A Crowd-Intelligence-Driven, Multi-Attribute Decision-Making Approach for Product Form Design in the Cloud Environment

In the traditional decision-making process for product form design, designers and experts often prioritize schemes based on their own knowledge and experience. This approach can lead to an oversight of user preferences, ultimately affecting decision outcomes. In contrast, crowd-intelligence-driven, multi-attribute decision-making for product form design in the cloud environment builds upon traditional approaches by leveraging the vast and diverse expertise of individuals on cloud platforms, engaging participants from various fields and roles in the decision-making process to enhance comprehensiveness and accuracy. To address the issue of a single decision-maker and limited user participation in the decision-making process for product form design schemes in the cloud environment, a multi-attribute decision-making method integrating expert knowledge and user preferences is proposed. This method aims to select a product form design scheme that optimally balances expert and user satisfaction. Initially, the Pythagorean Hesitant Fuzzy Set (PHFS) is used to quantify qualitative product attributes and to establish a comprehensive multi-attribute evaluation system. In the aspect of expert decision-making, a gray correlation coefficient decision matrix based on expert knowledge is established and the overall score of the base alternative is calculated by the ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method and the Improved Osculating Value method. In terms of user decision-making, weights are determined by calculating the similarity between user evaluation matrices, and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to calculate scores for product form designs based on user preferences. Ultimately, optimal selection is achieved by aggregating the aforementioned expert evaluation values and user preference values. The method’s effectiveness and feasibility are confirmed through a case study of coffee machine product form design schemes.