As　the　multi-criteria　decision-making　(MCDM)　problems　become　increasingly　complex,　experts　have　difficulty　in　quantifying　their　opinions　on　each　alternative　and　prefer　expressing　their　preference　information　linguistically.　Among　the　existing　linguistic　representation　models,　the　extended　comparative　linguistic　expressions　with　symbolic　translation　(ELICIT)　model　stands　out　due　to　its　powerful　ability　to　express　the　hesitancy　of　experts　and　obtain　results　with　higher　interpretability　and　accuracy.　Given　the　importance　of　the　aggregation　process　in　the　resolution　of　MCDM　problems,　the　definition　of　ELICIT　aggregation　operators　has　become　a　research　hotspot.　Among　them　is　the　ELICIT　-OWA　operator,　since　the　ordered　weighted　aggregation　(OWA)　operator　is　one　of　the　most　classical　and　popular　tools　to　fuse　decision　information.　However,　the　weights　used　in　the　aggregation　are　computed　from　the　assumption　that　the　criteria　are　mutually　independent,　which　may　be　not　realistic　in　some　MCDM　problems.　In　this　sense,　the　Choquet　integral　does　allow　for　reflecting　the　interrelationship　among　elements　by　means　of　the　definition　of　a　fuzzy　measure.　Therefore,　we　propose　a　novel　ELICIT-OWA　operator　that　calculates　weights　via　the　Choquet　integral,　taking　full　account　of　the　relationships　between　criteria,　in　order　to　obtain　a　realistic　aggregation　result.　On　this　basis,　a　new　approach　to　solving　MCDM　problems　is　presented.　Finally,　an　illustrative　example　is　applied　to　demonstrate　the　practicality　and　feasibility　of　the　proposed　method.　©　2024　selection　and　editorial　matter,　Walayat　Hussain,　Honghao　Gao,　Fethi　Rabhi　and　Luis　Martínez;　individual　chapters,　the　contributors.