Research on the use intention of potential designers of unmanned cars based on technology acceptance model.
Ontology highlight
ABSTRACT:
SUBMITTER: Huang T
PROVIDER: S-EPMC8378682 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The expansion of augmented reality across society, its availability in mobile platforms and the novelty character it embodies by appearing in a growing number of areas, have raised new questions related to people's predisposition to use this technology in their daily life. Acceptance models, which have been updated following technological breakthroughs and society changes, are known to be great tools for predicting the intention to use a new technological system. This paper proposes a new acceptance model aiming to ascertain the intention to use augmented reality technology in heritage sites-the Augmented Reality Acceptance Model (ARAM). ARAM relies on the use of the Unified Theory of Acceptance and Use of Technology model (UTAUT) model's constructs, namely performance expectancy, effort expectancy, social influence, and facilitating conditions, to which the new and adapted constructs of trust expectancy, technological innovation, computer anxiety and hedonic motivation are added. This model was validated with data gathered from 528 participants. Results confirm ARAM as a reliable tool to determine the acceptance of augmented reality technology for usage in cultural heritage sites. The direct impact of performance expectancy, facilitating conditions and hedonic motivation is validated as having a positive influence on behavioural intention. Trust expectancy and technological innovation are demonstrated to have a positive influence on performance expectancy whereas hedonic motivation is negatively influenced by effort expectancy and by computer anxiety. The research, thus, supports ARAM as a suitable model to ascertain the behavioural intention to use augmented reality in new areas of activity.
| S-EPMC10053472 | biostudies-literature
Project description:The purpose of this study was to develop and empirically test a model for predicting the key factors affecting nurses' behavioral intention to use mobile learning (m-learning). We explored behavioral intention from users' perspectives by applying an extended unified theory of acceptance and use of technology (UTAUT) model with the addition of information quality, system quality, technostress, and satisfaction. We conducted a survey of the district and regional hospitals in central Taiwan. Data were derived from 434 respondents. Structural equation modeling was applied to analyze the causal effects of 15 hypothesized predictive factors. We determined that satisfaction, social influence, performance expectancy, facilitating conditions, and effort expectancy positively impacted nurses' behavioral intention to use m-learning. In addition, technostress was a negative antecedent of effort expectancy. Information quality and system quality had significantly positive effects on satisfaction, performance expectancy, and effort expectancy. This study provides hospital managers with a reference when assessing future developments and informs approaches to promote m-learning.
| S-EPMC9150498 | biostudies-literature
Project description:PurposeSmart home devices have great potential to improve the quality of life and independence of older people, positively impacting their health, safety, and comfort. However, Chinese research in this field is still in its early stages. Therefore, more comprehensive and in-depth studies are needed to comprehend the various aspects influencing the acceptance and use of smart homes by older users.Patients and methodsThis study adopted the Technology Acceptance Model (TAM) and included perceived usefulness, perceived ease of use, usage intention, intergenerational technology support, perceived value, and perceived risk as extension variables to delve deeper into the behavioral intentions of older users in smart home services. The study used a convenience sampling method to randomly distribute 236 questionnaires among older adults over the age of 60 in the school's community and neighboring urban communities who have experience in smart home use and who can complete human-computer interactions either independently or with the help of others, mainly focusing on the four sections: user characteristics, family situation, experience of use, and usage intention. The study used structural equation modeling (SEM) and factor analysis to analyze the completion of questionnaires. Finally, we conducted a validation analysis of the rationality and scientificity of the model and derived the six dimensions of the model of the influencing factors on the use of smart home products by the elderly and the weight sizes of their corresponding 13 influencing factors.ResultsThe results show that perceived usefulness and perceived ease of use have a positive effect on users' intention to use smart homes. Perceived ease of use has a positive effect on the perceived usefulness of smart homes. In addition, intergenerational technology support, perceived value, and perceived risk impact users' perceived usefulness and perceived ease of use of the smart home.ConclusionThis research aims to describe the factors influencing older users' willingness to use smart homes. The findings are not only significant for the elderly in China but also of broad value to other regions and countries facing similar demographic challenges. The development of smart homes not only involves the elderly but is also closely related to all segments of society. The government should increase policy support and guide more social forces to participate in the development of the smart home industry. Service providers and designers should fully understand the demand situation and user experience of target users to develop easy-to-use smart home solutions. At the same time, smart homes, as intelligent products for the elderly, need to focus not only on the basic needs of the elderly such as material life and home safety, but also on the spiritual needs of elderly users. Children or caregivers should always pay attention to the psychological state of the elderly and actively guide them to use smart homes to help them realize their self-worth. We look forward to more research focusing on this area in the future and further exploring the specific issues and solutions involved.
| S-EPMC10971693 | biostudies-literature
Project description:Over recent years, online purchase platforms of fruits are increasingly emerged to advance the e-commerce development and improve quality of human life. Unfortunately, we empirically observed that a lot of enterprises selling fruits online have suffered from bankruptcy due to a lot of complicated factors, such as inefficient logistics, low acceptance of online platforms, and financial risks. One of the root causes responsible for such an unanticipated phenomenon is related to the purchase intention, which motivates us to investigate what are the dominant factors affecting the online purchase intention of fruits. The results can be of great significance to the development of fruit e-commerce enterprises in online marketing. Based on the technology acceptance model (TAM) and perceived risk theory (PRT), this research developed an integrated theoretical model to explore the influential factors underlying consumers' intention to purchase fruits online. A web-based survey of 344 consumers with ages below 30 was used to test the hypotheses in our theoretical model. Through sample collection with questionnaires, a structural equation model is developed to compute the coupling relationship between influential factors and purchase intention. The results reveal that fruit quality and price are dominantly affecting the willingness of consumers to purchase fruit. Surprisingly, we found that e-commerce platforms, information quality, and perceived risk are less significant. Finally, some specific suggestions are recommended for fruit e-commerce enterprises in devising effective marketing strategies.
| S-EPMC6116833 | biostudies-literature
Project description:ObjectiveThe primary aim of this study was to apply a novel technology acceptance model (TAM) for virtual reality (VR) in healthcare. The secondary aim was to assess reliability of this model to evaluate factors that predict the intentions of pediatric health providers' use of VR as an anxiolytic for hospitalized pediatric patients.Materials and methodsHealthcare providers that interacted with pediatric patients participated in a VR experience available as anxiolysis for minor procedures and then completed a survey evaluating attitudes, behaviors, and technology factors that influence adoption of new technologies.ResultsReliability for all domain measurements were good, and all confirmatory factor analysis models demonstrated good fit. Usefulness, ease of use, curiosity, and enjoyment of the VR experience all strongly predict intention to use and purchase VR technologies. Age of providers, past use, and cost of technology did not influence future purchase or use, suggesting that VR technologies may be broadly adopted in the pediatric healthcare setting.DiscussionPrevious VR-TAM models in non-healthcare consumers formulated that age, past use, price willing to pay, and curiosity impacted perceived ease of use. This study established that age, past use, and cost may not influence use in healthcare. Future studies should be directed at evaluating the social influences and facilitating conditions within healthcare that play a larger influence on technology adoption.ConclusionThe VR-TAM model demonstrated validity and reliability for predicting intent to use VR in a pediatric hospital.
| S-EPMC10483581 | biostudies-literature
Project description:The technology acceptance model (TAM) has not been applied beyond the technological context, despite its widespread applications. This study extends the TAM to consumer goods and validates the conceptualised consumer goods acceptance model (CGAM) using tea-to-go as a proxy for consumer goods. An exploratory research approach based on a quota sample is used to adjust and test the CGAM, showing that the adjusted CGAM and its measures are reliable and valid, thus supporting the hypothesis that extending the TAM to a non-technological context is possible. The results are discussed in light of the data collection, which is based on a cross-sectional setting, assuming consumers' knowledge of the good and forcing answers based on assumptions. The results show that despite major changes to the exogenous variables, the difference in variance levels between perceived usefulness (PU) and perceived ease of use (PEOU) is in accordance with TAM 3. Thus, PU is the strongest predictor of behavioural intention (BI), supporting the choice of constructs influencing PU. This also indicates that usefulness outweighs ease of use. The findings demonstrate that each variable category has a favourable influence on PU and PEOU. Specifically, cognitive instrumental processes (CIP) and value-related aspects (VRA) are significant predictors of PU, whereas CIP is the most critical driver, highlighting that consumer actions are driven by factors correlated with lifestyle, trends, and price. VRA_1 had the strongest impact on PU, accentuating the high potential of functional ingredients, such as vitamins. Furthermore, the results show that the anchor variables have a stronger impact on PEOU than the adjustment variables, emphasising the importance of enjoyment and indulgence in consumer goods, especially tea-to-go. These findings show that the empirically tested and adjusted CGAM provides a solid basis for measuring the acceptance of consumer goods and identifying key drivers.
| S-EPMC10966591 | biostudies-literature
Project description:Internet- and mobile-based interventions (IMI) offer an effective way to complement health care. Acceptance of IMI, a key facilitator of their implementation in routine care, is often low. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study validates and adapts the UTAUT to digital health care. Following a systematic literature search, 10 UTAUT-grounded original studies (N = 1588) assessing patients' and health professionals' acceptance of IMI for different somatic and mental health conditions were included. All included studies assessed Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions and acceptance as well as age, gender, internet experience, and internet anxiety via self-report questionnaires. For the model validation primary data was obtained and analyzed using structural equation modeling. The best fitting model (RMSEA = 0.035, SRMR = 0.029) replicated the basic structure of UTAUT's core predictors of acceptance. Performance Expectancy was the strongest predictor (γ = 0.68, p < .001). Internet anxiety was identified as an additional determinant of acceptance (γ = -0.07, p < .05) and moderated the effects of Social Influence (γ = 0.07, p < .05) and Effort Expectancy (γ = -0.05, p < .05). Age, gender and experience had no moderating effects. Acceptance is a fundamental prerequisite for harnessing the full potential of IMI. The adapted UTAUT provides a powerful model identifying important factors - primarily Performance Expectancy - to increase the acceptance across patient populations and health professionals.
| S-EPMC8463857 | biostudies-literature
Project description:The COVID-19 pandemic has accelerated implementation of telemedicine in healthcare facilities for delivery of care. Healthcare providers' acceptance of the telemedicine services is important for successful implementation of this new system. A questionnaire based on the Technology Acceptance Model (TAM) has been used to measure user acceptance of telemedicine service. The aim of this study was to translate and validate the English version of the questionnaire into Malay, to extend the availability and utilization of this questionnaire in Malaysia. A forward and backward translation of the questionnaire was conducted to produce the TAM in the Malay version (Malay-TAM). Panel experts assessed content validity. Internal consistency reliability was determined using Cronbach's alpha. Confirmatory factor analysis based on structural equation modelling was performed to validate the factor structure. The questionnaire was then tested on and completed by 149 healthcare workers from several public health clinics across Malaysia. The Malay-TAM demonstrated good reliability with Cronbach's alphas ranging from 0.823 to 0.912. Factor analysis showed good convergent validity but relatively poor discriminant validity. All five constructs were retained to preserve content validity. The findings suggest that the Malay-TAM can serve as a reliable and valid instrument to measure acceptance to telemedicine.
| S-EPMC9020140 | biostudies-literature
Project description:BackgroundArtificial intelligence-enabled clinical decision support systems (AI-CDSSs) offer potential for improving health care outcomes, but their adoption among health care practitioners remains limited.ObjectiveThis meta-analysis identified predictors influencing health care practitioners' intention to use AI-CDSSs based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Additional predictors were examined based on existing empirical evidence.MethodsThe literature search using electronic databases, forward searches, conference programs, and personal correspondence yielded 7731 results, of which 17 (0.22%) studies met the inclusion criteria. Random-effects meta-analysis, relative weight analyses, and meta-analytic moderation and mediation analyses were used to examine the relationships between relevant predictor variables and the intention to use AI-CDSSs.ResultsThe meta-analysis results supported the application of the UTAUT to the context of the intention to use AI-CDSSs. The results showed that performance expectancy (r=0.66), effort expectancy (r=0.55), social influence (r=0.66), and facilitating conditions (r=0.66) were positively associated with the intention to use AI-CDSSs, in line with the predictions of the UTAUT. The meta-analysis further identified positive attitude (r=0.63), trust (r=0.73), anxiety (r=-0.41), perceived risk (r=-0.21), and innovativeness (r=0.54) as additional relevant predictors. Trust emerged as the most influential predictor overall. The results of the moderation analyses show that the relationship between social influence and use intention becomes weaker with increasing age. In addition, the relationship between effort expectancy and use intention was stronger for diagnostic AI-CDSSs than for devices that combined diagnostic and treatment recommendations. Finally, the relationship between facilitating conditions and use intention was mediated through performance and effort expectancy.ConclusionsThis meta-analysis contributes to the understanding of the predictors of intention to use AI-CDSSs based on an extended UTAUT model. More research is needed to substantiate the identified relationships and explain the observed variations in effect sizes by identifying relevant moderating factors. The research findings bear important implications for the design and implementation of training programs for health care practitioners to ease the adoption of AI-CDSSs into their practice.
| S-EPMC11333871 | biostudies-literature
Project description:Unmanned aerial vehicles (UAVs) have become useful tools to extend human abilities and capacities. Currently UAVs are being used for the surveillance of environmental factors related to the transmission of infectious diseases. They have also been used for delivering therapeutic drugs and life-saving supplies to patients or isolated persons in extreme conditions. There have been very few applications of UAVs for disease surveillance, control and prevention to date. However, we foresee many uses for these machines in the fight against zoonotic disease. The control of zoonoses has been a big challenge as these diseases are naturally maintained in animal populations. Among 868 reported zoonoses, echinococcosis (hydatid disease) is one of the most severe public health problems and listed as one of 17 neglected tropical diseases targeted for control by the World Health Organization. Infected dogs (domestic or stray) play the most important role as definitive hosts in maintaining the transmission of echinococcosis. However, the actual contribution of wild canines to transmission has received little attention as yet, but should certainly not be ignored. This paper summarizes the history of development and application of UAVs, with an emphasis on their potential use for zoonosis control. As an example, we outline a pilot trial of echinococcosis control in the Qinghai-Tibet Plateau region, in which UAVs were used to deliver baits with praziquantel for wildlife deworming. The data suggested that this is a cost-effective and efficient approach to the control of zoonotic diseases transmitted among wild animal populations.
| S-EPMC5994646 | biostudies-literature