Technically-driven medical devices such as wireless implantable medical devices (WIMD) have become ubiquitous within healthcare. The use of these devices has changed the way nurses administer patient care. Consequently, the nursing workforce is large and diverse, and with it comes an expected disparity in personalities. Research involving human factors and technology acceptance in healthcare is not new. Yet due to the changing variables in the manner of which patient care is being administered, both in person and in the mechanism of treatment, recent research suggests that individual human factors such as personality traits may hold unknown implications involving more successful adoption of emerging technologies for patient care. The purpose of this research was to empirically investigate the influence of personality traits on a nurse’s intention to use WIMDs for patient care. One hundred and two nurses from a tertiary teaching hospital in Michigan were surveyed to determine if their identifiable personality traits statistically related to their intention to use a WIMD. A predictive model was developed by combining constructs from the unified theory of acceptance and use of technology (UTAUT) model and the Five Factor personality trait model (FFM). The model used moderated multiple regression (MMR) to statistically identify if the personality traits of openness, conscientiousness, extraversion, agreeableness, and neuroticism, moderated one or more statistically significant relationships between 1) performance expectancy (PE) and intention to use (IU), 2) effort expectancy (EE) and IU, 3) and social influence (SI) and IU. It was predicted that PE, EE, and SI would show statistical significance on a nurse’s IU of a WIMD when moderated by one or more of the five personality traits. Results showed statistical significance between PE and IU, and EE and IU, but not between SI and IU, when moderated by extraversion. Results showed no statistical significance between PE and IU, EE and IU, or SI and IU when moderated by openness, conscientiousness, agreeableness, or neuroticism. This research has contributed by conducting an investigation on individual human factors that may impact nurses’ intention to use emerging technologies; and by providing statistical evidence that may help to better predict the role personality traits have on a nurse’s adoption of WIMDs for patient care.

In educational institutions, the use of technology has been used to compliment face to face learning or used alone to deliver the educational needs and learning process for distance education. Where used alone, it is said to be online learning and where it has complimented traditional learning it can be said to be hybrid or blended learning. Before the pandemic, the question of choice or the voluntary use of these technology was there, and the student determined what was best suited for their educational and learning needs. This study looks at the how the students related with technology during the pandemic. It looks at constructs like performance expectancy, fit for use, effort expectancy, fit for task and ends with investigating the student’s perception on intention for future use. Using a mixed approach, the perception of students was sampled. First by using a quantitative method, hinged on the novelty of the disruption to reveal areas that could be of potential interest and then a qualitative method followed. The purpose of using a mixed method approach was for completeness and complimentary reasons. The results of the qualitative data and quantitative data were bridged to form meta-inferences, and these were used to answer the research questions and discuss the findings. The study revealed that technology was easy to use without little or no technical issues, it was fit for the task at hand, it aided the students to achieve their academic goals and needs, but intention to retain the use of technology for future academic activities was not welcomed. This was due to social factors like lack of motivation, feeling of isolation, lack of social interaction been missing but available in traditional classes. these are critical factors that affect the retention of technology for future use. In the presence of choice, they would rather go back to the traditional mode. They integration of technology with traditional mode of learning, i.e., blended mode of learning was highly welcomed.

Chatbots are increasing in popularity, both as a valuable tool for commercial purposes but also as an area of academic research. It has been successfully applied in multiple application areas such as healthcare, education, customer service and work support. Despite the successful use and application of chatbots research has identified two main user experience challenges: technical- and hedonistic limitations. Users also have a hard time understanding what level of competence and functionality they can expect from a chatbot. To combat these challenges, further research is needed to understand the user adoption and perception of chatbots. This study aims to research both the experiences and usage of customer service chatbots but also explore what preferences customers have when it comes to interacting with customer service chatbots or human customer service representatives in e-commerce. The theoretical technology acceptance model called Unified Theory of Acceptance and Use of Technology (UTAUT) was applied for this study. A quantitative study comparing customer service chatbots versus human customer service representatives was performed by conducting a questionnaire. The results from the questionnaire indicated that the participants of the study in general rated human customer service representatives higher in most question categories. The results indicate that the participants would prefer to interact with human service representatives over customer service chatbots which indicates that there is still opposition and challenges surrounding the adoption of customer service chatbots in e-commerce.

Background: The incorporation of artificial intelligence (AI), particularly OpenAI's ChatGPT, in higher education, has sparked substantial discourse since its introduction. AI's transformative role in higher education is largely recognized. Despite its potential to revolutionize the pedagogical field, its application raises several concerns. This research seeks to shed light on the dynamics of ChatGPT use in higher education, contributing to the dialogue surrounding AI's educational implications. Purpose: The analysis of the factors influencing ChatGPTs’ adoption, perception, and its effect on learning experience to help the higher education sector deal with challenges and opportunities presented by the chatbot. Method: The study is conducted on a constructivist-interpretivist ground, employing a qualitative, observation-based, exploratory cross-sectional case study. Semi-structured interviews, based on the UTAUT 2 model, are used as the primary data collection method. Thematic analysis was used to analyze the data and create themes, which combined with an abductive approach helped derive broader meaning and implications. Conclusion: Through a trichotomous model, the researchers have identified the primary factors contributing to ChatGPT adoption, its´ role in the post-adoption period, students’ perspectives on the tool and its future integration, as well as what they perceive the role of the educators is in this evolved landscape, and identifying main psychosocial effects the AI tool has on its users. The results highlight the importance of informed decision making, taking a balanced approach to2assimilating ChatGPT into education, paying attention not only to technical benefits but also to impacts on the learner. Suggestions to extend the UTAUT2 model are made. Avenues for further research are opened by the limitations of this study, and by the interplay of the segments in the tri-part model.

I mars 2016 meddelade regeringen och Sveriges kommuner och regioner tillsammans att Sverige ska vara bäst på Ehälsa år 2025. Syftet är att ta tillvara på digitaliseringens möjligheter inom hälso- och sjukvård då Sveriges befolkning beskrivs vara ett av de mest digitalt mogna i världen. Detta i sig ska öka individens egen kontroll och delaktighet som ska leda till effektivitet, tillgänglighet och medbestämmande i svensk sjukvård. Studien ämnar att ta reda på vad seniorer upplever inom området delaktighet för att således öka kännedomen om hur Vision Ehälsa2025 utformas i enlighet med detta. Tre kvalitativa metoder har genomförts för studiens datainsamling. Fokusgrupp, semistrukturerade intervjuer och användarscenario. Respondenternas ålder har varit 65-75 år. Datainsamlingen från metoderna har analyserats med Unified Theory of Acceptance and Use of Technology, förkortat UTAUT. Urval av litteratur har undersökts med diverse databaser och andra söktjänster för att hitta relevanta vetenskapsartiklar. Databasen Scopus har använts och tidigare relevant kurslitteratur för att säkerställa att studiens syfte och frågeställning besvaras samt styrka datainsamlingen. Datainsamlingen har slutligen jämförts och diskuterats gentemot den insamlade litteraturen och därefter kopplats till studiens syfte och frågeställning. / In March 2016, the government and Sweden's municipalities and regions jointly announced that Sweden should be the best in health by 2025. The aim is to take advantage of the opportunities of digitization in healthcare as Sweden's population is described as one of the most digitally mature in the world. This in itself should increase the individual's own control and participation, which should lead to efficiency, accessibility and co-determination in Swedish healthcare. The study aims to find out what seniors experience in the area of participation in order to thus increase knowledge of how Vision Ehälsa2025 is designed in accordance with this. Three qualitative methods have been implemented for the study's data collection. Focus group, semi-structured interviews and user scenarios. The age of the respondents has been 65-75 years and one of the requirements has been that they reside in Sweden. The data collection from the methods has been analyzed with the Unified Theory of Acceptance and Use of Technology, abbreviated UTAUT. Selection of literature has been implemented to find relevant scientific articles, where the database Scopus has been used together with previous relevant course literature in order to ensure that the purpose and question of the study are answered and to strengthen the data collection. The data collection has then been compared and discussed against the collected literature. It has finally been linked to the purpose and question of the study.

Library management systems (LMS) are a big part of the workday for most librarians. Everything from acquisitions, managing e-resources and circulation work is done through these kinds of systems. Umeå university library implemented a new LMS called Alma back in 2018. They moved from a local system to a more complex and advanced cloud-based system. This study has examined how the system has been received through the lens of the Unified theory of acceptance and use of technology (UTAUT). A survey containing 23 Likert items were answered by librarians at Umeå university’s libraries. The items were grouped under four overhead categories collected from UTAUT: performance expectancy, effort expectancy, social influence and facilitating conditions. Afterwards an analysis was made that examined whether age, gender, experience with the system and most used task in Alma had any influence over certain categories. The study shows that age and gender did not influence performance expectancy, but the most common task did with circulation work as an outlier with more negative scoring. Gender did not influence effort expectancy either, but age did where younger people tended to score lower and the age group 42–49 handing out higher scores. The most used task also influenced this factor but experience with the system did not influence the factor in a major way. Facilitating conditions was influenced by age where the age group in the middle once again scored much higher than the youngest group. Experience with Alma also influenced this factor in the sense that less experienced workers scored lower. Most used task in Alma followed the same pattern as the other factors with circulation tasks scoring lower and administration tasks scoring higher. Social influence did not pass the Cronbach’s alpha that was set at 0.7 and showed overall internal low correlation, therefore it was not included in the analysis.

This research paper examines the innovation adoption of technology, specifically Artificial Intelligence (AI) implementations in hospitals by exploring the capabilities that enables AI innovations using the dynamic capabilities (sensing, seizing and reconfiguring) framework and clinicians’ intentions to use AI innovations for patient care by applying the technology adoption/acceptance framework Unified Theory of Acceptance and Use of Technology (UTAUT) utilizing qualitative case study analysis and quantitative survey methodology respectively. This multi-disciplinary research has considerable relevance to both healthcare business leaders and clinical practitioners by identifying the key factors that drives the decisions to adopt innovations to improve healthcare organizations' competitiveness to enhance patient care as well as to reduce overall healthcare costs. The main findings are: (1) On an organizational level, healthcare organizations with strong and versatile dynamic capabilities, who build on their existing knowledge and capabilities are better able to integrate the innovations into their internal operations and existing services. The identified barriers provide a clear sense of organizational barriers and resistance points for innovation adoption (2) On an individual level, the impact of quality of care and organization leadership support are the key factors that facilitates the adoption of innovation among the clinicians. (3) Current trends and key impact areas of AI technology in the healthcare industry are identified Key words: Innovation, Innovation Adoption, Dynamic Capabilities, Healthcare, Artificial Intelligence, AI, Technology, Strategic Management / Business Administration/Management Information Systems

As low-voter-turnout continues to be a concern for the political system in the U.S., the idea online voting platforms (OVPs), to reduce access and use barriers, has been debated. Lowlevel elections in several states across the country have experimented with OVPs through U.S.based internet voting organization, Everyone Counts. These experiments resulted in both the confirmation of perceived benefits and problems. Surveying 196 U.S. citizens through Survey Sampling International, this study garnered respondents' feelings toward several factors correlated with voter-turnout, and the likelihood of adopting OVPs. Using the Unified Theory of Acceptance and Technology Use Model to frame the analysis, the data were analyzed using ols regression. I predicted that citizens would perceive OVPs as an improvement to the current system, and consequently, voter-turnout would increase if OVPs were available, especially among younger citizens (ages 18-44). The analyses illustrated that OVPs would not have a large impact on voter-turnout, and for some would even discourage participation. Furthermore, it was older respondents (ages 44+) who had a stronger positive correlation between effort expectancy and feeling empowered. I conclude by suggesting that low-voter-turnout might be best combated through efforts to improve political efficacy, and that accessibility to poll booths only accounts some of the story. / Master of Science

Yes / Which antecedents affect the adoption by users is still often a puzzle for policy-makers. Antecedents examined in this research include technological artefacts from the Unified Theory of Acceptance and Use of Technology (UTAUT), consumer context from UTAUT2 and psychological behaviour concepts such as citizens' channel preference and product selection criteria. This research also investigated cultural domination on citizens' behavioural perception. The data for this study was collected among citizens from three countries: USA, Canada, and Bangladesh. The findings suggest that the UTAUT model could partially shape technology artefact behaviour and the extended UTAUT must consider specific determinants relevant to cognitive, affective, and conative or behavioural aspects of citizens. The model helps policy-makers to develop mobile healthcare service system that will be better accepted. The finding also suggests that this mobile service system should reflect a country's cultural traits. These findings basically extend the theoretical concept of UTAUT model to articulate adoption behaviour of any complex and sensitive ICT related issues like mobile healthcare system.

Yes / Based on a critical review of the Unified Theory of Acceptance and Use of Technology (UTAUT), this study first formalized an alternative theoretical model for explaining the acceptance and use of information system (IS) and information technology (IT) innovations. The revised theoretical model was then empirically examined using a combination of meta-analysis and structural equation modelling (MASEM) techniques. The meta-analysis was based on 1600 observations on 21 relationships coded from 162 prior studies on IS/IT acceptance and use. The SEM analysis showed that attitude: was central to behavioural intentions and usage behaviours, partially mediated the effects of exogenous constructs on behavioural intentions, and had a direct influence on usage behaviours. A number of implications for theory and practice are derived based on the findings.