The degree of confidence and reliability placed in technology by users. It influences the adoption and usage of technological products and is shaped by WOM and prior experiences (King et al., 2014; Liu & Lopez, 2016).
Published in Chapter:
Consumers' Drivers of Generative Pre-Trained Transformer (GPT) Conversational Bot Adoption
Omar H. Fares (Toronto Metropolitan University, Canada), Queenie Zhu (Toronto Metropolitan University, Canada),
Seung Hwan (Mark) Lee (Toronto Metropolitan University, Canada), and
Joseph Aversa (Toronto Metropolitan University, Canada)
Copyright: © 2024
|Pages: 32
DOI: 10.4018/979-8-3693-1239-1.ch005
Abstract
This chapter examines the relationship between society and artificial intelligence (AI), emphasizing the factors driving consumer adoption of AI conversational bots. The authors examine how societal norms, past experiences, and trust in technology influence the acceptance and usage of generative-pre trained transformer (GPT) bots. They provide a theoretical framework, integrating key concepts from social influence and technology acceptance theory, to understand the complex dynamics of GPT bot adoption. Conducting a survey, they analyze data from 412 participants in North America to test various hypotheses. The findings broadly support the proposed model, highlighting the significant roles of social norms, word of mouth, and trust in shaping consumer behaviour towards AI conversational bots. However, an intriguing exception is found in the lack of a direct relationship between behavioural intention and actual technology usage, pointing to the need for further investigation into the factors that bridge the gap between the intention to use and the actual use of AI technologies in everyday contexts.