Alexa, what's on my shopping list? Transforming customer experience with digital voice assistants

Aw, Eugene Cheng-Xi; Tan, Garry Wei–Han; Cham, Tat-Huei; Raman, Ramakrishnan; Ooi, Keng‐Boon

doi:10.1016/j.techfore.2022.121711

Cited by 93 publications

(44 citation statements)

References 86 publications

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“…Thus, this factor is irrelevant to EE by minimizing setting up and action-tasks specific to VA usage. Ease of use as a non-relevant factor has been established in several studies (Wirtz et al, 2018 , 2019 ; Zarouali et al, 2018 ; Balakrishnan and Dwivedi, 2021 ; Lv et al, 2021 ; Aw et al, 2022 ; Moussawi et al, 2022 ).…”

Section: Resultsmentioning

confidence: 99%

Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants

2022

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Virtual Assistants, also known as conversational artificial intelligence, are transforming the reality around us. These virtual assistants have challenged our daily lives by assisting us in the different dimensions of our lives, such as health, entertainment, home, and education, among others. The main purpose of this study is to develop and empirically test a model to predict factors that affect users' behavioral intentions when they use intelligent virtual assistants. As a theoretical basis for investigating behavioral intention of using virtual assistants from the consumers' perspective, researchers employed the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). For this research paper, seven variables were analyzed: performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, habit, and price/value. In order to improve consumer behavior prediction, three additional factors were included in the study: perceived privacy risk, trust, and personal innovativeness. Researchers carried out an online survey with 304 responses. The obtained sample was analyzed with Structural Equation Modeling (SEM) through IBM SPSS V. 27.0 and AMOS V 27.0. The main study results reveal that factors, such as habit, trust, and personal innovation, have a significant impact on the adoption of virtual assistants. However, on the other side, performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, price/value, and perceived privacy risk were not significant factors in the users' intention to adopt this service. This research paper examines the effect of personal innovation, security, and trust variables in relation to the use of virtual assistants. It contributes to a more holistic understanding of the adoption of these intelligent devices and tries to fill the knowledge gap on this topic, as it is an emerging technology. This investigation also provides relevant information on how to successfully implement these technologies.

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Section: Resultsmentioning

confidence: 99%

Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants

2022

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“…This study suggests that in addition to the provision of user-friendly interfaces, smart retailers should strive to enrich smart technology functionalities to continuously facilitate customers’ sense of novelty and enjoyment from the dimension of social surroundings. For example, they can implement intelligent voice services, such as AI chatbots, to provide more vivid anthropomorphic interactions (Aw et al, 2022 ). Mobile recommendations and individualized promotions based on consumer consumption history or location can also be deployed (Riegger et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

“…In general, smart technology provides win–win opportunities whereby retailers engage consumers with retail innovations and consumers acquire convenient and novel experiences and cost-effective items (Lee & Lee, 2020 ; Shankar et al, 2021 ). To the best of our knowledge, most studies nevertheless have only focused on the unique value, investigating technological motivations at the antecedent level (Chang & Chen, 2021 ; Lin, 2022 ; Park & Zhang, 2022 ) and in-store technology adoption at the consequence level (Aw et al, 2022 ; Barann et al, 2022 ; Roy et al, 2020 ). Smart technology empowerment is not only limited to technological aspects, but very little is known about how smart technology empowers consumers in a holistic and comprehensive manner in smart retail.…”

Section: Introductionmentioning

confidence: 99%

How smart technology empowers consumers in smart retail stores? The perspective of technology readiness and situational factors

Chen

Chang

2023

Electron Markets

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“…In particular, the AI objects possess human-like appearance interaction following the underlying principles and expectations for human social interactions, thereby increasing the perception of social presence (Blut et al, 2021). Empirical evidence has articulated that perceived anthropomorphism facilitates consumers' adoption and engagement of AI objects (Aw et al, 2022).…”

Section: Perceived Anthropomorphismmentioning

confidence: 99%

Counteracting dark sides of robo-advisors: justice, privacy and intrusion considerations

Leong

Hew

et al. 2023

IJBM

Self Cite

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PurposeUnder the pressure of dynamic business environments, firms in the banking and finance industry are gradually embracing Fintech, such as robo-advisors, as part of their digital transformation process. While robo-advisory services are expected to witness lucrative growth, challenges persist in the current landscape where most consumers are unready to adopt and even resist the new service. The study aims to investigate resistance to robo-advisors through the privacy and justice perspective. The human-like attributes are modeled as the antecedents to perceived justice, followed by the subsequent outcomes of privacy concerns, perceived intrusiveness and resistance.Design/methodology/approachAn online survey was conducted to gather consumer responses about their perceptions of robo-advisors. Two hundred valid questionnaires were collected and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).FindingsThe results revealed that (1) perceived anthropomorphism and perceived autonomy are the positive determinants of perceived justice, (2) perceived justice negatively impacts privacy concerns and perceived intrusiveness and (3) privacy concerns and perceived intrusiveness positively influence resistance to robo-advisors.Originality/valueThe present study contributes to robo-advisory service research by applying a privacy and justice perspective to explain consumer resistance to robo-advisors, thereby complementing past studies that focused on the technology acceptance paradigm. The study also offers practical implications for mitigating resistance to robo-advisors.

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Alexa, what's on my shopping list? Transforming customer experience with digital voice assistants

Cited by 93 publications

References 86 publications

Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants

Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants

How smart technology empowers consumers in smart retail stores? The perspective of technology readiness and situational factors

Counteracting dark sides of robo-advisors: justice, privacy and intrusion considerations

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