我国医药制造业科技人力资源需求研究

上海交通大学硕士学位论文我国医药制造业科技人力资源需求研究姓名：蒋云飞申请学位级别：硕士专业：产业经济学指导教师：马德秀;王昌林20090101MatlabBP1998-2006R&D20102015ABSTRACTChinahasenteredastagewhichneedstoincreasethedegreeofdependenceontechnologyandinnovation.Competitioninhumanresourceespeciallyscienceandtechnologyhumanresourcesisgraduallybecomingthecentralpointinthisstage.Asanimportantcomponentofhigh-techindustry,pharmaceuticalmanufacturingindustryhasbecomenotonlyapowerfuldrivingforce,butalsoanimportantguaranteeofpeople'shealthandlivingstandard.Atthesametime,asaknowledge-intensiveindustry,pharmaceuticalmanufacturingindustryhasahighdemandforitshumanresource.Onlyhaveabetterunderstandingofthisdemand,cantheindustryhaveabetterandfasterdevelopment.Onthebasisofcharacteristicsofthepharmaceuticalmanufacturingindustry,thisarticlefirstlygavequalitativeanalysisfromtheaspectsofR&Dandindustrialdemand;thenestablishedquantitativeanalysismodelwithMatlabtoforecastthedemandin2010and2015.Finally,wemadesuggestionsfromfourareasoftraining,attracting,usingandmacro-managementofhumanresourcesandgavethesuccessfulexperienceofdevelopedcountries.KEYWORDSPharmaceuticalmanufacturingindustry,scienceandtechnologyhumanresources,Talentdemand,Industrialpolicy111.1213020076927.7725.09%6392.69629.9924.90%55.56%12007%200720076392.6924.90629.9955.563181.86286.641496.6725.06108.7853.521685.1923.62177.8656.141584.74171.781312.9921.69154.7859.79271.7537.371770.00495.3921.6263.1850.00547.9522.0559.4643.90298.831.1424.2750.0044.5525.002.6750.00200721.21.2.11.2.21.2.331.31.3.1R&DMatlabBP2010201541.3.222.1::2.1.12.1.22.1.352.22.2.1118%GMP121/50001/4000200448.532-3104103-5701GMP2000-30007612.2.2102.2.320035002.32.3.11237165082.3.2R&D910%R&DR&D2.3.32002201033.13.1.11210proteome()33.1.21CROContractResearchOrganization23.1.3113.23.2.1GMP,,,,1997199821200414280003.2.2123.2.3R&D97.4%1500702WTO1004-10500-600199219861119931176199311EPOG-CSFGM-CSF-21993515034020052007300020105.56201033.2.4200311131%10%2.6%7.444.14.1.1102005801144.1.2285200712620627832007117120200615010128200770.634002006194138446200738922020072504.1.33,1995250592006642781995108652006422413-1199543.3%65.72%1995942006324319952505910865942000378332248022620025305533946322200344561294242552004465943027726520055183236023292200664278422413242007154.24.2.1150LDCNICAICLDCGDP785NICGDP7869655AIC9656LDCNICAIC2003GDP10004250041995-2006DGPGDP19955046961.26200078581781.37200293982378.442003105422889.902004123363241.302005141034250.452006160845018.942007200716YGDPX0.9950.01ModelSummaryandParameterEstimatesDependentVariable:EquationModelSummaryParameterEstimatesRSquareFdf1df2Sig.Constantb1b2Linear.989460.79915.000-1042.782.369Theindependentvariableis:GDPY=-1042.782+0.369XR2=0.989Ft0.01GDP10036.94.2.2119981998GMPGSPGCPGAP2003GMPGSPGCPGAPGMPGMP200471GMP20066313101GMP60%197088417219992003OTCOTCOTC1990192003320100019971016015%2001331985411993111520199311188082624342002551.2.1.2.B1B2CE3.4.5.6.1.2.3.4.5.6.7.8.9.10.11.12.1913.14.15.16.20087181998200778CC200264.2.3207010%200716%19751.3819803.182001208.02200613.182040841522603704763995184345614455880100200300400500600198019851990199520002004200520062007Phrma2PhRMAProfile20082006NME31GardasilHPV6111618-4(DPP-4)sitagliptinphosphateJanuviasunitinibmalateSutent32200015%-20%10%1%-3%5-8356076621636.448.633.43.3%11.413.414.31.03.2%82.565.2126.473.110.53.19.08.610.37.93.02.45.89.710.71.12.3(%)26.143.125.32.2%70.457.261.298.32.1%2.22.43.12.21.3USPTO3.88.78.45.91.2EPO21.024.538.623.34.61.1R&D%(2004)36.448.633.43.3%11.413.414.31.03.2%82.565.2126.473.110.53.19.08.610.37.93.02.45.89.710.71.12.3(%)26.143.125.32.2%70.457.261.298.32.1%2.22.43.12.21.3USPTO3.88.78.45.91.2EPO21.024.538.623.34.61.1R&D%(2004)4.34.3.1GrayPredictiveModelgm(1,1),,4.3.2(ArtificialNeuralNetwork,ANN)22(BackPropagation)(Multiple-LayerFeed-forwardNetwork)BPBP4.44.4.1BPBPBP182-65GDPR&D1998-20068GDPR&D(((((199883024.330580.5467486432.9138594199988479.233873.4544583514.8636068200098000.538714.0643896633.88378332001108068.244361.67031044722.43400092002119095.749898.98161297834.65530552003135174.056004.797615631024.92445612004159586.764561.3109519661173.00465942005184739.173432.9133524501529.80518322006211808.082972.0168930031808.0964278GDP2000-200723R&D1998-20062004-20074.4.21MATLAB:pP=[83024.330580.5467486432.91;88479.233873.4544583514.86;98000.538714643896633.88;108068.244361.67031044722.43;119095.749898.98161297834.65;13517456004.797615631024.92;159586.764561.3109519661173;184739.173432.9133524501529.8;21180882972168930031808.09]’fori=1:5P(i,:)=log10(p(i,:))/10endtt=[385943606837833400095305544561465945183264278]’fori=1:1T(i,:)=log10(t(i,:))/10end2BPBP,StansigSlogsig[0,1]trainbfgMATLAB:P=[0.491920.448540.266930.268660.26364;0.494680.452990.273560.27657240.27117;0.499120.458790.280820.295230.2802;0.503370.46470.28470.301870.28588;0.513090.474820.298940.31940.30107;0.52030.4810.303940.329360.30693;0.526660.486590.312550.338920.31846]’T=[0.458650.455710.457790.460220.46490.466830.47146]’threshold=[01;01;01;01;01;];net=newff(threshold,[7,1],{'tansig','logsig'},'trainbfg');net.trainP