Affective Design of Smart TV Navigation Interface Considering the Diversity of User Needs

Abstract

Identifying users’ diversified needs and designing products that match those needs is important in the era of mass personalization. Smart TV navigation interfaces lack good affective design, and difficulties remain in responding to diversified affective needs. Therefore, an affective design approach that considers the diversity of user needs is presented to optimize the design of smart TV navigation interfaces. First, the laddering interview is conducted to capture the diversified affective needs and multi-layer interface design elements perceived by users. Kansei distance is introduced to characterize diversified needs. Then, single-user relationship models between user perceptions and interface attributes are constructed. Finally, the two-stage interface optimization is performed to obtain common and individual optimization attributes, which are further embodied as parameter-layer optimization solutions through user experiments. This method is capable of capturing the diversified affective needs for smart TV navigation interfaces and achieving differentiated product design.

Keywords:

• Affective design
• interface design
• laddering interview
• need diversity
• smart TV

Acknowledgments

We would like to acknowledge the participants for their time and involvement in the interview.

Disclosure statement

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

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (Grant Nos. 71771045 and 72071035).

Notes on contributors

Fu Guo

Fu Guo is a professor of Industrial Engineering at the School of Business Administration, Northeastern University, China. Her research interests include Human Factors, Kansei Engineering, User Experience Design, Human–Computer Interaction, Human–Robot Interaction, Occupational Safety and Health, and Product Placement.

Xiaohui Tian

Xiaohui Tian is a PhD candidate at the Department of Industrial Engineering, School of Business Administration, Northeastern University, China. Her research interests include Human Factors, Affective Design, Human–Computer Interaction, and User Experience Design.

Mingcai Hu

Mingcai Hu is a lecturer at the School of Management, Jiangsu University, Zhenjiang, China. He obtained his PhD degree in Management Science and Engineering from Northeastern University in 2021. His research interests include Human Factors, User Experience Design, and Human–Computer Interaction.

Zeyu Zhang

Zeyu Zhang is a PhD student at the Department of Industrial Engineering, School of Business Administration, Northeastern University, China. His research interests include Human Factors, Sentiment Analysis in Natural Language Processing, and Human–Computer Interaction.