Predicting continuance intention to fintech chatbot

Huang, Stanley Y. B.; Lee, Chih-Jen

doi:10.1016/j.chb.2021.107027

Cited by 45 publications

(23 citation statements)

References 62 publications

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“…The first "snapshot" shows that feelings of contentment (PACX), feelings of anger (NACX-A), the perceived usefulness (UCCX) and friendliness (SCCX) of the digital assistant, and willingness to trust in the digital assistant (TRU) are predictors of purchase intention (PI) (see Figure 6.16). These findings are aligned with other studies that show that emotions and perceptions of usefulness and social presence derived from interactions influence behavioural intentions, such as continued usage of a digital robot for searching tasks (Adam et al, 2021;Fan et al, 2016;S. Y.…”

Section: Relationships Between Affective and Cognitive Customer Exper...supporting

confidence: 90%

“…B. Huang & Lee, 2022;Trivedi, 2019). On the other hand, although in the context of health, some studies show that digital assistants can also deliver affective experiences, driven by human-likeness realism (HLR) (Clark et al, 2019;Daily et al, 2017;Tussyadiah & Park, 2018).…”

Section: Digital Assistants and Service Marketingmentioning

confidence: 99%

“…B. Huang & Lee, 2022). Human-like attributes are also important in creating a sense of engagement with a digital assistant by increasing the immersion in the interaction (Tao et al, 2008), thereby increasing the probabilities of compensatory behaviour, such as purchases (Michaud Trevinal & Stenger, 2014).…”

Section: Studymentioning

confidence: 99%

“…B. Huang & Lee, 2022), trust in the digital assistant (Nordheim et al, 2019) and purchase intention (Sands et al, 2021). Digital assistant interface technology has been developed to the point that human-robot interactions are more natural and human-like (Chaves & Gerosa, 2021).…”

Section: Introduction 11 Backgroundmentioning

confidence: 99%

“…Martin et al (2015) conducted an online survey on 555 users of an online retailer and find that affective experiences in the online interaction positively influence trust in the online retailer.Regarding behavioural intentions, S. Y. B Huang and Lee (2022). conducted a three-stage longitudinal study on 470 bank users to research attitudes towards chatbots, based on the social response theory (i.e., human tendency to convey human roles to computers and robots).The study finds that: (1) social experiences and chatbot credibility positively influence positive affective experiences; (2) positive affective experiences increase positive attitudes towards the chatbot; and (3) positive attitudes positively increase the intention to continue using the chatbot.…”

mentioning

confidence: 99%

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Human-Likeness Realism Of Digital Assistants’ Interface: Effects On Customer Experience, Trust In Digital Assistants And Purchase Intention

Gonzalez¹

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Companies are increasingly incorporating digital assistants on their websites to improve the customer experience in their online frontline services. However, despite their functional advantages, digital assistants have yet to provide optimal customer experiences and rewarding interactions for firms and customers. For example, customers are prone to stop interacting with digital assistants, which affects sales processes. Emotional and social aspects in service encounters provided by human contact are essential for excellent customer service, which is relevant in online services because online platforms limit human contact. In this context, designing an optimal digital assistant interface with adequate human-like characteristics is necessary to enhance digital assistants with emotional and social cues. Although several studies have found relationships between human likeness and concepts such as customer experiences, trust, and behavioural intentions, to the best understanding of this study, more research is needed to observe the effects of different types of human likeness realism on a wide range of types of feelings, thoughts and beliefs; to look at them from a multidimensional approach; and to use a combination of affect-as-information, information-processing, social presence, human-likeness realism and uncanny valley theories. A question identified is whether making a digital assistant interface look more human-like improves its acceptance and use by providing a more pleasant experience and making it look more trustworthy. This dissertation aims to answer the following research questions: (1) To what extent do different levels of human-likeness realism (HLR) in digital assistant interfaces influence affective and cognitive customer experiences, willingness to trust in digital assistants and purchase intention?; (2) To what extent do (a) affective and cognitive customer experiences formed from the interaction with digital assistants and (b) willingness to trust in digital assistants influence the intention to purchase from a digital assistant?; and (3) To what extent does HLR moderate the relationships between affective and cognitive customer experiences, willingness to trust in digital assistants and purchase intention? A conceptual model was built to help identify: (1) the effects of low, medium and high HLR characteristics of digital assistants on positive and negative affective customer experiences, cognitive customer experiences, willingness to trust in digital assistants, and intent to purchase from a digital assistant; and (2) the process that explains the role of customer experience and willingness to trust in digital assistants in customers’ intention to purchase from digital assistants with human-like characteristics. A between-subjects experiment was designed to test the effects of low, medium and high HLR in positive and negative affective customer experiences, utilitarian, immersive and social cognitive customer experiences, willingness to trust in a digital assistant and purchase intention. One-way ANOVA tests were used to test the differences produced by each type of digital assistant interface tested. Linear regressions were used to test the relationship between the variables. This study contributes in four ways. First, High HLR is presented as a breaking point where the perception of affective CX, TRU, and PI turns into negative outcomes. Second, it was observed that, although human likeness is a crucial element in creating positive feelings and thoughts about the digital assistant, low to medium HLR characteristics did not appear to produce significant changes in affective and cognitive customer experiences, willingness to trust in digital assistants and purchase intention. The non-significant differences are potentially explained by the presence of a human likeness ceiling in the effects of HLR on dependent variables. Third, affective customer experience is a major driver of cognitive customer experience, willingness to trust and purchase intention. Fourth, although interaction with digital assistants creates a state of immersion, this does not appear to convert into higher trust nor purchase intentions. These findings suggest to marketing practitioners that digital assistants should be designed with low or medium HLR characteristics in opposition to high HLR characteristics to produce optimal interactions.

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Section: Relationships Between Affective and Cognitive Customer Exper...supporting

confidence: 90%

Section: Digital Assistants and Service Marketingmentioning

confidence: 99%

Section: Studymentioning

confidence: 99%

Section: Introduction 11 Backgroundmentioning

confidence: 99%

mentioning

confidence: 99%

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Human-Likeness Realism Of Digital Assistants’ Interface: Effects On Customer Experience, Trust In Digital Assistants And Purchase Intention

Gonzalez¹

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Chatbots in frontline services and customer experience: An anthropomorphism perspective

Nguyen

Ferm

Quach

et al. 2023

Psychology and Marketing

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This study measures the effects of chatbot anthropomorphic language on customers' perception of chatbot competence and authenticity on customer engagement while taking into consideration the moderating roles of humanlike appearance and brand credibility. We conducted two experimental studies to examine the conceptual framework. Study 1 tests the moderating effect of a chatbot's anthropomorphic appearance on the relationship between chatbots' language and customer engagement. Study 2 tests the moderating effect of brand credibility on the relationship between a chatbot's anthropomorphic language and customer engagement. The findings confirm that the interaction between humanlike appearance via the use of avatars and anthropomorphic language, such as using emojis, in conversations with customers influences customer engagement, and that this effect is mediated by perceived chatbot competence and authenticity. Further, the positive effect of anthropomorphic language on perceived competence, and subsequently on authenticity and engagement, is only significant when the brand credibility was low (vs. high). This study offers insights into the effect of chatbots' anthropomorphic language and provides suggestions on how to devise efficient strategies for engaging customers using chatbots.

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Artificial Intelligence and Blockchain Technology in Banking: Bibliometric Analysis

Sirothiya,

Tiwari,

Khan

et al. 2024

Financial Mathematics and Fintech

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Predicting continuance intention to fintech chatbot

Cited by 45 publications

References 62 publications

Human-Likeness Realism Of Digital Assistants’ Interface: Effects On Customer Experience, Trust In Digital Assistants And Purchase Intention

Human-Likeness Realism Of Digital Assistants’ Interface: Effects On Customer Experience, Trust In Digital Assistants And Purchase Intention

Chatbots in frontline services and customer experience: An anthropomorphism perspective

Artificial Intelligence and Blockchain Technology in Banking: Bibliometric Analysis

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