Mobile technology has evolved drastically over the years, and so has the customer’s perception of and expectations on mobile services. Mobile phones have become the essential part of customer’s life style and they expect consumer services to be available on mobile phone. In this saturated market, providing better customer experience through the channel preferred by customers is as important as selling the actual product or services. In the quest to retain existing customers as well as attracting new, companies are developing innovative mobile customer relationship management (mCRM) strategies to strike a balance between its investments and fulfilling of customers need to generate maximum profit. However, not all mCRM strategies succeed leaving customers dissatisfied and switching to competitors providing better mobile services. The purpose of this study is to understand the dynamics between the customer acceptance, customer satisfaction and customer loyalty in the context of mCRM services. Thus, answering the following research questions: a) What are the factors behind customer acceptance? b) Do mCRM services have any effect on customer loyalty? Qualitative research method were utilized to closely study two different mCRM strategies from different industries with costumer in focus. Data for the study was gathered from a costumer survey as well as from interviews with informants within the company. In addition, external data from public domain was used to validate the findings of the study. Furthermore, a research model was developed by identifying the constructs adopted from literature study of technology acceptance model (TAM3) and customer loyalty. The research model was the basis for developing the customer feedback survey. In addition, the constructs helped in identifying the impact on customer acceptance and customer loyalty for the respective mCRM strategy. This study confirms previous findings and contributes to our understanding of technology acceptance as well as customer loyalty. The study reveals that mCRM services are mostly useful to urban customers with busy and on-the-go lifestyle. Furthermore, the study shows that through well practice use behavior customer develops a habit based on the prior evaluation of perceived usefulness and perceived value. In addition, the study indicates that customers build up a new trust towards the mCRM services through the usage of the service. Finally, the results of the study indicate that the mCRM services have an impact on company’s net customer loyalty.

In January 2021, one of the first large-scale implementations of an artificial intelligent computer-aided detection system (AI CAD) for detecting breast cancer was implemented at Capio S:t Göran hospital in Stockholm. AI CAD for detecting breast cancer is promising, however, it can only be a successful implementation if it is accepted by the end-users. This study examines and evaluates factors critical to the acceptance of the AI CAD, prior to the radiology professionals using it by applying the third version of the Technology Acceptance Model, that is TAM3. A questionnaire was designed and distributed accordingly to 28 professionals at the hospital’s breast screening unit. The quantitative data collected were further analyzed using the statistical tool SPSS. The empirical findings concluded that the intention to use the AI CAD was influenced directly by the perceived usefulness and indirectly by image, job relevance, and perceived ease of use. In addition, the association between subjective norm and image was shown to be significant. This study further revealed two new associations, contrary to what TAM3 postulates, the first one being between image and behavioral intention and the second one being between job relevance and behavioral intention. Organizational support, system-related activities, and information and communication are interventions suggested based on the findings in this study, in which the breast screening unit at S:t Göran should tap into to enhance the acceptance of the AI CAD system. / I januari 2021, implementerades ett artificiellt intelligent datorstött detektionssystem som ska upptäcka bröstcancer på Capio S:t Görans sjukhus i Stockholm. Användning av AI CAD för att upptäcka bröstcancer är lovande, men det kan endast bli en framgångsrik implementering om det accepteras av de som använder systemet. Denna studie undersöker och utvärderar de initiala faktorer som är avgörande för användaracceptansen av AI CAD hos radiologipersonal genom att utgå från den senaste versionen av teknologiacceptansmodellen – Technology Acceptance Model 3 (TAM3). Ett frågeformulär utformades i enlighet med modellen och distribuerades till 28 yrkesverksamma på S:t Görans mammografiavdelning. Den kvantitativa data som samlades in från enkäten analyserades med hjälp av det statistiska verktyget SPSS. De empiriska resultaten visade att radiologipersonalens avsikt att använda AI CAD påverkades direkt av den upplevda användbarheten av systemet och indirekt av personalens upplevda syn på hur enkelt systemet är att använda, att systemet är relevant för personalens jobb samt att systemet kan höja personalens image. Dessutom bekräftade studien att den subjektiva normen påverkar systemets image. Slutligen upptäcktes två nya associationer, i vilken TAM3 inte antar. Dessa påträffades mellan image och den beteendemässiga intentionen till att använda systemet samt mellan jobbrelevansen och den beteendemässiga intentionen till att använda systemet. Organisationsstöd, systemrelaterade aktiviteter samt information och kommunikation med personal är interventioner som föreslås baserat på resultaten i denna studie som mammografiavdelningen på S:t Görans sjukhus bör utnyttja för att öka acceptansen av AI CAD systemet.

Increased participation in various social media platforms have led to large amounts of user data being generated, creating an opportunity for businesses that run the platforms to store and sell the data. This has created a situation where users are forced to weigh the benefits of using the platforms against sharing their personal information, which is a risk to their privacy. To address this issue, this study investigates how users weigh usability benefits against the perceived risks of sharing personal information. A case study was conducted on platforms run by Facebook (FP). Data collection was done through interviews and by gathering previous research before the result was analyzed using a qualitative method. The interview questions addressed usefulness, perceived risk and integrity management and were, among other research, formulated from the Technology Acceptance Model. The study made several interesting findings about usefulness, users’ need for integrity and how they perceive and tolerate various risks. Conclusions could then be drawn about how these findings affect users’ decision making process regarding their intention to use FP.

Although many information system (IS) implementations are considered to have the resources necessary to be successful, they often fail. This is especially challenging for small IS providers who lack a proven process for gaining willingness to use and onboard a new customer. Hence, there is a need to develop a framework to identify potential pitfalls in such implementation matters, from designing the system until successfully onboarded customers. This paper aims to target this issue and proposes a framework for identifying common pitfalls during the implementation process of an IT system. Moreover, this paper applies the framework to an IS provider in the start-up phase by focusing on the system user. With the support of the framework and based on the company's context, this paper presents identified pitfalls and suggestions for actions that the IS provider can take to avoid them. IS models are selected and applied considering the company's needs and previous literature. The IS models considered are Value Network Analysis (VNA), Extended Technology Acceptance Model (TAM2), and Theory of Planned Behavior (TPB). As a result, seven pitfalls are identified considering organizational culture and leading change, user resistance, complexity, mandatory reliance, value demonstration, experience and control, and weak links.

Computer-mediated communication (CMC) offers opportunities to assist world language students to become global communicators in a digital society. However, perceptions of high school world language (HSWL) teachers on the suitability of these applications are not known. The purpose of this qualitative case study was to explore and document the professional perspectives of HSWL teachers who have taught over 10 years, to learn the benefits and obstacles that they must consider in teaching communicative language skills with CMC. The research questions explored possible reasons that would motivate or dissuade from teaching with these applications. The technology acceptance model extension (TAM2) provided the conceptual framework for this study because it elucidates the cognitive and social processes that affect teacher decisions when reviewing a technology to support their instruction. The collected data included 6 in-depth interviews, field observations, and document reviews. The data analysis began with a precoding based on TAM2, and coding to identify emergent themes such as student immaturity and content-specific professional development. In the findings, the teachers perceived CMC as unsuitable due to the digital divide and the focus on grammatical competence. However, the teachers noted the possible benefits of content-specific professional development. This study contributes to positive social change by providing insight into the current role of computer technology in HSWL instruction and suggestions for how to encourage teachers to adopt innovative uses of digital technology in their CLT practices.

The problem addressed in this study was the lack of understanding about failures of government leadership in accomplishing complex information technology (IT) projects and the ways such failures can negatively affect organizational performance. The purpose was to query subject matter experts and leaders with the intent to identify methods to reduce complex IT project failure rates in government organizations. This qualitative study drew on the technology acceptance model and the capability maturity model integration framework to evaluate organizations' abilities to manage complex IT projects. The research questions focused on exploring senior managers' experiences, the tacit knowledge of project management methodologies, and IT governance frameworks. The Delphi method was suitable for collecting and analyzing opinions of subject matter experts to help reach group consensus. Qualitative data analysis was used to identify themes, categories, and subcategories for thematic analysis. The result of the study was the identification of critical success factors and leadership attributes to increase the success rate of complex IT projects in federal agencies. This research may be beneficial to federal government program leaders who, as the result of increased insights and knowledge, can more effectively provide online government services using technology-enabled end-users' computing devices in a cost-effective and secure method.

Health portals are dedicated web pages for medical practices to provide patients access to their electronic health records. The problem identified in this quality improvement project was that the health portal in the urgent care setting had not been available to staff nor patients. To provide leadership with information related to opening the portal, the first purpose of the project was to assess staff and patients' perceived use, ease of use, attitude toward using, and intention to use the portal. The second purpose was to evaluate the portal education materials for the top 5 urgent care diagnoses: diabetes, hypertension, asthma, otitis media, and bronchitis for understandability and actionability using the Patient Education Material Assessment Tool, Simple Measures of Goobledygook, and the Up to Date application. The first purpose was framed within the technology acceptance model which used a 26-item Likert scale ranging from -3 (total disagreement) to +3 (total agreement). The staff (n = 8) and patients (n = 75) perceived the portal as useful (62%; 60%), easy to use (72%; 70%), expressed a positive attitude toward using (71%; 73%), and would use the technology (54%; 70%). All materials were deemed understandable (74%-95%) with 70% being the acceptable percentage. Diabetes, otitis media, and bronchitis were deemed actionable (71-100%), but hypertension (57%) and asthma (40%) had lower actionability percentages. Hypertension, asthma, and otitis media had appropriate reading levels (6-8th grade). However, diabetes (10th grade) and bronchitis (12th grade) were higher with the target being less than 8th grade level. All handouts were found to be evidence-based. Recommendations were to revise the diabetes and bronchitis educational handouts to improve readability. Social change can be promoted by this project by facilitating positive patient outcomes at urgent care clinics.

Diabetes type 1 is an autoimmune, incurable disease which requires careful monitoring and treatment to not result in life threatening complications. Managing the disease is to a great extent made by the patients themselves, implying the disease needs to be constantly taken into consideration when doing even the most simple and regular everyday tasks and activities.This study aims to examine the use of AI in everyday treatment for patients with diabetes type 1. The study investigated what areas AI is already used in diabetes care management, and where there is room for development. The purpose is to give an indication of what role AI has and potentially can have in making the life for patients with diabetes type 1 easier. The research was conducted by a combined literature review and a cross sectional multiple case-study, with semi-structured interviews with people diagnosed with diabetes type 1. The gathered data were analyzed in relation to the triangle of diabetes management and technology acceptance model 2. The first indicates what factors are of highest relevance to not create dangerous situations for a diabetic, and the second relates to whether users would accept the use of a complex technology. The result suggested wide current and further potential use of AI in creating functionality in treatment and everyday management of the disease. Further, it became evident that technological tools simplify the lives of diabetics but there are several areas where AI could be further implemented in order to improve it even further.

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This thesis explores the perception and trustworthiness of the users towards artificial intelligence (AI) -generated content on social media platforms. The study employs the Technology Acceptance Model (TAM) and Framing Theory as theoretical frameworks to understand the factors influencing user attitudes and behaviours towards AI-generated content. The research explores three main areas: user trust in AI-generated content, the ability to differentiate between AI-generated and human-generated content and the ethical implications of AI-generated content use. The research employed an online survey with 100 participants to collect quantitative data on their experiences and perceptions of AI-generated content. The findings indicate a range of trust levels in AI-generated content, with a general trend towards cautious acceptance. The results also reveal a gap between the participants' perceived and actual abilities to distinguish between AI-generated content, underlining the need for improved media literacy and awareness initiatives. The thematic analysis of the respondent's opinions on the ethical implications of AI-generated content underscored concerns about misinformation, bias, and a perceived lack of human essence. The study connects these findings with the TAM and Framing Theory, suggesting that perceived usefulness and the framing of AI-generated content significantly impact user trust and acceptance. This research contributes to the ongoing discourse on AI in media and communications, underlining the need for a more nuanced understanding and responsible AI ecosystem development. It highlights the crucial role of public perception, awareness, and ethical considerations in shaping the future of AI-generated content on social media platforms