiple entrances and exits are strategically positioned to link with surrounding commercial spaces and subway exits. This design increases the likelihood of interaction between the transportation network and the surrounding environment, thereby fostering consumer activity and boosting the station's spatial appeal. Furthermore, the inclusion of a prominent celebrity sculpture as a symbolic element strengthens the station's cultural identity. Wuyi Square also leads in the number of cultural industries and cultural symbols integrated into its design.

By comparing the rankings across each dimension and overall efficiency, we can identify the strengths and weaknesses of each station area. Overall, the place dimension tends to perform better, suggesting that the environmental foundation, particularly in historical districts, is relatively strong. However, the integration of these older areas with new transportation and cultural industries remains limited. This indicates that the potential for development and utilization of the old city under the new urban framework is still underexplored. For instance, Beihaibei Station shows high efficiency and strong overall ranking in the cultural dimension, reflecting a region primarily driven by cultural industries. However, it requires improvements in transportation network connectivity and the surrounding built environment to fully support its development. The stepwise regression analysis (Table 6) reveals that the traffic dimension does not significantly impact the comprehensive efficiency, while both the cultural and place dimensions have a significant positive effect. This suggests that while traffic efficiency is important, the cultural and environmental factors play a more crucial role in enhancing the overall performance of a station area. In the case of East Nanjing Road Station, the analysis highlights that while the station's focus has been on traffic dimension, its ranking is lower in both the cultural and place dimensions. As a result, the station's overall comprehensive efficiency is lower than expected. The research shows that the cultural and place dimensions have a more direct impact on the comprehensive spatial effectiveness.

5.2 Impact factor ranking

The Kendall correlation analysis is applied to the 29 indicators in the sample, as some of the data do not meet the assumptions of normal distribution. It shows that more than 70% of the total indicators show significant correlation, making them suitable for GRA. Using formulas (4) and (5), the correlation degrees between all impact factors within each dimension are calculated. The resulting values, which reflect the strength and direction of the relationships between the various factors, are visualized in Fig. 8. The analysis results, shown in grey, reveal the correlation between various indicators, with color blocks indicating the respective dimensions. The analysis reveals that all indicators within the traffic dimension show a high correlation, emphasizing the crucial role that transportation plays in connecting culture and place, thereby enhancing their value. This suggests that transportation can serve as a starting point for spatial optimization. Additionally, the correlation degree between the traffic and place dimensions is relatively high, with minimal differences between the indexes. This indicates a strong interconnection and mutual enhancement between the two dimensions, highlighting the importance of their combined influence on the overall spatial efficiency.

Notably, passenger flow (A8) demonstrates the highest correlation, supporting the idea that population vitality is closely linked to spatial behavior. B1 and B2, representing network search activity, are generated in the virtual space and are less directly connected to physical space elements. The weak correlation between C2 and C34 suggests that the area is predominantly residential, with small retail and food services making up the main business model. This aligns with survey findings, which show that 13 out of 16 stations have higher residential population densities than office populations (Fig. 9). Additionally, commercial formats are mostly small-scale, including retail, catering, and life services (Fig. 10).

In Fig. 8, the three distinct colors represent the traffic, culture, and place indicators. It is evident that the correlation between indicators under the combined influence of all dimensions tends to be higher than within each individual dimension. This suggests that the interaction between dimensions or factors can enhance the correlation between spatial elements and stimulate greater energy. In other words, optimizing the overall utilization of spatial resources during urban renewal is essential. However, indicators such as A8, B2, B1, and C1 exhibit opposite characteristics, where their correlation within each individual dimension is higher than in the combined scenario. This implies that these indicators are relatively independent, and their impact on other factors within the same dimension is more pronounced. For instance, the impact of passenger flow on traffic and transfer efficiency is both direct and immediate. However, in the short-term data considered, cultural and environmental factors have minimal influence on passenger flow. On the other hand, internet search data, which rely on textual and visual content, reflect the breadth of regional cultural communication and long-term potential benefits. This data shows weak correlation with traffic conditions and spatial attributes. Unlike the more immediate characteristics of other indicators, internet search data holds potential for sustainable value and is more influenced by factors such as the volume of cultural heritage and cultural industry activities. This analysis highlights the dynamic nature of spatial resource usage, suggesting that a holistic, multi-dimensional approach to urban renewal can lead to a more sustainable and integrated use of resources. Understanding both immediate and long-term influences on spatial efficiency is critical for informed decision-making in urban planning and cultural integration.

5.3 Analyse the relationship between transportation, culture and place

In recent years, the rapid advancement of artificial intelligence and the increasing accessibility of big data have significantly promoted interdisciplinary research integrating physical space with social behavior in urban studies. Correspondingly, researchers' attention has shifted from prominent spatial hotspots and prevalent issues toward more nuanced spatial analyses and the exploration of social value. Studies on public transportation have expanded beyond mobility concerns to incorporate discussions of spatial behavior, built environment, and societal applications―thereby enhancing both the practical relevance and equity implications of scientific inquiry. For example, AI-driven methodologies are now employed to assess user experiences around bus stops by synthesizing spatial behavior, transportation dynamics, and environmental factors, thus establishing an objective communication channel between planners and end-users (Wael et al., 2022). Moreover, such studies increasingly address the functional design and usage demands of bus stop facilities in real-world contexts, prompting a critical re-evaluation of planning policies and design practices (Inman et al., 2025). While research that integrates social characteristics often exhibits contextual specificity and regional constraints―particularly in urban areas shaped by long-term historical development―it nonetheless offers substantial benefits in terms of guiding design improvements, informing policy oversight, and optimizing implementation outcomes.

As demonstrated in the analysis of impact factors, the traffic dimension shows strong correlations with other dimensions. This underscores the dominant role of the traffic dimension in shaping spatial efficiency. The correlation analysis of the factors across each dimension highlights that strengthening the interconnections and synergies between them is the key to improving overall efficiency. This is because spatial efficiency is not solely determined by traffic efficiency, but rather by the combined effects of geographical space, social relations, and spatial behavior. Public transportation, in this context, serves as a mechanism to improve efficiency and foster connections. The cultural value, economic benefits, and environmental quality that arise from it are visible manifestations of improved spatial efficiency (Fig. 11). Based on the results and cross-analysis above, three spatial efficiency optimization strategies are proposed:

1) Leverage the traffic dimension: Use the traffic dimension as a guiding factor to implement a co-construction strategy that integrates “transportation + culture” and “transportation + place.”

2) Focus on cultural application: Emphasize the practical transformation and application of cultural elements.

3) Enhance the place dimension: Strengthen the awareness of how the built environment supports and enhances spatial efficiency.

5.3.1 Leverage the traffic dimension

According to a tourism report, over 82% of young people prefer “city walks” for short-distance travel, making it a growing cultural trend among the youth. From the perspective of geographical psychology, this phenomenon can be understood in two key aspects: “space walking” and “spiritual needs.” Geographical space has psychological effects and underlying principles, and spatial behavior can function as a form of psychological healing (Huang and Zhang, 2024). The connection between transportation networks and cultural spaces meets the fundamental need for this. A well-structured public transport network serves as the backbone, while the careful design of routes connecting cultural attractions and public spaces enables cultural immersion through “walking.” This framework also aligns with the spatial logic of field theory: the elements and network relationships within a space form a dynamic, stable, and irregular configuration that guides spatial behavior and coordinates spatial resources (Gao, 2004).

Traffic calming is commonly applied in street optimization within residential areas to reduce the impact of motor vehicles on residents' quality of life. By combining physical calming measures with policies, regulations, and technical standards, it aims to modify undesirable driving behaviors. The goal is to improve the road environment for pedestrians and non-motorized vehicles, enhancing safety, promoting road habitability, and facilitating walking (Lockwood, 1997). Ghafghazi and Hatzopoulou (2015) studies from European and American countries show that traffic calming measures are primarily implemented on roads with lower traffic volumes, such as residential areas or campuses, particularly in historic districts where road widening is difficult. In the Sinan Road historic district of Shanghai, Zhou and Li (2018) have proposed optimization methods such as using colored pavement to differentiate traffic lanes, installing speed limit signs, and prohibiting reverse traffic, all aimed at improving road accessibility and safety. At the practical level, traffic calming involves technical measures or management strategies, while at the ideological level, it represents a shift in spatial behavior awareness. This requires the combined influence of traffic design and the surrounding environmental context.

5.3.2 Focus on cultural application

The extent to which cultural elements are applied and transformed plays a crucial role in determining cultural efficacy and serves as a key pathway for culture to integrate into various other dimensions. In the era of new media, advancements in science and technology have directly influenced the modes and characteristics of cultural communication. Culture is now transmitted and shared through digital and networked social platforms, exhibiting traits of diversity, globalization, sustainability, and personalization. At the macro level, it is essential to focus on the development of urban cultural spaces, enriching their cultural functions and enhancing basic cultural services. Among the six major dimensions of the Global City Strength Index, the cultural exchange dimension ranks second only to the economic dimension, highlighting its significance. Cities like Seoul and Dubai saw notable jumps in the 2022 rankings, largely due to their hosting of cultural exchange events. Similarly, global cities such as London, New York, Paris, and Tokyo were early to recognize the stabilizing role that culture plays in both social and economic structures (Taylor and Derudder, 2015). At the micro level, in addition to promoting the application and transformation of cultural elements, it is also essential to focus on identifying and refining these elements. Traditional cultural elements are widely applied in architectural design (Yu and Cui, 2021), garden landscaping (Zhang and Dong, 2014), and industrial modelling (Wu, 2017). However, from the perspective of urban equity, there is still a need to enhance the diversification of cultural industries and infrastructure. As spiritual and material needs evolve, the cultural industry has expanded beyond its initial focus on industrial production to encompass areas such as aesthetic pursuit, game expression, symbolic representation, and knowledge acquisition (Zong, 2020).

5.3.3 Enhance the place dimension

In recent years, increasing investment in land development has been the primary approach to improving the overall utilization rate and economic benefits (Chu and Li, 2021; Kitada and Gao, 2020). However, the walking environment and supporting infrastructure are also key factors that impact the realization of economic efficiency (Xia and Zhang, 2019; Xia et al., 2019). In the sample of this study, Lindun Road Station has a high degree of commercial development, but its comprehensive efficiency ranking is lower than that of the nearby Xiangmen Station. This is largely due to the narrow network and street shops in the old city of Suzhou, which significantly affect the visibility and spatial recognition of the area. Using ArcScene to analyse the station area's visibility from a three-dimensional perspective, the visibility of each entrance and exit at Lindun Road Station is 3.19%, while at Xiangmen Station, it is 5.05%. As shown in Fig. 12, the surrounding area of Xiangmen Station has high visibility and a better walkable environment. Although road widening is not feasible, this issue can be mitigated through policy controls and urban management measures. Policies should regulate building heights around the old city to improve the visual environment, while also addressing infrastructure issues such as road occupation by non-motorized vehicles and residential encroachment.

6 Conclusion

Overall, this research begins by addressing the social challenges and spatial contradictions present in subway station areas within historical districts. It selects representative subway station areas in Chinese historical districts as case studies to evaluate spatial efficiency and investigate the interactions and influences among transportation, culture, and place resources. First, drawing on theories from VP and CST, we establish a quantification pathway for cultural value with spatial objects as carriers: cultural elements ‒ object carriers ‒ object quantification. This approach constructs a substantive link between culture and space. Second, we develop a CRITIC-VIKOR-GRA composite evaluation model to assess the current state of spatial efficiency in these station areas. The findings indicate that Wuyi Square Station demonstrates the highest level of comprehensive efficiency among the studied cases. Further regression analysis of each dimension reveals that the cultural and place dimensions exert a more direct influence on spatial efficiency. Building on this finding, we analyse the interrelationships among various factors and discover that the transportation factor exhibits stronger integrative power and cohesion over other dimensions―indicating a significant internal agglomeration effect. Finally, based on these conclusions, we examine the functional relationships among transportation, culture, and place within urban space. We propose integrated development strategies guided by transportation, including “transportation + culture” and “transportation + place” approaches, along with optimization strategies focused on enhancing cultural application and supporting the role of the built environment.

In terms of innovation, this study first introduces a systematic framework of “cultural elements ‒ implementation object ‒ quantification channels ‒ quantification indicators” grounded in VP and CST. This approach differs significantly from the subjective evaluation methods commonly used in existing literature, offering a more objective and measurable pathway for assessing cultural value through the establishment of a substantive link between culture and space. Secondly, the research focuses on subway station areas adjacent to historical districts, exploring integrated development strategies that reconcile new urban functions with traditional spatial layouts in the context of urban space and resource utilization. Following large-scale initial development phases, the study emphasizes the fine-grained coordination and optimization of spatial elements to enhance the interconnectivity of urban components and improve overall resource efficiency.

While this paper proposes a quantification path for cultural value and clarifies the factors and mechanisms influencing the spatial efficiency of subway station areas neighboring historic districts, we acknowledge several limitations. The study selects research objects based on the type and quantity of cultural attributes, ensuring the typicality of these attributes, but it does not fully account for geographical factors. Although land use diversity is used as an indicator of land development intensity in the evaluation, variations in land value across different areas are not considered. Future research could refine the selection of study objects and evaluation models to yield more reliable and comprehensive conclusions.

The research provides valuable analytical insights for decision-makers and stakeholders, contributing to the enhancement of value and coordination of resources within subway station areas neighboring historic districts. While focused on China, the methods developed in this study can also be applied to efficiently utilize urban historic districts and old urban spaces in other countries. By expanding the application of rail transit, this research plays an important role in enhancing the sustainability of rail transit systems.

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