{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T17:09:43Z","timestamp":1783703383566,"version":"3.55.0"},"reference-count":102,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2021,12,24]],"date-time":"2021-12-24T00:00:00Z","timestamp":1640304000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["INTR"],"published-print":{"date-parts":[[2022,7,4]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>This study investigates the determinants of effective human and artificial intelligence (AI) relationship-building strategies for brands. It explores the antecedents and consequences of consumers' interactant satisfaction with communication and identifies ways to enhance consumer purchase intention via AI chatbot promotion.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Microsoft Xiaoice served as the focal AI chatbot, and 331 valid samples were obtained. A two-stage structural equation modeling-artificial neural network approach was adopted to verify the proposed theoretical model.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>Regarding the IQ (intelligence quotient) and EQ (emotional quotient) of AI chatbots, the multi-dimensional social support model helps explain consumers' interactant satisfaction with communication, which facilitates affective attachment and purchase intention. The results also show that chatbots should emphasize emotional and esteem social support more than informational support.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title><jats:p>Brands should focus more on AI chatbots' emotional and empathetic responses than functional aspects when designing dialogue content for human\u2013AI interactions. Well-designed AI chatbots can help marketers develop effective brand promotion strategies.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This research enriches the human\u2013AI interaction literature by adopting a multi-dimensional social support theoretical lens that can enhance the interactant satisfaction with communication, affective attachment and purchase intention of AI chatbot users.<\/jats:p><\/jats:sec>","DOI":"10.1108\/intr-01-2021-0030","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T00:26:46Z","timestamp":1640219206000},"page":"1329-1356","source":"Crossref","is-referenced-by-count":123,"title":["Artificial intelligent chatbots as brand promoters: a two-stage structural equation modeling-artificial neural network approach"],"prefix":"10.1108","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2451-1353","authenticated-orcid":false,"given":"Crystal T.","family":"Lee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1218-1254","authenticated-orcid":false,"given":"Ling-Yen","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2708-5166","authenticated-orcid":false,"given":"Sara H.","family":"Hsieh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2021,12,24]]},"reference":[{"key":"key2022070106501987400_ref001","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.ijinfomgt.2019.02.006","article-title":"Applying artificial intelligence technique to predict knowledge hiding behavior","volume":"49","year":"2019","journal-title":"International Journal of Information Management"},{"issue":"5","key":"key2022070106501987400_ref002","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1016\/S0731-7085(99)00272-1","article-title":"Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research","volume":"22","year":"2000","journal-title":"Journal of Pharmaceutical and Biomedical Analysis"},{"key":"key2022070106501987400_ref003","doi-asserted-by":"crossref","first-page":"560","DOI":"10.1016\/j.chb.2017.05.032","article-title":"Forecasting social CRM adoption in SMEs: a combined SEM-neural network method","volume":"75","year":"2017","journal-title":"Computers in Human Behavior"},{"key":"key2022070106501987400_ref004","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.chb.2018.03.051","article-title":"Living up to the chatbot hype: the influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions","volume":"85","year":"2018","journal-title":"Computers in Human Behavior"},{"key":"key2022070106501987400_ref005","doi-asserted-by":"crossref","first-page":"101473","DOI":"10.1016\/j.tele.2020.101473","article-title":"I, Chatbot: modeling the determinants of users' satisfaction and continuance intention of AI-powered service agents","volume":"54","year":"2020","journal-title":"Telematics and Informatics"},{"key":"key2022070106501987400_ref006","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1016\/j.chb.2018.08.028","article-title":"A perceived moral agency scale: development and validation of a metric for humans and social machines","volume":"90","year":"2019","journal-title":"Computers in Human Behavior"},{"issue":"15-16","key":"key2022070106501987400_ref007","doi-asserted-by":"crossref","first-page":"1401","DOI":"10.1080\/0267257X.2019.1687571","article-title":"Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications","volume":"35","year":"2019","journal-title":"Journal of Marketing Management"},{"key":"key2022070106501987400_ref008","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.jretconser.2017.10.002","article-title":"Feel the VIBE: examining value-in-the-brand-page-experience and its impact on satisfaction and customer engagement behaviours in mobile social media","volume":"46","year":"2019","journal-title":"Journal of Retailing and Consumer Services"},{"key":"key2022070106501987400_ref009","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.chb.2018.05.027","article-title":"Mobile-mediated multimodal communications, relationship quality and subjective well-being: an analysis of smartphone use from a life course perspective","volume":"87","year":"2018","journal-title":"Computers in Human Behavior"},{"key":"key2022070106501987400_ref010","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.chb.2018.08.048","article-title":"Should AI-based, conversational digital assistants employ social-or task-oriented interaction style? 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