{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["16"],"submitter":["Liu J"],"pubmed_abstract":["<h4>Introduction</h4>The rapid integration of machine learning has positioned product recommendation chatbots as essential tools in the e-commerce landscape, shaping how consumers engage and make purchasing decisions. Generation Z, as a tech-savvy and AI-adept demographic, plays a central role in this transformation. While prior studies have examined chatbot-consumer interactions, limited research has explored how both personality traits and information source characteristics jointly influence purchase intentions.<h4>Methods</h4>This study develops an integrative framework to assess how the Big Five personality traits-extraversion, agreeableness, conscientiousness, neuroticism, and openness-and key chatbot features-expertise, interactivity, trustworthiness, and customization-affect Generation Z's willingness to purchase chatbot-recommended products. The moderating role of personal innovativeness is also examined. Data were collected from 480 Generation Z chatbot users in China through an online survey and analyzed using structural equation modeling (SEM), artificial neural networks (ANN), and necessary condition analysis (NCA).<h4>Results</h4>Results indicate that extraversion, agreeableness, openness, expertise, interactivity, and customization significantly influence purchase intention. Moreover, personal innovativeness positively moderates the effect of extraversion on purchase intention.<h4>Discussion</h4>These findings contribute to the literature by bridging personality psychology and human-AI interaction and offer practical insights for enhancing chatbot effectiveness in e-commerce."],"journal":["Frontiers in psychology"],"pagination":["1454197"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12425985"],"repository":["biostudies-literature"],"pubmed_title":["Chatbot-aided product purchases among Generation Z: the role of personality traits."],"pmcid":["PMC12425985"],"pubmed_authors":["Liu J","Chen J"],"additional_accession":[]},"is_claimable":false,"name":"Chatbot-aided product purchases among Generation Z: the role of personality traits.","description":"<h4>Introduction</h4>The rapid integration of machine learning has positioned product recommendation chatbots as essential tools in the e-commerce landscape, shaping how consumers engage and make purchasing decisions. Generation Z, as a tech-savvy and AI-adept demographic, plays a central role in this transformation. While prior studies have examined chatbot-consumer interactions, limited research has explored how both personality traits and information source characteristics jointly influence purchase intentions.<h4>Methods</h4>This study develops an integrative framework to assess how the Big Five personality traits-extraversion, agreeableness, conscientiousness, neuroticism, and openness-and key chatbot features-expertise, interactivity, trustworthiness, and customization-affect Generation Z's willingness to purchase chatbot-recommended products. The moderating role of personal innovativeness is also examined. Data were collected from 480 Generation Z chatbot users in China through an online survey and analyzed using structural equation modeling (SEM), artificial neural networks (ANN), and necessary condition analysis (NCA).<h4>Results</h4>Results indicate that extraversion, agreeableness, openness, expertise, interactivity, and customization significantly influence purchase intention. Moreover, personal innovativeness positively moderates the effect of extraversion on purchase intention.<h4>Discussion</h4>These findings contribute to the literature by bridging personality psychology and human-AI interaction and offer practical insights for enhancing chatbot effectiveness in e-commerce.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025","modification":"2026-06-03T02:52:12.593Z","creation":"2026-04-23T03:12:32.434Z"},"accession":"S-EPMC12425985","cross_references":{"pubmed":["40949325"],"doi":["10.3389/fpsyg.2025.1454197"]}}