Hesitant　multiplicative　preference　relations　(HMPRs)　are　utilized　to　describe　situations　where　a　decision　maker　gives　several　possible　values　by　Saaty’s　1-9　scale　in　pairwise　comparison.　For　further　applications　of　HMPRs,　this　paper　develops　two　priority　methods　based　on　data　envelopment　analysis　(DEA)　for　group　decision　making.　These　methods　include　self-weight　prioritization　and　the　cross-weight　prioritization,　which　are　similar　to　the　self-evaluation　efficiency　and　the　cross-evaluation　efficiency　in　DEA　theory,　respectively.　We　prove　that　both　of　them　can　generate　true　priority　weights　for　consistent　HMPRs.　The　mechanisms　of　these　proposed　methods　are　illustrated　with　numerical　examples.　Also,　comparisons　with　other　methods　are　performed　to　show　the　advantages　of　the　proposed　methods.　©　2017,　The　Natural　Computing　Applications　Forum.