{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T06:48:25Z","timestamp":1772261305627,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MAKE"],"abstract":"<jats:p>This study investigates the relationship between consumer personality traits, specifically openness, and responses to product designs. Consumers are categorized based on their levels of openness, and their affective responses to nine vase designs, varying in curvature and line quantity, are evaluated. The study then introduces the inverse clustering approach, which prioritizes maximizing predictive model accuracy over within-cluster similarity. This method iteratively refines cluster assignments to optimize prediction performance, minimizing errors in forecasting consumer design preferences. The results demonstrate that the inverse clustering approach yields more effective clusters than personality-based clustering. Moreover, while there is some overlap between personality-based and accuracy-based clustering, the inverse clustering method captures additional individual characteristics, extending beyond personality traits and improving the understanding of consumer product design response. The practical implications of this study are significant for product designers, as it enables the development of more personalized designs and optimization of product features to enhance specific consumer perceptions, such as robustness or esthetic appeal.<\/jats:p>","DOI":"10.3390\/make7010009","type":"journal-article","created":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T05:59:42Z","timestamp":1736920782000},"page":"9","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Enhancing Consumer Agent Modeling Through Openness-Based Consumer Traits and Inverse Clustering"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9472-9331","authenticated-orcid":false,"given":"Brahim","family":"Benaissa","sequence":"first","affiliation":[{"name":"Design Engineering Lab, Department of Mechanical Systems Engineering, Toyota Technological Institute, 2-12-1 Hisakata, Tenpaku-ku, Nagoya 468-8511, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1212-2879","authenticated-orcid":false,"given":"Masakazu","family":"Kobayashi","sequence":"additional","affiliation":[{"name":"Design Engineering Lab, Department of Mechanical Systems Engineering, Toyota Technological Institute, 2-12-1 Hisakata, Tenpaku-ku, Nagoya 468-8511, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroshi","family":"Takenouchi","sequence":"additional","affiliation":[{"name":"Department of Information Management, Faculty of Information Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-Higashi, Higashi-ku, Fukuoka 811-0295, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1016\/j.jbusres.2015.05.017","article-title":"Beyond form and function: Why do consumers value product design?","volume":"69","author":"Minu","year":"2016","journal-title":"J. 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