Volume 1, Issue 1, January 2008, Pages 24 - 49
Assessment of Strategic R&D Projects for Car Manufacturers Based on the Evidential Reasoning Approach
- Xin-Bao Liu, Mi Zhou, Jian-Bo Yang, Shan-Lin Yang
- Corresponding Author
- Xin-Bao Liu
Available Online 10 February 2008.
- https://doi.org/10.2991/ijcis.2008.1.1.3How to use a DOI?
- Assessment of strategic R&D projects is in essence a multiple-attribute decision analysis (MADA) prob- lem. In such problems, qualitative information with subjective judgments of ambiguity is often provided by people together with quantitative data that may be imprecise or incomplete. A few approaches can be used to deal with such quantitative and qualitative MADA problems under uncertainty, such as the evidential reasoning (ER) approach that has its own unique features. In this paper, the ER approach is applied to the assessment of strategic R&D projects for a car manufacturer, which is characterized by many qualitative factors that may be imprecise or fuzzy. The ER approach is well-suited for dealing with such problems and can generate comprehensive distributed assessments for different projects. The group analytic hierarchy process (GAHP) method is applied to calculate the weights of attributes in the E-R assessment process, where a group of people from the company were involved. We also provide a new algorithm for the comparison of two alternatives under utility interval. Our research that has been undertaken for the car manufacturer has contributed to the improvement of the quality and efficiency of its strategic R&D projects. The research has also helped the personnel of the company better understand the benefits of using scientific methods for systematic project assessment.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Xin-Bao Liu AU - Mi Zhou AU - Jian-Bo Yang AU - Shan-Lin Yang PY - 2008 DA - 2008/02 TI - Assessment of Strategic R&D Projects for Car Manufacturers Based on the Evidential Reasoning Approach JO - International Journal of Computational Intelligence Systems SP - 24 EP - 49 VL - 1 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.2008.1.1.3 DO - https://doi.org/10.2991/ijcis.2008.1.1.3 ID - Liu2008 ER -