Identifying the spatial patterns and environmental predictors of card skimming at gas stations: a remote systematic social observation of Google Street View imagery

An increased reliance on payment system technologies globally has led to the proliferation of card skimming as an unintended consequence. Moreover, skimming prevention has also proved challenging, particularly at lesser supervised public places like gas stations. The current study aims to determine if there are identifiable spatial patterns or environmental characteristics that predict skimming at gas stations. Density analyses and a remote systematic social observation (SSO) of Google Street View imagery were used to assess the environmental contexts associated with high skimming gas stations compared to controls. Results indicate place management features related to increased visibility and lines of sight significantly predict skimming risk. Policy and practice implications are discussed, as well as relevant applications to environmental criminology approaches explaining crime occurrence at the micro-level.