Factors influencing consumers' adoptions of biometric recognition payment devices: combination of initial trust and UTAUT model

Liu, Dawei; Tu, Wanying

doi:10.1504/ijmc.2021.114324

Cited by 14 publications

(7 citation statements)

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“…, 2020; Liu et al. , 2021; Liu and Tu, 2021; Moriuchi, 2021). Previous studies have indicated that users' intention is an antecedent of their resistance and behavior.…”

Section: Literature Reviewmentioning

confidence: 99%

“…After the system was applied to offline retail, it quickly gained the attention of scholars. Particularly in 2021, numerous studies on user behavior in facial recognition payment were published (Gao et al, 2020;Liu and Tu, 2021;Moriuchi, 2021). Previous studies have indicated that users' intention is an antecedent of their resistance and behavior.…”

Section: Facial Recognition Paymentmentioning

confidence: 99%

“…Unlike other mobile payment methods that use electronic information hidden in the phone, facial recognition payment exposes facial feature information during transactions. The existence of such information exposure sheds light on why a number of consumers believe that facial recognition payment entails a huge substantial privacy risk Liu and Tu, 2021;Abrahão et al, 2016). The risk of the potential occurrence of criminal activities makes privacy risk the greatest concern for individuals who use this payment method offline.…”

Section: Research Model and Hypothesesmentioning

confidence: 99%

“…Other studies have used the technology acceptance model (TAM) or the unified theory of acceptance and use of technology (UTAUT) model to analyze factors that drive users' intention (Ciftci et al. , 2021; Liu and Tu, 2021; Zhong et al. , 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Some studies have focused on the benefits and risks of facial recognition payment and analyzed its effects on consumers' resistance to or willingness to use facial recognition payment (Li et al, 2020a;. Other studies have used the technology acceptance model (TAM) or the unified theory of acceptance and use of technology (UTAUT) model to analyze factors that drive users' intention (Ciftci et al, 2021;Liu and Tu, 2021;Zhong et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Insights into customers' psychological mechanism in facial recognition payment in offline contactless services: integrating belief–attitude–intention and TOE–I frameworks

Shiau

Liu

Zhou

et al. 2023

INTR

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PurposeFacial recognition payment is an emerging mobile payment method that uses human biometrics for personal identification. The purpose of this study is to examine how users' salient beliefs regarding the technology–organization–environment–individual (TOE–I) dimensions affect their attitudes and how attitudes subsequently influence the intention to use facial recognition payment in offline contactless services.Design/methodology/approachThis study comprehensively investigates customers' decision-making psychological mechanism of using facial recognition payment by integrating the belief–attitude–intention (B–A–I) model and the extended TOE–I framework. Data from 420 valid samples were collected through an online survey and analyzed using partial least squares structural equation modeling.FindingsResearch results indicate that convenience and perceived herd exert positive effects on trust and satisfaction. Meanwhile, familiarity has a significantly positive effect only on trust but not on satisfaction. In contrast, perceived privacy risk exhibits a negative effect on both trust and satisfaction. Trust and satisfaction positively influence the intention to use facial recognition payment. Unexpectedly, self-awareness negatively moderates the effect of satisfaction on intention to use, but its effect on the relationship between trust and intention to use is non-significant.Originality/valueTo the best of the authors’ knowledge, this study is one of the early studies that explicate customers' psychological mechanism in facial recognition payment in offline contactless services through an understanding of the B–A–I causal linkages with the identification of users' perceptions from a comprehensive context-specific perspective. This study enriches the literature on facial recognition payment and explores the moderating role of self-awareness in the relationship between users' attitudes and intention to use, thereby revealing a complex psychological process in the usage of offline facial recognition payment systems.

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“…, 2020; Liu et al. , 2021; Liu and Tu, 2021; Moriuchi, 2021). Previous studies have indicated that users' intention is an antecedent of their resistance and behavior.…”

Section: Literature Reviewmentioning

confidence: 99%

Section: Facial Recognition Paymentmentioning

confidence: 99%

Section: Research Model and Hypothesesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Insights into customers' psychological mechanism in facial recognition payment in offline contactless services: integrating belief–attitude–intention and TOE–I frameworks

Shiau

Liu

Zhou

et al. 2023

INTR

View full text Add to dashboard Cite

show abstract

Acceptance of or resistance to facial recognition payment: A systematic review

Yu,

Wang,

Bian

et al. 2024

J of Consumer Behaviour

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With increasing evidence supporting the use of biometric identification methods for authentication, this study aims to enhance our understanding of the factors influencing the acceptance of and resistance to facial recognition payment (FRP) systems. To provide a comprehensive review of these factors, we conducted a systematic literature review (SLR) of empirical studies. We examined 22 key research articles from an initial pool of 1372 publications, identifying 37 factors that influence consumer acceptance or resistance to FRP. These factors were categorized into usage‐related aspects, attitudes and evaluations, user‐related traits, privacy and security concerns, and other factors. Our findings reveal that the most frequently cited factors include performance expectancy, effort expectancy, perceived usefulness, and perceived ease of use. These factors are crucial in contexts where FRP can increase productivity by providing prompt information and effective assistance. This research proposes a collective model for understanding the determinants of FRP acceptance or resistance, integrating theoretical frameworks and empirical findings. The model emphasizes the context‐dependency of user acceptance, highlighting the importance of addressing both technological and psychological factors. It incorporates usage characteristics, user characteristics, and privacy and security concerns, which are mediated by attitudes and evaluations. The proposed model provides a comprehensive framework for understanding and addressing the factors influencing acceptance of and resistance to FRP, guiding FRP service providers in developing effective strategies to increase user adoption, with future research needed to refine and assess the model further.

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Canopy-attention-YOLOv4-based immature/mature apple fruit detection on dense-foliage tree architectures for early crop load estimation

Chen

Zhang

et al. 2022

Computers and Electronics in Agriculture

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Factors influencing consumers' adoptions of biometric recognition payment devices: combination of initial trust and UTAUT model

Cited by 14 publications

References 0 publications

Insights into customers' psychological mechanism in facial recognition payment in offline contactless services: integrating belief–attitude–intention and TOE–I frameworks

Insights into customers' psychological mechanism in facial recognition payment in offline contactless services: integrating belief–attitude–intention and TOE–I frameworks

Acceptance of or resistance to facial recognition payment: A systematic review

Canopy-attention-YOLOv4-based immature/mature apple fruit detection on dense-foliage tree architectures for early crop load estimation

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