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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Guerreiro, J. & Loureiro, S. M. C. (2020). How the Mind Perception of Artificial Intelligence in Smart Devices Affects Customer-Brand Relationships. In AIRSI 2020.
Exportar Referência (IEEE)
J. R. Guerreiro and S. M. Loureiro,  "How the Mind Perception of Artificial Intelligence in Smart Devices Affects Customer-Brand Relationships", in AIRSI 2020, 2020
Exportar BibTeX
	author = "Guerreiro, J. and Loureiro, S. M. C.",
	title = "How the Mind Perception of Artificial Intelligence in Smart Devices Affects Customer-Brand Relationships",
	booktitle = "AIRSI 2020",
	year = "2020",
	editor = "",
	volume = "",
	number = "",
	series = "",
	publisher = "",
	address = "",
	organization = "",
	url = ""
Exportar RIS
TI  - How the Mind Perception of Artificial Intelligence in Smart Devices Affects Customer-Brand Relationships
T2  - AIRSI 2020
AU  - Guerreiro, J.
AU  - Loureiro, S. M. C.
PY  - 2020
SN  - 0000-0000
UR  -
AB  - Artificial Intelligence (AI) has grown from an established science focused on improving its techniques and algorithms to be incorporated in our daily lives. The demand in AI systems will hit $77.6 billion in 2022 (IDC, 2019) and there are already many examples of AI systems embedded in self-driving cars, surveillance cameras and in voice-assistant smart devices. Despite data privacy concerns, consumers still value the advantages of an integrated smart society which reduces repetitive tasks and improves convenience and performance (TechCrunch, 2019).
The current paper explores the role of mind perception in establishing customer-brand relationships using artificial intelligence enabled-devices. As smart devices powered by AI become more knowledgeable, they also gain the ability to recommend and sometimes even make decisions (e.g. deciding the next best music to play on Spotify). Such intelligence, driven from customer-data, may sometimes suggest that the AI agent has a mind of its own. Mind perception refers to the ability to determine and organize behaviors (agency dimension) and the ability to feel emotions and display personality (experience dimension) (Morera et al., 2018). To understand the role of mind perception in customer-brand relationships, the current paper is grounded on attachment-aversion (AA) theory (Park, 2013; Schmitt, 2013). The AA theory suggests that moods and emotions (affective dimension), actions and interactive experiences (behavioral dimension) and convergent/analytical thinking and divergent/imaginative thinking about a brand (intellectual dimension) – the marketing determinants - may influence if a brand entices/annoys the self, enables/disables the self, or enriches/impoverishes the self – the psychological determinants (Schmitt, 2013). Such determinants are then suggested to have a role in explaining attachment-aversion relationships and motivational strength (approach, avoidance and enhancement). Following the AA theory, we suggest that experiences between consumers and the AI agents in the smart devices positively entices the self – an experiential (hedonic) benefit which refers to how appealing and attractive the AI agent embedded in the smart device is to the consumer (H1), positively enables the self – a functional benefit which refers to the extent to which the AI agent embedded in the smart device satisfies the needs of the consumer and helps the consumer to manage daily activities (H2) and positively enriches the self – a symbolic benefit which measures the extent to which the smart device expresses, represents or reinforces the consumer values  (H3). We also suggest that as consumers are more enabled (H4), enticed (H5) or enriched (H6) due to the experiences with the AI-enabled smart devices, they feel a higher level of attachment towards the brand and therefore, a higher level of motivational strength (higher approach, maintenance and enhancement). Yet, given that smart devices mind perception may reduce the consumers’ sense of control over their own actions, we suggest that smart devices perceived as having a higher degree of mind perception will reduce the link between enriching and motivational strength (H7).
An online survey was conducted focusing on both US and Indian consumers via the Amazon Mechanical Turk (MTurk). The scales to measure the constructs were adapted from past research (see Figure 1). A total of 99 consumers that own and use a smart device for at least a month, participated in the study. 49 participants are from India and 51 participants from the US. A reflective PLS-SEM model was estimated with all outer loadings equal or above 0.7 and reliability measures confirming to the standards with all composite reliability scores above 0.7 and AVE above 0.5 (Hair et al., 2010). There were also no multicollinearity effects.

Results show that all the hypothesis are supported. The affective dimension of the smart device experience is positively related to enticing (?=.321, p < .01), the behavior dimension of the experience positively enables consumers (?=.246, p < .05) and the intellectual experience has a positive relationship with enriching consumers (?=.501, p < .01). Also, results show that enticing, enabling and enriching explain 78.0% of motivational strength and are all significant and positively related to such construct. The study also shows that mind perception of artificial intelligence in smart devices has a negative moderation on the relationship between enriching and motivational strength. Therefore, as mind perception increases, the effect of enriching the self in motivational strength to continue the relation is lower. 
The current paper makes some key contributions. First, we empirically test the validity of the AA theory of customer-brand relationships using artificial intelligence enabled-devices. Second, we show how the impact of psychological determinants on motivational strength is moderated by the mind perception of the AI agents. Such findings may present valuable insights for managers that want to design AI systems to interact with their consumers in the future.

ER  -