The impact of voice assistants’ intelligent attributes on consumer well-being: Findings from PLS-SEM and fsQCA

Kang, Weiyao; Shao, Bingjia

doi:10.1016/j.jretconser.2022.103130

Cited by 74 publications

(38 citation statements)

References 75 publications

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“…Based on the data, the first article using this method was published in 2003 (Tsutsumi & Yong-Sun, 2003) and then in 2005 (Byrne, 2005). The most recent article is published in 2023 (Kang & Shao, 2023). As shown in Figure 2, a few consumer research journals published articles using fsQCA.…”

Section: Resultsmentioning

confidence: 99%

“…Future Research Question 1: How do contextual variables at different levels interact with one another to trigger a specific consumption pattern? Kang and Shao (2023); Septianto and Chiew (2018); Um et al (2022) Future Research Question 2: What variables within the consumer behavioral contexts are complementary and which variables are non-complimentary?…”

Section: Factors Affecting Consumer Behaviormentioning

confidence: 99%

“…Researchers have used fsQCA along with other methods to finder deeper insights and also to achieve data triangulation(Das & Jebarajakirthy, 2020;Sa gkaya Güngör & Ozansoy Çadırcı, 2022) Manosuthi et al (2022). used fsQCA with IGSCA-SEM to examine green consumption behavior within tourism Kang and Shao (2023). also used it with SEM to understand the impact of voice assistants' intelligent attributes on consumer wellbeing.…”

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confidence: 99%

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Fuzzy‐set qualitative comparative analysis in consumer research: A systematic literature review

Diwanji

2022

Int J Consumer Studies

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The traditional symmetrical methods may not be sufficient for effectively examining the asymmetries that are evident in the real‐world complex consumption context in the form of pandemic, and other technological, sociocultural, environmental, and geo‐political factors. As a result, the use of innovative and asymmetrical methods such as fuzzy‐set qualitative comparative analysis (fsQCA), which draws from the complexity theory could help better predict and explain consumer decisions in the age of disruptions. Through a comprehensive method‐based systematic literature review of 129 research articles published in the consumer behavior research literature, this study helps to identify the key trends, leading publication sources and contributors, and the current knowledge structure of consumer research using fsQCA. In doing so, this review also sheds light on the state of diversity within this particular area of research. The findings help identify the key future avenues for utilizing fsQCA within consumer research. This review is a useful resource for practitioners to gain a direct access to key consumer research scholars for identifying the constructs (e.g., antecedents, mediators, moderators, enablers, inhibitors) shaping consumer behaviors to inform strategic decisions.

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Section: Resultsmentioning

confidence: 99%

Section: Factors Affecting Consumer Behaviormentioning

confidence: 99%

mentioning

confidence: 99%

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Fuzzy‐set qualitative comparative analysis in consumer research: A systematic literature review

Diwanji

2022

Int J Consumer Studies

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“…Furthermore, psychological and design-specific factors impact smart voice assistant usage and word-of-mouth according to Mishra et al (2022). Also, Aw et al (2022) (Kautish et al, 2023), consumer-brand relationships, and consumers' well-being (Kang & Shao, 2023), the well-being and emotional connection that users have with both AI devices and their associated brands (Prentice et al, 2023), and the relationship between customer experience, satisfaction and recommendation (De Oliveira et al, 2023).…”

Section: Background On Voice Assistantsmentioning

confidence: 99%

“…Furthermore, Maroufkhani et al (2022) focused on the effect of brand credibility and the hedonic, utilitarian, and social presence factors on brand loyalty and continuous intention in voice assistant context. Recently, studies have examined what motivates users to adopt voice assistants for different purposes such as enhancing fashion shopping (Kautish et al, 2023), consumer–brand relationships, and consumers' well‐being (Kang & Shao, 2023), the well‐being and emotional connection that users have with both AI devices and their associated brands (Prentice et al, 2023), and the relationship between customer experience, satisfaction and recommendation (De Oliveira et al, 2023).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Consumer engagement with AI‐powered voice assistants: A behavioral reasoning perspective

Açikgöz

Perez‐Vega

Okumuş

et al. 2023

Psychology and Marketing

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This study draws upon Behavioral Reasoning Theory and the Technology Acceptance Model to investigate consumer engagement with AI‐powered voice assistants. The study creates a theoretical model to examine the effects of reasons for and reasons against using voice assistants. This research exemplifies attitudes towards using voice assistants and willingness to provide personal information as key constructs. The current study tests data from 491 voice assistant users via mTurk, and we utilize a multimethod analysis scheme including the partial least squares technique and the fuzzy set qualitative comparative analysis approach to provide an assessment of the proposed model. Findings indicated that while privacy cynicism has a negative impact upon the attitude towards using voice assistants, the countervailing values of trust, perceived usefulness, and ease of use have off‐setting positive impact. The study also highlights the moderating role of habit on the behavioral mechanisms driving consumer engagement via willingness to provide privacy information. This research advances the emerging literature on voice assistants with respect to privacy‐related factors driving consumer engagement.

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Love it or hate it? Deconstructing consumers' attitudes towards AI enabled voice shopping

Kamoonpuri,

Sengar

2024

J of Consumer Behaviour

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The conversational, social and intelligent capabilities of Artificial Intelligence (AI) enabled voice assistants (VAs) to assist humans have grown. However, their use still remains limited for complex tasks such as shopping. While some studies find that consumers are willing to use them, others report negative reactions that lead to rejection, especially for complex activities. This study aims to bridge the gap between the dichotomous streams of literature by investigating the overall attitude towards the use of AI VAs for a multi‐step task that is, shopping. We first identify 27 attitudinal criteria through a comprehensive literature review in light of the Uncanny Valley Theory and the Self Determination Theory. The criteria are organized using the cognitive, affective and conative framework of attitude, and ranked using the Fuzzy Analytical Hierarchy Process. Sensitivity analysis is done to affirm the robustness of the framework. Findings reveal that the behavioral intentions to use (conative criteria) are the strongest, followed by feelings evoked during use (affective criteria), followed by beliefs people hold regarding AI VAs (cognitive criteria). Intention to use AI voice assistants during all stages of the purchase journey takes precedence over negative feelings such as loss of control, unfulfillment and vulnerability. This study reconciles the existing stream of literature on conversational AI and provides managerial implications based on the dimensions of attitude.

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The impact of voice assistants’ intelligent attributes on consumer well-being: Findings from PLS-SEM and fsQCA

Cited by 74 publications

References 75 publications

Fuzzy‐set qualitative comparative analysis in consumer research: A systematic literature review

Fuzzy‐set qualitative comparative analysis in consumer research: A systematic literature review

Consumer engagement with AI‐powered voice assistants: A behavioral reasoning perspective

Love it or hate it? Deconstructing consumers' attitudes towards AI enabled voice shopping

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