A multi-subgroup decision-making method for design selection based on subjective reports and objective physiological index data

Selecting an optimal product design scheme requires considering multiple criteria and engaging the wisdom of crowds. However, existing studies regarding design selection rarely considered the participation of group wisdom, and few studies considered subjective reports and physiological index data comprehensively for evaluation. This study developed a multi-subgroup decision-making method based on the participation of designers, experts, and customers. Multi-modal aggregation strategies are applied to aggregate subjective evaluations of both individuals and groups represented in probabilistic linguistic term sets (PLTSs), objective eye movement, and Electroencephalogram feature data. Specifically, a probabilistic linguistic information aggregation operator based on the Choquet integral is proposed to aggregate the values of subjective criteria with correlations, and the double normalization-based multi-aggregation method is then applied to aggregate objective criteria values, which can avoid information loss in the normalization and aggregation. Finally, the Choquet integral -based Borda operator is developed to integrate the evaluation results of multiple subgroups. An example of evaluating intelligent shared vehicle design schemes is presented to validate the proposed method. & COPY; 2023 Elsevier B.V. All rights reserved.

Automated summary

This study develops a multi-subgroup decision-making method that incorporates the participation of designers, experts, and customers. It applies multi-modal aggregation strategies to combine subjective evaluations, eye movement, and Electroencephalogram feature data. The proposed method uses Choquet integral-based operators to aggregate subjective and objective criteria values and integrates the evaluation results from multiple subgroups.