Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot

Abstract

Consumers sometimes describe their experience of interacting with artificial intelligence‐based human‐like chatbots as creepy. This study investigates the antecedents of creepiness (i.e., the chatbot's usability, privacy concerns, and user variables such as technology anxiety and the need for human interaction) and its impact on consumer loyalty. Grounded in the technology paradox, it deepens the understanding of creepiness in light of the theoretical underpinnings of the privacy paradox and privacy cynicism. Presented with the task of obtaining a car insurance quote, 430 consumers participated in a simulation involving interaction with a chatbot, followed by a questionnaire. The findings show that creepiness decreases loyalty and indirectly impacts it through trust and negative emotions. While usability reduces perceptions of creepiness, privacy concerns raised by the interaction with the chatbot increase creepiness, which is positively associated with consumer traits (i.e., technology anxiety and need for human interaction). The main contribution of the research lies in its focus on creepiness, a concept under‐researched in the marketing literature, and which can be seen from the perspective of a coping mechanism for consumers’ privacy concerns. This paper provides practical implications to orient managers in the design and implementation of chatbots, as a promising touch point to build customer loyalty.

What drives continuance intention to use a food-ordering chatbot? An examination of trust and satisfaction

“…Concerning the factors of positive attitude, trust and satisfaction will be the main factors of online behaviors in the chatbot context (Rajaobelina et al, 2021;Cheng et al, 2021;Nguyen et al, 2021). Previous research indicated that trust could be an affective attitude (Jones, 1996).…”

“…Concerning the factors of positive attitude, trust and satisfaction will be the main factors of online behaviors in the chatbot context (Rajaobelina et al. , 2021; Cheng et al , 2021; Nguyen et al.…”

Reinforcing customer journey through artificial intelligence: a review and research agenda

“…(2017), this stage “covers all customer interactions with the brand and its environment during the actual purchase event itself. Characterised by behaviors such as choice, ordering, payment.” Chatbot helps customers make online purchasing processes in the insurance sector by categorizing the customers into segments and providing apt responses to each segment (Rajaobelina et al. , 2021).…”

Trust and digital privacy: willingness to disclose personal information to banking chatbot services

“…Similarly, Alashoor et al ( 2017 ) explored these dimensions of trust with respect to users’ privacy concerns in relation to user self-disclosure behaviour, while Nyugen and Khoa ( 2019 ) explored online trust. Rajaobelina et al, ( 2021a , b ) went as far as to better understand the creepiness of chatbots, of which privacy concerns were key.…”

“…Additional research can focus on messaging specific themes (use of language, colloquialism and personalities) in order to create a more comfortable user experience that encourages the disclosing of information as well as the possibilities of chatbot to chatbot interactions (Hasal et al 2021 ; de Cosmo et al 2021 ). A comparison between chatbot interactions and live chat interactions (Rajaobelina 2021b ) could also help to build an effectiveness measurement framework. Finally, emergent legislation like the General Data Protection Regulation (GDPR) in Europe or the Protection of Personal Information (POPIA) in South Africa where this study was based will shape the way people feel about disclosing personal information (potentially both positively and negatively) and hence future research will need to encompass a legislative viewpoint as this develops further globally (Coopamootoo et al 2022 ; Netshakhuma 2020 ).…”