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Virtual assistants are increasingly used for persuasive purposes, employing the different modalities of voice and text (or a combination of the two). In this study, the authors compare the persuasiveness of voice-and text-based virtual assistants. The authors argue for perceived human-likeness and cognitive load as underlying mechanisms that can explain why voice- and text-based assistants differ in their persuasive potential by suppressing the activation of consumers' persuasion knowledge.

A pre-registered online-experiment (n = 450) implemented a text-based and two voice-based (with and without interaction history displayed in text) virtual assistants.

Findings show that, contrary to expectations, a text-based assistant is perceived as more human-like compared to a voice-based assistant (regardless of whether the interaction history is displayed), which in turn positively influences brand attitudes and purchase intention. The authors also find that voice as a communication modality can increase persuasion knowledge by being cognitively more demanding in comparison to text.

Simply using voice as a presumably human cue might not suffice to give virtual assistants a human-like appeal. For the development of virtual assistants, it might be beneficial to actively engage consumers to increase awareness of persuasion.

The current study adds to the emergent research stream considering virtual assistants in explicitly exploring modality differences between voice and text (and a combination of the two) and provides insights into the effects of persuasion coming from virtual assistants.

Voice command and voice search are becoming increasingly popular in the hospitality and tourism industry, with many hotels and travel companies investing in voice-enabled technology to improve guest experiences and streamline operations. This technology allows travellers to manage their travel plans, request services and get information through natural voice commands on any voice-enabled device. Voice assistants are also multilingual, allowing hotels to customise responses to guests who do not speak the local language. Angie, a multilingual, in-room voice assistant, is an example of this technology. It can fulfil guest requests, answer common questions about the property and create streamlined access to a wide range of hotel amenities, such as ordering room service or requesting extra towels. Hotels can control questions and responses to assist stretched staff and provide upsell and advertising revenue through digital promotions or recommended onsite amenities or discounts. In addition, voice command technology can be used to book travel and find things to do at a destination. Google Assistant can help with travel plans like booking a hotel, checking flight status and finding things to do at a destination. In conclusion, voice command and voice search technology are transforming the hospitality and tourism industry by improving guest experiences, reducing operational costs and increasing revenue.

Digital voice assistants use wake word engines (WWEs) to monitor surrounding audio for detection of the voice assistant's name. There are two failed conditions for a WWE, false negative and false positive. Wake word false positives threaten a loss of personal privacy because, upon activation, the digital assistant records audio to the voice cloud service for processing.

This observational study attempted to identify which Amazon Alexa wake word and Amazon Echo smart speaker resulted in the fewest number of human voice false positives. During an eight-week period, false-positive data were collected from four different Amazon Echo smart speakers located in a small apartment with three female roommates.

Results from this study suggest the number of human voice false positives are related to wake word selection and Amazon Echo hardware. Results from this observational study determined that the wake word Alexa resulted in the fewest number of false positives.

This study suggests Amazon Alexa users can better protect their privacy by selecting Alexa as their wake word and selecting smart speakers with the highest number of microphones in the far-field array with 360-degree geometry.

Voice assistant technology represents one of the most radical artificial intelligence innovations. Drawing on the processing fluency theory and consumer learning literature, this study aims to explore how consumer acceptance of new products is influenced by voice assistant function (VAF), along with the impacts of role clarity and learning modality.

Four between-subjects experimental studies were conducted. Study 1 tested the main effect of VAF on consumer acceptance. Study 2 included role clarity as a mediator between VAF and consumer acceptance. Study 3 examined the moderation effect of learning modality and contrasted the effectiveness of experiential and verbal learning in helping increase consumer acceptance. Study 4, as a post hoc study, tested serial mediations to validate whether processing fluency was indeed the mechanism explaining the indirect relationship between VAF and consumer acceptance via role clarity.

The negative impact of VAF on consumer acceptance was demonstrated in all four studies. Studies 2 and 3 showed VAF decreased role clarity which further influenced consumer acceptance. Moreover, Study 3 evidenced that experiential learning was more effective than verbal learning in increasing consumer acceptance of voice-assisted products via role clarity. Study 4 demonstrated that VAF decreased role clarity, which in turn decreased processing fluency, leading to lower consumer acceptance.

This research views the usage of voice-assisted products as a coproduction process between consumers and the VAF. Accordingly, findings provide novel insights into processing fluency of tasks assisted by VAF through the lens of role clarity and learning modality, which enriches the understanding of potential barriers and opportunities for consumers to accept voice-assisted products.

The research aims to understand how smart speakers are perceived by their actual and potential users, their attitude towards smart speakers and consequently their intention to use them.

The authors apply a structural equation modelling (SEM) approach to test the research hypotheses through data coming from a structured questionnaire.

The results show that the higher the importance attributed to usefulness and ease of use, the higher the positive attitude that in turn positively affects the intention to use smart speakers. A significant relationship also emerged between task technology fit and attitude towards smart speakers, as well as between perceived enjoyment and attitude towards smart speakers. Perceived privacy risk, innovativeness and social attraction have been found to not significantly impact attitudes towards smart speakers.

Although several academic studies have focused on various aspects of smart technologies, only a few studies discuss the factors that push consumers to use smart speakers for activities related to commercial transactions. Therefore, looking at the rapid rise of smart speakers for daily tasks and the gradual acceptance of voice interaction with digital tools, the authors proposed a study about Italian users' intention to use smart speakers. Specifically, to fill the gap in the existing literature, the authors applied a SEM approach to identify utilitarian and hedonic benefits that motivate the use of these devices.

This paper aims to categorize users of voice assistants and analyze decision-making conflicts to predict intention to adopt voice commerce (v-commerce).

This exploratory study used expert survey-based data collection founded on data saturation.

This study identifies three forms of voice systems based on senses aroused (screen first, voice only and voice first) and four profiles of voice users (passive resistant, hedonistic adopter, utilitarian adopter and active resistant), each with a different appraisal of the benefits and costs of v-commerce adoption and the experiences (positive or negative) felt during the shopping experience. This study proposes a conceptual model to predict intention to adopt v-commerce depending on voice-system and -user characteristics.

Learning from this study can help improve the marketing strategies and actions put in place by voice-assistant brands and advertisers by providing insights for adapting product recommendation algorithms to meet the needs of the identified profiles.

This paper provides an answer to the limits of classical approaches based on “one-size-fits-all” strategy by showing how voice-assistant users have different profiles that span a gradient of advance in technology adoption.

Alexa’s integration in rural primary schools has improved the pedagogy and has created an engaging and objective learning environment. This study investigates the integration, with a specific focus on exploring its various aspects. The impact of Alexa’s on students' English vocabulary, comprehension and public speaking are examined. This study aims to provide insights the teachers and highlight the potential of artificial intelligence (AI) in rural education.

This content analysis study explores the use of Alexa in primary education in rural areas of India. The study focuses on the types of the questions asked by the students and examines the pedagogical implications of these interactions. By analyzing the use of Alexa in rural educational settings, this study aims to contribute to our understanding of how voice assistants are utilized as educational tools in underprivileged areas.

Alexa significantly improved students' English vocabulary, comprehension and public speaking confidence. Alexa increased school enrollment and retention. Virtual voice assistants like Alexa may improve pedagogy and help India’s rural education. This study shows AI improves rural education.

The study only covers rural India. Self-reported data and observations may bias the study. The small sample size may underrepresent rural educational institutions in India.

Alexa is used to study rural India’s primary education. Voice assistants in rural education are understudied. The study examines Alexa’s classroom use, student questions, and policy and teacher education implications. AI’s education transformation potential addresses UNESCO’s teacher shortage. This novel study examines how AI can improve rural education outcomes and access.

The main objective of this chapter is broadening the understanding of anthropomorphic artificial intelligence (AI) (e.g. avatars, humanoid robots, chatbots) in both physical and digital environments. The chapter strives to demonstrate how organisations can curate relationship marketing and enhance customer experience by employing anthropomorphic AI. To achieve this, the chapter extends existing understanding in three ways. First, it explains the interconnectivity between relationship marketing and customer experience. Second, it presents anthropomorphic AI along with its different characteristics and technologies. Third, it offers some real-life uses cases and examples of such AI drawing from practical insights into five selected industries. Overall, the chapter provides some food of thoughts concerning the successful application and deployment of anthropomorphic AI in marketing practices.

Artificially intelligent (AI) assistant-enabled smart speaker not only can provide assistance by navigating the massive amount of product and brand information on the internet but also can facilitate two-way conversations with individuals, thus resembling a human interaction. Although smart speakers have substantial implications for practitioners, the knowledge of the underlying psychological factors that drive continuance usage remains limited. Drawing on social response theory and the technology acceptance model, this study aims to elucidate the adoption process of smart speakers.

A field survey of 391 smart speaker users were obtained. Partial least squares structural equation modeling was used to analyze the data.

Media richness (social cues) and parasocial interactions (social role) are key determinants affecting the establishment of trust, perceived usefulness and perceived ease of use, which, in turn, affect attitude, continuance usage intentions and online purchase intentions through AI assistants.

AI assistant-enabled smart speakers are revolutionizing how people interact with smart products. Studies of smart speakers have mainly focused on functional or technical perspectives. This study is the first to propose a comprehensive model from both functional and social perspectives of continuance usage intention of the smart speaker and online purchase intentions through AI assistants.

Launched in 2014, Amazon's Echo and Echo Dot smart speakers led the category's rapid adoption by households and enabled the penetration of artificial intelligence (AI) voice assistants into the everyday lives of millions of people. By 2019, Alexa the virtual brains behind Amazon's smart speakers was able to play music, create reminders, get weather reports, control lights and other home appliances, shop, and do much more in response to voice commands. Amazon had developed significant new capabilities for Alexa, developed an entire ecosysgtem around it, expanded Alexa's user base to more than 100 million users, and made significant progress in monetizing its digital voice assistant. However, Alexa's progress also created new challenges for Amazon, its Alexa-enabled customers, and society at large. Amazon needed to identify and address these challenges in order to encourage continued consumer acceptance and preclude detrimental government or regulatory action.