Matches in SemOpenAlex for { <https://semopenalex.org/work/W2897712047> ?p ?o ?g. }
- W2897712047 endingPage "25" @default.
- W2897712047 startingPage "2" @default.
- W2897712047 abstract "Purpose This paper aims to examine the different impacts of six variables on firm technological innovation performance in different high-tech industries in China. Through a comparative analysis of data about growth enterprises market board (GEM)-listed companies, this study attempts to get some conclusions, to help firms in different high-tech industries use resources more rationally and to improve technological innovation performance more effectively. Design/methodology/approach This paper constructs semi-parametric models based on the relevant data of GEM-listed companies during 2010 to 2015 for different high-tech industries. These models can ensure that the influencing factors of firm technological innovation performance are no longer restricted to a particular aspect but can provide a comprehensive comparative analysis of the effects of factors on firm technological innovation performance in different high-tech industries. Findings The empirical results show that R&D expenditures have a significant positive impact on firm technological innovation performance in most high-tech industries, but not in electronic and communication equipment manufacturing industry; R&D personnel investment and government subsidies have significant positive impacts on firm technological innovation performance in knowledge-oriented industries; technology diversity has a significant positive impact on firm technological innovation performance in technology-oriented industries; the proportion of exports shows an inverted U-shaped relationship with firm technological innovation performance in electronic and communication equipment manufacturing industry, while firm size shows an inverted U-shaped relationship with firm technological innovation performance in general equipment manufacturing industry; and the effect of semi-parametric model fit is superior to the general parameters model. Originality/value Drawing on the resource dependence perspective, this paper is the first to consider a comprehensive treatment of differential effects of internal resources (R&D personnel, R&D expenditure), external resources (government subsides) and firm characteristics (firm size, export ratio) on firm technological innovation performance in different high-tech industries in an emerging country, in particular in contrast to previous studies that have focused on a single industry or taken the type of industry as a control variable. In addition, most studies about the determinants of firm innovation performance are based on survey questionnaires, which may introduce large subjective errors. Setting the relationship between variables in advance may also introduce fit error when using a general-parameter model. Semi-parametric regression which is used in this paper is able to prevent this shortcoming effectively. When constructing a regression model, this can be exempted from the formal constraints, thus estimating data more accurately and ensuring superior fit." @default.
- W2897712047 created "2018-10-26" @default.
- W2897712047 creator A5012368185 @default.
- W2897712047 creator A5017917541 @default.
- W2897712047 creator A5031653957 @default.
- W2897712047 date "2019-04-01" @default.
- W2897712047 modified "2023-09-23" @default.
- W2897712047 title "A comparative study of the effects of different factors on firm technological innovation performance in different high-tech industries" @default.
- W2897712047 cites W1574732353 @default.
- W2897712047 cites W1590350024 @default.
- W2897712047 cites W1917490756 @default.
- W2897712047 cites W1971782430 @default.
- W2897712047 cites W1990360714 @default.
- W2897712047 cites W1990694252 @default.
- W2897712047 cites W1992598870 @default.
- W2897712047 cites W2001696637 @default.
- W2897712047 cites W2001956398 @default.
- W2897712047 cites W2004195467 @default.
- W2897712047 cites W2025757679 @default.
- W2897712047 cites W2034990006 @default.
- W2897712047 cites W2048250722 @default.
- W2897712047 cites W2050705076 @default.
- W2897712047 cites W2056851805 @default.
- W2897712047 cites W2057027993 @default.
- W2897712047 cites W2073739411 @default.
- W2897712047 cites W2083937691 @default.
- W2897712047 cites W2092200968 @default.
- W2897712047 cites W2094948292 @default.
- W2897712047 cites W2095149004 @default.
- W2897712047 cites W2108783505 @default.
- W2897712047 cites W2118917768 @default.
- W2897712047 cites W2121125513 @default.
- W2897712047 cites W2130582315 @default.
- W2897712047 cites W2133067791 @default.
- W2897712047 cites W2135344246 @default.
- W2897712047 cites W2148109447 @default.
- W2897712047 cites W2152112386 @default.
- W2897712047 cites W2165690106 @default.
- W2897712047 cites W2276106622 @default.
- W2897712047 cites W2511209221 @default.
- W2897712047 cites W2527177845 @default.
- W2897712047 cites W2601562046 @default.
- W2897712047 cites W2625989575 @default.
- W2897712047 cites W2735115046 @default.
- W2897712047 cites W3122121511 @default.
- W2897712047 cites W3123766169 @default.
- W2897712047 cites W3124536214 @default.
- W2897712047 cites W3125710220 @default.
- W2897712047 cites W3125765819 @default.
- W2897712047 doi "https://doi.org/10.1108/cms-10-2017-0287" @default.
- W2897712047 hasPublicationYear "2019" @default.
- W2897712047 type Work @default.
- W2897712047 sameAs 2897712047 @default.
- W2897712047 citedByCount "17" @default.
- W2897712047 countsByYear W28977120472019 @default.
- W2897712047 countsByYear W28977120472020 @default.
- W2897712047 countsByYear W28977120472021 @default.
- W2897712047 countsByYear W28977120472022 @default.
- W2897712047 countsByYear W28977120472023 @default.
- W2897712047 crossrefType "journal-article" @default.
- W2897712047 hasAuthorship W2897712047A5012368185 @default.
- W2897712047 hasAuthorship W2897712047A5017917541 @default.
- W2897712047 hasAuthorship W2897712047A5031653957 @default.
- W2897712047 hasConcept C137996800 @default.
- W2897712047 hasConcept C138885662 @default.
- W2897712047 hasConcept C139719470 @default.
- W2897712047 hasConcept C144133560 @default.
- W2897712047 hasConcept C162324750 @default.
- W2897712047 hasConcept C162853370 @default.
- W2897712047 hasConcept C175700187 @default.
- W2897712047 hasConcept C17744445 @default.
- W2897712047 hasConcept C191920346 @default.
- W2897712047 hasConcept C199539241 @default.
- W2897712047 hasConcept C206034944 @default.
- W2897712047 hasConcept C27548731 @default.
- W2897712047 hasConcept C2778137410 @default.
- W2897712047 hasConcept C40700 @default.
- W2897712047 hasConcept C41008148 @default.
- W2897712047 hasConcept C41895202 @default.
- W2897712047 hasConcept C54750564 @default.
- W2897712047 hasConcept C76155785 @default.
- W2897712047 hasConcept C94625758 @default.
- W2897712047 hasConceptScore W2897712047C137996800 @default.
- W2897712047 hasConceptScore W2897712047C138885662 @default.
- W2897712047 hasConceptScore W2897712047C139719470 @default.
- W2897712047 hasConceptScore W2897712047C144133560 @default.
- W2897712047 hasConceptScore W2897712047C162324750 @default.
- W2897712047 hasConceptScore W2897712047C162853370 @default.
- W2897712047 hasConceptScore W2897712047C175700187 @default.
- W2897712047 hasConceptScore W2897712047C17744445 @default.
- W2897712047 hasConceptScore W2897712047C191920346 @default.
- W2897712047 hasConceptScore W2897712047C199539241 @default.
- W2897712047 hasConceptScore W2897712047C206034944 @default.
- W2897712047 hasConceptScore W2897712047C27548731 @default.
- W2897712047 hasConceptScore W2897712047C2778137410 @default.
- W2897712047 hasConceptScore W2897712047C40700 @default.
- W2897712047 hasConceptScore W2897712047C41008148 @default.
- W2897712047 hasConceptScore W2897712047C41895202 @default.