Introduction:　Numerous　studies　have　demonstrated　the　close　relationship　between　alcohol　availability　and　alcohol-related　crashes.　However,　there　is　still　a　lack　of　spatial　empirical　analysis　regarding　this　relationship,　particularly　in　large　cities　of　developing　countries.　Differences　in　alcohol　outlets　and　drinking　patterns　in　these　cities　may　lead　to　quite　different　patterns　of　crash　outcomes.　Method:　3356　alcohol-related　crashes　were　collected　from　the　blood-alcohol　test　report　of　a　forensic　institution　in　Tianjin,　China.　Density　of　alcohol　outlets　such　as　retail　locations,　entertainment　venues,　restaurants,　hotels,　and　companies　were　extracted　based　on　2114　Traffic　Analysis　Zones　(TAZ)　together　with　the　residential　and　demographic　characteristics.　After　applying　the　exploratory　spatial　data　analysis,　this　research　developed　and　compared　the　traditional　Ordinary　Least　Square　model　(OLS),　Spatial　Lag　Model　(SLM),　Spatial　Error　Model　(SEM)　and　Spatial　Durbin　Model　(SDM)　to　explore　spatial　effects　of　all　the　variables.　Results:　The　results　of　incremental　spatial　autocorrelation　show　that　the　most　significant　distance　threshold　of　alcohol-related　roadway　traffic　crashes　is　3　km.　The　SDM　is　found　to　be　the　optimal　spatial　model　to　characterize　the　relationship　between　alcohol　outlets　and　crashes.　The　number　of　alcohol-involved　traffic　crashes　is　positively　related　to　population　density　and　retail　density,　but　negatively　related　to　the　company　density,　hotel　density,　and　residential　density　within　the　same　TAZ.　Meanwhile,　dense　population　and　hotels　have　reverse　spillover　effects　in　adjacent　zones.　Conclusions:　The　significant　spatial　direct　effect　and　spillover　effect　of　alcohol　outlet　densities　on　drunk　driving　crashes　should　not　be　neglected.　These　findings　could　help　improve　transportation　planning,　traffic　law　enforcement　and　traffic　management　for　large　cities　in　developing　countries.　(C)　2020　National　Safety　Council　and　Elsevier　Ltd.　All　rights　reserved.