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Researchers explore the impact of an intelligent assistant in virtual teams by applying the theoretical lens of a transactive memory system (TMS) to understand the relationships between trust in a specific technology, knowledge sharing and knowledge application.

An online survey was administered to a Qualtrics-curated panel of individual, US-based virtual team members utilizing an intelligent assistant with team collaboration software. Partial least squares structural equation modeling (PLS-SEM) was utilized to examine the hypothesized relationships of interest.

Results suggest that knowledge application is strongly influenced by trust in a specific technology and knowledge sharing. Additionally, a transactive memory system positively increases trust in the intelligent assistant, and similarly, trust in the intelligent assistant has a significant positive relationship with knowledge sharing.

The research model contributes to our understanding of the impact of an intelligent assistant in virtual teams. Although the transactive memory system construct has been explored in various contexts and models, few have explored the impact of an intelligent assistant and trust in a specific technology.

With the continuous improvement of artificial intelligence (AI) technology, intelligent personal assistants (IPAs) based on AI have seen unprecedented growth. The present study investigates the effect of anthropomorphism on cognitive and emotional trust and the role of interpersonal attraction in the relationship between anthropomorphism and trust.

A structural equation modeling technique with a sample of 263 consumers was used to analyze the data and test the conceptual model.

The findings illustrate that the anthropomorphism of IPAs did not directly induce trust. Anthropomorphism led users to assign greater social attraction and task attraction to IPAs, which in turn reinforced cognitive or emotional trust in these assistants. Compared with task attraction, social attraction was more powerful in strengthening both cognitive trust and emotional trust. The present study broadens the current knowledge about interpersonal attraction and its role in AI usage by examining two types of interpersonal attraction of IPAs.

As trust plays an important role in the rapid development of human–computer interaction, it is imperative to understand how consumers perceive these intelligent agents and build or improve trust. Prior studies focused on the impact of anthropomorphism on overall trust in AI, and its underlying mechanism was underexplored. The findings can help marketers and designers better understand how to enhance users' trust in their anthropomorphic products, especially by increasing social interactive elements or promoting communication.

With the upgrade of natural language interaction technology, the simulation extension of intelligent voice assistants (IVAs) and the uncertainty of products and services have received more and more attention. However, most of the existing research focuses on investigating the application of theories to explain consumer behavior related to intention to use and adopt IVAs, while ignoring the impact of its privacy issues on consumer resistance. This article especially examines the negative impact of artificial intelligence-based IVAs’ privacy concerns on consumer resistance, and studies the mediating effect of perceived creepiness in the context of privacy cynicism and privacy paradox and the moderating effect of anthropomorphized roles of IVAs and perceived corporate social responsibility (CSR) of IVAs’ companies. The demographic variables are also included.

Based on the theory of human–computer interaction (HCI), this study addresses the consumer privacy concerns of IVAs, builds a model of the influence mechanism on consumer resistance, and then verifies the mediating effect of perceived creepiness and the moderating effect of anthropomorphized roles of IVAs and perceived CSR of IVAs companies. This research explores underlying mechanism with three experiments.

It turns out that consumers’ privacy concerns are related to their resistance to IVAs through perceived creepiness. The servant (vs. partner) anthropomorphized role of IVAs is likely to induce more privacy concerns and in turn higher resistance. At the same time, when the company’s CSR is perceived high, the impact of the concerns of IVAs’ privacy issues on consumer resistance will be weakened, and the intermediary mechanism of perceiving creepiness in HCI and anthropomorphism of new technology are further explained and verified. The differences between different age and gender are also revealed in the study.

The research conclusions have strategic reference significance for enterprises to build the design framework of IVAs and formulate the response strategy of IVAs’ privacy concerns. And it offers implications for researchers and closes the research gap of IVAs from the perspective of innovation resistance.

The purpose of this paper is to develop a comprehensive research model that can explain customers’ continuance intentions to adopt and use intelligent personal assistants (IPAs).

This study proposes and validates a new theoretical model that extends the parasocial relationship (PSR) theory. Partial least squares analysis is employed to test the research model and corresponding hypotheses on data collected from 304 survey samples.

Interpersonal attraction (task attraction, social attraction, and physical attraction) and security/privacy risk are important factors affecting the adoption of IPAs.

First, this is the first empirical study to examine user acceptance of IPAs. Second, to the authors’ knowledge, no research has been conducted to test the role of PSR in the context of IPAs. Third, this study verified the robustness of the proposed model by introducing new antecedents reflecting risk-related attributes, which has not been investigated in prior PSR research. But this study has limitations that future research may address. First, key findings of this research are based only on data from users in the USA. Second, individual differences among the survey respondents were not examined.

To increase the adoption of IPAs, manufacturers should focus on developing “human-like” and “professional” assistants, in consideration of the important role of PSR and task attraction. R&D should continuously strive to realize artificial intelligence technology advances so that IPAs can better recognize the user’s voice and speak naturally like a person. Collaboration with third-party companies or individual developers is essential in this field, as manufacturers are unable to independently develop applications that support the specific tasks of various industries. It is also necessary to enhance IPA device design and its user interface to enhance physical attraction.

This study is the first empirical attempt to examine user acceptance of IPAs, as most of the prior literature has concerned analysis of usage patterns or technical features.

This paper aims to use the concept of machine learning to enable people and machines to interact more certainly to extend and expand human expertise and cognition.

Intelligent code reuse recommendations based on code big data analysis, mining and learning can effectively improve the efficiency and quality of software reuse, including common code units in a specific field and common code units that are not related to the field.

Focusing on the topic of context-based intelligent code reuse recommendation, this paper expounds the research work in two aspects mainly in practical applications of smart decision support and cognitive adaptive systems: code reuse recommendation based on template mining and code reuse recommendation based on deep learning.

On this basis, the future development direction of intelligent code reuse recommendation based on context has prospected.

The growing integration of artificial intelligence (AI) assistants and voice assistants provides a platform for AI to enter consumers’ everyday lives. As these voice assistants become ubiquitous, their widespread adoption underscores the need to understand how to create voice assistants that can naturally interact with and support users. Grounded in the stereotype content model from social psychology, this study aims to investigate the influence of perceived humanness and personality on building trust and continuous usage intentions in voice assistants. Specifically, a fresh perspective examining the determining factors that shape personality trait perceptions of competence and warmth in voice assistants is proposed.

An online survey of 457 participants and structural equation modeling is conducted to validate the research model.

Anthropomorphism, social presence and interactivity drive perceived warmth, whereas performance and effort expectations drive perceived competence. Perceived competence and perceived warmth together positively affect users’ trust in voice assistants, leading to a higher likelihood of continuous usage intentions.

This research provides profound theoretical contributions to the emerging field of human-AI interaction and offer practical implications for marketers aiming to leverage voice assistant personalities to build trusted and long-lasting interactions.

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.

The purpose of this study is to discuss the development of Android-based Intelligent Software Assistant application for visually challenged or blind people. The application is intended to help people with visual limitations or blind people to access Android-based devices so that they can use library resources by using android devices.

The necessary data are collected from journals, articles, books and questionnaires, and similar applications are analyzed. The application design method used is the Scrum method, which consists of Backlog, Sprint and Scrum Meeting. From the operational side of the application, the method used is speech-to-text and text-to-speech.

This application has been tried with some users who have total blindness and low vision, and all provided a good response to this application. From the performance side, the user gives a very satisfied response to this application. While the ease of using the application, the user also provides a satisfactory response to the ease of using this application.

The application still has limitations in penetration to the user, and the application is only built using Android as its platform. In addition, the dependence on libraries from Google has caused difficulties in implementing this application with local dialect, which is only understood by the local community.

This application has implications for the society, especially those with limitations in eyesight can be so much more productive and independent. This can reduce the social burden in society.

This application provides an easy access of an android device to blind people and people with low vision, as well as access to library resources with devices that have been installed with this application. This facility can improve the library accessibility to the blind and visually challenged community.

The recent COVID-19 pandemic affects all segments of the population in all possible fields of life. To encounter this critical situation and to safeguard the health of the library users & library staff, the library services have been forced to adapt and accept the “new normal” and give a greater use and reliance on virtual space than ever before with physical spaces. This paper aims to demonstrate an artificial intelligence (AI)-driven solution that can be practically implemented in the form of a “InfoBot” or “Chatbot” to fulfil user needs 24/7 with minimal or without human intervention.

To give a general overview of the use of AI Chatbot in libraries and its multitasking features followed by the practical implementation, a versatile AIchatbot service, Engati is used as a target bot with its basic free plan.

The study findings reveal that AI Chatbots offer a dependable solution for the libraries to initiate virtual assistance, thus augmenting the reference service while adding a newer dimension to virtual reference service.

Innovative and intelligent information service would be overcoming the time and location barriers reaffirming the concept of “library without walls” while falling in line with the five laws of library science as propounded by Dr S.R. Ranganathan, the father of library science in India.

Though the implementation of bots and chatbots is not a purely novel concept to explore, no such research has been conducted focusing particularly on its exceptional benefits in the library in reference to the recent pandemic.

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.