创新和企业绩效外文翻译

本科毕业论文（设计）外文翻译原文：InnovationandfirmperformanceFactorsinfluencingthedecisiontoinnovateSeveralstudiesempiricallytestthepropensityoffirmstoinnovate.Felder,etal.(1996)usedtheMannheimInnovationPaneltotesttherelationbetweenR&Dandotherinnovationexpenditures.Thedatasetcontainsasmallfirmsubsetcontainingfirmswith5uptill49workers.Theparticipationdecisiontoinnovateraisesstronglywithsize.However,onceinnovating,theamountsinvestedaspercentageoftotalsalesislargerwithsmallfirmsthanwithlargefirms.ThisisconfirmedbyVossen&Nooteboom(1996).Thiseffectismostpronouncedforthetotalinnovationexpenditures.TherelationshipbetweenfirmsizeandR&DseemsU-shaped.Vossen&NooteboomconcludethatsmallfirmsparticipatelessinR&D,butatagreaterintensityandwithagreaterproductivityoncetheyparticipate(Vossen&Nooteboom,1996,167).AlsoKleinknecht(2000)andKleinknechtandMohnen(2002)foundthatthepropensitytoinnovateispositivelyrelatedwithsizealthoughtherelationshipmaynotbelinearandthatamongtheinnovators,smallerfirmstendtohavehighersharesinsalesofinnovativeproducts.Lööfetal.(2001)usedOECDandCISdataintheirempiricalwork.UsingaCobb-DouglasproductionfunctiontheytrytoexplainvariationinproductivitygrowthbetweentheNordiccountries,usingstandardinputs(labourandcapital)andtheinnovationinvestmentvariable,whichsubstitutestheR&Dvariable.UsingaCrépon,DuguetandMairessemodel(1998)theyestimatethefollowingfourequations:(1)firms’prosperitytoinnovate/decisiontoinnovate;(2)innovationinputs(innovationinvestmentperworker);(3)innovationoutput(logofinnovationsalesperworker);and(4)productivity(salesperemployee).Throughputisnotformallyincludedinthissetofequations.Atwo-stepinvestmentmodelisapplied:First,thedecisiontoengageinresearchmustbetaken(eq.1);Next,conditionalonengaginginresearch,theamountofinvestmentmustbedecidedupon(eq.2).ThedecisiontoinnovateismodelledasaProbit[0,1]model.ToexplainthepropensitytoinnovateLööfetal.(2001)usethefollowingvariables:firmsize(employees),exportintensity,priorpatentapplications,%non-R&Dengineers,%administratorsandseveralcontrolvariables.Firmsizeandpatentapplicationsaresignificantinallthreecountries,exportintensityintwocountries,theothervariablesinonlyonecountry.Thecontrolvariableswerenotsignificant.Technologicalopportunities,factorintensityandsectorcharacteristicsalsoinfluencetheinnovationdecision(Lööfetal.,2001).Inasectorwithhightechnologicalpotentials,firmsaremoreinclinedtoinnovate.Iftheydonotinnovate,theymaylosetheirmarketposition.Toestimatetheeffectsofthesevariables,dummieswereincludedintheregression,however,theresultsarenotreported.Tosummarize,thedecisiontoinnovateisanimportantdecisionforcompanies.Onceacompanydecidestobeactiveininnovation,thecompanyhastodedicateresourcestotheinnovationprocess.Thedecisionisinfluencedbythesizeofthefirm,theexportintensity,priorR&Dandcharacteristicsoftheemployees(levelofeducation).Alsoprocesscharacteristicssuchasthemissionofthefirminfluencetheinnovationdecision.InnovativeintensityConditionalonengagingininnovations,theinnovationintensitymustbeassessed.Itconcentratesonunderstandingthedeterminantsthatinfluencethelevelofresourcesdedicatedtotheinnovationprocess.Theseresourcesaretypicalfinancialorhuman.Theliteratureprovidesuswithseveralindicatorsoftheinnovationintensity.TraditionallyandstillthemostpopularinputindicatoristheexpendituresonR&D(KlompandVanLeeuwen,1999,Lööfetal.,2001).TheexpendituresareoftendividedbytotalsalestocometotheR&Dintensityofacompany.TheR&Dindicatorisstillfurtherdevelopedasanindicator.Themainadvantageofthisindicatoristhatitisrelativelyeasytomeasureandcollect.Theextensiveuseofthisindicatoralsoimprovesthecomparabilityofthedifferentstudies.However,severalweaknessescanbementioned(seeKleinknecht,2000,foranextensivereview).First,R&Dexpendituresaremerelyaninputtotheinnovationprocess,butitstatesnothingontheresults,ortheefficiency.Second,R&Drelatedinputsmakeforaminorityofinnovationexpenditures,varyingfrom25-50percent.Third,R&Ddatatendtounderestimateinnovationsinservices.Finally,R&DquestionnairesunderestimatethesmallscaleandofteninformalR&Dactivitiesinsmallercompanies.Complexquestioningmayresultinsuchunderestimation.SeveralnewdefinitionsandimprovedR&Dexpenditureshavebeenproposed.First,the1992Oslo-manualoftheOECDpositsanewdefinitionofexpendituresrelatedto(technological)effort.ItaddedtoR&Dexpendituressixothercostcategories,namelyproduct/industrialdesign,trials,marketanalysis/introduction,training,patentsandlicensing,andinnovation-relatedfixedassetinvestments(Felderetal.,1996:129;Klomp,2001:3).Vossen&Nooteboom(1996)claimthattherelationshipbetweenfirmsizeandtheamountsofmoneyallocatedtoinnovationsismostpronouncedfortotalinnovationexpenditures.ThisinnovationintensityvariablewasprecededbyR&Dintensity,denotingthe(internalandexternal)R&Dexpendituresscaledbytotalsales.R&Dandinnovationexpendituresarehighlycorrelated(Mohnen&Dagenais,2002,13).TotalR&Dexpenditures,alsocalledR&Dinvestments,consistofinternalR&D,externalR&DandR&Dincollaborationwithuniversitiesandresearchinstitutes(Klomp&VanLeeuwen,1999:12).Thesethreesubsetstogetherandrespectivelylistthe‘make,buy,orco-operate’alternativestomanagementdecisionsoninnovationinvestments.Empiricalresultsprovetheimportanceofthesedistinctexpenditures.Itturnsoutthatinasampleof3,000GermanindustrialenterprisesinternalR&Dcoversslightlyabove40percentoftotalinnovationexpenditures(Felder,etal.,1996:130).ThisissupportedbytheCISresearch,fromwhereitisconcludedthatinternalR&Damountsforlessthan50percentofthetotalinnovationexpenditures(Klomp,2001:3).Whenservicesareincludedapercentageevenaslowas25percentwasarrivedat(Kleinknecht,2000:3).Thisnewindicatorhasasadownsidethatincludingnon-R&D-itemsinthequestionnairelowerstheresponseratesandlowersalsotheprecisionofanswers.Thereasonisthatmanyfirmsdonotkeeprelatedrecords(Kleinknecht,2000:3).AnothertraditionalindicatoristhenumberofemployeesdedicatedtoR&D.Itisalsoeasytomeasureandisbettersuitableforservicessectors.Alsothisindicatorhasseveralweaknesses,partlyoverlappingtheweaknessesofR&Dexpenditures(e.g.noinformationonefficiency,minorityoftotalexpenditures).Furthermore,itdoesnotincludethequalityoftheemploymentinputandthetimedevotedtoinnovation.MairesseandMohnen(2001)taketheshareofnewproductsintotalsalesasindicatorforinnovationintensity.Ithastheadvantagethatthefinalobjectivesofinnovationtrajectoriesaretakenintoaccount,i.e.extraturnoverand/orprofit.However,theshare-insalesvariableisbetterusedforoutputmeasurement.Thiswillbefurtherdiscussedbelow.Inthisstudy,weusethenumberofemployeesdedicatedtoR&Dasanindicatorforinnovativeintensity.Thisindicatorisimprovedbycorrectingfortheaveragetimetheemployeesspentoninnovation.Thisvariableisalsoappropriateforsmallcompanies.FactorsinfluencingtheinnovativeintensitySeveralstudiesexaminedthefactorsthatinfluencetheinnovationintensity.Innovationintensityisusuallydefinedasthetotalofinnovationexpendituresdividedbythetotalturnoverofcompaniesinacountryorthenumberofemployeesdedicatedtoinnovation.ThisdependentvariableismodelledasaTobitmodel,conditionalonhavingdecidedtoinvestininnovations(Lööf,etal.2001,p.11).Theliteratureprovidesuswithseveralvariablesthatinfluencetheinnovationintensity.Lööfetal.(2001)includethesamevariablessoastoexplainthepropensitytoinnovate(firmsize(employees),exportintensity,priorpatentapplications,%non-R&Dengineers,%administratorsandseveralcontrolvariables)plusobstaclestoinnovate,informationforinnovation,innovationstrategies/innovationobjectives,cooperation(domesticandforeign).Theresultsaresomewhatconfusingatcross-countrylevel.ForexampleinFinland,firmsizehasanegativeeffectoninnovationinvestment,inNorwaytheeffectwaspositiveandinSwedentheeffectwasnotsignificant.Oftheextravariablesonlytheinnovationobjectiveextendingtheproductrange,informationsourceswithinthefirmitselfandcustomersanddomesticcooperationwithcustomersaresignificantandpositivelyrelatedwiththeinnovationinvestmentinallthreecountries.KlompenVanLeeuwen(1999)developedasimultaneous-equationmodelfortherelationshipbetweeninnovationandfirmperformance.Theyexplainedtheinnovationintensitybythefollowingvariables:priortotalsales,priorcashflows,technologicalopportunities,ageofthefirm,subsidies,R&Donapermanentbase,cooperationandinnovationpushand/orpullfactors.Therearefeedbackloopsfromtheperformance(developmentofthesales).Theyalsoincludesectordummiesanddummiesforsector-sizeinteractions.Theytestthemodelforallinnovativefirmsandinnovativefirmswithinnovativeoutput.Theyusedasingle-equationapproachandthesimultaneousapproach.Inthesingle-equationapproachmostofthevariablesprovedtobesignificant,withtheexceptionofpushandpullfactors.Inthesimultaneous-equationmodelpriorcashflow,priorsales,developmentofsalesandsubsidiesprovedtobesignificantinvariousmodels.InastudyonthecausalitybetweenR&Dintensityandexportintensity,KleinknechtandOostendorp(2002)provedthatanincreaseintheexportintensityofafirmsignificantlyandpositivelyinfluencestheR&Dintensity.Inarecentpaper,StatisticsNetherlandstogetherwithTNOdetailedtheinput,throughputandoutputorderoftheinnovationprocessfortheKnowledgeBasedEconomy(Klomp,etal.,2002).Theinputstageconsistsofhumancapital(students,secondaryvocationaltraining,graduatesfindingajob,company-financedcourses,and,finally,humanresourcesinscienceandtechnology),nexttothetechnologicalknowledgebaseofDutchinstitutes(researchinstitutes,universities,andprivatefirms).Thepaperisdescriptiveinprinciple.Theelaborateandmulti-facetedconceptseemspromisingbutashortageofdatawillmakeithardtotestit.Innovationintensitycanbeseenastheeffortafirmputsininnovation.ItisoftenmeasuredbytheR&Dexpendituresdividedbytotalsalesorthenumberofemployeesdedicatedtoinnovation.Theinnovationintensityisinfluencedbythefirmsize,exportintensity,priorsalesleveloreducationoftheemployees,externalsupport(subsidies)andinnovationprocesscharacteristics.Thefollowingconclusionscanbedrawnfromourempiricaltest.Theinnovativeinputisexplainedforsmallandmedium-sizedfirmsbydifferentfactors.Thesizeeffectbecomesclearfortheuseofsubsidies.Smallfirmsusenationalsubsidies,medium-sizedfirmsuseEuropeansubsidies.Smallfirmshavemoreinnovativeinputiftheyinnovateinacontinuousway.Alsomedium-sizedfirmshavehigherinnovativeinputiftheyinnovateinacontinuousway.Forsmallfirmsalsoperformancemarketresearch,havingcontactswithanintermediateorganizationandcooperationwithotherfirmsandresearchinstituteshaveapositiveeffectontheinnovativeinput.Ifweonlylookatfirmswithinnovativesalesinthelastthreeyears(i.e.firmsthathavebeensuccessfulintheinnovationprocessinthepast),wegetasomewhatdifferentpicture.Forsmallfirmsnationalsubsidiesandcontinuousinnovationremainimportant.Marketresearch,contactswiththeintermediateorganizationandcooperationwithresearchinstitutesarenotsignificantanymore.Formedium-sizedfirms,onlyEuropeansubsidiesandcontinuousinnovationhaveaweakeffectontheinnovativeinput.Basedontheseresults,onemayconcludethatthenationalinnovationpolicyhasapositiveeffectonthelevelofinnovativeinputofsmallfirms.Theuseofnationalsubsidiesandcontactwiththe(government-supported)intermediateorganizationhasasignificantandpositiveeffectonthelevelofinnovativeinput.Oncesmallfirmshaveinnovativeoutput,thesevariablesdonothaveaneffectanymoreontheleveloftheinnovativeoutput.Theabsenceofthiseffectmaybeexplainedbythefactthatsmallfirmsthathaveinnovativeoutputarerelativelyhomogeneousconcerningthesevariables.Asaresultthesevariablescannotexplainthelevelofinnovativeinputanymore.Thevariableshelptodiscriminatebetweenfirmshavinginnovativeoutputandfirmsnothavinginnovativeoutput.Ifthevariablesofthenationalinnovationpolicyarestudiedinisolation,itappearsthatcompaniesthatuse(national)subsidiesorhavecontactswiththeintermediateorganizationhavehigherinnovativeinputandoutput.Anotherinterestingfindingisthatthelevelofinnovativeinputofsmallfirmswithinnovativeoutputisnotanymoreinfluencedbythecooperationwithotherfirms.Alsothisvariableseemstohelptodiscriminatebetweenfirmswithinnovativeoutputandfirmswithnoinnovativeoutput.Furthermore,wefoundanegativerelationshipbetweenfirmsize(measuredinturnover)andinnovativeinput.Exportgrowthhasapositiveeffectoninnovativeinput.Ifthesampleissplitupinsmallandmedium-sizedfirms,theserelationshipsareonlysignificantforsmallfirms.Thisfindingisinlinewithpreviousempiricalresearch(VossenandNooteboom,1996;Kleinknecht,2000;Lööf,2001).Ourfindingsindicatethatthenegativerelationshipisespeciallyrelevantforsmallfirms.Ifthefirmsarebiggerandmorehomogeneous(inourresearchtenormoreemployees),thenegativerelationshipdisappears.Asimilarargumentcanbegivenforthepositiverelationshipbetweenexportgrowthandinnovativeinput.TheeffectsofdifferentvariablesontheinnovativeoutputaretestedwithtwodifferentTobitmodels.Thedecisiontohaveinnovativeoutputispositivelyinfluencedbythecontinuityoftheinnovationefforts,changesintheorganization,themeasurementofcustomersatisfactionandthefocusonproductinnovations.Strikingly,contactswiththeintermediateorganizationhaveanegativeeffectonthedecisiontohaveinnovativeoutput.Theeffectdisappearsformedium-sizedfirms.Thismightindicatethatcontactswiththeintermediateorganizationhaveanegativeeffectonthetransformationprocessfrominnovativeinputtoinnovativeoutput.Ontheotherhand,firmsmaygetincontactwiththeintermediateorganizationoncetherearenotsuccessfulintransforminginputintoinnovativeoutput.Itmaytaketimebeforethecontactwiththeintermediateorganizationresultsininnovativeoutput.Ourresultssuggestthatinnovationcontributestotheturnoverandemployeegrowth.Theemploymentgrowthisalsoinfluencedbyturnovergrowth.Forsmallfirms,theinnovativeoutputdoesnotinfluencetheleveloftheemployeegrowth.Theinnovativeoutputhasnoeffectontheprofitabilityandproductivityofthefirm.Toconclude,ourresearchshowsthattheinnovationprocessofsmallfirmsdiffersfrommedium-sizedfirms.Therefore,itisimportanttotreatbothgroupsdifferently.Ourresultsfurthermoresuggestthatthenationalinnovationpolicystimulatesespeciallysmallfirmstoincreasetheirinnovativeinput.Ontheotherhand,theinnovationpolicydoesnothaveadirecteffectontheinnovativeoutput.Thismightaskforslightchangeinpolicy,focusingmoreonthetransformationprocessfrominnovativeinputtoinnovativeoutput.Stressingtheimportanceofcontinuousinnovation,measuringcustomersatisfactionandtheimportanceofproductinnovationmayleadtoanincreaseofthenumberoffirmsthathaveinnovativeoutput.Oncetheyhaveinnovativeoutput,thelevelofinputisimportant.Asstatedbefore,policyonthisaspectseemstobeeffective,atleastforsmallfirms.Finally,innovationseemstohaveapositiveeffectontheturnovergrowthandemploymentgrowthoforganizations,althoughthesizeoftheeffectisrelativelysmall.Wecouldnotfindaneffectontheprofitabilityofthefirmortheproductivity.Source:R.G.M.Kemp;M.Folkeringa;J.P.J.deJong;E.F.M.Wubben;Zoetermeer,2003.“Innovationandfirmperformance”.ResearchReportH200207译文：创新和企业绩效决定进行创新的影响因素：几项研究实证证实了企业创新的倾向。Felder等人(1996)成立曼海姆创新小组测试R＆D支出和其他创新的关系。该数据集包含一个含5至49人注册公司的样本合集。这为大力创新提出了尺寸，然而，一旦创新，占总销售额的比例投入的资金大公司比小公司大得多。Vossen和Nooteboom(1996)也证实了这一观点。效果最明显的是全面创新支出。企业规模和R＆D之间的关系似乎是U形的。Vossen和Nooteboom得出结论，小企业参与研发少，但一旦他们参与，力度更大，能提供更大的生产力（Vossen和Nooteboom，1996，167）。此外Kleinknecht（2000年）和Kleinknecht和Mohnen（2002）发现，创新的倾向与企业大小相关，虽然可能不是线性的，在创新力度方面，小企业往往有较高的创新产品的销售份额。Lööf等人(2001)把经合组织和独联体国家的数据用在他们的研究中。使用柯布道格拉斯生产函数，他们试图解释在北欧国家之间的生产率增长差异，使用标准的投入（劳动和资本）和创新的投入作为变量。使用Crépon，Duguet和Mairesse模型（1998年），他们得到以下四个方程式：（1）公司的繁荣决定创新;（2）创新投入（每个工人创新投资）;（3）创新输出（每个工人的创新销售记录）;（4）生产力（每员工销售）。生产量没有正式列入这个方程组。投资模型分两步应用：首先，决定研究必须采取，其次，在有条件从事研究时，必须做出投资金额的决定。创新的决定是一个概率模型。为了解释创新的倾向，Lööf等人（2001年）使用以下变量：企业规模（员工），出口的力度，专利申请之前，非研发工程师比例，行政人员和其他几个控制变量。企业规模和专利申请在所有三个国家较为显着。技术机会：要素密集度和行业特点也会影响到创新的决定（(Lööf等人2001）。在具有较高的技术潜力的行业，企业更倾向于创新。如果他们不创新，他们可能会失去自己的市场地位。总之，创新是决定一个企业的重大决策。一旦一个公司决定要积极创新，公司将会把拥有的资源集中到创新。这个决定是受到了公司的出口力度，事先研发程度和员工的特点（教育程度）的大小的影响的。该公司的影响力也决定了创新过程。创新力度：在有条件搞创新的企业，创新的力度，必须进行评估。必须对其有充分的理解，因为这影响了创新过程中的资源水平。这些资源的典型是财力和人力。文献为我们提供的几个创新力度的指标。传统上，目前仍为最常用的指标是研发的支出（Klomp和VanLeeuwe，1999年，Lööf等人，2001）。通常利用支出和销售额的比例来表示研发的强度。研发指标正在进一步发展成为另一个指标。本指标的主要优点是，它相对容易测量和收集。这一指标的广泛使用也提高了不同的研究之间的可比性。然而，他的一些缺陷也很明显（参见了Kleinknecht,2000的广泛审查）。首先，R＆D支出仅仅是对创新过程的输入，不是结果，或者效率。第二，研发相关投入的创新支出占到了25%-50%不等。第三，研发数据往往低估了服务创新。最后，研发问卷规模小，常常是非正式的小型研发的活动，可能带来复杂的问题。几个R＆D支出新的定义和改进措施已提出。首先，1992年奥斯陆的经合组织经过努力假定了有关（技术）支出新定义。它把R＆D支出补充到其他六个费用类别中，即产品/工业设计，试验，市场分析/引进，培训，专利和许可证，以及创新相关的固定资产投资（Felder等人，1996;Klomp，2001）。Vossen和Nooteboom(1996)声称，与企业规模和分配给创新的金额的关系是创新支出的最全面表现。这种创新的力度变量之前称为R＆D强度，指的R＆D支出占总销售规模（内部和外部）的比例。研发支出与创新是高度相关的。总的R＆D支出，也称为R＆D投资，包括内部研发，外部研发以及和大学与研究机构的合作研发（Klomp和VanLeeuwen,1999:12）。这三个方面在一起，分别形成了制造，购买或合作经营的创新投资管理决策方案。实证结果证明了这些不同的支出的重要性。在3000个德国工业企业中在3内部的研发样本比例略高于支出总额的百分之40（Felder等人1996）。对独联体国家的研究证实了这一观点：研究表明独联体企业内部研发比例至少占全面创新支出的50%（Klomp,2001）。服务的比例只有25%（(Kleinknecht,2000）。这一新的指标，缺点是非研发项目在问卷中的答复率较低，答案的准确性也较低，原因是许多公司不保留相关记录。另一种传统的指标是致力于研发的员工人数，这也很容易衡量，对于服务行业有更好的适用性。这个指标也有几个缺点，如部分重叠的R＆D支出（如无效率，总支出少数信息）。此外，它不包括创新投入的质量和致力于创新的时间。Mairesse和Mohnen（2001）指出反应创新的力度指标为总销售额中新产品的份额。它的优点是，考虑到创新轨迹的最终目标，即额外的营业额和利润的比例。但是，股权分析变量能更好地利用输出测量。以下将进一步讨论。在这项研究中，我们使用了专用的强度指标，即创新研发人员数目，该指标对提高员工花在创新的平均时间进行了纠正。这个变量也非常适合小型公司。创新强度经过研究审查的是影响创新的力度的因素。创新的力度通常被定义为，由公司总营业额在一公司员工人数被分入创新，致力于创新的支出总额。Lööf等人2001指出几个变量，作为解释创新倾向（企业规模（员工），出口力度，事先申请专利，非研发工程师比例，行政人员比例和几个控制变量）的变量，加上阻碍创新，创新信息，创新战略/创新目标和合作（国内