{"id":{"repo_id":"auckland-tech","oai_identifier":"oai:openrepository.aut.ac.nz:10292/18190"},"canonical_url":"https://search.dev.ndltd.org/etd/auckland-tech/oai:openrepository.aut.ac.nz:10292/18190","repository":{"repo_id":"auckland-tech","name":"AUT University","base_url":"https://openrepository.aut.ac.nz/server/oai/request"},"display":{"title":"Towards a Model of Customer Satisfaction in the Digital Era: A Systematic Literature Review of the Impact of Artificial Intelligence on Customer Satisfaction","abstract":"My research explores the effect of artificial intelligence (AI) capabilities on customer satisfaction. A systematic literature review methodology was conducted to achieve this research's objective by analysing 70 carefully selected journal articles in the marketing domain. By synthesising the findings from relevant, qualified peer-reviewed journal articles, the study synthesises a comprehensive understanding of AI's impact on service interactions and customer experience. My data analysis reveals five themes associated with AI and customer satisfaction: AI system quality, AI anthropomorphism, AI communication quality, AI competency, and customer trust. Following the themes of AI and customer satisfaction identified from the data analysis, I propose a conceptual framework integrating AI and customer satisfaction themes with AI business value (automation and augmentation) and AI customer experiences (data capture, classification, delegation, and social experience). The framework provides a foundation for understanding the relationship between customer satisfaction factors and the interplay of current AI capability. My research makes a notable theoretical contribution by addressing the need for a holistic view of AI and customer satisfaction, establishing clear definitions of AI functions, and integrating insights from diverse fields. Practical implications include providing managers with a multi-dimensional understanding of AI-driven customer satisfaction and a roadmap for aligning AI initiatives with customer experience priorities. Future research directions involve empirically validating the proposed framework, exploring human-AI collaboration effects, and refining the AI-customer-experience (AI-CX) model proposed herein. The study's limitations include potential omissions of relevant research and the need for further validation of the AI-CX components.","abstract_html":"My research explores the effect of artificial intelligence (AI) capabilities on customer satisfaction. A systematic literature review methodology was conducted to achieve this research's objective by analysing 70 carefully selected journal articles in the marketing domain. By synthesising the findings from relevant, qualified peer-reviewed journal articles, the study synthesises a comprehensive understanding of AI's impact on service interactions and customer experience. My data analysis reveals five themes associated with AI and customer satisfaction: AI system quality, AI anthropomorphism, AI communication quality, AI competency, and customer trust. Following the themes of AI and customer satisfaction identified from the data analysis, I propose a conceptual framework integrating AI and customer satisfaction themes with AI business value (automation and augmentation) and AI customer experiences (data capture, classification, delegation, and social experience). The framework provides a foundation for understanding the relationship between customer satisfaction factors and the interplay of current AI capability. My research makes a notable theoretical contribution by addressing the need for a holistic view of AI and customer satisfaction, establishing clear definitions of AI functions, and integrating insights from diverse fields. Practical implications include providing managers with a multi-dimensional understanding of AI-driven customer satisfaction and a roadmap for aligning AI initiatives with customer experience priorities. Future research directions involve empirically validating the proposed framework, exploring human-AI collaboration effects, and refining the AI-customer-experience (AI-CX) model proposed herein. The study's limitations include potential omissions of relevant research and the need for further validation of the AI-CX components.","abstract_has_math":false,"creators":["Ha Ngoc, Khuong"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024","date_published":"2024","updated_at":"2026-07-27T18:46:20Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:10292/18190"],"render_values":[{"text":"hdl:10292/18190","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2024"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:10292/18190"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.other","label":"Dc Description Other","values":["My research explores the effect of artificial intelligence (AI) capabilities on customer satisfaction. A systematic literature review methodology was conducted to achieve this research's objective by analysing 70 carefully selected journal articles in the marketing domain. By synthesising the findings from relevant, qualified peer-reviewed journal articles, the study synthesises a comprehensive understanding of AI's impact on service interactions and customer experience. My data analysis reveals five themes associated with AI and customer satisfaction: AI system quality, AI anthropomorphism, AI communication quality, AI competency, and customer trust. Following the themes of AI and customer satisfaction identified from the data analysis, I propose a conceptual framework integrating AI and customer satisfaction themes with AI business value (automation and augmentation) and AI customer experiences (data capture, classification, delegation, and social experience). The framework provides a foundation for understanding the relationship between customer satisfaction factors and the interplay of current AI capability. My research makes a notable theoretical contribution by addressing the need for a holistic view of AI and customer satisfaction, establishing clear definitions of AI functions, and integrating insights from diverse fields. Practical implications include providing managers with a multi-dimensional understanding of AI-driven customer satisfaction and a roadmap for aligning AI initiatives with customer experience priorities. Future research directions involve empirically validating the proposed framework, exploring human-AI collaboration effects, and refining the AI-customer-experience (AI-CX) model proposed herein. 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My data analysis reveals five themes associated with AI and customer satisfaction: AI system quality, AI anthropomorphism, AI communication quality, AI competency, and customer trust. Following the themes of AI and customer satisfaction identified from the data analysis, I propose a conceptual framework integrating AI and customer satisfaction themes with AI business value (automation and augmentation) and AI customer experiences (data capture, classification, delegation, and social experience). The framework provides a foundation for understanding the relationship between customer satisfaction factors and the interplay of current AI capability. My research makes a notable theoretical contribution by addressing the need for a holistic view of AI and customer satisfaction, establishing clear definitions of AI functions, and integrating insights from diverse fields. Practical implications include providing managers with a multi-dimensional understanding of AI-driven customer satisfaction and a roadmap for aligning AI initiatives with customer experience priorities. Future research directions involve empirically validating the proposed framework, exploring human-AI collaboration effects, and refining the AI-customer-experience (AI-CX) model proposed herein. The study's limitations include potential omissions of relevant research and the need for further validation of the AI-CX components."],"dc:identifier":["hdl:10292/18190"],"dc:title":["Towards a Model of Customer Satisfaction in the Digital Era: A Systematic Literature Review of the Impact of Artificial Intelligence on Customer Satisfaction"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T18:46:20Z"}