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Scholars have highlighted personal interactions between employees and their leaders in an increasingly distributed and hybrid work environment as an essential mechanism that engages employees toward organizational goals. Enhanced employee engagement significantly contributes to sustained organizational performance and growth. While Artificial Intelligence (AI) applications in the HR domain are increasing, research to understand the implication of AI-based virtual assistants on enabling trust and managing human resources is, at best, limited.

Drawing on the social response theory and the social exchange theory, and based on a multi-source, time-lagged field study spanning over ten months, we investigated the impact of AI-based virtual assistants on employee attitudes, namely perception of fairness and employee engagement.

The usage of AI-based virtual assistants is associated directly with employee engagement and indirectly through employees’ perceptions of fairness. While employees’ past performance moderates the relationship between perceived fairness and employee engagement, the interaction effect becomes non-significant with AI-based virtual assistants.

Our study contributes to the emerging literature on AI-based virtual assistants in HRM and employee engagement. The virtual assistants’ use to enhance employee engagement emerges as an opportunity for task substitution and augmentation. Our study demonstrates that AI-based virtual assistants can enhance employee engagement and help build perceptions of fairness among employees.

With the emerging importance of AI, there is an increasing interest in explaining human-computer interactions and their effect on employee engagement. Our study is among the early empirical studies examining the implications of AI-based virtual assistants on employee outcomes.

Examines the complex and varied instructional leadership tasks of high school assistant principals and factors that enhance or restrict the enactment of these tasks. Research on the assistant principal is not extensive and that on the assistant principal as an instructional leader is virtually non‐existent. It has been one of the main purposes of this study to investigate the instructional leadership roles of the assistant principal and to expand the information to the field of educational administration and research. The findings from this study would be particularly beneficial to practising secondary school administrators in designing a better job description for their assistant principals or in making a decision as to whether their students might be better served by the addition of an assistant principal.

With the expansion of artificial intelligence (AI) technology in everyday life, it is critical to discuss how and why consumers respond in certain ways to AI agents. However, few studies have examined the mechanisms underlying users’ responses to these agents. This study aims to identify such mechanisms and discuss how users form loyalty toward AI agents. Specifically, this study addresses interactivity with AI voice assistants as a key determinant of user loyalty, presenting user perceptions of the human-likeness of AI voice assistants and communication self-efficacy as sequential mediators.

We investigate the effects of human-likeness and communication self-efficacy on the relationship between interactivity and loyalty to AI voice assistants by developing a sequential mediation model. To estimate the empirical model, data were collected through an online survey with 330 respondents.

The results indicate that interactivity influences loyalty directly and positively. In addition, interactivity affects loyalty indirectly sequentially through human-likeness and communication self-efficacy.

By uncovering the psychological mechanisms underlying users’ loyalty to AI voice assistants, this study provides new academic and managerial insights that have not been clearly identified in the current literature.

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.

This study social based on cognitive theory (SCT), aims to better understand how transformational leadership affects team-level knowledge sharing and absorptive ability in the construction industry. It also examines the moderating influence of the AI-based virtual assistant on the indirect relationship between transformational leadership and team innovation through knowledge sharing and absorptive ability at the team level.

This study used a simple random sample approach to gather data from several small and medium-sized construction firms in Anhui Province, China. A total of 407 respondents, including 89 site engineers and 321 team members, provided their responses on a five-point Likert scale questionnaire.

The findings showed that AI-based virtual assistants significantly moderated the direct and indirect association between transformational leadership and knowledge sharing, and subsequently with team innovation. Unexpectedly, the findings showed that AI-based virtual assistant did not moderate the direct relationship between transformational leadership and team-level absorptive capacity.

This study adds a fresh perspective to the literature on construction management by examining team innovation driven by transformational leadership through an underlying mechanism. It is unique in that it uses the team adaptation theory to investigate the understudied relationship between transformational leadership and team innovation in the construction industry.

This study focuses on assistant principals, the “forgotten future workforce” of educational leadership. We explored the current landscape of assistant principalship within the context of work performance, including both task and discretionary performance, and the future career aspirations of assistant principals from a cross-national perspective. Specifically, the study aimed to fulfill the following objectives: (a) to identify the factors affecting the task and discretionary performance of assistant principals, (b) to identify the factors affecting three future career aspirations of assistant principals, and (c) to determine whether the influences of these factors differ by national origin. Personal initiative and perceived organizational support (POS) were the independent variables. This study also examined the demographic attributes of the participants and their schools. Two randomly selected samples, which composed of 227 Turkish and 144 American assistant principals were the participants. The data-gathering instrument incorporated the revised versions of the Personal Initiative Scale (Fay & Frese, 2001), the Perceived Organizational Support Scale (Eisenberger, Huntington, Hutchison, & Sowa, 1986), and the School Organizational Citizenship Behavior Scale (DiPaola & Tschannen-Moran, 2001). The findings of the study showed that personal initiative and POS significantly predicted the task performance, discretionary performance, and certain future career aspirations of assistant principals. National origin appeared to be a significantly differentiating factor of the assistant principals' task performances, discretionary performances, and future career aspirations. We drew conclusions and provided suggestions for future research.

This chapter explores how a perpetual beta mentality allows public services spaces and staffing to be more flexible, responsive, and dynamic to meet the needs of a university community. In one library’s experience, this led to a redeveloped Student Assistant Program which made better use of student employee time and prompted the authors to begin exploring the impact of library employment on the future work life of student employees. Through various data collection metrics, pilot project testing, and staged implementation, public services have expanded and become more adaptable. This approach included collecting usage pattern statistics, focus groups, and surveys. A perpetual beta mindset and career-oriented work for student employees makes for more responsive public services. The sample size for each focus group was small, but spanned a broad range of student stakeholders. Because perpetual beta allows for constant change, it can be hard to compare data between iterations. Libraries should make employment more meaningful to student assistants and their future careers. This chapter further explores the current research of library employment for student assistants and begins to track their perceptions of said impact after graduation.

Teachers play a vital role in the structure of their classrooms. Part of this structure is having a clear understanding of the importance of not only supporting their students, but also the teacher assistants/support staff with whom they collaborate. Providing teacher assistants/support staff with guidance, information on student needs and classroom structures, team-building strategies, training, and supervision sets the stage for a positive climate for collaboration, teamwork, and learning. Consequently, teachers should be proactive and diligent to ensure high-quality training and supervision for teacher assistants/support staff, as this will have a direct impact on the services and learning opportunities being provided to the students.

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.

The present study investigates the customers' behavioural intention to use voice-based artificial intelligence (AI) to find the appropriate hotels and resorts in an emerging nation. This study determines the influences of information quality, system quality, privacy, and novelty value on attitude and behavioural intention to use voice-based artificial intelligence to obtain the appropriate information and find the location of the hotels and resorts.

This study used a purposive sampling method for collecting data from the respondents, who are customers of the hotels and resorts in Bangladesh. A self-administered survey questionnaire was used to obtain responses from 378 respondents. After collecting the data, the reliability and validity of the constructs and hypotheses were tested via partial least squares structural equation modelling (PLS-SEM).

The findings of the study indicate that information quality, system quality, privacy and novelty value have a positive and significant impact on attitude and behavioural intention to use voice-based AI assistant services in an emerging nation. However, system quality does not significantly influence behavioural intention to use voice-based AI assistant but it has an indirect significant influence on behavioural intention through the mediation effect of attitude.

The study’s findings provide essential guidelines for practitioners to understand the impacts of information quality, system quality, privacy, and novelty value on attitude and behavioural intention to use voice-based artificial intelligence to find the appropriate hotels and resorts to meet customers' needs and expectations.

This study contributes to the existing literature on technology adoption by highlighting the interconnectedness of various factors influencing users' behavioural intentions. The study’s focus on an emerging nation provides a valuable theoretical contribution. It highlights that user perceptions and attitudes towards technology adoption may differ from those in developed nations due to unique contextual factors.