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A fuzzy group decision making approach to new product concept screening at the fuzzy front end

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  • Hong-Bin Yan
  • Tieju Ma

Abstract

Efficient new product concept screening plays an important role in new product development (NPD). Due to the inherent complexity, incompleteness and ambiguity in NPD, fuzzy approaches have been widely developed and used for new product concept screening. Because of the group behaviours (diversity of gate-team members and senior management’s preference), the new product concept screening is typical group decision-making problem. Moreover, it is usually more efficient to conduct the screening evaluation in a gate-team and make a screening decision outside the gate-team by senior management. Therefore, it is necessary to provide a result with a high degree of flexibility and credibility so as to better support the senior management to make a screening decision in NPD. Existing fuzzy approaches neglect these two issues. Towards this end, a three-stage fuzzy group decision-making approach is proposed to assist the senior management perform new product concept screening. A case study is borrowed from the literature to illustrate our proposed approach. Our approach is compared with two existing techniques from theoretical and empirical perspectives. The results show that the proposed approach can capture the group behaviours and present a relatively realistic and informative result which gives the senior management a high degree of flexibility and credibility in new product concept screening.

Suggested Citation

  • Hong-Bin Yan & Tieju Ma, 2015. "A fuzzy group decision making approach to new product concept screening at the fuzzy front end," International Journal of Production Research, Taylor & Francis Journals, vol. 53(13), pages 4021-4049, July.
  • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:4021-4049
    DOI: 10.1080/00207543.2014.986297
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    Cited by:

    1. Yan, Hong-Bin & Ma, Tieju & Huynh, Van-Nam, 2017. "On qualitative multi-attribute group decision making and its consensus measure: A probability based perspective," Omega, Elsevier, vol. 70(C), pages 94-117.

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