A data mining approach to explore the causal rules between environmental conditions of neighborhood parks and seniors' satisfaction

Abstract

A growing body of research has investigated the associations between the physical environment features of neighborhood parks (NPs) and seniors' attitudes, usage intentions or behavior in the parks. However, research to date has not produced sufficient knowledge about the causal relationships between the physical features of neighborhood parks and seniors' attitudes. To fill this gap, this study takes 142 neighborhood parks located in Zhuhai of China as examples to explore the causal rules of the “environment-satisfaction” in neighborhood parks by using Rough Set Approach (RSA). This paper presents the results of 11 causal rules (i.e., if-then rules) between the physical features of neighborhood parks and seniors' positive/negative judgements. The findings can contribute to not only extending the academic research on the environmental preference of neighborhood green spaces among the seniors, but also to providing decision-makers with optimization strategies for designing or improving the neighborhood parks under the goal of aging in place.