This　study　investigated　the　potential　factors　affecting　the　injury　severity　of　shared　electric　bike　(e-bike)　riders　and　analyzed　potential　heterogeneity　using　a　dataset　comprising　of　1　343　shared　e-bike　insurance　accidents　recorded　by　a　shared　e-bike　company　as　the　research　object.　The　injury　severity　was　categorized　into　two　levels:　not　injured　and　injured.　Twelve　independent　variables　were　selected　based　on　six　aspects　involving　attributes　of　shared　e-bike　rider,　vehicle,　road,　environment,　time,　and　accident.　The　effects　of　different　factors　on　the　injury　severity　of　shared　e-bike　riders　were　assessed　using　the　random　parameter　logit　model　with　heterogeneity　in　means.　Results　indicate　that　the　variable　＇other　traffic　participants　at　fault＇　in　the　accident　scenarios　featured　a　random　parameter　that　adhered　to　a　normal　distribution　and　exhibited　mean　heterogeneity.　This　increased　the　likelihood　of　injury　among　shared　e-bike　riders.　However,　the　probability　of　injury　decreased　when　the　scenario　involved　both　the　variable　＇　other　traffic　participants　at　fault　＇　and　component　damage.　The　variables　female,　intact　road　surface,　dry　road　pavement,　nighttime,　single-vehicle　accidents,　and　both　at-fault　accidents　could　increase　the　injury　probability　among　shared　electric　bike　riders　to　varying　degrees.　The　findings　of　this　research　provide　a　theoretical　basis　for　the　development　of　traffic　safety　strategies　targeted　at　shared　electric　bike　riders.　©　2023　Southeast　University.　All　rights　reserved.