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Nonlinear influence on R&D project performance

Author

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  • Chen, Yu-Shan
  • Chang, Ke-Chiun
  • Chang, Ching-Hsun

Abstract

This study applies artificial neural network (ANN) to explore the relationships between the performance of R&D projects and its determinants. The results indicate that the quality of project environment has an inverse U-shaped effect on the performance of R&D projects, and both project managers' skills and the effectiveness of teamwork have monotonic positive influences on it. Besides, this study utilizes self-organizing map (SOM) to classify the Taiwanese information and electronics companies into three groups and further provides some suggestions. In addition, this paper uses an in-depth interview of qualitative research to explore why the quality of project environment has an inverse U-shaped effect on the R&D project performance, and finds out the main reason. There are two managerial implications in this study. First, the relationships between the performance of R&D projects and its determinants are not always linear in the complex and uncertain environment nowadays. Second, companies must care about the inverse U-shaped effect of the quality of project environment on the performance of R&D projects, although they can enhance the extent of project managers' skills and the effectiveness of their teamwork as much as possible.

Suggested Citation

  • Chen, Yu-Shan & Chang, Ke-Chiun & Chang, Ching-Hsun, 2012. "Nonlinear influence on R&D project performance," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1537-1547.
    • Handle: RePEc:eee:tefoso:v:79:y:2012:i:8:p:1537-1547
    DOI: 10.1016/j.techfore.2012.04.007
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    Cited by:

    1. María Jesús Rodríguez-Gulías & David Rodeiro-Pazos & Sara Fernández-López & Manuel Ángel Nogueira-Moreiras, 2021. "The effect of regional resources on innovation: a firm-centered approach," The Journal of Technology Transfer, Springer, vol. 46(3), pages 760-791, June.
    2. Rodríguez-Gulías, María Jesús & Fernández-López, Sara & Rodeiro-Pazos, David, 2024. "Foreign knowledge sources and innovation: Differences across large and small and medium-size multinational enterprises (MNEs)," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 741-757.
    3. Lee, Changyong & Kwon, Ohjin & Kim, Myeongjung & Kwon, Daeil, 2018. "Early identification of emerging technologies: A machine learning approach using multiple patent indicators," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 291-303.

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