This　paper　addresses　an　advanced　manufacturing　technology　selection　problem　by　proposing　a　new　common-weight　multi-criteria　decision-making　(MCDM)　approach　in　the　evaluation　framework　of　data　envelopment　analysis　(DEA).　We　improve　existing　technology　selection　models　by　giving　a　new　mathematical　formulation　to　simplify　the　calculation　process　and　to　ensure　its　use　in　more　general　situations　with　multiple　inputs　and　multiple　outputs.　Further,　an　algorithm　is　provided　to　solve　the　proposed　model　based　on　mixed-integer　linear　programming　and　dichotomy.　Compared　with　previous　approaches　for　technology　selection,　our　approach　brings　new　contributions.　First,　it　guarantees　that　only　one　decision-making　unit　(DMU)　(referring　to　a　technology)　can　be　evaluated　as　efficient　and　selected　as　the　best　performer　while　maximising　the　minimum　efficiency　among　all　the　DMUs.　Second,　the　number　of　mixed-integer　linear　programs　to　solve　is　independent　of　the　number　of　candidates.　In　addition,　it　guarantees　the　uniqueness　of　the　final　optimal　set　of　common　weights.　Two　benchmark　instances　are　used　to　compare　the　proposed　approach　with　existing　ones.　A　computational　experiment　with　randomly　generated　instances　is　further　proceeded　to　show　that　the　proposed　approach　is　more　suitable　for　situations　with　large　datasets.