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This study focuses on the effects of user characteristics and the human-like attributes of robo-advisors on downstream outcomes such as trust, financial well-being and loyalty.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Partial least squares structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) was applied.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The findings indicate that (1) human-like characteristics of robo-advisors are essential for fostering users\u2019 trust in robo-advisors; (2) while not necessary conditions, financial self-efficacy and financial socialization positively influence trust; (3) trust, particularly its congruence, communication and commitment dimensions, is key to enhancing financial well-being; (4) the frequency of robo-advisor usage moderates the trust\u2013financial well-being relationship and (5) financial well-being positively impacts customer loyalty.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This research advances robo-advisory service studies by exploring how user traits and humanoid robot features affect trust and loyalty, extending prior research focused on adoption and continuous use. 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