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    題名: Giving Fish or Teaching to Fish? An Empirical Study of the Effects of Government R&D Policies
    作者: 黃國峯
    Xu, K.;Huang, K.F.;Xu, E.
    貢獻者: 企管系
    日期: 2014.11
    上傳時間: 2014-11-14 18:17:44 (UTC+8)
    摘要: This study compares how government research and development (R&D) subsidy and knowledge transfer from universities and public research institutions stimulate a firm's new product development. More importantly, we emphasize that the effects of these governmental R&D policies on new product development can be achieved not only directly, but also via a mediating role – a firm's innovation capability. Furthermore, we test how other external knowledge sources (such as knowledge from universities and public research institutions) interact with government R&D support to stimulate new product development. The results, based on an investigation of 270 Chinese firms, suggest that both government R&D subsidy and knowledge transfer from universities and public research institutions enhance new product development. The results also show that although government R&D subsidy and knowledge transfer from universities and public research institutions has a direct impact on new product development, innovation capability does mediate the above relationships. Moreover, unlike the findings that other external knowledge sources have a direct influence on new product development as indicated by the previous literature, our findings suggest that external knowledge sources substitute with the government R&D subsidies and complement with knowledge transfer from universities and public research institutions. The results confirm the old sayings that teaching to fish (knowledge transfer from universities and public research institutions can complement with other external knowledge sources) is much better than giving fish (government R&D subsidies substitute other external knowledge sources). This paper enriches current literature of government R&D support policies to firm new product development by providing empirical evidences.
    關聯: R&D Management, 44(5), 484-497
    資料類型: article
    DOI 連結: http://dx.doi.org/10.1111/radm.12087
    DOI: 10.1111/radm.12087
    顯示於類別:[統計學系] 期刊論文

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