The　transportation　industry　is　considered　the　foundation　and　bridge　of　national　economic　development,　enabling　the　growth　of　the　social　economy.　However,　it　also　consumes　a　considerable　amount　of　energy,　resulting　in　high　levels　of　carbon　dioxide　(CO2)　emissions.　As　a　component　of　China＇s　vigorous　promotion　of　energy-saving　and　emissions-reducing　policies　in　recent　years,　it　is　crucial　to　maximize　transportation　efficiency　without　increasing　transportation　energy　consumption　and　CO2　emissions.　In　this　article,　the　transportation　process　in　China　is　divided　into　two　stages　while　maintaining　the　same　total　energy　consumption　and　CO2　emissions.　Additionally,　the　generalized　equilibrium　efficient　frontier　data　envelopment　analysis　(GEEFDEA)　model　is　enhanced　to　achieve　this.　The　improved　model　extends　the　single-stage　GEEFDEA　model　to　a　two-stage　process,　allowing　for　a　more　detailed　analysis　of　the　internal　dynamics　within　the　transportation　system.　Furthermore,　in　this　article,　the　fixed　inputs　and　outputs　of　the　original　model　are　further　extended　to　include　fixed　undesired　outputs,　expanding　the　applicability　of　the　model.　This　also　enables　the　possibility　of　energy　conservation　and　emissions　reduction　while　promoting　development　and　enhancing　efficiency.　Based　on　the　improved　model,　the　transport　efficiency,　energy　consumption　adjustment,　and　CO2　emissions　adjustment　of　30　provinces　in　China　are　measured.　Finally,　the　transportation　situation　and　characteristics　of　three　regions,　consisting　of　30　provinces,　are　analyzed,　and　reasonable　suggestions　for　the　development　of　transportation　in　each　region　are　presented.　Furthermore,　this　article　utilizes　spatial　econometric　methods　to　analyze　the　impact　factors　of　transportation　economic　efficiency　and　their　corresponding　spatial　spillover　effects　by　taking　into　consideration　the　intricate　interrelationships　among　regions.　The　results　indicate　several　findings.　First,　there　is　a　significant　positive　spatial　correlation　in　the　transportation　economic　efficiency　among　Chinese　provinces.　Second,　an　increase　in　per　capita　gross　domestic　product,　highway　transportation,　and　the　proportion　of　secondary　industry　have　negative　effects　on　transportation　economic　efficiency.　Moreover,　the　increase　in　the　proportion　of　secondary　industry　is　negatively　correlated　with　the　efficiency　of　neighboring　provinces.　Finally,　the　improvement　of　energy-saving　technology　significantly　promotes　an　increase　in　transportation　economic　efficiency.