Edit Content

Seminaire E-Commerce recense pour vous les différents ateliers marketing digital et événements autour du numérique afin de vous accompagner dans votre formation dans le digital.

Using and Interacting with AI-Based Intelligent Technologies : Practical Applications on Autonomous Cars and Chatbots by Giulia Pavone


Artificial Intelligence (AI) is often considered as one of the most promising and disruptive innovation of our times. Despite its rapid development, there is still a high level of uncertainty about how consumers are going to adopt AI. In this context, this four-article dissertation aims to comprehend how consumers use and interact with intelligent technologies, in particular focusing on two current applications: chatbots and autonomous vehicles (AVs). First, we conduct an in-depth analysis of the existing marketing literature adopting Scientometric and Theory-Context-Characteristics-Methodology approaches. Thus, we define our research questions related to 1) consumers ‘cognitive and emotional reactions when interacting with AI-based technologies that are able to simulate human-like conversations; 2) factors affecting consumers ‘intention to use AI-based technologies able to make decision in critical situations, and their evolution across levels of automation; 3) consumers ethical concerns towards AI products and their effect on trust and usage intentions. By applying three between-subject experimental designs, we answer our first research question comparing human–human versus human–chatbot interactions and highly anthropomorphic versus lowly anthropomorphic chatbots. We leverage insights mainly from Cognitive Appraisal Theory of Emotions (Roseman et al. 1990), Attribution Theory (Weiner 2000) and Theory of Anthropomorphism (Aggarwal and McGill 2007; Epley et al. 2018), showing that consumers’ responses differ when interacting with a human and a chatbot, according to the different attributions of responsibility and the different levels of anthropomorphism of the service agent. Next, we investigate the way consumers’ experience with different levels of automation affect perceptions of AI-based technologies. We use AVs as unit of analysis, integrating the UTAUT framework with Trust Theory (Mcknight et al. 2011), Privacy Calculus Theory (Dinev and Hart 2006) and Theory of Well-being (Diener 1999; Diener and Chan 2011). After implementing a within subject-design with field and simulator studies, results suggest that differentiating between the different automation levels play a key role to better understand the potential drivers of adoption as well as the cognitive reactions when using intelligent applications. Finally, we investigate consumers’ ethical concerns surrounding chatbots and AVs. We employ a mixed methods approach, using topic modeling and structural equation modeling. We show that for chatbots, the interactional and emotional component of the technology is predominant, as consumers highlight, between others, the emotional design and the lack of adaptability as main ethical issues. However, for autonomous cars, the ethical concerns rather involve cognitive perceptions related to the transparency of the algorithms, the ethical design, the safety of the technology and the accessibility. Our research offers contributions to the emerging literature on consumer behaviors related to intelligent products by highlighting the need to take into account the complexity of AI technologies across their different levels of automation and according to their intrinsic characteristics. We also offer methodological contributions thanks to the implementation of innovative experimental research designs, using advanced tools and combining qualitative and quantitative approaches. To conclude, we present implications for both managers and policymakers who want to implement AIbased disruptive technologies, such as chatbots and AVs.

Source: http://www.theses.fr/2021TOU10063


Leave a Reply

Votre adresse e-mail ne sera pas publiée. Les champs obligatoires sont indiqués avec *

Releated Posts