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Manage. Inf. Syst."],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:p>Given the profound impact of diet on cardiovascular health, appropriate dietary intake in home cooking is widely acknowledged as being instrumental in preventing cardiovascular diseases (CVDs). However, contemporary dietary recommendation systems for patients with CVDs are limited by population-level guidelines, static advice, as well as a lack of consideration for contextual conditions and individual preferences. We hence subscribe to the Theory of Planned Behavior (TPB) to design a novel recipe recommender system. Our proposed recipe recommender system takes into account users\u2019 personal attitudes, subjective norms, and perceived behavioural control as focal considerations in recipe recommendations. Particularly, our recipe recommendation system assimilates personalized considerations\u2014including health conditions, taste preferences, and available ingredients in the user's refrigerator\u2014with social elements in the likes of cooking frequency, recipe viewing intensity, and user comments to bolster the acceptability of recommended recipes. Additionally, by incorporating user interactions in the likes of adding and liking recipes, our proposed recipe recommender system streamlines recipe discovery and strengthens users\u2019 perceived behavioural control to maintain dietary choices. This integration aims to alleviate the practical challenges associated with adopting recommended recipes, rendering it much easier for users to adhere to dietary guidelines. Based on empirical validation, we not only deliver detailed insights into the implementation of a recipe recommendation system, but we also validate its utility in enhancing user engagement and satisfaction.<\/jats:p>","DOI":"10.1145\/3814605","type":"journal-article","created":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T10:58:01Z","timestamp":1778237881000},"page":"1-39","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Personalized and Adaptive Diet Recommendation for Individuals with Cardiovascular Diseases"],"prefix":"10.1145","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4071-9904","authenticated-orcid":false,"given":"Quanchen","family":"Liu","sequence":"first","affiliation":[{"name":"International Business School, Beijing Foreign Studies University","place":["Beijing, China"]},{"name":"Department of Digitalization, Copenhagen Business School","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2614-6051","authenticated-orcid":false,"given":"Bingqing","family":"Xiong","sequence":"additional","affiliation":[{"name":"Deakin Business School, Department of Information Systems and Business Analytics, Deakin University","place":["Melbourne, Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8705-4164","authenticated-orcid":false,"given":"Zhao","family":"Cai","sequence":"additional","affiliation":[{"name":"Nottingham University Business School China, University of Nottingham Ningbo China","place":["Ningbo, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7405-9588","authenticated-orcid":false,"given":"Hengrun","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Department of Computer Science and Engineering, East China University of Science and Technology","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4245-541X","authenticated-orcid":false,"given":"Chee-Wee","family":"Tan","sequence":"additional","affiliation":[{"name":"Faculty of Business, Department of Management and Marketing, The Hong Kong Polytechnic University","place":["Hong Kong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4988-7469","authenticated-orcid":false,"given":"Xiaohui","family":"Liu","sequence":"additional","affiliation":[{"name":"Business School, Department of Artificial Intelligence, University of Shanghai for Science and Technology","place":["Shanghai, China"]},{"name":"School of Intelligent Emergency Management, University of Shanghai for Science and Technology","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,10]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.3390\/nu14173520"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.25300\/MISQ\/2019\/13949"},{"issue":"4","key":"e_1_3_3_4_1","first-page":"18","article-title":"Data mining techniques to find out heart diseases: An overview","volume":"1","author":"Ahmed A.","year":"2012","unstructured":"A. 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