Urban　rail　transit　has　become　an　indispensable　option　for　Beijing　residents.　Subway　inelastic　users　(SIUs)　are　the　main　component　among　all　users.　Understanding　the　proportion　of　SIUs　and　their　characteristics　is　important　in　developing　service　promotions　and　helpful　for　subway　agencies　in　making　marketing　policies.　This　paper　proposes　a　novel　and　simple　identification　process　for　identifying　regular　subway　inelastic　trips　(SITs)　in　order　to　distinguish　SITs　and　non-SITs　and　extract　their　characteristics.　Weekly　station　sequence　(WSS)　is　selected　as　the　data-based　format,　principles　of　SIUs　are　discussed　and　chosen,　and　the　framework　of　SIT　identification　is　applied　to　a　large　weekly　sample　from　the　Beijing　Subway.　A　revealed　preference　(RP)　survey　and　results　analysis　are　undertaken　to　estimate　the　performance　of　the　proposed　methods.　The　RP　survey　validation　shows　that　accuracy　reaches　as　high　as　94%,　and　the　distribution　analysis　of　SITs　and　their　origin-destinations　(ODs)　indicate　that　the　SIT　characteristics　extracted　are　consistent　with　the　situation　in　Beijing.　The　proportion　of　SIUs　is　stable　on　workdays　and　is　more　than　80%　during　rush　hour.　The　efforts　described　in　this　paper　can　provide　subway　managers　with　a　useful　and　convenient　method　to　understand　the　characteristics　of　subway　passengers　and　the　performance　of　a　subway　system.