Cross-efficiency　evaluation　has　been　widely　used　for　identifying　the　most　efficient　decision　making　unit　(DMU)　or　ranking　DMUs　in　data　envelopment　analysis　(DEA).　Most　existing　approaches　for　cross-efficiency　evaluation　are　focused　on　how　to　determine　input　and　output　weights　uniquely,　but　pay　little　attention　to　the　aggregation　process　of　cross-efficiencies　and　simply　aggregate　them　equally　without　considering　their　relative　importance.　This　paper　focuses　on　aggregating　cross-efficiencies　by　taking　into　consideration　their　relative　importance　and　proposes　three　alternative　approaches　to　determining　the　relative　importance　weights　for　cross-efficiency　aggregation.　Numerical　examples　are　examined　to　show　the　importance　and　necessity　of　the　use　of　relative　importance　weights　for　cross-efficiency　aggregation　and　the　most　efficient　DMU　can　be　significantly　affected　by　taking　into　consideration　the　relative　importance　weights　of　cross-efficiencies.　©　2013　Operational　Research　Society　Ltd.　All　rights　reserved.