13 citations as recorded by crossref.

1. The influences of product similarity on consumer preferences: a study based on eye-tracking analysis C. Ye et al. https://doi.org/10.1007/s10111-019-00584-1
2. Review of the use of neurophysiological and biometric measures in experimental design research Y. Borgianni & L. Maccioni https://doi.org/10.1017/S0890060420000062
3. The impact of vehicle silhouettes on perceptions of car environmental friendliness and safety in 2009 and 2016: a comparative study Y. Bi et al. https://doi.org/10.1017/dsj.2017.22
4. A structural analysis of frontal car styling Ü. Bayırlı https://doi.org/10.1080/14606925.2023.2259239
5. Supporting computer-aided product form design research with a cognitive model of the creative process W. Yang et al. https://doi.org/10.1007/s11042-022-12119-4
6. Opportunities for using eye tracking technology in manufacturing and logistics: Systematic literature review and research agenda T. Zheng et al. https://doi.org/10.1016/j.cie.2022.108444
7. Applying Eye-Tracking in Kansei Engineering Method for Design Evaluations in Product Development M. KÖHLER et al. https://doi.org/10.5057/ijae.IJAE-D-15-00016
8. Cross-cultural evaluation of consumer’s dynamic multisensory and emotional experience L. Zhang et al. https://doi.org/10.1108/APJML-07-2017-0139
9. Current Status of Korean Fashion Design Sensibility Evaluation Methods and Their Application Overseas H. An & I. Lee https://doi.org/10.5850/JKSCT.2016.40.4.660
10. Using psychophysiological measures to evaluate the multisensory and emotional dynamics of the tea experience L. Zhang et al. https://doi.org/10.1007/s11694-018-9754-z
11. Observing Pictures and Videos of Creative Products: An Eye Tracking Study A. Berni et al. https://doi.org/10.3390/app10041480
12. Exploratory study on the perception of additively manufactured end-use products with specific questionnaires and eye-tracking Y. Borgianni et al. https://doi.org/10.1007/s12008-019-00563-w
13. A learning model for perceived visual complexity assessment of automotive 3D shapes based on visual perception elements C. Shen et al. https://doi.org/10.1016/j.compind.2025.104358