# Fuzzy Relationship between Kansei Images: A Grey Decision-Making Method for Product Form
## 5 Discussion  
A product form is a concrete manifestation of a variety of Kansei image styles, and the current research on the decision-making process often ignores the fuzzy relationship between multiple Kansei images. In addition, the existing weighting methods seldom consider the change in Kansei image weights caused by morphological differences. In this study, variable weight theory is introduced into the design decision-making process to adjust the Kansei image weights of different samples. And on the basis of the CGTDM for multiple Kansei images, the fuzzy relationship between Kansei images is explored from the perspective of the Kansei image. The model can help designers make more convenient decisions to meet market demands, improve the authenticity of design decision-making to a great extent, and provide new research ideas and methods for multiple Kansei image decision-making in product development. However, the method proposed in this study also has limitations, such as the minimal consideration of the absolutisation of cognitive information, the cognitive limitations of design participants, the comprehensive impact of product elements, the practicality validation of the new method, computational complexity and decision-making speed, and the precision of the decision-making model. The specifics are as follows:  
1. The absolutisation of cognitive information: Human cognition is characterised by fuzziness and complexity due to different factors, such as educational level and living environment. In this study, the SD method is used to obtain the user's cognitive information about the sample form, which tends to result in absolute data. 2. The cognitive limitations of design participants: In actual product development, designers, engineers, and salespeople will participate in addition to users. This study focuses only on user cognition and does not consider the Kansei image cognition of other design participants. 3. The comprehensive impact of product elements: Form, colour, technology, and brand are all important elements of products, and the Kansei image characteristics of products can be reflected only by the integration of various elements. This study takes only the product form as the starting point to construct the grey decision-making model, which weakens the comprehensive impact of various elements on human cognition. 4. The practicality validation of the new method: The new method needs to be tested repeatedly with a large number of examples to verify its practicability. The method proposed in this study is a combination of variable weight theory and the CGTDM for multiple Kansei images, and only a hand-held electric drill is taken as an example; its practicability needs to be further verified. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Difference** & **The Method in** & **CGTDM for Multiple** & **Decision-Making Model** \\
**Coefficient** & **This Paper** & **Kansei Images** & **Based on TOPSIS** \\ \hline \(Cv\) & 0.5627 & 0.4957 & 0.3613 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Comparison of the difference coefficients of the three decision-making models. (5) Computational complexity and decision-making speed: Variable weight theory aims to adjust the constant weight in different states, so that it can better meet the needs of indicators. However, this theory increases the amount of calculation of Kansei image weights to a certain extent, which may reduce the decision-making speed of the grey decision-making model for product form driven by the fuzzy relationship between the Kansei images. (6) The precision of the decision-making model: The decision-making model should have high accuracy to better simulate the decision-making thinking of designers, and intelligent design needs to be combined with a highly accurate decision-making model to select the product scheme that meets the market demand. This study did not deeply explore the accuracy of the model.