DEA　cross-efficiency　evaluation　method　can　rank　decision　making　units　(DMUs)　more　reasonably　than　the　classical　DEA　model,　but　the　existing　cross-efficiency　evaluation　methods　still　have　many　deficiencies.　The　most　evident　drawback　is　that　the　potential　multiple　solutions　of　the　optimal　weights　lead　to　the　non-uniqueness　of　the　cross-efficiency　value.　Moreover,　the　traditional　cross-efficiency　ranking　methods　neglect　the　interaction　between　DMUs.　It　is　a　common　scenario　that　the　decision-making　unit　will　incline　to　give　high　evaluation　scores　to　those　in　same　coalition,　and　relatively　low　evaluation　scores　to　those　with　different　coalitions　on　the　contrary　in　the　process　of　cross-efficiency　evaluation.　Aiming　at　solving　the　above　problems,　this　study　proposes　a　cross-efficiency　game　model　considering　correlation　coordination　degree　among　DMUs.　The　generalized　Shapley　value　of　cross-efficiency　game　is　defined,　and　its　desirable　properties　are　proved　in　detail.　Finally,　a　global　correlation　coordination　(GCC)　model　is　developed　for　ranking　decision-making　units　comprehensively.　The　comparative　example　and　practical　application　on　R&D　efficiency　evaluation　are　provided　to　illustrate　the　rationality　and　feasibility　of　the　GCC　model.　©　2023　Elsevier　Ltd