[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121607-en":3,"doc-seo-121607-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121607,7971461741311,"Ophelia","https://ap-avatar.wpscdn.com/avatar/74000253aff267980c6?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779345379180704826",8,"Research & Report","Emotional design engineering for packaging of olive oil using machine learning techniques - Research article","Consumer behaviour and purchase intentions are shaped by the visual cues of food packaging, with olive oil being a high-impact case. The study analyses how olive oil users perceive different packaging options by applying machine learning tools within the synthesis phase of the Kansei Engineering methodology. Four properties define the property space (material, colour, price, capacity), while a semantic space is built via literature search, affinity analysis, and pilot surveys. A final survey of 100 Andalusian citizens supports model-based synthesis to optimise packaging design and can inform future agri-food and AI applications.","Cogent Engineering  \nISSN: 2331-1916 (Online) Journal [homepage: ](homepage: www.tandfonline.com/journals/oaen20)[www.tandfonline.com/journals/oaen20](homepage: www.tandfonline.com/journals/oaen20)  \nEmotional design engineering for packaging of olive oil using machine learning techniques  \nAna de las Heras, Francisco Zamora-Polo, Antonio Ferramosca & Amalia Luque  \nTo cite this article: Ana de las Heras, Francisco Zamora-Polo, Antonio Ferramosca & Amalia Luque (2025) Emotional design engineering for packaging of olive oil using machine learning techniques, Cogent Engineering, 12:1, 2555340, DOI: 10.1080/23311916.2025.2555340  \nTo link to this article: [https://doi.org/10.1080/2331](https://doi.org/10.1080/2331)1916.2025.2555340  \n© 2025 The Author(s) . Published by Informa UK Limited, trading as Taylor & Francis Group  \n\n|  Published online: 12 Sep 2025. |  |\n| --- | --- |\n|  | Submit your article to this journal  |\n|  | Article views: 44 |\n|  | View related articles  |\n|  View Crossmark data |  |\n\nFull Terms & Conditions of access and use can be found at [https://www.tandfonline.com/action/journalInformation?journalCode=oaen20](https://www.tandfonline.com/action/journalInformation?journalCode=oaen20)  \nCOGENT ENGINEERING  \n2025, VOL. 12, NO. 1, 2555340  \n[https://doi.org/10.1080/23311916.2025.2555340](https://doi.org/10.1080/23311916.2025.2555340)  \nPRODUCTION AND MANUFACTURING| RESEARCH ARTICLE    \nEmotional design engineering for packaging of olive oil using machine learning techniques  \nAna de las Herasa , Francisco Zamora-Poloa , Antonio Ferramoscab and Amalia Luquea, b   \n􀀁  \naDepartamento de Ingeniera del Dise~no, Escuela Politcnica Superior, Universidad de Sevilla. Virgen de Africa, Sevilla, Spain; bDepartment of Management, Information and Production Engineering, University of Bergamo, Dalmine, BG, Italy  \nABSTRACT  \nConsumer behaviour, and therefore purchase intentions, are affected by the visual elements of packaging. This is particularly important for products in the agri-food sector, especially for olive oil. In this work, the perception of different packaging options by olive oil users is analysed. For this, machine learning tools are employed in the synthesis phase of the Kansei Engineering (KE) methodology. On the one hand, four properties (material, colour, price, capacity) were considered for the definition of the property space. Subsequently, for the determination of the semantic space, a literature search was first performed, and an affinity analysis was then carried out, followed by a pilot survey to reduce the number of Kanseis. The semantic space consisted of 17 and 6 Kanseis, respectively. The final survey was given to a sample of 100 Andalusian citizens. Machine learning techniques (linear regression, ridge regression SVR) were employed for the synthesis phase. The results show that KE can be used as a tool tooptimise the design of olive oil packaging by using machine learning tools in the synthesis phase. This study can provide the basis for other studies of other agri-food products and for the use of other artificial intelligence tools.  \nARTICLE HISTORY  \nReceived 3 September 2024 Revised 3 January 2025 Accepted 8 May 2025  \nKEYWORDS  \nKansei engineering;  \nmachine learning;  \nsustainable design; engineering design; olive oil packaging  \nSUBJECTS  \nPackaging; Food Engineering; Environmental Studies; Computer Science (General)  \nIntroduction  \nPrevious studies show that the visual elements of packaging affect consumer behaviour and purchase intentions. Moreover, the material and colours of packaging are crucial with respect to the level of attractiveness and, therefore, to consumer preferences (Abdelazim-Mohamed et al., 2019; Gunaratne et al., 2019) . In the purchase decision in the case of olive oil, the type of packaging is of the highest importance. This variable increases consumers’ willingness to pay for olive oil, as demonstrated by Delgado et al. (2013) . It also significantly impacts the pri","cbCailLJuoNZSctk","https://ap.wps.com/l/cbCailLJuoNZSctk","pdf",3897227,1,28,"English","en",105,"# Introduction\n## Packaging design and consumer perception in olive oil\n## Prior work and research motivation","[{\"question\":\"How does the study connect packaging visuals to consumer behaviour for olive oil?\",\"answer\":\"It explains that visual elements influence perception and purchase intentions, and it highlights how material and colour are linked to attractiveness and consumer preferences in olive oil decisions.\"},{\"question\":\"What methodology and machine learning approach are used to design packaging?\",\"answer\":\"The work applies Kansei Engineering and uses machine learning tools in the synthesis phase, including linear regression and ridge regression SVR.\"},{\"question\":\"What inputs and user data does the Kansei Engineering model rely on?\",\"answer\":\"The property space considers material, colour, price, and capacity, while the semantic space is refined through literature search, affinity analysis, and pilot surveys; the final model uses responses from 100 Andalusian citizens.\"}]","Emotional design engineering for packaging of olive oil using machine learning techniques - Research article | PDF",1785736457,71,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"emotional-design-engineering-for-packaging-of-olive-oil-using-machine-learning-techniques-research-article","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/emotional-design-engineering-for-packaging-of-olive-oil-using-machine-learning-techniques-research-article/121607/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"How does the study connect packaging visuals to consumer behaviour for olive oil?","Question",{"text":75,"@type":76},"It explains that visual elements influence perception and purchase intentions, and it highlights how material and colour are linked to attractiveness and consumer preferences in olive oil decisions.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What methodology and machine learning approach are used to design packaging?",{"text":80,"@type":76},"The work applies Kansei Engineering and uses machine learning tools in the synthesis phase, including linear regression and ridge regression SVR.",{"name":82,"@type":73,"acceptedAnswer":83},"What inputs and user data does the Kansei Engineering model rely on?",{"text":84,"@type":76},"The property space considers material, colour, price, and capacity, while the semantic space is refined through literature search, affinity analysis, and pilot surveys; 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