With the current downturn in the real estate and construction industries, the construction job market is saturated, and architects are facing an urgent employment crisis. Architectural education should understand the skill requirements of individuals in the labor market and make adjustments accordingly. This study examines the evaluation of and demand for skills from the perspective of employers. A research questionnaire was constructed based on the Kano theoretical model and distributed to 810 practitioners, and the results were analyzed. The results of the data analysis of demand attributes, importance, and group differences showed that the construction industry pays the most attention to strengthening professional soft abilities, while improving personal comprehensive abilities and maintaining professional hard abilities can support architects in maintaining strong competitiveness in the job market. Furthermore, different groups and regions have different needs for architectural skills. The cultivation of skills in colleges and universities must be targeted. This study provides an adjusted direction for architectural education and training and also provides guidance for architectural practitioners in improving their skills and expanding their career development with the trend of industry saturation.

Traffic flow characterizes vitality in commercial clusters, and the accurate prediction of traffic flow based on the street network has significant implications for street planning and vitality regulation in commercial clusters. However, existing studies are limited by certain problems, such as difficulty in obtaining traffic flow data and carrying out technical methods. The purpose of this study is to use urban physical data to study traffic flow so as to quickly and effectively estimate the traffic flow in commercial clusters. This study takes the street networks of 100 commercial clusters in China as the research objects and classifies them into three forms according to the theory of “A city is not a tree”. Taking typical commercial clusters in these three forms as the research unit, space syntax was used to study five metrics of street network connectivity, and integration (Dn) was selected as a proxy variable for street network connectivity. The results show that the traffic flow in the three forms of commercial clusters can be predicted using the multiple regression models established based on the three metrics of integration, the traffic level, and the operation cycle. This study establishes the connection between the street network form and the traffic flow, which enables the possibility of obtaining the traffic flow of commercial clusters quickly and effectively. For areas with poorly structured urban data, the results can help urban planning administrators to predict the potential economic attributes using easily accessible street network data in commercial clusters.

With accelerating urbanization and a global emphasis on quality of life, the effects of the built environment on individual physiological and psychological well-being have become a critical research focus. However, existing studies remain fragmented in terms of theoretical perspectives, spatial scales, and methodological approaches, and a comprehensive synthesis of the physiological and psychological effects of the built environment is still lacking. This review adopts an interdisciplinary approach, integrating architecture, urban planning, landscape architecture, geography, and psychology to systematically review the literature on the health impacts of the built environment. Its findings indicate that the scope of the built environment has expanded from natural settings to residential areas, streets, and public spaces. Research scales have progressed from macro-level districts to streets and public spaces and further to micro-level physical environments. The impacts have extended from emotional responses to broader health and well-being outcomes, with increasing attention being given to specific population groups. Technological advances have shifted research paradigms from traditional surveys to approaches incorporating big data, machine learning, virtual reality, and physiological monitoring, enabling more precise analyses of links between spatial perception and emotional responses. This review identifies gaps in interdisciplinary integration, long-term monitoring, and the consideration of individual differences, highlighting the need for future studies to integrate multimodal data with theory-informed practice to support more human-centered, health-promoting built environments.

Against the background of traffic conflicts arising due to the highly concentrated population in high-density cities, this study aims to systematically identify the core transport needs of patients awaiting medical treatment; based on the theory of the Kano model, we construct a measurement system relating to patient transport needs when awaiting medical treatment that encompasses multiple levels. Taking 10 large general hospitals in Guangzhou as samples, this study collected data through questionnaires and auxiliary interviews, using the importance–sensitivity analysis method to accurately measure the degree of patient needs for each influencing factor of the transport environment for medical treatment. The study found that, among the primary needs (core basic needs), the perfection of public transport (which directly affects the convenience of medical care) is the core need with the highest degree of demand. Among the second-level needs (refined categorised demand levels), specifically relating to important attributes (essential needs), priority attention should be given to patient diversion, hospital–city connection, and corridor settings. As concerns the high value-added one-dimensional attributes (desired needs), focus should be placed on controlling health and safety distances and guiding the flow of medical treatment, while for high glamour attributes (glamour needs), primary consideration should be given to crowd distribution, stopping and resting, and direct access to the ground floor. The group difference analysis (grouped by emotional state, transport mode, and group type) showed that the first-level demand sensitivity ranking was highly consistent, and the second-level demand for urban connectivity, convenient transfer, and direct underground access were also common priorities. This study is the first to introduce the Kano model into the analysis of high-density urban healthcare transport systems, providing a clear basis for the grading of demand for the design of the transport environment for patients’ medical care. This is of great practical value for alleviating congestion and improving the resilience of emergency response in mega-cities in relation to medical care.

Designing reasonable commercial transportation space is of great significance to enhancing the overall value of commerce. This study takes the classic cases of three typical plans of commercial wholesale centres (CWCs) as the research object, uses space syntax to analyse the connectivity of the architecture of the traffic space, simulates the current situation of the pedestrian flow distribution through ArcGIS, and constructs a multiple regression model for the association between connectivity and pedestrian flow distribution. The results of this study show that for CWCs with a single business type and a focus on traffic efficiency, the distribution of the pedestrian flow is most affected by the main entrance and the vertical traffic distribution. For different types of planes, when the commercial traffic space has strong symmetry, its group relationship is more concise. While a uniform form is more conducive to achieving a balanced distribution of commercial traffic, the asymmetry of the plan layout helps to establish a psycho-spatial map for the visitors. In addition, the commercial value of the first floor is greatly influenced by the layout of the building entrance, and the commercial value of the second floor is greatly influenced by the location of the vertical transportation. In conclusion, when commercial building development planning is in the stage of traffic flow design, the use of space connectivity traffic data can assist in the selection of construction plans and predict the distribution of the economic value in CWCs.