Nonlinear influence on R&D project performance

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

Technological Forecasting and Social Change, 2012, vol. 79, issue 8, 1537-1547

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.

Keywords: Nonlinear nature of management; Project performance; Quality of project environment; Project managers' skills; Effectiveness of teamwork (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162512000820
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:79:y:2012:i:8:p:1537-1547

DOI: 10.1016/j.techfore.2012.04.007

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().