Multi-criteria evaluation of smart product-service design concept under hesitant fuzzy linguistic environment: A novel cloud envelopment analysis approach

Design concept evaluation is an essential but challenging task in smart product service system (SPSS) design. It is critical to select the design concept with better smart experience to ensure the success of SPSS design. Meanwhile, SPSS design concept evaluation is an expert knowledge-based decision process with scant data and a short time window under a hesitant, ambiguous, and subjective environment, which would lead to low decision-making efficiency and inaccurate evaluation results. Hence, this paper proposes a novel cloud envelopment analysis method to evaluate SPSS design concept with respect to smart experience criteria. The proposed method integrates hesitant fuzzy linguistic terms (HFLTs), cloud model and data envelopment analysis (DEA) method to accurately evaluate SPSS design concepts with handling the hesitancy, fuzziness and randomness in qualitative and subjective information. A hybrid model of normal cloud and trapezium cloud is used to quantify hybrid-length HFLT variables to avoid decision information loss and distortion. A novel cloud non-linear programming model is constructed to extend the classical DEA into cloud environment. Finally, a case study and some comparison analyses illustrate the effectiveness and advantages of proposed method.