Exploring the influence of artificial intelligence technology on consumer repurchase intention: The mediation and moderation approach

Nazir, Sajjad; Khadim, Sahar; Asadullah, Muhammad; Syed, Nausheen

doi:10.1016/j.techsoc.2022.102190

Cited by 38 publications

(16 citation statements)

References 99 publications

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“…The study also contributes by demonstrating the applicability of both regulatory focus and regulatory fit in explaining the interaction between consumers and AI‐powered technologies. Literature in the past has employed different psychological theories to explain the interaction, such as behavioural reasoning theory (Acikgoz et al, 2023; Jan et al, 2023), stimulus‐organism‐response theory (Nazir et al, 2023), and unified theory of acceptance and use of technology (Moriuchi, 2021; Silva et al, 2023). Based on the regulatory focus theory, the present study demonstrates that promotion focus can mitigate the negative effect of AI‐powered technology, such as chatbots, on consumers.…”

Section: Discussionmentioning

confidence: 99%

Consumers' promotion focus mitigates the negative effects of chatbots on purchase likelihood

Khan,

Sararueangpong,

Mathmann

et al. 2023

J of Consumer Behaviour

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Marketers and consumers are adopting chatbots widely. However, the benefits of this technology remain unclear due to a lack of understanding about individual differences in consumers' purchase decisions when interacting with chatbots. This research investigates the influence of individual differences in promotion focus on purchase likelihood for the products recommended by chatbots. Two experiments demonstrated that consumers generally report a lower purchase likelihood for products recommended by chatbots (vs humans). However, compared to consumers with a low promotion focus, consumers with a high promotion focus report a higher purchase likelihood for the products. The findings also suggest that the relationship between consumer individual differences in promotion focus and purchase likelihood is mediated by engagement. By applying both regulatory focus and regulatory fit theories, the present study provides insights into how promotion focus influences purchase likelihood for products recommended by chatbots. Marketers can utilise both chronic and situational promotion focus to improve consumers' reactions to chatbots using segmentation and promotion‐focus‐related words, respectively.

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Section: Discussionmentioning

confidence: 99%

Consumers' promotion focus mitigates the negative effects of chatbots on purchase likelihood

Khan,

Sararueangpong,

Mathmann

et al. 2023

J of Consumer Behaviour

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“…Theoretical foundations AI-based technologies have been extensively deployed by the hospitality industry to enhance service quality and engage consumers (Prentice et al, 2020). These systems can replace human tasks while increasing transaction speed and accuracy (Nam et al, 2021), becoming similar to humans by replicating human cognition and behavior through their enhanced abilities (Nazir et al, 2023). Hence, autonomous AI-based agents are increasingly replacing a significant part of human-to-human interactions with an artificial mind that enables them to act like humans (Nath and Sahu, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

“…growth in sales (Hollebeek et al , 2014), intentions to stay (Wang et al , 2022), intentions to revisit (Rather, 2021; Rather et al , 2022) and positive price perceptions (Bergel and Brock, 2019). Hence, increased levels of engagement with AI-based systems derived from positive warmth and competence perceptions may result in positive consumer experiences and increased revenue with a loyal customer base (Nazir et al , 2023) and increased intentions to stay. Additionally, positive consumer experience may lead consumers to leave a larger tip (Lynn et al , 1993) that can be used as a training mechanism for AI-based systems allowing them to continuously learn consumers’ preferences and make better decisions (Cain and Berezina, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Tips and trips: a structural model of guests’ intentions to stay and tip for AI-based services in hotels

Morosan,

Dursun-Cengizci

2023

JHTT

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Purpose Given the rapid development in artificial intelligence (AI), the hotel industry is deploying AI-based systems. In line with this important development, this study aims to examine the impact of trust in the hotel and AI-related performance ambiguity on consumers’ engagement with AI-based systems. This study ultimately examined the impact of engagement on consumers’ intentions to stay in hotels offering such systems, and intentions to tip. Design/methodology/approach This study developed a conceptual model based on the social cognition theory. The study used an online survey methodology and collected data from a nationwide sample of 400 hotel consumers from the USA. The data analysis was conducted with structural equation modeling. Findings Consumers’ engagement is strongly influenced by their trust in the hotel but not by performance ambiguity associated with AI. In turn, engagement strongly influenced consumers’ intentions to stay in hotels that have such systems and their intentions to tip. Originality/value As AI systems capable of making decisions for consumers are becoming increasingly present in hotels, little is known about the way consumers engage with such systems and whether their engagement leads to economic impact. This is the first study that validated a model that explains intentions to stay and tip for services facilitated by autonomous AI-based systems that can make decisions for consumers.

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“…AI‐powered marketing is increasingly popular in various industries, as it reduces costs, increases revenue, and boosts customer satisfaction. It influences purchases and enables impulse buying using big data (Johnson et al, 2022; Nazir et al, 2023). Many organizations and their marketing teams utilize innovative and speedy technology solutions to enhance operational efficiency and customer satisfaction.…”

Section: Introductionmentioning

confidence: 99%

“…tion. It influences purchases and enables impulse buying using big data (Johnson et al, 2022;Nazir et al, 2023). Many organizations and their marketing teams utilize innovative and speedy technology solutions to enhance operational efficiency and customer satisfaction.…”

mentioning

confidence: 99%

AI marketing and AI‐based promotions impact on consumer behavior and the avoidance of consumer autonomy threat

Spais,

Phau,

Jain

2023

J of Consumer Behaviour

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Exploring the influence of artificial intelligence technology on consumer repurchase intention: The mediation and moderation approach

Cited by 38 publications

References 99 publications

Consumers' promotion focus mitigates the negative effects of chatbots on purchase likelihood

Consumers' promotion focus mitigates the negative effects of chatbots on purchase likelihood

Tips and trips: a structural model of guests’ intentions to stay and tip for AI-based services in hotels

AI marketing and AI‐based promotions impact on consumer behavior and the avoidance of consumer autonomy threat

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