This study explores causes of variation in auto theft rates using spatial data with face blocks as a unit of analysis. An integration of routine activity theory and social disorganization theory is proposed, premised on an empirical basis of interaction effects and a pattern of automobile theft diffusion. The results show that the integration of social disorganization theory and routine activity theory significantly increases the predictive power of the analyses and reveals several new socioecological implications for how and why auto theft occurs.