The objective of this study was to establish a satisfaction evaluation model of industrial heritage renewal by evaluating the performance of old industrial buildings after renewal, then judging the adaptability and accuracy of the transformation strategy and putting forward targeted improvement suggestions. The data were collected through a questionnaire survey and analyzed by the statistical package for social science (SPSS) software using a structural equation model (SEM) and importance–performance analysis (IPA). The results show that (1) history, culture, and placeness have the largest average satisfaction and a positive and significant impact on overall satisfaction; (2) the building regeneration effect has a significant impact on overall satisfaction; and (3) social influence, external environmental perception, and economic benefits have no significant effect on overall satisfaction, indicating the need to strengthen public participation for further research into environmental creation, market-based operation, and land conservation. This case study reflects the distinctive features of internationalization and localization, and provides an indication of local practice in China for world urban renewal and architectural heritage theories.

Purpose: Construction enterprises are achieving the goal of production safety by increasingly focusing on the critical factor of “human” and the impact of individual characteristics on safety performance. Emotional intelligence is categorized into three models: skill-based, trait-based and emotional learning systems. However, the mechanism of action and the internal relationship between emotional intelligence and safety performance must be further studied. This study intends to examine the internal mechanism of emotional intelligence on safety performance in construction projects, which would contribute to the safety management of construction enterprises.Design/methodology/approach: A structural equation model exploring the relationship between emotional intelligence and safety performance is developed, with political skill introduced as an independent dimension, situational awareness presented as a mediator, and management safety commitment introduced as a moderator. Data were collected by a random questionnaire and analyzed by SPSS 24.0 and AMOS 26.0. The structural equation model tested the mediation hypothesis, and the PROCESS macro program tested the moderated mediation hypothesis.Findings: The results showed that construction workers' emotional intelligence directly correlates with safety performance, and situational awareness plays a mediating role in the relationship between emotional intelligence and the safety performance of construction workers. Management safety commitment weakens the positive predictive relationships between emotional intelligence and situational awareness and between emotional intelligence and safety performance.Originality/value: This research reveals a possible impact of emotional intelligence on safety performance. Adding political skills to the skill-based model of emotional intelligence received a test pass. Political skill measures the sincere and cooperative skills of construction workers. Using people as a critical element plays a role in the benign mechanism of “Emotional Intelligence – Situational Awareness – Safety Performance.” Improving emotional intelligence skills through training, enhancing situational awareness, understanding, anticipation and coordination and activating management environment factors can improve safety performance. Construction enterprises should evaluate and train workers' emotional intelligence to improve workers' situational awareness and safety performance.

Site selection is the key to carrying out the industrial layout of construction and demolition waste (CDW) resourcing enterprises. The current study needs more data on CDW industry location. The current construction waste resource utilization rate and industrial layout need to be improved. This study uses statistical and visualization methods to analyze key factors affecting the location of CDW recycling enterprises. Additionally, it identifies planning strategies and policy incentives to drive industry development. The study explicitly adopts global and weighted geographic regression (GWR) analysis methods and uses ArcGIS 10.8 to visualize point of interest (POI) data. It was found that (1) the main factors affecting the spatial distribution of the CDW recycling economy, in order of importance, are river network density, financial subsidies, R&D incentives, the number of building material markets, the value added by the secondary industry, the area of industrial land, and the density of the road network. The three main drivers of site selection decisions are government subsidies, market size, land, and transportation resources. (2) Enterprise industry chain and transportation costs are industrial economic decision-making considerations. Enterprises are generally located on flat terrain, around industrial parks, near the center of urban areas, and close to demand and cost reduction. (3) At the city level, there are more resource-based enterprises in cities with high levels of economic development and strong policy support. The spatial distribution of enterprises is consistent with the direction of urban geographic development. There is a positive global correlation between construction waste resourcing enterprises. Ningbo, western Qingdao, and northern Beijing show high aggregation characteristics. Low–low aggregation characteristics exist in regions other than central Chongqing. High–low aggregation characteristics are found in the center of the main city of Chongqing, eastern Shanghai, and central Nanjing. Low–high aggregation is distributed in northeastern Ningbo, northern Guangzhou, and southern Shenzhen. (4) Regarding industrial agglomeration, except for Nanjing, construction waste industrial agglomeration occurs in all 11 pilot cities. Among them, Shanghai, Xiamen, and Hangzhou have industries that are distributed evenly. Xi’an and Chongqing have a centralized distribution of industries. Guangzhou, Shenzhen, Beijing, Ningbo, and Qingdao have multi-center clustering of industries. Nanning’s industry has a belt-shaped distribution. This research explores the micro elements of industry chain integration in the CDW industry. It combines incentive policies and urban planning at the macro level. Together, these efforts promote sustainable city construction. This research provides CDW location data and dates for future digital twin and city model algorithms. It supports industrial planning, transportation, spatial optimization, carbon emission analysis, city operations, and management and aims to enhance the city’s green and low-carbon operations.

Smart healthcare management is one of the frontier research directions. It is vital to achieve life assistance through data science, innovative technology, and wearable devices for residents who age at home. This paper analyzes 42 aids of intelligent communities in residents’ physical, psychological, and medical aspects to understand the demand factors for health-assisted public products and services. The results show that: (1) the importance of intelligent assistance technology is significant; (2) the demand for medical monitoring is the highest, especially for an emergency button, fall detection, sleep drop detection, electronic fence, and medication management; (3) remote nursing and telemedicine has the most significant direct and indirect effect on the need for elderly assistance respectively; and (4) health monitoring affects the need for aging assistance by affecting emergency assistance and psychological assistance. Finally, this paper proposes construction strategies for the space design and the elderly care system of communities.