Evidence map›Paper›PMID 41213995›Full record

ArticleScientific reports2025

Using entropy weight method and quality function deployment to develop emotion-driven dashboard interfaces for NEV.

Xinwei Guan, Lin Li, Jinchi Fu, Dengkai Chen, Suihuai Yu

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xinwei GuanKey laboratory of Ministry of Industrial Design and Ergonomics, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi'an, 710072, China.
Lin LiShanghai Academy of Fine Arts, Shanghai University, Shanghai, 200444, China.
Jinchi FuKey laboratory of Ministry of Industrial Design and Ergonomics, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi'an, 710072, China.
Dengkai ChenKey laboratory of Ministry of Industrial Design and Ergonomics, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi'an, 710072, China. chendengkai@nwpu.edu.cn.
Suihuai YuKey laboratory of Ministry of Industrial Design and Ergonomics, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi'an, 710072, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

New energy vehicles (NEVs) demand dashboard interfaces that not only present critical driving information but also evoke positive user emotions to enhance satisfaction and safety. This study develops a structured framework that integrates the Entropy Weight Method (EWM) and Quality Function Deployment (QFD) to embed emotion-driven requirements into NEV dashboard design. 56 Kansei words were collected through an online survey (n = 300) and prioritized to 15 through experts interviews. An anonymous online questionnaire (n = 101, 98 valid responses) collected adult drivers' emotional perceptions across 15 descriptive adjectives. Exploratory factor analysis distilled these descriptors into four principal dimensions: Pleasant, Technological, Stylish, and Minimalist. Entropy weight calculation quantified the relative importance of each dimension, revealing Pleasantness as the highest-priority factor. The QFD process then translated these weighted emotional dimensions into specific design attributes, including optimal color contrast ratios, iconography style guidelines, typography choices, and interface layout coherence. Prototype dashboards developed according to this schema were evaluated in a pilot study, demonstrating strong congruence between user-prioritized emotions and perceived design quality. This framework offers a replicable, data-driven method for systematically aligning emotional user needs with interface design parameters in NEVs, thereby providing actionable guidance for designers aiming to improve user experience through emotion-driven dashboard development.

Indexed as

Dashboard interface designEmotion-driven designEntropy weight method (EWM)Kansei engineeringNew energy vehicles (NEVs)Quality function deployment (QFD)

Identifiers

PMID41213995
PMCPMC12603269

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.