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.

As the basic unit of a smart city, the smart community has received considerable attention and problems in community governance have appeared simultaneously. Previous studies of smart community governance have failed to encompass all aspects, especially the evaluation tools for ensuring its outcomes. Therefore, this paper developed a comprehensive evaluation framework based on the CRITIC-TOPSIS method combined with the identified evaluation indicators. Seven smart communities from four cities in China were selected as cases to show how this evaluation framework could be applied to decision-making. The results indicated that the evaluation indicator ”Mediation of Conflict” had the highest weight while ”The participation of social enterprises in governance” had the lowest weight. Furthermore, the Yucun community presented the highest governance performance among these seven smart communities. Several strategies are proposed for improving the level of smart community governance, such as devoting significant resources to develop infrastructure in smart communities, facilitating communication among multiple participants, and increasing funding for the implementation of smart communities. This research contributes both to the innovation of community governance evaluation and to the improvement of smart communities.

In recent years, sponge-style old community renewal (SOCR) has attracted considerable attention as an essential component of urban renewal and sponge city construction in China. As a new method of community governance, the government has increasingly valued residents’ participation in the SOCR. However, as a new concept, the SOCR has not been studied from the perspective of management, and there are few explorations of residents’ participation in the research field. Thus, this study aimed to explore the determinants of residents’ behavior toward participating in the SOCR of China based on the extended theory of planned behavior (TPB), which will further promote residents’ engagement in the SOCR. Data from 1657 respondents were analyzed using the structural equation model (SEM) to verify the direct or indirect relationship between potential variables. The results show that residents’ participation cognition (RPC), attitude (RPA), and intention (RPI) all significantly affect residents’ participation behavior (RPB). The RPC can not only have an indirect impact on the RPB by influencing the RPA but also have an indirect impact on the RPB through the RPA and the RPI. This research not only expands the application boundary of the TPB but also enriches the knowledge system of residents’ participation and the SOCR. Several practical implications for promoting residents’ participation are obtained in the context of the SOCR projects.

As a sustainable and cleaner type of facility, prefabricated buildings face more design barriers than traditional non-prefabricated buildings. Identifying and managing these barriers is key to improving the success rate of prefabricated building design. However, direct studies on these design barriers are extremely rare. The present study solved this problem by combining multiple methods, including grounded theory (GT), structured self-intersection matrix (SSIM), analytic network process (ANP), and the linear weighted sum method (LWSM). GT was adopted to identify the barriers to prefabricated building design and then SSIM was used to analyze the interactions among them. The eight design barriers were finally identified and classified into three clusters: technical barriers, economic barriers, and management barriers. A further analysis found that there is dependence and feedback among these clusters. The technical barrier cluster and management barrier cluster experience self-feedback. A network model based on ANP was next established to calculate the weights of the barrier elements and then this model was combined with LWSM to evaluate the overall design barrier strength of a project case. The results showed that architectural individualization has the greatest impact on prefabricated building design, followed by the collaborative issues among multiple units and professional designer issues. The overall design barrier strength of the project case was larger. Therefore, the first suggestion provided to the facility management sector is to establish a library for standard house types to achieve architectural design through multihouse combinations.

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 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.