Purpose:　This　study　aims　to　provide　a　new　framework　for　analyzing　the　path　of　technology　diffusion　in　the　innovation　network　at　the　regional　level　and　industrial　level　respectively,　which　is　conducive　to　the　integration　of　innovation　resources,　the　coordinated　development　of　innovative　subjects,　and　the　improvement　of　innovation　abilities.　Design/methodology/approach:　Based　on　the　Z-Park　patent　cooperation　data,　we　establish　Inter-Enterprise　Technology　Transfer　Network　model　and　apply　the　concept　of　Pivotability　to　describe　the　key　links　of　technology　diffusion　and　quantify　the　importance　of　innovative　partnerships.　By　measuring　the　topologically　structural　characteristics　in　the　levels　of　branch　park　and　the　technosphere,　this　paper　demonstrates　how　technology　spreads　and　promotes　overall　innovation　activities　within　the　innovation　network.　Findings:　The　results　indicate　that:　(1)　Patent　cooperation　network　of　the　Z-Park　displays　heterogeneity　and　the　connections　between　the　innovative　subjects　distribute　extremely　uneven.　(2)　Haidian　park　owns　the　highest　pivotability　in　the　IETTN　model,　yet　the　related　inter-enterprise　patent　cooperation　is　mainly　concentrated　in　its　internal,　failing　to　facilitate　the　technology　diffusion　across　multiple　branch　parks.　(3)　Such　fields　as　＂electronics　and　information＂and　＂advanced　manufacturing＂are　prominent　in　the　cross-technosphere　cooperation,　while　fields　such　as　＂new　energy＂and　＂environmental　protection　technology＂can　better　promote　industrial　integration.　Research　limitations:　Only　the　part　of　the　joint　patent　application　is　taken　into　account　while　establishing　the　patent　cooperation　network.　The　other　factors　that　influence　the　mechanism　of　technology　diffusion　in　the　innovation　network　need　to　be　further　studied,　such　as　financial　capital,　market　competition,　and　personnel　mobility,　etc.　Practical　implications:　The　findings　of　this　paper　will　provide　useful　information　and　suggestions　for　the　administration　and　policy-making　of　high-tech　parks.　Originality/value:　The　value　of　this　paper　is　to　build　a　bridge　between　the　massive　amount　of　patent　data　and　the　nature　of　technology　diffusion,　and　to　develop　a　set　of　tools　to　analyze　the　nonlinear　relations　between　innovative　subjects.　　©　2021　Jun　Guan　et　al.,　published　by　Sciendo.