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The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.

Telepresence robots have gained prominence as a novel technological modality for mobile videoconferencing. Although the technology has mass appeal in the realm of telehealth and patient–health provider communication, its integration in community living settings for older adults has not been extensively studied. The aim of this study was to gather the perspectives of residents, trainers and staff at a retirement facility on their experience with a telepresence robot during and following a five-week wellness program.

The study employed semi-structured interviews with ten stakeholders who were involved in the wellness program followed by a qualitative content analysis of the data. The Unified Theory of Acceptance and Use of Technology served as the interview framework to explore the facilitators and barriers to the implementation of the robot.

Independent coding of the data by the study investigators identified discrete as well as interconnected categories among the stakeholders. Residents expressed their changing ideation of the robot, affinity toward the technology, preference for human connection and future value. Perspectives of the trainers, the fellow residents (ambassadors) and staff pertained to their need for increased engagement, growing comfort with the technology, usability challenges and importance of coordination and training.

Older adults' outlook and comfort with telepresence robots improve with continuing exposure to the technology for healthcare and social connectivity needs. However, in-person care is also preferred initially and periodically to engage with their health providers meaningfully and effectively via the robot. To address long term feasibility and usability, the authors propose a hierarchical approach when integrating telepresence robots in community living facilities for older adults. Information technology education, staff training and reliable internet connectivity are the precursors to optimizing the value and perceived usefulness of the technology.

The purpose of this paper is to investigate students' adoption intention (ADI) and actual usage (ATU) of artificial intelligence (AI)-based teacher bots (T-bots) for learning using technology adoption model (TAM) and context-specific variables.

A mixed-method design is used wherein the quantitative and qualitative approaches were used to explore the adoption of T-bots for learning. Overall, 45 principals/directors/deans/professors were interviewed and NVivo 8.0 was used for interview data analysis. Overall, 1,380 students of higher education institutes were surveyed, and the collected data was analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique.

The T-bot's ADI’s antecedents found were perceived ease of use, perceived usefulness, personalization, interactivity, perceived trust, anthropomorphism and perceived intelligence. The ADI influences the ATU of T-bots, and its relationship is negatively moderated by stickiness to learn from human teachers in the classroom. It comprehends the insights of senior authorities of the higher education institutions in India toward the adoption of T-bots.

The research provides distinctive insights for principals, directors and professors in higher education institutes to understand the factors affecting the students' behavioral intention and use of T-bots. The developers and designers of T-bots need to ensure that T-bots are more interactive, provide personalized information to students and ensure the anthropomorphic characteristics of T-bots. The education policymakers can also comprehend the factors of T-bot adoption for developing the policies related to T-bots and their implications in education.

T-bot is a new disruptive technology in the education sector, and this is the first step in exploring the adoption factors. The TAM model is extended with context-specific factors related to T-bot technology to offer a comprehensive explanatory power to the proposed model. The research outcome provides the unique antecedents of the adoption of T-bots.

The aim of the study is to conduct a thematic review of assessment tools and types of activities in the application of robotics to autistic students during the period 1996–2021 using Web of Science and Scopus. The sample consisted of 119 documents.

Nowadays, emerging technologies have become increasingly prevalent across various fields of knowledge. In this regard, robotics is being increasingly applied in the educational environment. The characteristics of this tool are the ones that best suit the needs of autistic students.

Results reveal that 16.80% of the studies used automatic measurement systems, whilst 15.96% of the studies used user observation and recording techniques. As for the tasks, 37.80% were focussed on imitation tasks. Amongst the practical implications is the need to include tasks that could be developed collaboratively in the regular classroom.

With this research, it is intended to disseminate in the scientific community what are the characteristics that should have the interaction activities between a robot and autistic students. In addition, the type of tool needed to evaluate the improvements in the interaction is proposed.

Sustainability has been the subject of several scientific investigations. Many researchers in the construction industry have also examined a range of sustainability-related studies. However, few studies have thoroughly reviewed implementing sustainability concepts in high-rise residential buildings (HRRBs).

By adopting scientometrics and systematic review (SR), this study seeks to map out recent sustainability trends and concepts in the design, development and operation of HRRBs worldwide and in Hong Kong. With a focus on bibliographic records from the Web of Science (WoS) database, 1,395 journal articles from 2013 to 2022 were analysed. Furthermore, thirteen studies were systematically reviewed.

The SR indicated that sustainable practices in developing Hong Kong's HRRBs emphasised zero-carbon buildings, reduced energy usage and energy-efficient retrofitting. Likewise, terms such as BIM, urban density, life cycle assessment and system dynamics are strongly connected with clusters that include “residential buildings”, “high-rise buildings” and “high-rise residential buildings”. The study identified significant themes in establishing HRRBs by combining sustainable practices, emphasising urban governance and policy management, building performance and thermal comfort, energy and design optimisation, occupant behaviour and sensitivity analysis. Core sustainability ideas have improved resource management, air quality management and knowledge of user behaviour in HRRBs.

The study allows researchers and practitioners to explore future research directions in the built environment per the application of sustainable concepts in the development of HRRBs from design, construction and post-construction phases.

This study aims to investigate tourists’ intentions to use hotel service robots with a focus on safety and hygiene. It examines the impact of perceived safety, health awareness and service assurance on consumer engagement and robot usage.

Survey data from 275 participants with experience in robotic service were analyzed using structural equation modeling (SEM). The study used purposive sampling and collected data via the Prolific platform, using SEM and SmartPLS Ver. 3.0 for analysis.

Results indicate customers prioritize safety and hygiene, valuing effective service responses and cleanliness. Perceived robotic safety and service assurance positively influence personal engagement, with a preference for service robots among female guests.

While emphasizing the importance of safety and service assurance in hotel robotics, the study acknowledges limitations in personalization and conclusive use of service robots.

This research contributes to understanding the role of perceived safety in service robot usage, highlighting the significance of user trust and comfort in human–robot interactions. It also explores the novel connection between service assurance and service robots, offering insights into robotic performance reliability in user-centric contexts.

This study investigates the influence of artificial intelligence (AI) stimuli on customer stickiness (CS), the mediation effects of social presence (SP) and the moderating impacts of customer traits in this influencing process.

Drawing on the arousal theory and social response theory, a conceptual model was established and tested by a data set of 268 customers in the catering industry.

The results indicate that AI stimuli, such as perceived personalization and perceived interactivity, positively affect CS. SP partially mediates the influence of AI stimuli on CS. Customer traits such as customers' need for interaction (NFI) and novelty seeking (NS) actively moderate the mediating effects of SP.

This study advances the interactive marketing literature from three aspects. Firstly, instead of focusing on the functional aspects of AI stimuli, it extends our understanding of AI-enabled interactive marketing by examining the effects of social and emotional aspects of AI stimuli on customer response. Secondly, it extends our understanding of social response by illuminating the mediating effects of SP between AI stimuli and CS. Finally, it provides new insights and empirical evidence for the research focus on customer traits in AI-enabled interactive marketing.

The present paper answers two significant questions: (1) What are the relative consumer and firm-level effects of marketing through metaverse compared to conventional marketing endeavors? (2) What are the current trends in utilizing the metaverse as reported in the recent literature?

This study employs a systematic literature review methodology, utilizing a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart to synthesize existing research. Thirty-five articles written in English were selected and analyzed from two databases, Web of Science and EBSCO Host.

The findings indicate that consumer-level effects of the metaverse include consumer loyalty and brand attachment. The firm-level benefits are decentralization and cost reductions. The paper proposes a framework indicating variables that could attenuate or enhance the association between immersive components of the metaverse and their resultant effects.

This study contributes to understanding the role of metaverse in marketing practices related to the marketing mix components. The study conceptualizes a novel framework for the metaverse and its resultant effects.

Powered by artificial intelligence, voice assistants (VAs), such as Alexa, Siri and Cortona, are at early-stage adoption rates in service contexts. Customers express hesitance in using the technology. Furthermore, the effect of a relevant variable (VA empathy) as a determinant of VAs is not widely researched. This study aims to extend the unified theory of acceptance and use of technology (UTAUT) and social response theory (SRT) to propose and test a conceptual model of the role of customer perceptions of VA empathy and risk on VA adoption and usage intensity.

In this study, data were collected from 387 VA users in the USA using a survey administered through Amazon MTurk. Data cleaning retained a final n = 318 for structural equation modeling analysis.

Findings show that perceived VA empathy enhances customers’ attitude toward VA and drives adoption, thereby increasing VA usage intensity. Perceived risk is a moderator; users with high perceptions of VA empathy have greater VA adoption rates when they have high (vs low) risk perceptions of using VA.

This research is one of the first known studies to provide empirical evidence of the role of customer perceptions of VA empathy and risk on VA adoption in service delivery. It goes beyond VA adoption research to provide empirical evidence of the impact of VA adoption on actual usage intensity. By extending the UTAUT and SRT, this research adds to the theoretical foundation for research on VA adoption, offering practical insights for firms regarding empathetic VA design to enhance customer service delivery.

Surgical services are settings where resilient performance (RP) is necessary to cope with a wide range of variabilities. Although RP can benefit from a supportive built environment (BE), prior studies have focused on the operating room, giving scant attention to support areas. This study takes a broader perspective, aiming at developing BE design knowledge supportive of RP at the surgical service as a whole.

Seven BE design prescriptions developed in a previous work in the context of internal logistics of hospitals, and thus addressing interactions between workspaces, were used as a point of departure. The prescriptions were used as a data analysis framework in a case study of the surgical service of a medium-sized private hospital. The scope of the study included surgical and support areas, in addition to workflows involving patients and family members, staff, equipment, sterile instruments and materials, supplies, and waste. Data collection included document analysis, observations, interviews, and meetings with hospital staff.

Results identified 60 examples of using the prescriptions, 77% of which were related to areas other than the operating rooms. The developed design knowledge is framed as a set of prescriptions, examples, and their association to workflows and areas, indicating where it should be applied.

The design knowledge is new in surgical services and offers guidance to both BE and logistics designers.