Exploring entry-exit correlation coefficient (EEC) as new quantitative social activities performance measurement of public space: The case of Dilworth Park, Philadelphia - Jae Min Lee (Frontiers of Architectural Research)
This study explores a new public space performance measure by integrating public space and walking research to examine the relationship between pedestrian traffic volume and social activity intensity in parks and plazas. Introducing the entry-exit correlation coefficient (EEC), the study utilized bootstrap resampling methods to analyze data and compare to 59 manual observations. Findings reveal a statistically significant negative relationship between EEC and social activities, with a coefficient of −0.2. Lower EEC values, indicating closer correlation between entry and exit, were associated with increased social activities in Dilworth Park. The high synchronization observed between EEC and social activities underscores the potential of EEC as a complementary tool to manual observation in public space research. Additionally, the study emphasizes the importance of considering thermal comfort in monitoring public spaces using EEC. While the study focused on a single case study, its results lay the groundwork for future research to apply automated pedestrian counting and EEC as performance measurements for public spaces.