Analysis of co-location pattern in Surabaya city convenience franchise store

• Main Authors: Hirzi, Naufal Muhammad, Imanto, Teguh, Arymurthy, Aniati Murni, Setiyoko, Andie, Yulianto, Fajar
• Format: Conference Proceeding
• Language: English
• Subjects: Data analysis; Digital mapping; Franchises; Pattern analysis; Retail stores; Site selection; Spatial data
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0181449

The Indonesian retail industry continues to grow, especially modern retail owned by individuals, which needs to reflect on the successful franchise retail industry. This study discusses the analysis of location selection at one of the largest retailers in Indonesia through a spatial pattern analysis approach that is useful as a role model for individual retailers. The object of this research is Indomaret retail in Surabaya city, the second big city in Indonesia after Jakarta based on its population. Data are collected from OpenStreetMap and co-location mining is performed on relevant location attributes and then evaluated using the participation index (PI). PI is calculated against major attributes, combinations of 2 minor attributes, and combinations of 3 minor attributes, then sorted to get the top 3 attributes. The major attribute with the highest PI score is footfall, while the minor attribute with 2 combinations results is worship facility, and with 3 combinations results in food service. Spatial data analysis is proven to detect retail store location patterns. The results of this study can be applied as a reference for location selection in opening new retail stores, especially in the high-density population area which has a similar type to Surabaya city.