Brand visual identity is a critical component of brand image and impacts consumers' brand perception and attitude. Although scholars and practitioners have increasingly researched brand visual identity, most focus on brand communication and corporate management perspectives, necessitating a systematic review of consumer attitudes based on brand visual identity elements. This study aims to review the impact of brand visual identity on consumer attitudes and provide directions for future research. We conducted a systematic search using PRISMA guidelines, reviewed relevant articles published in four databases (Web of Sciences, ProQuest, Scopus, and Elsevier) in the past two decades (2004-2024), and obtained 559 articles in May 2024. We conducted a thorough peer-review of both theoretical and empirical journal articles, followed by a scoping review. Thirty-four studies were eligible, analysing consumers' perceptions of various core elements of brand visual identity (BVI) (such as brand logo, colour, name, typography, and font), as well as the impact of brand visual identity on consumer attitudes and the practical implications of brand management. The results show that the consumption of visual identification elements affects consumers' perceived brand quality, brand personality, brand satisfaction, loyalty, favourability, and so on., as well as purchase intentions and social attitudes. In summary, the findings indicate that brand visual identity elements impact consumer perceptions and attitudes. However, despite some progress, further research is necessary to arrive at more definitive and robust conclusions.

INPLASY202450048 Effects of brand visual identity on consumer attitude ：A Systematic Literature Review Keywords: Brand visual identity; visual identity elements; consumer perception; consumer attit…

This study proposes a theoretical architecture model of an AI-driven in-vehicle interactive system, optimizing and adjusting key aspects such as target group selection, driving stages, consumer needs, interaction modes, and interface design through detailed demonstration. It emphasizes the personalization factor and proposes a model more aligned with the user's personalized needs by subdividing the driving stages and analyzing consumer needs. In terms of interaction modes, attention is paid to the integration of clicks, voice control, gestures, sliding, and other interaction methods to improve the flexibility of the user's operating experience. In terms of interface design, through elements such as colour, icons, typography, and fonts, combined with the automatic optimization of AI, personalized design is achieved to adapt better to the user's driving situation and preferences. Overall, this model aims to improve in-vehicle interactive systems' performance and user experience and provide a valuable reference for the future intelligent driving field. The study also profoundly explores the application of AI in the personalized design of vehicle interactive interfaces through a literature review and empirical cases, providing critical insights into achieving personalization and intelligence for future vehicle interaction design.

With the rapid development of social modernization and informatization, students' information technology skills are improving, leading to higher demands on schools for digital teaching capabilities. To meet these needs, application-oriented undergraduate colleges are increasingly adopting a blended teaching model that combines "online + offline" methods with "intelligent education platforms + traditional education." However, despite significant investment in Cloud Class and the course "New Media Operation and Management," student usage remains low. This study explores factors affecting students' adoption of Cloud Class by constructing a theoretical model based on the Technology Acceptance Model (TAM) and Information Adoption Model (IAM). The findings reveal that Perceived usefulness and Perceived ease of use positively impact Information adoption behavior, with Perceived ease of use also enhancing Perceived usefulness. While Information accuracy positively influences Perceived usefulness, Information completeness, currency, and format do not. Perceived usefulness mediates the relationship between Information accuracy and adoption behavior. Additionally, Gender and grade do not significantly affect adoption behavior. Based on these results, the paper suggests optimizing Cloud Class by focusing on Information accuracy and ease of use to enhance its role in teaching.