Empirical Study Of R&D Inputs And Corporate Performance Based On The100Top Electronics&Information Enterprises In China

As one of the main source of technological innovation&D activities is the key factorto guide technological innovation and promote scientific and technological progress,and then have a major impact on industrial competitiveness. The ICT industry R&Defficiency is affecting not only their own development, but also other traditionalindustries by the correlation effects, and plays an important role in the upgrading andadjustment of industrial structure. Therefore it is necessary to comprehensively studythe association between the R&D input and corporate performance output, and toevaluate the output efficiency, and identify the efficiency of the influencing factorsand the specific impact of the mechanism and manner.Selecting the top100electronic information enterprises as the empirical researchsample of the ICT sector’s R&D Input and Corporate Performance has a very goodrepresentation. These regard few and gain contradictions conclusion in the past. Forthat based on panel data of the ranking of top100electronic information enterprisesfor five consecutive years from2004to2008, firstly an overview of the generalcharacteristics of the relationship between corporate R&D inputs and profits and thecapacity of development and profit is given, secondly measurement (panel) analysis isused for intensity indicators of R&D inputs and performance outputs, and then thestochastic frontier production function model analysis is used for the absolute numberof indicators of R&D inputs and performance outputs, and finally by DEA analysiscombined with the Malmquist TFP index to measure R&D inputs and performanceoutputs, we can deal with the absolute number of indicators to reflect the efficiency(or productivity) and efficiency of dynamic characteristics, and analyze theinfluencing factors and manner to efficiency.Statistical analysis shows that firm size differences affect inputs in R&D. The firmswhich own R&D investment highest intensity have most profitable capacity and thesample enterprises whose intensity are ranging from1%to5%have most developingcapacity. The sample enterprises whose R&D staff intensity between10%to30%have most profitable capacity and group whose R&D staff intensity are higher than30%have the strongest developing capacity. The econometric analysis shows that between the scales of operation and operatingmargin there is a negative correlation. Between R&D investment intensity and R&D staff intensity and sales profit rate there is no linear relationship from2004to2007and a positive correlation in2008. The corresponding lagging effects of R&Dinvestment intensity and R&D staff intensity to sales profit rate are negative andnot.Stochastic frontier analysis shows that between R&D investment and R&Dinformation input and performance output there is no linear relationship. R&D staffinput can bring about positive impact on firms performance output. The deviationmainly due to technical invalid.DEA static and dynamic analysis shows that:(1) The Bohai Sea region, has highertechnical efficiency and higher scale efficiency value, maintaining the average annualproductivity growth rate of nearly10%. The Yangtze River Delta region has mediumtechnical efficiency and the highest technical allocative efficiency, maintaining theaverage annual productivity growth rate of nearly1%. Having higher technicalefficiency, but the Pearl River Delta region appears diseconomies of scale andproductivity recession.(2) Mechanical equipment, instrumentation, electronicsmanufacturing, information technology and scale efficiency in turn increase, whichimpact on productivity, growth in turn increases the correspondingproductivity.(3)Small-scale enterprises have higher rate of technological progress andlarge-scale enterprises have higher technical efficiency and higher scale efficiencyvalue, and then the latter have a great advantage aspects of the purely technicalallocativing efficiency and their innovation are more efficient.Efficiency factors, including firm size, regional industrial structure and local policyare the key external environment variable to affect sample corporeity’s R&Dperformance.