Modeling Rent Performance of Shopping Centers in a Cluster

This paper aims to model rent performance of shopping centers in a cluster with the use of hedonic regression models. The current literature about shopping center rent or sales performance focuses on stand-alone shopping centers. To date, no research has examined the determinants of rent performance of shopping centers in a cluster context, in which the clustering effects may play important roles in explaining rent performance. Synthesizing clustering effects and elements of the traditional and contemporary theory for shopping center researches, an empirical framework is formulated for exploring the rent performance of shopping centers in a shopping cluster. Three groups of variables are employed in the hedonic shopping center rent models: shopping center's characteristics, shopping center owner's management expertise, and clustering and competitive factors such as relative size, relative location, and mix of the cluster. The methodology of this study differs substantially from that of previous studies on shopping center performance. This study focuses on a cluster of shopping centers at the microlevel. The unit of analysis is the shopping center in a shopping district rather than retail units agglomerating in a single shopping center. With more than thirty-three clustering shopping centers, Orchard Road/Scotts Road in Singapore is a good case for this study. Data for shopping centers along Orchard Road/Scotts Road span the years 1995-2005.