China industrial design award evaluation: Explicit features, implicit values, and participation experience

Abstract

This study examines China Excellent Industrial Design (CEID) through structural equation modeling, analyzing 209 participants’ evaluation data on explicit features, implicit values, and participation experience. Findings guide organizers in enhancing strategic approaches, maintaining high-level features, fostering unique elements, and addressing developmental shortcomings. The research offers a quantitative evaluation framework for CEID advancement and a reference for other developing countries’ design award assessments.

Keywords:

• China Industrial Design Award
• evaluation system
• explicit features
• implicit values
• participation experience

Ethics approval and consent to participate

Ethical approval for this study was obtained.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This study was funded by the National Social Science Foundation Art Science Project (No.21BG125).

Notes on contributors

Lei Yu

Lei Yu is an Associate Professor at the School of Arts and Design, Yanshan University, and also a researcher at the Inner Mongolia Institute of National Culture and Art. His research interests include computational art design, complex system evaluation, design psychology, design cognition, and design strategies.

Xin Feng

Xin Feng is currently an Associate Professor at Shijiazhuang Tiedao University and a Doctoral Supervisor. He is a third-level talent in Hebei Province’s “333 Talent Project” and a young top talent in Hebei Province. He received the Second Prize of Hebei Province Social Science Achievement Award in 2022 (as the project leader) and has hosted more than 20 projects including the National Natural Science Foundation and the Ministry of Education’s Humanities and Social Sciences Foundation. He has published over 40 high-level papers. His research interests include red culture and social computing, quantitative management and complex networks, and science and technology evaluation and intelligent computing. His ORCID link is https://orcid.org/0000-0002-0140-8003.

Anran Wang

Anran Wang is a master’s student in design at the School of Arts and Design, Yanshan University. Her research interests include design theory, complex system design, and design evaluation research.

Guoqiang Chen

Guoqiang Chen is a professor at the School of Arts and Design, Yanshan University, and a doctoral supervisor. He also serves as the Deputy Director of the Industrial Design Branch of the Chinese Mechanical Engineering Society and the Director of the Hebei Industrial Design Innovation and Development Research Center. His research interests include theoretical and methodological innovation in innovative design of high-end equipment and innovative theory of intelligent industrial design.