MODELING THE CONSUMER ACCEPTANCE OF RETAIL SERVICE ROBOTS

This study uses the Computers Are Social Actors (CASA) and domestication theories as the underlying framework of an acceptance model of retail service robots (RSRs). The model illustrates the relationships among facilitators, attitudes toward Human-Robot Interaction (HRI), anxiety toward robots, anticipated service quality, and the acceptance of RSRs. Specifically, the researcher investigates the extent to which the facilitators of usefulness, social capability, the appearance of RSRs, and the attitudes toward HRI affect acceptance and increase the anticipation of service quality. The researcher also tests the inhibiting role of pre-existing anxiety toward robots on the relationship between these facilitators and attitudes toward HRI. The study uses four methodological strategies: (1) incorporating a focus group and personal interviews, (2) using a presentation method of video clip stimuli, (3) empirical data collection and multigroup SEM analyses, and (4) applying three key product categories for the model’s generalization— fashion, technology (mobile phone), and food service (restaurant). The researcher conducts two pretests to check the survey items and to select the video clips. The researcher conducts the main test using an online survey of US consumer panelists (n = 1424) at a marketing agency. The results show that usefulness, social capability, and the appearance of a RSR positively influence the attitudes toward HRI. The attitudes toward HRI predict greater anticipation of service quality and the acceptance of the RSRs. The expected quality of service tends to enhance the acceptance. The relationship between social capability and attitudes toward HRI is weaker when the anxiety toward robots is higher. However, when the anxiety is higher, the relationship between appearance and the attitudes toward HRI is stronger than those with low anxiety. This study contributes to the literature on the CASA and domestication theories and to the human-computer interaction that involves robots or artificial intelligence. By considering social capability, humanness, intelligence, and the appearance of robots, this model of RSR acceptance can provide new insights into the psychological, social, and behavioral principles that guide the commercialization of robots. Further, this acceptance model could help retailers and marketers formulate strategies for effective HRI and RSR adoption in their businesses

Anthropomorphism of AI-based Intelligent Customer Service, and Its Affective and Behavioral Consequences

Recently, as many users turn to social media to interact with service providers, organizations apply Artificial intelligence (AI) to improve the efficiency and effectiveness of the operation. This type of customer service system is called intelligent customer service (ICS) which one of the most commonly adopted tools is chatbot. Since chatbot is AI-empowered, whether this system can effectively interact with customers and solve their problems is critical. However, the quality of ICS has received significant attention recently, and a lack of systematic study on the outcomes of anthropomorphism leaves this question unanswered in an ICS context. Based on a cognitive-affective-behavioral framework, this study attempts to understand whether anthropomorphism can promote desired behaviors (including usage and citizen-ship behaviors) through enhancing affective out-comes, such as satisfaction and identity. Data collected from 183 chatbot-ICS users, this study illustrates how anthropomorphism can increase quality, enhance satisfaction and identity. Furthermore, we also show that satisfaction and identity lead to further usage and citizenship behaviors. This highlights the importance of increasing anthropomorphism for the chatbot-ICS

The Role of Congruity And Rejection Sensitivity

Goncalves, A. R., Meira, A. B., Shuqair, S., & Pinto, D. C. (2023). Artificial Intelligence (AI) in Fintech Decisions: The Role of Congruity And Rejection Sensitivity. International Journal of Bank Marketing. https://doi.org/10.1108/IJBM-07-2022-0295 --- This work received partial support from national funds through FCT (Fundação para a Ciência e a Tecnologia), under the projects - UIDB/04152/2020 - DSAIPA/DS/0113/2019 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS project.Purpose - The digital revolution has changed consumer–service provider interaction, spawning a new generation of FinTech. This paper analyzes consumers' reactions to Artificial Intelligence (AI) (vs. human) decisions. Design/methodology/approach – We tested our predictions by conducting two experimental studies with FinTech consumers (n=503). Findings – The results reveal that consumers' responses to AI (vs. human) credit decisions depend on the type of credit product. For personal loans, the rejection by an AI provider triggers higher levels of satisfaction compared to a credit analyst. This effect is explained via the perceived role congruity. In addition, the findings reveal that consumers' rejection sensitivity determines how they perceive financial services role congruity. Originality/value – To the best of the authors' knowledge, this research is the first to jointly examine AI (vs. human) credit decisions in FinTech and role congruity, extending prior research in the field.authorsversionepub_ahead_of_prin

Artificial Intelligence and Robotics in Marketing

This chapter illustrates the role of artificial intelligence (AI) and robotics in marketing and will help managers develop a deeper understanding of its potential to revolutionize the service experience. We summarize the use of AI and robots in practice and show that the adoption of AI predominantly occurs at the task level rather than the job level, implying that AI takes over some tasks that are part of a job and not the entire job. Based on these insights, we discuss opportunities and drawbacks of AI and robots and reflect on whether service robots will complement or substitute human employees. Moreover, we explain why many consumers are still reluctant to engage with these new technologies and which conditions should be met in order to benefit from using service robots

AI and Gender in Persuasion: Using Chatbots to Prevent Driving Under The Influence of Marijuana

Will new media techniques, such as artificial intelligence (AI), help refresh public safety advertising campaigns and help better target specific populations, and aid in persuasive, preventative marketing? This paper used hypocrisy induction as a persuasive tool for standalone artificial intelligence chatbots to test potential behavioral change in the context of marijuana. This research further tested whether the chatbots\u27 gender and language styles impact how persuasive and effective the chat agents are perceived to be using hypocrisy induction. An online experiment conducted with 705 participants (Mage = 42.9, 392 women). where participants interact with a chatbot that is manipulated as male/female and uses formal/causal language. Half of the participants received the hypocrisy induction manipulation. hypocrisy induction is more effective when chatbot gender and linguistic styles are appropriately paired. Participants in the hypocrisy induction condition exhibited higher WTP than those in the non-hypocrisy induction condition when the chatbot they interacted with was female in gender and used casual language. However, hypocrisy induction increased WTP than those who did not receive the hypocrisy induction manipulation when the gender of the chatbot they interacted with was male and used formal language. To the researchers\u27 knowledge, this is among the first studies testing the persuasive power of hypocrisy induction using new media platforms in public safety and health advertising in marijuana studies. Findings not only help to shed light on the persuasiveness of gender and language in standalone chatbots but also provide practical implications for practitioners on the future usage of chatbots

New Bots – The Influence of a Conversational Agent’s Rookie Personality on Users’ Satisfaction

Conversational agents (CAs) are not likely to be error-free, and efforts are being made by research and practice to mitigate the negative consequences of such errors (e.g., reduced service satisfaction). In this context, our study examines the impact of a CA\u27s rookie personality (i.e., the CA expresses that it is new and still learning) on users. Our findings reveal that the rookie personality is a double-edged sword: while it increases users\u27 perception of humanness, which increases the perception of reliability, it also directly reduces perceived reliability, resulting in less service satisfaction. To explain these seemingly contradictory effects, we turn to the dual processing theory of cognition and propose that the rookie personality influences both automatic and deliberate thinking. Users actively and consciously contemplate the CA\u27s messages, leading them to view the software artifact as broken and low-quality. Additionally, users\u27 automatic thinking is influenced by the perception of humanness