Chapter 10: Supply Networks

Title: Development of benchmark-based hybrid evaluation methodology for design chain partners

Author(s): Chih-ling Chuang, Tzu-an Chiang, Z.H. Che, H.S. Wang

Address: Department of Industrial Engineering & Management, National Taipei University of Technology, Taipei (106), Taiwan and Department of Commerce Automation & Management, National Pingtung Institute of Commerce, Pingtung (900), Taiwan | Department of Industrial Engineering & Management, National Taipei University of Technology, Taipei (106), Taiwan and Department of Commerce Automation & Management, National Pingtung Institute of Commerce, Pingtung (900), Taiwan | Department of Industrial Engineering & Management, National Taipei University of Technology, Taipei (106), Taiwan and Department of Commerce Automation & Management, National Pingtung Institute of Commerce, Pingtung (900), Taiwan | Department of Industrial Engineering & Management, National Taipei University of Technology, Taipei (106), Taiwan and Department of Commerce Automation & Management, National Pingtung Institute of Commerce, Pingtung (900), Taiwan

Reference: International Conference on Product Lifecycle Management 2009 pp. 473 - 484

Abstract/Summary: Design chain partner evaluation is a crucial factor to the success of new product development. With the gradual shortening of life cycles, and increases of product complexity, companies must develop new products in combination with core technologies of partners within a short period. To assist companies searching for optimum design chain partners, this research established a design chain partner evaluation hierarchy structure, and developed a benchmark-based hybrid evaluation methodology for design chain partners. Firstly, data envelopment analysis (DEA) is employed to establish a preliminary evaluation model of design chain partners and identify an efficient design chain partners. By combining the technique for order preference by similarity to ideal solution (TOPSIS) and analytic hierarchy process (AHP), this research establishes priority ranking of design chain partners to determine the optimum partner combination. Moreover, for partners without efficiencies, this research uses slack variables analysis to provide concrete suggestions for improvement.

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