Design Strategies for Multi-Unit Residential Buildings During the Post-pandemic Era in China.

Objective: The sudden outbreak of COVID-19 has greatly endangered public health and life safety, leading to new changes in people's housing needs. The purpose of this study is to establish design strategies that are suitable for China's Multi-Unit Residential Buildings (MURBs) in the post-pandemic era, and to identify the users' preferences for these strategies. Methods: This study compiles a set of design requirements by means of a literature review and expert interviews. Three hundred ninety-five online and on-site questionnaires, based on the refined Kano model, were distributed to respondents to reveal their preferences for these strategies. The relationship between the different demographic variables, the preferences of design strategies, as well as the housing unit preferences of home-buyers were also verified by means of an actual project. Results: This study summarizes the four dimensions and 26 design strategies of MURBs in China during the post-pandemic era. These strategies are further extracted into 6 highly attractive, 5 high-value-added and 4 critical quality attributes. In terms of demographic variables, males need more social space, and the elderly need less office space and separate bathrooms in the master bedroom. Due to the impact of the epidemic, people with higher education levels are more required to work at home, and the overall demand for a home working environment is also higher. Conclusion: The home-buyers' preference survey reveals that the housing unit designed based on the refined Kano model is more attractive to home-buyers. The proposed approach can help to provide important and customized decisions to design firms, housing developers, and the government for MURBs planning and strategy formulation in the post-pandemic era in China. More in-depth user surveys in other regions and investigations into the cost assessment of these strategies might be further conducted in the future.

Optimal Decision Model for Sustainable Hospital Building Renovation-A Case Study of a Vacant School Building Converting into a Community Public Hospital.

Much attention has been paid to hospitals environments since modern pandemics have emerged. The building sector is considered to be the largest world energy consumer, so many global organizations are attempting to create a sustainable environment in building construction by reducing energy consumption. Therefore, maintaining high standards of hygiene while reducing energy consumption has become a major task for hospitals. This study develops a decision model based on genetic algorithms and A* graph search algorithms to evaluate existing hospital environmental conditions and to recommend an optimal scheme of sustainable renovation strategies, considering trade-offs among minimal renovation cost, maximum quality improvement, and low environmental impact. Reusing vacant buildings is a global and sustainable trend. In Taiwan, for example, more and more school space will be unoccupied due to a rapidly declining birth rate. Integrating medical care with local community elder-care efforts becomes important because of the aging population. This research introduces a model that converts a simulated vacant school building into a community public hospital renovation project in order to validate the solutions made by hospital managers and suggested by the system. The result reveals that the system performs well and its solutions are more successful than the actions undertaken by decision-makers. This system can improve traditional hospital building condition assessment while making it more effective and efficient.