Objective　More　attention　should　be　given　to　bicycle-motor　vehicle　(BMV)　crashes,　as　cyclists　are　at　a　higher　risk　of　suffering　injuries　than　motor　vehicle　users　in　a　crash.　This　study　aims　to　explore　the　factors　influencing　the　injury　severity　of　bicycle-motor　vehicle　(BMV)　crashes　in　Beijing　(China)　and　discusses　the　commonalities　and　differences　between　the　urban　and　suburban　areas.　Methods　Information　regarding　1,136　crashes　between　bicycles　and　motor　vehicles　were　collected　using　police　reported　data　from　2014　to　2015.　A　two-stage　approach　integrating　random　parameters　logit　(RP-logit)　model　and　two-step　clustering　(TSC)　algorithm　was　proposed　to　investigate　the　significant　influence　factors　and　their　combination　characteristics.　Specifically,　the　RP-logit　model　was　first　used　to　identify　the　significant　influence　factors　of　urban　and　suburban　areas,　and　then　the　TSC　algorithm　was　applied　to　reveal　the　combination　characteristics　of　significant　influence　factors　for　the　fatal　crashes.　Results　Five　factors　were　found　to　be　statistically　significant　and　had　random　effects　on　the　injury　severity　in　urban　areas,　i.e.,　type　of　motor　vehicle,　motor　vehicle　license　ownership,　type　of　bicycle,　signal　control　mode　and　lighting　condition;　and　seven　factors　were　found　to　be　statistically　significant　on　the　injury　severity　in　suburban　areas,　i.e.,　type　of　motor　vehicle,　motor　vehicle　license　ownership,　physical　isolation　facility,　signal　control　mode,　weather,　visibility　and　lighting　condition.　Based　on　TSC,　the　combination　of　significant　factors　showed　different　characteristics　for　fatal　crashes　in　urban　and　suburban　areas,　in　which　two　types　of　the　scene　including　five　factors　should　be　concerned　in　urban　areas　while　one　type　of　scene　containing　four　factors　in　suburban　areas.　Conclusions　The　results　suggest　that　different　influence　factors　and　individual　heterogeneity　exist　in　the　RP-logit　model　for　injury　severity　analysis　of　BMV　crashes　in　urban　and　suburban　areas.　It　shows　that　in　urban　areas,　heavy　truck,　light　truck　and　bus　significantly　increase　the　likelihood　of　fatal　injury　than　that　of　suburban　areas.　These　findings　can　provide　valuable　reference　information　for　BMV　crashes　response,　such　as　heavy　truck　restriction,　to　facilitate　regional　safety　measures　for　urban　and　suburban　areas.