Cluster map of hot spots and cold spots in the study area. 370 of the observations in the sample show spatial autocorrelation, represented by categories such as high-high (154), high-low (64), low-low (92), and low-high (60). This indicates clusters of similar or dissimilar property values across neighbouring locations. Source: Authors’ own work. The analysis was conducted using GeoDa™ (Anselin et al., 2006)