{"title":"Integrating trust and satisfaction into the UTAUT model to predict Chatbot adoption – A comparison between Gen-Z and Millennials","authors":"Himanshu Joshi","doi":"10.1016/j.jjimei.2025.100332","DOIUrl":null,"url":null,"abstract":"<div><div>This paper examines the key determinants of behavioral intention, user satisfaction, and chatbot adoption among urban, college-educated student populations within Generation Z and Millennials in India. While Millennials grew up with the Internet, Gen Z was born into the era dominated by social media and smartphones, making them inherently tech-savvy and drawn to chatbots for information access. This study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating technological elements with trust and satisfaction to propose a conceptual model. Using a mixed-method approach, data were collected through a cross-sectional online survey of 487 chatbot users from urban educational institutions in India. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to test 11 hypothesized direct relationships. The results suggest that users' willingness to adopt chatbots is significantly influenced by performance expectancy, social influence, trust, and satisfaction. Regarding user satisfaction, both facilitating conditions and trust played substantial roles. Additionally, this study found meaningful associations between facilitating conditions, satisfaction, intention, and adoption. Multi-group analyses revealed notable differences in chatbot adoption factors between Gen Z and Millennials within the study's sampled population. Given the importance of trust in chatbot adoption, the paper highlights that reducing perceived risks can strengthen trust, enhance user satisfaction, and drive chatbot intention and adoption. The above findings offer context-specific insights for chatbot providers in devising strategies to improve user trust, satisfaction, and adoption within similar demographics.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100332"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Information Management Data Insights","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266709682500014X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper examines the key determinants of behavioral intention, user satisfaction, and chatbot adoption among urban, college-educated student populations within Generation Z and Millennials in India. While Millennials grew up with the Internet, Gen Z was born into the era dominated by social media and smartphones, making them inherently tech-savvy and drawn to chatbots for information access. This study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating technological elements with trust and satisfaction to propose a conceptual model. Using a mixed-method approach, data were collected through a cross-sectional online survey of 487 chatbot users from urban educational institutions in India. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to test 11 hypothesized direct relationships. The results suggest that users' willingness to adopt chatbots is significantly influenced by performance expectancy, social influence, trust, and satisfaction. Regarding user satisfaction, both facilitating conditions and trust played substantial roles. Additionally, this study found meaningful associations between facilitating conditions, satisfaction, intention, and adoption. Multi-group analyses revealed notable differences in chatbot adoption factors between Gen Z and Millennials within the study's sampled population. Given the importance of trust in chatbot adoption, the paper highlights that reducing perceived risks can strengthen trust, enhance user satisfaction, and drive chatbot intention and adoption. The above findings offer context-specific insights for chatbot providers in devising strategies to improve user trust, satisfaction, and adoption within similar demographics.