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Results showed that aesthetic fixations were the strongest predictors of brand attention, accounting for 40.3% of variance in brand engagement, while materialism dimensions selectively influenced attention toward symbolic status cues The findings support a gaze-driven Human–Computer Interaction (HCI) framework in which aesthetic salience functions as a primary attentional signal within visually dense digital environments. From a systems-design perspective, the study proposes an attention-adaptive interface model integrating real-time ocular metrics into rendering and layout optimization processes. 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Journal of Marketing, 73(6), 1–17" }, { "path": "references.9.doi", "from": null, "to": "10.1016/j.jcps.2009.02.011" }, { "path": "references.9.key", "from": null, "to": "ref10" }, { "path": "references.9.unstructured", "from": null, "to": "Valenzuela, A., & Raghubir, P. (2009). Position-based beliefs: The center-stage effect. Journal of Consumer Psychology, 19(2), 185–196" }, { "path": "referent", "from": null, "to": "Creation" }, { "path": "structural_type", "from": null, "to": "Digital" }, { "path": "titles.0.lang", "from": null, "to": "en" }, { "path": "titles.0.type", "from": null, "to": "PrincipalTitle" }, { "path": "titles.0.value", "from": null, "to": "Attention-Driven Rendering and Interface Adaptation Using Eye-Tracking Data" }, { "path": "type", "from": null, "to": "JournalArticle" } ], "record_after": { "format": "smartscholars-doi-metadata/1.0", "doi": "10.46243/jst.2026.v11.i02.pp01-15", "referent": "Creation", "type": "JournalArticle", "structural_type": "Digital", "modes": [ "Visual" ], "characters": [ "Language" ], "titles": [ { "value": "Attention-Driven Rendering and Interface Adaptation Using Eye-Tracking Data", "type": "PrincipalTitle", "lang": "en" } ], "identifiers": [ { "type": "DOI", "value": "10.46243/jst.2026.v11.i02.pp01-15" } ], "agents": [ { "role": "author", "name": { "given": "", "family": "First Author Dr Zoi Zoupanou" }, "sequence": "first" }, { "role": "author", "name": { "given": "", "family": "Second Author Dr Max Tookey" }, "sequence": "additional" }, { "role": "publisher", "name": { "org": "Longman Publishers" } } ], "dates": { "published": "2026-02-17", "date_type": "PublicationDate", "online": "2026-02-17" }, "language": "en", "container": { "type": "Journal", "titles": [ { "value": "Journal of Science & Technology", "type": "PrincipalTitle" } ], "identifiers": [ { "type": "ISSN", "value": "2456-5660", "medium": "electronic" } ], "volume": "11", "issue": "02", "pages": { "first": "01" } }, "links": [ { "url": "https://www.jst.org.in/index.php/pub/article/view/1556", "return_type": "text/html", "primary": true }, { "url": "https://www.jst.org.in/index.php/pub/article/download/1556/1130", "purpose": "text-mining", "return_type": "application/pdf" }, { "url": "https://www.jst.org.in/index.php/pub/article/download/1556/1169", "purpose": "text-mining", "return_type": "application/xml" }, { "url": "https://jst.org.in/index.php/pub/article/view/1556/1130", "purpose": "similarity-checking" } ], "abstract": { "value": "This study investigates computational attention mechanisms in digital luxury interfaces using eye-tracking and predictive modeling. Across three experiments (N = 60), ocular biometric measures, including fixation duration, saccadic frequency, and fixation density, were analyzed during exposure to high-fidelity fashion stimuli containing aesthetic and brand-specific elements. Results showed that aesthetic fixations were the strongest predictors of brand attention, accounting for 40.3% of variance in brand engagement, while materialism dimensions selectively influenced attention toward symbolic status cues The findings support a gaze-driven Human–Computer Interaction (HCI) framework in which aesthetic salience functions as a primary attentional signal within visually dense digital environments. From a systems-design perspective, the study proposes an attention-adaptive interface model integrating real-time ocular metrics into rendering and layout optimization processes. The research contributes a computational framework linking biometric attention sensing with adaptive interface engineering for mobile commerce, social media, and immersive digital environments.", "lang": "en" }, "license": { "url": "https://creativecommons.org/licenses/by/4.0/", "start": "2026-02-17", "applies_to": "vor" }, "references": [ { "key": "ref1", "doi": "10.1007/s10660-021-09523-7", "unstructured": "De Keyser, F., Dens, N., & De Pelsmacker, P. (2023). The processing of native advertising compared to banner advertising: an eye-tracking experiment. Electronic Commerce Research, 23(3), 1921–1940" }, { "key": "ref2", "unstructured": "Pieters, R., & Wedel, M. (2008). Informativeness of eye movements for visual marketing: Six cornerstones. In M. Wedel & R. Pieters (Eds.), Visual Marketing: From Attention to Action (pp. 43–72). Erlbaum" }, { "key": "ref3", "doi": "10.1080/02699930903205698", "unstructured": "Yiend, J. (2010). 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ACM Transactions on Graphics, 36(4), Article 50" }, { "key": "ref57", "doi": "10.1038/s41598-024-62365-9", "unstructured": "Qian, K., Arichi, T., Edwards, A. D., & Hajnal, J. V. (2024). Instant interaction driven adaptive gaze control interface. Scientific Reports, 14, Article 11661" }, { "key": "ref58", "doi": "10.1007/978-3-319-94706-8_41", "unstructured": "Nayak, B. K., & Karmakar, S. (2018). Eye Tracking Based Objective Evaluation of Visual Aesthetics: A Review. In F. Rebelo & M. Soares (Eds.), Advances in Ergonomics in Design, Proceedings of the AHFE 2018 (pp. 370–381). Springer" }, { "key": "ref59", "doi": "10.3758/bf03212870", "unstructured": "Eriksen, C. W., & Hoffman, J. E. (1972). Temporal and spatial characteristics of selective encoding from visual displays. Perception & Psychophysics, 12(2), 201–204" }, { "key": "ref60", "doi": "10.1146/annurev.ps.37.020186.000355", "unstructured": "Johnston, W. A., & Dark, V. J. (1986). Selective Attention. 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Perception & Psychophysics, 49(1), 83–90" }, { "key": "ref66", "doi": "10.1108/jpbm-04-2022-3937", "unstructured": "Razmus, W., Razmus, M., & Grabner-Kräuter, S. (2024). Joy and excitement in the purchase process: the role of materialism and brand engagement. Journal of Product & Brand Management, 33(3), 330–344" }, { "key": "ref67", "doi": "10.1016/j.ijhcs.2009.12.006", "unstructured": "Djamasbi, S., Siegel, M., & Tullis, T. (2010). Generation Y, web design, and eye tracking. International Journal of Human-Computer Studies, 68(5), 307–323" }, { "key": "ref68", "doi": "10.1108/ejmbe-03-2024-0090", "unstructured": "Munoz-Leiva, F., Herzallah, D., & Liebana-Cabanillas, F. (2024). Surprise me with the visual representation of the brand in social commerce! An eye-tracking study based on user characteristic. European Journal of Management and Business Economics. Emerald Publishing" }, { "key": "ref69", "doi": "10.1177/18344909211000452", "unstructured": "Yu, J., Peng, X. R., & Yan, M. (2021). Effects of age on memory for pragmatic implications in advertising: an eye movement study. Journal of Pacific Rim Psychology, 15, 18344909211000452" } ], "record": { "registrant": "Longman Publishers", "registered": "2026-08-26", "updated": "2026-09-20", "issue_number": 1, "source": "crossref-api", "source_agency": "Crossref (member 25296)" } }, "url_after": "https://www.jst.org.in/index.php/pub/article/view/1556", "sha256_before": null, "sha256_after": "5b8e421185274b1f1cd2e081278de334d5b6bf31b8442c8491932c922ba823a6" }, { "seq": 2, "kind": "update", "at": "2026-09-29 23:59:51", "by": "Administrator (admin)", "by_kind": "user", "note": "record re-read from api.crossref.org", "changes": [ { "path": "container.titles.0.value", "from": "Journal of Science & Technology", "to": "Journal of Science & Technology" } ], "record_after": { "format": "smartscholars-doi-metadata/1.0", "doi": "10.46243/jst.2026.v11.i02.pp01-15", "referent": "Creation", "type": "JournalArticle", "structural_type": "Digital", "modes": [ "Visual" ], "characters": [ "Language" ], "titles": [ { "value": "Attention-Driven Rendering and Interface Adaptation Using Eye-Tracking Data", "type": "PrincipalTitle", "lang": "en" } ], "identifiers": [ { "type": "DOI", "value": "10.46243/jst.2026.v11.i02.pp01-15" } ], "agents": [ { "role": "author", "name": { "given": "", "family": "First Author Dr Zoi Zoupanou" }, "sequence": "first" }, { "role": "author", "name": { "given": "", "family": "Second Author Dr Max Tookey" }, "sequence": "additional" }, { "role": "publisher", "name": { "org": "Longman Publishers" } } ], "dates": { "published": "2026-02-17", "date_type": "PublicationDate", "online": "2026-02-17" }, "language": "en", "container": { "type": "Journal", "titles": [ { "value": "Journal of Science & Technology", "type": "PrincipalTitle" } ], "identifiers": [ { "type": "ISSN", "value": "2456-5660", "medium": "electronic" } ], "volume": "11", "issue": "02", "pages": { "first": "01" } }, "links": [ { "url": "https://www.jst.org.in/index.php/pub/article/view/1556", "return_type": "text/html", "primary": true }, { "url": "https://www.jst.org.in/index.php/pub/article/download/1556/1130", "purpose": "text-mining", "return_type": "application/pdf" }, { "url": "https://www.jst.org.in/index.php/pub/article/download/1556/1169", "purpose": "text-mining", "return_type": "application/xml" }, { "url": "https://jst.org.in/index.php/pub/article/view/1556/1130", "purpose": "similarity-checking" } ], "abstract": { "value": "This study investigates computational attention mechanisms in digital luxury interfaces using eye-tracking and predictive modeling. Across three experiments (N = 60), ocular biometric measures, including fixation duration, saccadic frequency, and fixation density, were analyzed during exposure to high-fidelity fashion stimuli containing aesthetic and brand-specific elements. Results showed that aesthetic fixations were the strongest predictors of brand attention, accounting for 40.3% of variance in brand engagement, while materialism dimensions selectively influenced attention toward symbolic status cues The findings support a gaze-driven Human–Computer Interaction (HCI) framework in which aesthetic salience functions as a primary attentional signal within visually dense digital environments. From a systems-design perspective, the study proposes an attention-adaptive interface model integrating real-time ocular metrics into rendering and layout optimization processes. The research contributes a computational framework linking biometric attention sensing with adaptive interface engineering for mobile commerce, social media, and immersive digital environments.", "lang": "en" }, "license": { "url": "https://creativecommons.org/licenses/by/4.0/", "start": "2026-02-17", "applies_to": "vor" }, "references": [ { "key": "ref1", "doi": "10.1007/s10660-021-09523-7", "unstructured": "De Keyser, F., Dens, N., & De Pelsmacker, P. (2023). The processing of native advertising compared to banner advertising: an eye-tracking experiment. Electronic Commerce Research, 23(3), 1921–1940" }, { "key": "ref2", "unstructured": "Pieters, R., & Wedel, M. (2008). Informativeness of eye movements for visual marketing: Six cornerstones. In M. Wedel & R. Pieters (Eds.), Visual Marketing: From Attention to Action (pp. 43–72). Erlbaum" }, { "key": "ref3", "doi": "10.1080/02699930903205698", "unstructured": "Yiend, J. (2010). 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