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This paper aims to explore factors impacting wearable fitness tracking (WFT) device continued usage intention from perspectives of technology attributes (autonomy benefits), health attributes (self-health management benefits, diet-control benefits and health self-efficacy), and consumer attributes (age, gender, technological innovativeness, symbolic benefits, social benefits and hedonic benefits).

The study integrates constructs from the technology acceptance theories and the health promotion model to develop the research model and hypothesis. The empirical analysis was conducted using data from 217 respondents from India. Logistic regression was used to identify factors that discriminate between groups with low and high continued usage intentions.

Results indicate higher continued usage intention for WFT devices is driven by perceived benefits-health, autonomy, social and hedonic, and individual characteristics-technological innovativeness and perceived health self-efficacy. Further, perceived symbolic benefits, diet control benefits, age, and gender does not discriminate between the groups with low and high continued usage intentions.

The results may be limited to the context of the sample and the factors considered. The study suggests future research areas.

The paper offers insights for marketers, governments, insurance firms, and related healthcare services on promoting higher usage of WFT devices to yield dual benefits of preventive healthcare and higher profitability.

The study extends existing research by examining factors across consumer, health, and technological domains in a single framework and adds to the limited research in the context of usage of WFT devices in developing countries.

Following the increasing trend of artificial intelligence (AI) research in hospitality literature, this critical reflection paper aims to identify AI-assisted mindfulness as a critical yet under-investigated issue and to contribute feasible directions for future research.

The authors first conceptualize a framework explaining the effects of mindfulness design in AI interventions on improving human mindfulness. The authors then identify opportunities for interventions in AI-assisted mindfulness for the tourism, hospitality and events industries. Finally, the authors propose potential themes for AI-assisted mindfulness research.

This study contributes three major conceptual works. First, we conceptualize a framework of AI-assisted mindfulness, showcasing that the scope of AI-assisted mindfulness spans from AI interventions to state mindfulness and then to trait mindfulness. Second, the authors offer two approaches to strategic thinking, one from mindfulness (i.e. mindfulness-focused niche markets and activities) and one from AI applications (i.e. AI-facilitated devices and platforms), to identify opportunities for AI-assisted mindfulness interventions. Third, for both management- and marketing-oriented AI-assisted mindfulness research, the authors propose 18 themes.

This critical reflection paper offers directions for future knowledge creation in AI-assisted mindfulness in the tourism, hospitality and events industries.

To the best of the authors’ knowledge, this critical reflection paper serves as the first in hospitality and tourism literature to systematically propose the research issue of AI-assisted mindfulness, offering directions and themes for future research.

This paper analyses whether the humanisation of smart home speakers can improve users' attitudes towards covert information collection. Additionally, it examines the direct and indirect impact of trust, social presence and user's perceived surveillance on attitude towards covert information collection.

A total of 679 American users of smart home speakers are surveyed, and their responses are analysed using structural equation modelling. Mediating effects are also examined.

Humanisation increases social presence, improves users' attitude towards covert information collection and has a U-shaped effect on trust. A negative effect of humanisation on perceived surveillance is demonstrated. Social presence reduces perceived surveillance levels and improves users' attitude towards covert information collection.

We examine attitude towards covert information collection as a new outcome variable. This study contributes to the growing body of research on humanisation by providing new evidence of how humanisation helps improve users' attitude towards covert information collection and generates trust in the service provider. This research indicates the important role of social presence.

The proliferation of smartwatches in the digital age has radically transformed health and fitness management, offering users a multitude of functionalities that extend beyond mere physical activity tracking. While these modern wearables have empowered users with real-time data and personalized health insights, their environmental implications remain relatively unexplored despite a growing emphasis on sustainability. To bridge this gap, this study extends the UTAUT2 model with smartwatch features (mobility and availability) and perceived security to understand the drivers of smartwatch usage and its consequent impact on environmental sustainability.

The proposed theoretical model is evaluated based on data collected from 303 smartwatch users using a hybrid structural equation modeling–artificial neural network (SEM-ANN) approach.

The PLS-SEM results supported smartwatch features’ effect on performance and effort expectancy. The results also supported the role of performance expectancy, social influence, price value, habit and perceived security in smartwatch usage. The use of smartwatches was found to influence environmental sustainability significantly. However, the results did not support the association between effort expectancy, facilitating conditions and hedonic motivation with smartwatch use. The ANN results further complement these outcomes by showing that habit with a normalized importance of 100% is the most significant factor influencing smartwatch use.

Theoretically, this research broadens the UTAUT2 by introducing smartwatch features as external variables and environmental sustainability as a new outcome of technology use. On a practical level, the study offers insights for various stakeholders interested in smartwatch use and their environmental implications.

In the last few years, environmental issues have become a matter of survival. In this sense, e-waste management is among the major problems since it may be a way of mitigating mineral depletion. In this context, the literature lacks e-waste supply chain studies that systematically map supply chain challenges and risks concerning material recovery.

Given this context, the authors' paper conducted a systematic literature review (SLR) to build a framework to identify the constructs of e-waste supply chain risk management.

The paper revealed the theoretical relationship between important variables to achieve e-waste supply chain risk management via a circular economy (CE) framework. These variables include reverse logistics (RL), closed-loop supply chains (CLSC), supply chain risk management, supply chain resilience and smart cities.

The literature contributions of this paper are as follows: (1) a complete list of the risks of the e-waste supply chains, (2) the techniques being used to identify, assess and mitigate e-waste supply chain risks and (3) the constructs that form the theoretical framework of e-waste supply chain risk management. In addition, the authors' results address important literature gaps identified by researchers and serve as a guide to implementation.

Effective construction safety training has been considered to play a significant role in reducing the incidence of accidents. However, the current safety training methods pay less attention to the relationship between workers' personalized characteristics and their learning needs, which results in workers' low learning participation and poor training effect. The purpose of this paper is to improve the participation and effect of safety training for construction workers with a persona-based approach.

This paper presents a persona-based approach to safety tag generation and training material recommendation. By extracting the demographic characteristics and behavior patterns tags of construction workers, a neural network algorithm is introduced to calculate the learning needs tags of workers, and the collaborative filtering recommendation method is integrated to enrich the innovation of recommendation results. Offline experiments and online experiments are designed to verify the rationality of the proposed method.

The results show that the learning needs of workers are closely related to their background. The proposed method can effectively improve workers' interest in materials and the training effect compared with conventional safety training methods. The research provides a theoretical and practical reference for promoting active safety management and achieving worker-centered safety management.

First, a persona-based approach is introduced to establish a novel framework for solving the problem of personalized construction safety management. Second, an artificial intelligence algorithm is used to automatically extract the learning needs tag values and design a hybrid recommendation method for construction workers' personalized safety training. The collaborative filtering method is integrated to enrich the innovation of recommendation results.

The purpose of this review paper was identifying barriers to the use of telemedicine systems in primary health-care individual level among professionals.

This study used Scopus and PubMed databases for scientific records identification. A systematic review of the literature structured by PRISMA guidelines was conducted on 37 included papers published between 2009 and 2019. A qualitative approach was used to synthesize insights into using telemedicine by primary care professionals.

Three barriers were identified and classified: system quality, data quality and service quality barriers. System complexity in terms of usability, system unreliability, security and privacy concerns, lack of integration and inflexibility of systems-in-use are related to system quality. Data quality barriers are data inaccuracy, data timeliness issues, data conciseness concerns and lack of data uniqueness. Finally, service reliability concerns, lack of technical support and lack of user training have been categorized as service quality barriers.

This review identified and mapped emerging themes of barriers to the use of telemedicine systems. This paper also through a new conceptualization of telemedicine use from perspectives of the primary care professionals contributes to informatics literature and system usage practices.

This study aims to investigate customers' personal innovativeness (PI) as an influencing factor of omni-channel customer experience throughout pre-purchase, purchase and post–purchase stages of the customer journey, and their subsequent influences on customers' reuse intention.

Data were collected from customers who had experience with omni-channel shopping in South Korea through a questionnaire made with Naver Forms, both online and offline from 15 June to 15 July 2022. Out of the received responses, only valid and consistent questionnaires were considered for statistical analysis. In total, 272 valid samples were utilised for the final analysis. Analyses included reliability, validity, path, structural equation modelling and mediation effects, using SPSS and AMOS software.

The results revealed a significant influence of personal innovativeness on the omni-channel customer experience across all purchase stages. Personal innovativeness was found to influence the customer experience in the pre- and post–purchase stages, thus affecting reuse intention. However, it did not have the same effect in the purchase stage. The omni-channel experience customer experience also played an indirect mediating role in the relationship between personal innovativeness and reuse intention.

First, personal innovativeness in the IT domain may be very prominent in studies examining innovative behaviours related to computing technology. Second, this study provides further understanding of customers' intentions to reuse omni-channel shopping. Third, the path analysis showed that personal innovativeness significantly affects customer experience at all pre-purchase, purchase and post–purchase stages of the customer journey. However, except for the purchase experience, both pre- and post–purchase experiences significantly impact customers' intention to reuse omni-channels and play a mediating role.

First, omni-channel retailers should launch new products, innovative promotional activities and explore new channels or new service modes to stimulate the need recognition of customers with high personal innovativeness. Second, omni-channel retailers should pay attention to the users' reviews of each channel because they play a key role in potential customers' purchase decisions. Third, offering customers a seamless shopping experience is essential as a marketing strategy for omni-channel retailing.

This study elucidates the causal relationship between personal characteristics and behaviour by dividing the omni-channel customer journey. In particular, personal innovativeness is identified as an important predictor of the intention to reuse omni-channels during the pre- and post–purchase stages. This suggests that omni-channel retailers need to strategically manage these stages to boost customers' reuse intention.

This study aims to investigate the dual solutions for axisymmetric flow and heat transfer due to a permeable radially shrinking disk in copper oxide (CuO) and silver (Ag) hybrid nanofluids with radiation effect.

The partial differential equations that governed the problem will undergo a transformation into a set of similarity equations. Following this transformation, a numerical solution will be obtained using the boundary value problem solver, bvp4c, built in the MATLAB software. Later, analysis and discussion are conducted to specifically examine how various physical parameters affect both the flow characteristics and the thermal properties of the hybrid nanofluid.

Dual solutions are discovered to occur for the case of shrinking disk (λ < 0). Stronger suction triggers the critical values’ expansion and delays the boundary layer separation. Through stability analysis, it is determined that one of the solutions is stable, whereas the other solution exhibits instability, over time. Moreover, volume fraction upsurge enhances skin friction and heat transfer in hybrid nanofluid. The hybrid nanofluid’s heat transfer also heightened with the influence of radiation.

Flow over a shrinking disk has received limited research focus, in contrast to the extensively studied axisymmetric flow problem over a diverse set of geometries such as flat surfaces, curved surfaces and cylinder. Hence, this study highlights the axisymmetric flow due to a shrinking disk under radiation influence, using hybrid nanofluids containing CuO and Ag. Upon additional analysis, it is evidently shows that only one of the solutions exhibits stability, making it a physically dependable choice in practical applications. The authors are very confident that the findings of this study are novel, with several practical uses of hybrid nanofluids in modern industry.