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Investigate the Influencing Factors of Industrial Design Platform Demand: From the Perspective of Emotional Interaction.
Zhang, Chenxiao; Yang, Qin; Tong, Lei; Zhou, Rong.
Afiliación
  • Zhang C; School of Architecture and Artistic Design, University of Science and Technology Liaoning, Anshan, China.
  • Yang Q; School of Architecture and Artistic Design, University of Science and Technology Liaoning, Anshan, China.
  • Tong L; School of Tourism Management, Wuhan Business University, Wuhan, China.
  • Zhou R; Faculty of Business and Economics, University of Malaya, Kuala Lumpur, Malaysia.
Front Psychol ; 13: 892771, 2022.
Article en En | MEDLINE | ID: mdl-35677138
ABSTRACT
With the deep integration of industries brought about by big data technology, users' design needs are diversifying and individuating. Thanks to big data technology, users' diverse design needs can be precisely met. Meanwhile, big data can be used to realize emotional interaction for personalized design needs of users, resulting in a better user experience. Using grounded theory to mine user demand text data, this paper investigates the influencing factors of emotional interaction and dynamic resource allocation in the digital design supply chain. The results show that government-driven factors have a direct impact on the demand for industrial design in user emotional interactions. Market factors are the most fundamental in the development of an industrial design service platform, and universities play an important role in this. Furthermore, a lack of market sensitivity stems from a lack of emotional interaction with users, resulting in a schism between industry, university, and research, which has become a major impediment to the development of China's industrial design industry. This study not only lays the theoretical groundwork for understanding the mechanisms of user emotional interaction on IDSPs, but it also points the way forward for future industrial design service platform development.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: Front Psychol Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: Front Psychol Año: 2022 Tipo del documento: Article País de afiliación: China