Opportunities and implications of consumers’ use of artificial intelligence (AI)

Abstract

This thesis explores the implications and opportunities presented by customer-facing artificial intelligence (AI) on consumer behavior and decision-making, service delivery, and value co-creation. The overarching aim of this thesis is to advance conceptual and empirical understanding of consumer-facing artificial intelligence (AI) in retailing and service industries. My objectives are to conduct a systematic review of literature on consumer AI (CAI) and propose unifying concepts that can be used across consumer industries, to develop a taxonomy that categorizes current and emerging shopper AI applications., and to examine consumer willingness to share personal data for CAI value co-creation through a multi-industry measurement model and experiment. As a pragmatist, I rely on mixed methods research approaches that blend paradigms and methodologies to provide comprehensive understanding of complex real-world research problems. The findings are derived from direct evidence and measurable data and focus on practical applied research outcomes where qualitative methods are used to describe social realities and enrich these studies and quantitative methods provide explanatory relationships between variables. This thesis presents three papers designed to provide insight about how can retailers and service providers effectively plan and leverage consumer AI technologies to enhance value co-creation for both the firm and customers. First, a systematic literature review establishes the current state of knowledge about consumer AI. It demonstrates significant fragmentation in the consumer AI literature, a need for more consensus about approaching the novel aspects of consumer-AI interactions, inadequate evidence about how AI alters consumer decisions, and a lack of AI-specific theories to explain observed behaviors. The Shopper AI Taxonomy organizes consumer AI to facilitate understanding and analysis of the shopper AI landscape. Based on the Shopper AI Taxonomy, we identify one specific group of autonomous shopper AI, Intelligent Shopping Agents (ISA), that have the potential to disrupt marketing, retailing, and services practice. Shopper AI can engage customers in AI-assisted value co-creation (AIVC), which presents new opportunities to create value for consumers and firms. However, it also raises questions about consumers’ willingness to share personal information. The AIVC Co-Creation Model and an evaluation of the role of CAI trust in AIVC participation are proposed. This article also provides some considerations for AIVC concepts, designs, and implementation that may increase AIVC customer engagement. Finally, the thesis provides a synthesis exploring optimal strategies for retailers to capitalize on AI’s unique capacity to cost-effectively support personalization, presents overarching theoretical and managerial implications, and indicates directions for future work. 

Date of Award	19 Dec 2023
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Hongwei He (Supervisor) & Panagiotis Sarantopoulos (Supervisor)