Evaluating intelligent residential communities using multi-strategic weighting method in China

•The intelligence indicators of residential communities (RCs) in China are elicited.•A multi-strategic weighting method is presented to evaluate intelligent RCs in China.•The analytic network process, entropy method and their combination are applied.•The method is applied to a case study and its feasibility is highlighted.•The method enables the evaluation of intelligent RCs on more fair ground.

Many residential communities are claimed to be “intelligent”, but their level of intelligence noticeably varies corresponding to the functionality and operational efficiency of the installed intelligent systems. This raises the need for having an effective and practicable method that would allow decision-makers to measure the degree of intelligence of one residential community against another. To achieve this objective, this paper elicits a general list of intelligence indicators of residential communities in China by means of system modeling as a base. Then, focusing in particular on the importance of these intelligence indicators’ weights, this paper proposes a dynamic multi-strategic weighting method to facilitate the evaluation of intelligent residential communities. The analytic network process (ANP), entropy method and their combination are proposed as three weighting strategies to meet the need of evaluation at different stages of intelligent residential community's development in China. An experimental case study has been presented to demonstrate how to use the multi-strategic method to confront real-world design tasks. The research aims to provide a practical method to enable the evaluation of intelligent residential communities on more fair ground.