Substantial　research　is　required　to　ensure　that　micro-mobility　ride　sharing　provides　a　better　fulfilment　of　user　needs.　This　study　proposes　a　novel　crowdsourcing　model　for　the　ride-sharing　system　where　light　vehicles　such　as　scooters　and　bikes　are　crowdsourced.　The　proposed　model　is　expected　to　solve　the　problem　of　charging　and　maintaining　a　large　number　of　light　vehicles　where　these　efforts　will　be　the　responsibility　of　the　crowd　of　suppliers.　The　proposed　model　consists　of　three　entities:　suppliers,　customers,　and　a　management　party　responsible　for　receiving,　renting,　booking,　and　demand　matching　with　offered　resources.　It　can　allow　suppliers　to　define　the　location　of　their　private　e-scooters/e-bikes　and　the　period　of　time　they　are　available　for　rent.　Using　a　dataset　of　over　9　million　e-scooter　trips　in　Austin,　Texas,　we　ran　an　agent-based　simulation　six　times　using　three　maximum　battery　ranges　(i.e.,　35,　45,　and　60　km)　and　different　numbers　of　e-scooters　(e.g.,　50　and　100)　at　each　origin.　Computational　results　show　that　the　proposed　model　is　promising　and　might　be　advantageous　to　shift　the　charging　and　maintenance　efforts　to　a　crowd　of　suppliers.