What Role Does AI Chatbot Perform in the F&B Industry? Perspective from Loyalty and Value Co-Creation: Integrated PLS-SEM and ANN Techniques

Abstract

Purpose: This study examines the process formation of customer loyalty and customer value co-creation towards AI chatbots by exploring the successive effects of perceived value aspects, perceived information quality, technological self-efficacy for online trust, aspects of loyalty, and value co-creation.   Theorical framework: The increasingly strong reception of humans for a new wave of digitalization has promoted the need to learn about customer loyalty and customers' value co-creation formation for businesses applying AI chatbots to their operations business to attract and retain customers. The study utilized the perceived value dimension, as well as perceived information quality, technological self-efficacy, and online trust, to comprehend loyalty and value co-creation.   Design/methodology/approach: The study was conducted using a self-administered questionnaire survey with 447 participants, who had used Pizza Hut's AI chatbot service in Vietnam. The data was analyzed by integrating two techniques: partial least square structural equation modeling (PLS-SEM) and artificial neural networks (ANN).   Findings: The results show that aspects of perceived value, perceived information quality, and technological self-efficacy all have a significant impact on online trust except hedonic value, which in turn leads to the formation of aspects of loyalty and high ability to create value co-creation. The analysis results show that perceived information quality has a stronger impact on online trust than technological self-efficacy. In addition, the non-linear results from the ANN analysis show that attitudinal loyalty has relatively stronger importance for value co-creation than behavioral loyalty.   Research, Practical & Social Implication: This study contributes to the emerging literature on the use of AI chatbots by investigating the possibility of consumers and providers co-creating value. Second, in this study, the authors delved into the internal aspects of loyalty and separated it into two primary aspects, behavioral and attitudinal, in order to clarify their impact on the factors that influence AI chatbot and value co-creation. In conclusion, this research contributes to the existing body of knowledge by providing a more multidimensional perspective on theories. Originality/value: The integration of PLS-SEM and ANN techniques into the analysis to simultaneously explore both linear and non-linear mechanisms of this study explained the influence of aspects of perceived value, perceived information quality, and technological self-efficacy on aspects of loyalty and value co-creation via online trust in AI chatbots context. In addition, this study extends the perceived value to explore the impact of internal and external personal factors on AI chatbots.