Developing　China＇s　high-tech　industry　is　important　to　make　the　country　innovation-oriented.　This　requires　optimising　the　allocation　of　innovation　resources　and　improving　innovation　efficiency.　However,　few　studies　have　investigated　this　topic　and　the　realisation　path　for　the　high-tech　industry.　This　study　develops　an　input-oriented　inverse　data　envelopment　analysis　(DEA)　model　with　frontier　changes　to　analyse　the　optimisation　of　resource　allocation　in　China＇s　high-tech　industry　during　2019-2025.　With　this　method,　decision　makers　can　scientifically　analyse　the　specific　amount　of　resource　investment.　We　also　construct　an　analysis　framework　from　short-　and　long-term　perspectives.　The　results　show　that　the　excessive　input　of　research　and　development　(R&D)　personnel　and　unbalanced　allocation　of　capital　resources　are　the　main　barriers　to　the　development　of　high-tech　industries　in　the　short　term,　and　in　the　mid-　and　long　terms,　the　demands　for　investment　in　talent　and　capital　will　continue　to　increase.　Improvement　directions　for　promoting　the　development　of　China＇s　high-tech　industry　are　discussed.　Finally,　we　present　valuable　information　for　policymaking　to　promote　progress　in　high-tech　industries　in　different　regions.