A multi-stage approach for design concept evaluation based on complex network and bounded confidence to achieve consensus

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Abstract

Purpose: A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the interaction among evaluators and improve the credibility of evaluation results. Design/methodology/approach: This paper proposes a multi-stage approach for design concept evaluation based on complex network and bounded confidence. First, a network is constructed according to the evaluation data. Depending on the consensus degree of evaluation opinions, the number of evaluation rounds is determined. Then, bounded confidence rules are applied for the modification of preference information. Last, a planning function is constructed to calculate the weight of each stage and aggregate information at multiple evaluation stages. Findings: The results indicate that the opinions of the evaluators tend to be consistent after multiple stages of interactive adjustment, and the ordering of design concept alternatives tends to be stable with the progress of the evaluation. Research limitations/implications: Updating preferences according to the bounded confidence rules, only the opinions within the trust threshold are considered. The attribute information of the node itself is inadequately considered. Originality/value: This method addresses the need for considering the evaluation information at each stage and minimizes the impact of disagreements within the evaluation group on the evaluation results.

Original languageEnglish
Pages (from-to)4074-4099
Number of pages26
JournalKybernetes
Volume53
Issue number11
DOIs
StatePublished - 12 Nov 2024

Keywords

  • Bounded confidence
  • Complex networks
  • Consensus reaching
  • Design concept evaluation (DCE)
  • Preference

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