The importance of aligning information technology and business strategies to exploit capabilities and change business practices has increased as firms strive for competitive advantage in a diverse and changing marketplace. Nevertheless, over 50% of firms implementing enterprise resource planning (ERP) systems ranked expected process and value enhancements as inadequate, whereas only 13% indicated that implementations met their needs. The unified theory of acceptance and use of technology (UTAUT) model formed the conceptual framework of this single case study. The study comprised a purposeful sampling of 8 business managers in Southeast Alabama working in related job roles and based on established eligibility criteria. Data collection involved semistructured interviews, casual observations, and document analysis. Through method triangulation and predetermined themes directly related to the UTAUT conceptual framework, 5 themes emerged: management endorsement, change management, training and education, dedicated resources, and governance. Results of this research may influence the elimination of key barriers central in the deployment and adoption of ERP systems by the public sector. The study's implications for positive social change include the potential to enhance social and intellectual capital formation through recognizing strategies that mitigate employees' gender and age variances during an ERP implementation.

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.

Indiana University-Purdue University Indianapolis (IUPUI) / Background: Pulmonary rehabilitation (PR) has the potential to reduce the symptoms and complications of respiratory diseases through an interdisciplinary approach. Providing PR services to the increasing number of patients with chronic respiratory diseases challenges the current health care systems because of the shortages in health care practitioners and PR programs. Using telerehabilitation may improve patients’ participation and compliance with PR programs. The purpose of this study was to examine the applicability of the technology acceptance model (TAM) to explain telerehabilitation acceptance and to determine the demographic variables that can influence acceptance. Methods: A cross-sectional survey-based design was utilized in the data collection. The survey scales were based on the TAM. The first group of participants consisted of health care practitioners working in PR programs. The second group of participants included patients attending traditional PR programs. The data collection process started in January 2017 and lasted until May 2017. Results: A total of 222 health care practitioners and 134 patients completed the survey. The results showed that 79% of the health care practitioners and 61.2% of the patients reported positive intention to use telerehabilitation. Regression analyses showed that the TAM was good at predicting telerehabilitation acceptance. Perceived usefulness was a significant predictor of the positive intentions to use telerehabilitation for health care providers (OR: 17.81, p < .01) and for the patients (OR: 6.46, p = .04). The logistic regression outcomes showed that age, experience in rehabilitation, and type of PR increased the power of the TAM to predict the intention to use telerehabilitation among health care practitioners. Age, duration of the disease, and distance from the PR center increased the power of the TAM to predict the intention to use telerehabilitation among patients. Conclusion: This is the first study to develop and validate a psychometric instrument to measure telerehabilitation acceptance among health care practitioners and patients in PR programs. The outcomes of this study will help in understanding the telerehabilitation acceptance. It will help not only to predict future adoption but also to develop appropriate solutions to address the barriers of using telerehabilitation.

Indiana University-Purdue University Indianapolis (IUPUI) / Medication nonadherence among middle-aged to older adults with chronic conditions often stems from forgetting to take or fill medications as prescribed. A pilot study indicated the feasibility of technology acceptance model (TAM)-based smartphone medication reminder app (SMRA) training as a way to promote their app use and medication adherence. This dissertation assesses the viability and effect size of the modified TAM-based SMRA training in promoting app use and medication adherence, as well as its delivery design in preparation for a larger efficacy study. A two-group pretest-posttest design was employed. Twenty-nine adults aged over 40 years and taking medications for chronic condition management were recruited from Midwestern university and community sites. The training group (n = 15) received the modified TAM-based SMRA training; whereas the non-training group (n = 14) self-navigated app features. The training group reported significantly higher levels of perceived usefulness, perceived ease of use, positive subjective norm, and intention to use the app. In addition, the training group reported a higher proportion of active app use than the non-training group. Modified TAM-based SMRA training was not viable in increasing the levels of medication adherence variables. Effect sizes suggested at least 52 participants as a sample size for a larger efficacy study. Participants suggested that training could be improved by scheduling separate group training for iPhone and Android phone users, providing a live online training option, providing small group training with peer helper, tailoring training length to participant preference, and working with family members and healthcare providers as co-trainees and co-trainers.

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Predictive AI has huge potential to increase efficiency in taxi networks, improving incomes of drivers and passengers’ time, by calculating passenger demands and making the informationaccessible to drivers. However, to gain these benefits, drivers must accept the technology, and designers must understand how their perceptions govern acceptance. This study evaluates predictive AI applied to taxi fleet management from a user acceptance perspective, in the context of a proposed extended technology acceptance model, with added user experience constructs.Process modelling of a taxi organisation was performed to see how the algorithm fit into that context, and an app was designed to give taxi drivers access to its output. After a period, semistructured interviews were conducted, and thematic analysis was performed to identify what factors were important for their acceptance. The study found that visual design, interactivity, complexity, compatibility, utility, inclusivity, norms, presentation, and trustworthiness were factors that needed to be addressed by designers for successful implementation of predictive AI in the context of taxi fleet management.

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.

[pt] Esta pesquisa teve como objetivo investigar os principais fatores que influenciam a adoção e uso de tecnologias no setor de serviços, mais especificadamente no setor de serviços financeiros. O arcabouço teórico permitiu a definição de construtos cognitivos e afetivos para a elaboração do modelo conceitual. Além disso, este modelo incluiu construtos de elevada importância para o consumo de serviços financeiros, como Confiança e Risco Percebido. Por fim, o construto de Prontidão para a Tecnologia, desenvolvido por Parasuraman e Colby (2014) foi adicionado ao modelo, a fim de analisar a influência da predisposição individual em relação às tecnologias em geral, enquanto antecedente dos demais construtos. Os dados da pesquisa foram obtidos por meio de uma survey online, que foi respondida por 402 estudantes ou recém-formados de cursos de graduação e pós-graduação. O modelo final da pesquisa, denominado Modelo de Prontidão e Aceitação de Mobile Payments, indicou que a Prontidão para a Tecnologia exerce maior influência sobre os aspectos cognitivos do que sobre os afetivos, indicando que a prontidão auxilia significativamente o processo racional de avaliação da tecnologia. Além disso, os resultados indicaram que o construto de Utilidades e Vantagens Percebidas exerceu a maior influência sobre a Atitude, seguido pela Confiança e pela Apreciação da Qualidade Percebida, confirmando que os aspectos cognitivos são predominantes no processo de decisão quanto ao uso de serviços financeiros. Por fim, o Risco Percebido apresentou uma influência negativa, mas de pequena magnitude, sobre a Intenção de Uso. O Modelo de Prontidão e Aceitação de Mobile Payments foi capaz de explicar cerca de 76 porcento da Atitude e 68 porcento da Intenção em relação ao uso de tecnologias, mostrando-se um modelo com boa capacidade preditiva e de contribuição relevante para a literatura de aceitação de tecnologias. / [en] This research aimed to investigate what factors influence the adoption and use of technologies in services, more specifically in the financial services sector. The theoretical framework allowed the definition of cognitive and affective constructs for the preparation of the conceptual model. Furthermore, this model also includes constructs with high relevance for consumption of financial services, like Trust and Perceived Risk. Finally, the Technology Readiness construct, developed by Parasuraman and Colby (2014), was added to the model in order to analyze the influence of individual predisposition in relation to technology in general, as an antecedent of the other constructs. Data was collected via an online survey, which was answered by 402 students or recent graduated of graduate and post-graduate courses. The final model, named Model of Readiness and Acceptance of Mobile Payments, indicated that the Readiness Technology has stronger effects on cognitive aspects than on the affective aspects, indicating that readiness significantly assists the rational evaluation process about the use of technologies. Furthermore, the results indicated that the Perceived Usefulness and Advantage construct has the strongest effect over Attitude, followed by Trust and by Enjoyment of Perceived Quality, confirming that the cognitive aspects are predominant in decision-making regarding the use of financial services. Finally, Perceived Risk had a negative but very little effect over Intention. The Model of Readiness and Acceptance of Mobile Payments was able to explain about 76 percent of Attitude and 68 percent of Intention, showing itself a model with good predictive capability and presenting significant contribution to the literature of acceptance of technologies.

Industries with conservative mindsets are known for being reluctant toward adoption of new technologies and resistant to change. The diamond business is one of those examples that encounter challenges in implementing disruptive innovations like blockchain technology despite its potential benefits. The purpose of this thesis is to explore the antecedents influencing adoption of disruptive innovations in conservative industries, with a particular emphasis on benefits and challenges of embracing blockchain technology in the diamond industry. Employing a qualitative research approach, this thesis utilizes semi-structured interviews with the four industry experts from different companies. The empirical data is analyzed using the Technology Acceptance Model, the Innovation Diffusion Theory frameworks, and contextual data.Findings reveal that most of the antecedents are not favorable to the adoption of disruptive innovations in traditional sectors. Competition was found to enhance the adoption process, while resistance to change, industry heritage, uncertainty, and dependency on industry leaders have unfavorable effects. Transparency, customer trust/pressure were found to have both positive and negative impacts. Findings show that benefits of blockchain technology implementation outweigh its challenges for the diamond industry, however, its observability, and complexity, hinder the adoption due to the fact blockchain is a relatively new technology that is still hard to grasp for most industry professionals. This thesis contributes to the body of knowledge by linking findings to the Technology Acceptance Model and Innovation Diffusion Theory frameworks, exploring deeply conservatism within industries, and identifying antecedents as obstacles and opportunities to widespread blockchain acceptance. Additionally, the researchers provide a solution for observability in the form of an in-depth marketing strategy, which aims at creating a differentiation between ‘blockchain diamonds’ and naturally mined diamonds.

The purpose of this research was to investigate the effect of technology acceptance on post secondary African American students' achievement in Mathematics. The study was conducted in a historically Black four-year college in Daytona Beach, Florida on students using the computer to enhance their mathematics performance in an introductory algebra mathematics course. By using Technology Acceptance Model (TAM) developed by F. Davis (1989), this study focused on variables such as perceived usefulness, perceived ease of use, computer self-efficacy, subjective norms, attitude and actual use of the computer to account the effect towards the achievement in the final exam which is an outcome variable. The data were collected over four different time periods during the fall semester of 2004 to find how these results changed over time. The study was conducted by using six instruments to measure perceived usefulness, perceived ease of use, computer self-efficacy, subjective norms, actual use of computer (frequency and duration), attitude and an additional demographic instrument. The data were analyzed by path analysis using multiple regressions (SPSS for windows) to find the contribution of each independent variable to the dependent variable that ultimately predicted the final outcome. Computer self-efficacy and subjective norms were determinants of perceived usefulness and perceived ease of use which in turn determined the attitude of students using computer for enhancing their math score in the final. The findings of path analysis indicated that the research did not support TAM. The results suggested that perceived usefulness is the most significant predictor of perceived ease of use. The duration of actual use of the computer in a single session contributed significantly towards their final score for achievement in mathematics. The students preferred a face-to-face instruction in mathematics by the instructor than interaction with a computer. Additional research endeavors should be devoted to the measurement of system use in different set up with different ethnic background to further analyze students' acceptance or rejection of technology towards their achievement in mathematics.