Abstract
In this paper, the author uses an evaluative criteria model and their associated criteria status, product evaluative criteria software of results and product objective function of optimal values solution, along with product morphological analysis, to synthesize evaluative criteria and optimize product design values. This study focuses on how to use an evaluative criteria model’s imprecise market information by evaluative criteria design software; product mapping relationships between design parameters and customer requirements using product predicted value method; synthesizing design alternative by morphological analysis and plan; realizing the synthesis in multi criterion decision making (MCDM), using its searching software capacity to obtain the optimal solution.
Keywords. Multi criterion decision making (MCDM), Evaluative criteria model, Digital product design, Fuzzy theory, Products design.
JEL. F31, F47, L83, L88.References
Cocuhman, P. K., McLoughlin, I., & Charles, D. (2008). Lost in translation? Building science and innovation city strategies in Australia and the UK, Innovation Managemen Policy and Practice, 10(3), 211–223.
Howard, J. (2007). Csiro: Partnering for the future, Innovation Management Policy and Practice, 9(2), 146–158.
Huang. J., Tzeng. G., & Ong, C. (2006). Optimal fuzzy multi-criteria expansion of competence sets using multi-objectives evolutionary algorithms, Expert Systems with Application, 30(2), 739-745. doi: 10.1016/j.eswa.2005.07.033
Hüsing, S., & Mann, H. G. (2010). The role of promoters in effecting innovation in higher education institutions, Innovation Managemen Policy and Practice, 12(2), 180-191. doi: 10.5172/impp.12.2.180
Kennedy, N. (2007). CSIRO and Australian innovation: a business commentary, Innovation Managemen Policy and Practice, 9(2), 203-214. doi: 10.5172/impp.2007.9.2.203
Lee, S., & Kim, M. (2010). Inter-technology networks to support innovation strategy: An analysis of Korea’s new growth engines, Innovation Management Policy and Practice, 12(1), 88–104. doi: 10.5172/impp.12.1.88
Lin, C., Hsieh, M., & Tzeng, G. (2010). Evaluating vehicle telematics system by using a novel MCDM techniques with dependence and feedback, Expert Systems with Applications, 37(10), 6723-6736. doi: 10.1016/j.eswa.2010.01.014
Mercure, J. L. (2008). Innovation and the food industry volume, Innovation Management Policy and Practice, 10(1), 2-3. doi: 10.5172/impp.453.10.1.2
Rogers, E. (1995). Diffusions of innovations, The Free Press, New York.
Tzeng, G., Chiang, C., & Li, C. (2007). Evaluating intertwined effects in e-learning programs: A novel hybrid MCDM model based on factor analysis and DEMATEL, Expert systems with Applications, 32(4), 1028-1044. doi: 10.1016/j.eswa.2006.02.004
Wolfe, D., A., & Bramwell, A. (2008). Innovation, creativity and governance: Social dynamics of economic performance in city-regions, Innovation Managemen Policy and Practice, 10(2), 170-182.
