The older neighborhoods in Chinese cities are the main areas in which the elderly live. Both housing and the older adults have experienced the resonance process of co-growth and co-aging. Along with the acceleration of the aging population, the older neighborhoods with the aging physical space environment are increasingly unable to meet the needs of the elderly, which affects their health and well-being. Although the Chinese government has launched a program of retrofitting older neighborhoods to make them more hospitable for older residents through, for example, elevator installation and infrastructure improvement, these practices are merely associated with various neighborhood features. Most existing research starts from small-scale case studies and consequently lacks macro-level analysis of the characteristics of the physical spaces and aging population in older neighborhoods. Therefore, this paper selects old neighborhoods constructed from 1949–1999 in the central city of Beijing (within the Fifth Ring Road) as research subjects. The research begins with an analysis of the construction and evolution of the standards of selected older neighborhoods in Beijing and establishes measurement metrics for the spatial characteristics of both the neighborhood and aging population. This article concludes that older neighborhoods in central Beijing can be classified into seven clusters based on their spatial characteristics and three clusters based on aging population characteristics through K-means classification. Additionally, this paper conducts an overlay analysis of these two classification results to identify different spatial features of older neighborhoods within varying characteristics of the aging population and proposes suggestions for the renovation of selected old neighborhoods. The study aims to provide a reference for retrofitting older neighborhoods with the goal of creating an aging-friendly community, and to supply a scientific basis for empirical research on the middle scale and micro scale.

This study aims to start from the macroscale of the megacity, explore a top-down operational technical path from the identification of community regeneration units as the evaluation objects to the BID priority intervention evaluation, and then propose differentiated community regeneration strategies based on the BID model. In the post-epidemic era, it is necessary for global megacities to take new measures in urban regeneration to respond to worldwide changes and challenges. As an innovative tool to promote central city revitalization, the BID model has played an important role in community transformation. In the context of the continuous decentralization of population and industry in China’s megacities, it is urgent to explore the technical path to apply the BID model to local community regeneration. Given the shortcomings of existing studies in the method to identify the scope of BID implementation and evaluate intervention priorities, this study takes Tianjin, a megacity in China, as an example and uses DBSCAN (density-based spatial clustering of applications with noise) and service area analysis to define the community regeneration units with commercial agglomeration characteristics as the objects. Then, the BID priority intervention evaluation system is constructed from the two measurement aspects of the intervention potential and the necessity of community regeneration to classify the BID intervention priorities of community regeneration units. The main conclusions are as follows: 1. When the DBSCAN analysis parameters take the minimum number of elements as 30 and the search distance as 120 m, the result is most suitable for identifying community units with commercial agglomeration of the study area; 2. Population vitality, especially working and residential population density, is the key factor affecting BID intervention potential, while road network density is an important indicator for determining the necessity of community regeneration; 3. Community regeneration units with high BID priority levels need to develop differentiated regeneration strategies combining their BID intervention potential, regeneration necessity characteristics, and location attributes. These conclusions can provide references for the governments of megacities to screen and establish BIDs.

The “double aging” problem of the aging population and the simultaneous aging of the community's physical environment will become a huge challenge in highly urbanized areas of the world, and China's performance is becoming more and more obvious, affecting the physical and mental health and quality of life of the elderly. Nowadays, the paradigm of solving the double aging problem with the concept of “active aging” is gaining international acceptance, which means the elderly are centered on the design and construction of a community environment that maintains their ability to live independently and promotes active social interaction in urban regeneration. However, existing research still has shortcomings in how to apply the perspective of active aging to establish an indicator system for evaluating the built environment of “double aging” neighborhoods and formulate action strategies. The study constructs a theoretical analysis framework of EPA-S (E-Environment supports, P-Personal abilities, A-Activity behaviors, S-State of healthy and active life) from the perspective of active aging and builds the model based on that. This observational study designed the survey content and collected sample data in four typical double-aging neighborhoods in Beijing for multi-layer linear regression analysis to verify the reliability of the model and the correlation between indicators. It found that the design of the “EPA-S” model has a certain degree of credibility. In addition to personal socioeconomic factors, active living abilities, and material environmental support also have a significant impact on the mental health and happiness of the elderly. Specifically, being more involved in community public affairs and collective cultural and recreational activities, and better improving the quality of public activity venues and service facilities within walking distance of the elderly are related to the elderly maintaining good physical and mental health. The “EPA-S” model established in this study can be used as a reference tool to evaluate the active aging level of “double-aging” neighborhoods. At the same time, the analysis results of each variable also provide important inspiration for formulating specific neighborhoods' regeneration strategies.

As a neighborhood-scale derivative of the Business Improvement District (BID) model, the Neighborhood Business Improvement District (NBID) represents a collaborative governance framework aimed at fostering spontaneous urban regeneration. Its successful establishment critically depends on building consensus among diverse stakeholders during the preparatory phase. This study addresses a significant gap by investigating the psychological mechanisms that shape stakeholders’ willingness to engage in NBIDs prior to their formation. Employing an exploratory sequential mixed-methods approach, we conducted semi-structured interviews in the Tiyuan North Community (Tianjin) and the Yulin East Road Community (Chengdu). Insights from the qualitative phase informed a subsequent quantitative survey administered to 215 stakeholders in Tianjin. Data were analyzed using regression analysis and Structural Equation Modeling (SEM). The results reveal that stakeholders’ performance expectations and collaborative willingness are significantly influenced by three core confidence factors: “Confidence in Authority Support (AS)” (particularly “Confidence in Council Representation”), “Confidence in Organization Capability (OC)” (especially “Confidence in Coordination Ability”), and “Confidence in Multi-party Collaboration.” Crucially, “Confidence in Enabling collaboration (MC_3)” itself acts as a key mediator, translating institutional trust into performance expectations. This study contributes a novel “Confidence–Expectation” framework to the literature on collective action and offers practical, context-sensitive insights for designing collaborative community governance structures aimed at sustainable urban regeneration in China and beyond.