- P-ISSN2765-6934
- E-ISSN2765-7027
- KCI
ISSN : 2765-6934
Using the MCDM of the Innovative Product Value Chain to Promote New Product Design
Abstract
Purpose - In the past, designs for traditional products have usually focused on historic techniques. However, this tradition of using historic techniques has now been replaced by the trend of using the innovative design concept. Research design, data, and methodology - To measure future market trends and quality requirements, we apply the results of the questionnaires and analyze them with various experimental processes and a design methodology. In this way, we gauge the impact of the innovative product value chain on the promotion of new products. Results - Accompanied with an innovative product value chain, the product can stimulate the development of enterprise management, which has become the main issue in social and economic development in every developed country, and can facilitate the progress of enterprise management throughout the enterprise. Conclusions – Customer demand should be emphasized as the primary means to solve design problems, to design optimal solutions, to create differentiation with competitors, and to pursue optimal marketing strategies.
- keywords
- Multi Criteria Decision Making Theory (MCDM), Target decision system, Fuzzy theories, Gray system theories, Analytic network process (AHP)
Reference
Tseng, F. M., & Tzeng, G..H. (2002). A fuzzy seasonal ARIMA model for forecasting. Fuzzy Sets and Systems, 126(3), 367-376.
Carlos, R. (2004). A general structure of achievement function for a goal programming model. European Journal of Research, 153(2004), 675-686.
Hirotaka, N., Ye, B. Y., & Takeshi, A., Min, Y. (2005). MOP/GP models for machine learning. European Journal of Operational Research, 166, 756-768.
Yu, R., & Tzeng, G.. H. (2006). A soft computing method for multi-criteria decision making with dependence and feedback. Applied Mathematics and Computation, 180, 63–75.
Hu, Y.C., Chen, R.S., Tzeng, G.H., and Chiu, Y.J. (2003). Acquisition of Compound Skills and Learning Costs for Expanding Competence Sets. Management Review, 1(2), 257-273.
Tzeng, G..H., & Chiang, C.H., & Li, C.W. (2006). Evaluating intertwined effects in e-learning programs: A novel hybrid MCDM model based on factor analysis and dematel. European Journal of Operational Research, 173 (3), 1026-1046
Peter, I. S., Hongwei, H., Brian, W. D., & Douglas, E. A. (2003). Control and perception of balance at elevated and sloped surfaces. Zootaxa, 365, 1-20.
Marc, J.R., & Lao, W.N. (2001). E-Learning- Strategies for Delivering Knowledge in the Digital Age. Taiwan:McGraw-Hill Int, Enterprises Inc.
Wan, A.C., Tung, C. H. (2010). The impact of human resource capabilities on internal customer satisfaction and organisational effectiveness. Total Quality Management &Business Excellence, 6(21), 633-648.
Wang, C.H., Chin, Y.C., Tzeng, G.H. (2010). Mining the R&D innovation performance processes for high-tech firms based on rough set theory, Technovation, 30(7), 447-458.
- Downloaded
- Viewed
- 0KCI Citations
- 0WOS Citations