An integrated consensus reaching process for product appearance design decision-making: Combining trust and empathy relationships
Year: 2025
Type: article
Abstract: Product design decision-making (PDDM) is a crucial process in new product development (NPD), where achieving consensus among decision-makers (DMs) is essential for optimal outcomes. Within this broader context, product appearance design decision-making (PADDM) plays a particularly important role, as visual appeal, aesthetics, and user perception often significantly influence market success. Traditional consensus reaching processes (CRPs) in PADDM often depend on a single type of social relationship, resulting in the loss of information dimensions and biased decision outcomes. Our method overcomes these limitations by leveraging the complementary strengths of trust and empathy to enhance the robustness and adaptability of the PADDM process. The intuitionistic fuzzy sets (IFSs) are used to depict DMs’ assessments and their mutual trust, while a Likert-7 scale is employed to evaluate the degree of empathy among DMs. Through trust propagation, a complete trust relationship is established, and by integrating the empathy relationship, a composite trust-empathy matrix is formulated. This matrix helps determine DMs’ weights and facilitates the implementation of the CRP in PADDM. An illustrative case study on vibratory rolling mill design selection is presented to illustrate the effectiveness and feasibility of the proposed method. Our findings indicate that integrating empathy and trust relationships can effectively address cases where direct or indirect trust paths are missing and stabilize the PADDM process when empathy is weak. This dual-integration approach ensures a more holistic understanding of DM interactions, leading to improved decision quality and reliability in product appearance design scenarios.
Source: Advanced Engineering Informatics
Authors: Yanpu Yang, Jialing Liu, Wenhao Meng, Yueming Zhuo, Zhihong Wu
Institution: Chang'an University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,560
Awards: G6631975271, G7330935341
OpenAlex ID: W4411434580
