Enyang Hao

Green infrastructure (GI) can generate multiple ecological, environmental, and social benefits for cities. Evaluating GI is therefore essential for understanding its performance, supporting evidence‐based planning and governance, and ultimately promoting sustainable urban development. However, GI evaluation research remains thematically fragmented, while existing GI‐related reviews have not specifically focused on the GI evaluation field, resulting in a lack of systematic synthesis of its knowledge structure, thematic evolution, methodological development, and future development. This study reviews 144 research articles published between 2014 and 2025 using bibliometric analysis, thematic clustering, and methodological synthesis to explore the current research progress and future research directions of GI evaluation research. The results show that GI evaluation expanded rapidly between 2014 and 2025, with growing international collaboration and diverse research themes emerging. Ecological function evaluation remains dominant, while integration with urban governance and planning has strengthened. Methodologically, GI evaluation shows a shift toward data‐ and model‐driven multi‐method integration. In addition, this study summarizes future research directions from theoretical, contextual, and methodological perspectives, emphasizing the need to strengthen socio‐ecological‐governance theoretical integration for GI evaluation, expand comparative research across cities, scales, and GI types, and advance standardized evaluation methods based on multi‐source data. From a practical perspective, the insights and synthesized methodological tools generated by this review can be used to support more integrated GI evaluation in planning and governance practice, thereby contributing to Sustainable Development Goal (SDG) 11 through improved urban environmental management, enhanced resilience, and more sustainable urban development.

Resident engagement is highlighted as a crucial aspect that directly impacts the residents’ well-being of life in the process of sponge-style old community renewal (SOCR). However, there is a lack of in-depth study on exploring the classification of resident engagement clusters in the SOCR and developing a comprehensive evaluation system to measure this engagement. Therefore, this paper categorizes resident engagement into distinct clusters and develops an evaluation method for quantifying resident engagement in the SOCR. First, this study identified seven types of engagement clusters in the SOCR drawing from educational psychology and Arnstein’s citizen engagement ladder theory. Second, an evaluation indicator system with 5 primary indicators and 21 secondary indicators was developed through a literature review and expert interviews. Third, a hybrid evaluation method combining the Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II) was established to effectively quantify resident engagement in the SOCR. Finally, 16 typical communities from five Chinese cities were selected as study areas to examine resident engagement in the SOCR. The results demonstrated that the full engagement cluster achieved the highest scores at the individual level, while the non-engagement cluster recorded the lowest scores. At the city level, Shanghai attained the highest overall engagement score, whereas Chizhou recorded the lowest. Several strategies were proposed to improve resident engagement in the SOCR. This study not only contributes to the body of knowledge on resident engagement in the SOCR but also provides guidance for fostering resident engagement in sponge city construction.

As a vital part of smart city development, smart community development is in full swing, aiming to improve residents’ sense of safety (RSS). Most research focuses on the technological innovation and infrastructure construction of smart communities; few studies have evaluated smart community development from the perspective of the RSS. Thus, this paper aims to propose a system of evaluation indicators for assessing the RSS of smart community development. After the relevant evaluation indicators were identified, an evaluation method was proposed using the CRITIC-FCE approach. To validate the feasibility of this method, 31 smart communities in China were selected in this study. The results showed the following: (1) The indicator of the highest weight was ‘cultural activities for the elderly’, while ‘overall design’ had the lowest weight, highlighting the importance of community services in enhancing the RSS of smart community development. (2) The selected cities and communities achieved a generally high level in the RSS of smart community development, and some differences were observed among them. (3) Emergency services and property services play an important role in enhancing the RSS of smart community development, with communities excelling in these areas, achieving higher overall rankings. Conversely, the score of pension service was relatively low, which is a common problem in the evaluation results, reflecting the shortcomings of the current smart community in providing pension service. Consequently, several strategies are suggested to enhance the RSS of smart community development, such as building an emergency information system based on advanced technology, establishing mobile and Internet of Things-based emergency assistance services for the elderly, and enhancing the maintenance of public facilities. This research enriches the knowledge of RSS and provides guidance for further research for the RSS of smart community development.

Smart community construction (SCC) is pivotal for urban modernization, yet extant research often neglects the residents’ perceptions of these initiatives, focusing predominantly on technological advancements. A hybrid evaluation method integrating the Entropy Weight Method (EWM) and PROMETHEE II was developed to quantify residents’ perceptions of SCC. Through the literature review and expert interview, the evaluation indicators for residents’ perceptions of the SCC were identified, leading to the development of an evaluation indicator system consisting of 5 dimensions and 25 indicators. The hybrid evaluation method that combines EWM and PROMETHEE II was then applied to quantify the level of residents’ perceptions of SCC across five communities in Shenzhen city of China, using data from 410 valid questionnaires. The results indicated that the Baolong community had the highest level of the SCC, while the Nanyuan community exhibited the lowest ranking. Sensitivity analysis confirmed the robustness of these results, thereby validating the evaluation process. Moreover, recommendations were proposed to enhance residents’ perceptions of smart community initiatives. This research not only introduces a novel evaluation method that expands the body of knowledge on the SCC and residents’ perceptions but also helps the government develop sustainable SCC strategies.

The smart city is recognized as a potent instrument for creating efficient urban environments and improving the quality of life of urban residents. However, there is an absence of research establishing a comprehensive evaluation model for the smart cities (SCs) and focusing on their spatiotemporal analysis. Thus, a comprehensive evaluation framework was developed and applied to 26 cities in the Yangtze River Delta Urban Agglomeration (YRDUA) in China from 2017 to 2020 to assess the smart city level (SCL) in China and analyze these cities’ spatial–temporal characteristics. The results indicated the following: (1) The overall SCL in the YRDUA has exhibited sustainable improvement, and the gap between cities is gradually narrowing. (2) The SCL of the YRDUA exhibits a higher SCL in the east and a lower SCL in the west of the YRDUA. The global spatial correlation of the SCL was random. Nantong, Hefei, Jiaxing, Zhoushan, Chizhou, Tongling, and Wuhu showed significant local spatial correlation. (3) The comprehensive evaluation framework is applicable for analyzing the SCs in China, and this framework can also be extended to other countries. Pertinent recommendations are put forth to enhance the SCL through the formulation of policies and fostering intercity collaboration. This research not only enriches the theoretical research on smart city evaluation but also clarifies the spatial–temporal characteristics of the SCs in China, thereby providing valuable insights that can foster sustainable smart city development.

Smart community enables a sustainable and livable community future, in which residents’ demands play an important role in its success. Though great efforts have been made to encourage residents’ participation in the implementation of smart communities, inefficient service supply still exists. Thus, this study aimed to classify residents’ demands for community services in smart communities and to explore relevant influencing factors based on the developed conceptual framework. Data from 221 respondents in Xuzhou city of China were analyzed by using binary logistic regression. The results indicated that more than 70% of respondents had demands for all community services in smart communities. Moreover, the demands were influenced by distinct factors, including sociodemographic characteristics, living characteristics, economic characteristics, and individual attitude characteristics. The types of community services in smart communities are clarified and fresh insights are provided into associated factors related to residents’ demands for these services in this study, through which enhanced provision of community services and effective implementation of smart communities can be achieved.

As a micro-unit of the smart city, smart communities have transformed residents’ lives into a world that connects physical objects. Simultaneously, though, they have brought community safety problems. Most studies of the smart community have only focused on technical aspects, and little attention has been paid to community safety. Thus, this paper aims to develop an evaluation system for smart community safety, which will further promote community safety development. On the basis of identifying evaluation indicators, an evaluation framework was built to assess the level of smart community safety by a comprehensive CRITIC-TOPSIS method. Five smart communities in Shenzhen city were selected as cases to validate the feasibility of the evaluation framework. There was an indication that the indicator with the highest weight was the ‘building monitoring’, and the indicator with the lowest weight was the ‘emergency shelter guidelines’. In addition, the Yucun community showed the highest safety level among these five smart communities. Some suggestions for enhancing the safety level of the smart community are proposed, such as strengthening the training of community safety management talents, establishing good emergency protective measures, and encouraging residents to participate in the development of community safety. This research not only provides an innovative community safety assessment method; it also enriches the knowledge of smart community safety.