Repository logo
 

Towards a Model of Customer Satisfaction in the Digital Era: A Systematic Literature Review of the Impact of Artificial Intelligence on Customer Satisfaction

Files

Dissertation(793.73 KB)

Date

2024

Authors

Supervisor

Xu, Yingzi
De Villiers, Rouxelle

Item type

Thesis

Degree name

Master of Business

Journal Title

Journal ISSN

Volume Title

Publisher

Auckland University of Technology

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.

Description

Keywords

Source

DOI

Publisher's version

Rights statement

Permanent link

http://hdl.handle.net/10292/18190

Collections

Masters Dissertations