Big data-driven spatio-temporal heterogeneity analysis of Beijing's catering service industry during the COVID-19 pandemic

Abstract

The Catering Service Industry (CSI) experienced profound impacts due to the COVID-19 pandemic. However, the long-term and multi-timepoint analysis using big data remained limited, influencing governmental decision-making. We applied Kernel Density Estimation, Shannon Diversity Index, and the Geographic detector to explore the spatial heterogeneity and determinants of the CSI in Beijing during the pandemic, with monthly granularity. The temporal-spatial dynamics of the CSI presented a "W"-shaped trend from 2018 to 2023, with pivotal shifts aligning with key pandemic stages. Spatial characteristics exhibited heterogeneity, with greater stability in the city center and more pronounced shifts in peripheral urban zones. Districts facing intricate outbreaks showed lower catering income, and Chinese eateries exhibited heightened resilience compared to others. The CSI displayed strong interconnections with living service sectors. Development in each district was influenced by economic level, population distribution, service facilities convenience, and the risk of the COVID-19 pandemic. Dominant factors included total retail sales of consumer goods, permanent population, average Baidu Heat Index, density of transportation and catering service facilities, infection cases and the consecutive days with confirmed cases existing. Consequently, we suggested seizing post-pandemic recovery as an avenue to unlock the CSI's substantial potential, ushering a fresh phase of growth.

Exploring the Spatio-Temporal Evolutionary Characteristics of Paomo Restaurants in Xi’an’s Central Urban Area through POI Data Analysis

“…Recent studies within the urban and regional planning disciplines have increasingly emphasized the spatial analysis of the catering industry, acknowledging the crucial role that geographical location plays in the success of food service establishments. Research indicates that factors such as visibility, accessibility, and proximity to high-traffic urban areas significantly influence the performance and sustainability of restaurants [4][5][6]. These spatial characteristics are pivotal in determining the competitive dynamics within local and regional markets, impacting both the economic outcomes for individual businesses and the broader culinary landscape of urban centers.…”