An approach to measure walkability integrating individual walking decision and service facility preference: Community-wide study of Chongqing, China

Despite walkability has become a critical concern for citizens, academic researchers, and policymakers, the conventional walkability methods limited validity and applicability in different urban contexts. One of the key reasons is that the index ignores individual microscale walking preference behaviors that are important in assessing walkability. The incorporation of subjective decision preferences into walking decision-making process for service facilities represents a significant advancement for walkability measurement. To address this gap, this study introduces a novel walkability measurement approach based on discrete choice stated preference (DCSP) to investigate individual walking decision behavior preferences for service facilities, termed the Facility Stated Preference (FSP) method, and reveals the decision utility of walking preferences for 21 types of service facilities using three key variables: Use Frequency Preference (UFP), Use Diversity Preference (UDP), and Spatial Distance Preference (SDP). To validate the effectiveness and applicability of the FSP method, a case study is conducted across eight diverse communities in Qixinggang. The findings indicate significant spatial disparities in walkability scores across different geographical units, with modern residential areas along urban arterial roads exhibiting better walkability compare to older communities in the south and north. Additionally, the study highlights varying levels of walkability associated with different types of service facilities, with subway stations, bus stations, and primary and middle schools emerging as key contributors to overall walkability. These insights provide a deeper understanding of individual walking decision preferences and enhance predictive capabilities for service facility planning, serving as a valuable resource for urban planning authorities and policymakers in forecasting walking demand and optimizing service facility allocation.