Restaurants play a crucial role in shaping urban vibrancy, particularly in smart cities where they attract people and stimulate urban activities. While previous studies have primarily focused on the number of restaurants, the impact of restaurant genre diversity on urban vibrancy remains unclear. This study analyzes the relationship between restaurant genre diversity and the staying population around train stations using data from "Tabelog," Japan’s largest gourmet review website, along with public statistics.

A total of 111,104 restaurants in Tokyo’s 23 wards were classified into 16 genres, and Simpson’s Diversity Index (λ) was calculated for each 250-meter grid. Furthermore, an Ordinary Least Squares (OLS) regression analysis was conducted to examine the effect of genre diversity on the staying population while controlling for the number of restaurants, proximity to train stations, and business density. The results show that restaurant genre diversity significantly impacts urban vibrancy (coefficient = 0.674, p < 0.001). Additionally, areas with higher diversity indices and a larger number of restaurants tend to have higher staying populations, and proximity to train stations also contributes to increased urban vibrancy.

The findings suggest that enhancing restaurant genre diversity is as important as increasing the number of restaurants. Moreover, integrating private-sector gourmet data with public urban datasets is beneficial for optimizing urban planning and restaurant location strategies.

From a smart data perspective, the significance of this study lies in demonstrating that detailed urban analysis can be achieved using individual restaurant data from private gourmet information sites, which influences the increase in urban vibrancy.