Addressing　the　global　challenge　of　sustainable　waste　management,　this　research　investigates　the　influence　of　social　dynamics　and　digital　connectivity　on　rural　residents’　willingness　to　adopt　waste　classification　practices,　essential　for　sustainable　environmental　management.　Through　a　comprehensive　analysis　of　5413　rural　participants　surveyed　in　the　China　Labor-force　Dynamic　Survey　(CLDS),　this　study　employs　a　novel　mixed-methods　approach.　It　integrates　quantitative　analysis　with　the　Manski　social　interaction　framework　and　a　Recursive　Bivariate　Probit　model　to　explore　the　intricate　interplay　between　community　interactions,　internet　access,　and　environmental　behaviors.　Our　methodology　stands　out　for　its　unique　combination　of　social　theory　and　econometric　modeling　to　address　a　pressing　environmental　issue.　Results　highlight　a　significant　effect　of　mobile　internet　use　and　social　interactions　within　communities　on　enhancing　willingness　towards　waste　classification.　Notably,　digital　connectivity　emerges　as　a　key　facilitator　of　environmental　engagement,　mediating　social　influences,　and　fostering　a　collective　approach　to　waste　management.　Considering　these　insights,　we　propose　targeted　policy　interventions　that　blend　digital　strategies　with　traditional　community　engagement　efforts.　Recommendations　include　crafting　digital　literacy　programs　and　leveraging　social　media　to　bolster　community-centric　environmental　governance.　By　harnessing　the　synergistic　potential　of　digital　tools　and　social　dynamics,　these　strategies　aim　to　elevate　the　effectiveness　of　waste　classification　initiatives　in　rural　China,　offering　a　scalable　model　for　environmental　sustainability.　©　2024　by　the　authors.