## 1 Introduction  
After the outbreak and unprecedented spread of COVID-19, governments implemented various response policies, and the fear of infection led to structural changes across society, such as suspending inter-city public traffic, closing schools, canceling mass events and encouraging working from home [1; 2]. Particularly, several studies have identified a relationship between decreased crime rates and government policies, such as social distancing, globally [3; 4; 5]. True crime data also speak to this trend, with the average number of crimes decreasing by 5.48% at the end of 2020 compared to 2019 (the year before the outbreak) in Korea. Additionally, crimes in commercial districts decreased by 13.1%, suggesting that the lifestyle changes brought by COVID-19 may have had a direct impact on commercial area crime. The significance of crime in commercial districts is highlighted by the fact that 55.98% of crimes from 2016 to the end of 2020 were committed in commercial areas [6]. Thus, it is important to study these areas to better understand the factors that influence crime ratesand how they change in response to new policies and societal shifts. This is especially important in alley commercial districts, as they are the closest to daily life. There have been a range of studies investigating and analyzing the causes of crime in commercial districts while considering various factors. Particularly, urban built environment factors (e.g., the number of CCTVs, parks and streetlights, building age), urban greenery characteristics (e.g., the number and size of parks/green spaces) and demographic features (e.g., population density, percentage of foreign residents, elderly population, living population) have been commonly explored as potential crime-influencing factors [7; 8; 9; 10; 11; 12; 13]. Despite the extensive body of work investigating the drivers of urban crime, there are notable gaps in the Korean literature. The first is the study of crime factors at a micro level, such as individual market areas studied through granular crime reports that are able to give a detailed picture of market-specific crime frequency. Most existing research in Korea has predominantly concentrated on examining factors at the administrative district level or larger. Additionally, the specific focus on commercial crime, which constitutes a significant proportion of overall urban crime activity, is largely absent in the current literature. Furthermore, recent variables related to social policies precipitated by the COVID-19 pandemic, which have substantially impacted daily life, are yet to be thoroughly explored as influential factors in the context of commercial district crime. Therefore, this study aims to examine the factors affecting the number of 112 crime report calls, defined as the number of verified reports officially received at the \"112 Emergency Number\" reporting center (hereafter, commercial crime reports) before the outbreak (2019), after the outbreak (2020) and after the implementation of strict social distancing rules (2021) in Seoul alley commercial districts to understand the changes in the importance and influence of variables over time. Across the sampled dataset, there were 451,478 total crimes reported in 2019, 542,068 in 2020 and 538,031 in 2021. The crime reports are valuable big data, as they show the interaction between citizens and police at a micro scale and reflect the trend of crime over time. The number of reported calls (crime reports), which has rarely been used in prior studies in Korea, make up our dependent variable [14]. In addition, regression-based machine learning models, as opposed to classification-based models, were employed to identify the importance and non-linear relationship between a diverse set of factors and our dependent variable. We chose to frame our research as a regression problem due to our dependent variable being a continuous variable, making it unsuitable for classification modeling.