Artificial intelligence has grown in importance in many application areas. However, the application in the education sector is in an embryonic state, where a variety of trials has been conducted. The purpose of this master’s thesis is to investigate the factors that influence the acceptability of AI chatbots by university students in higher education which might point subsequently to the lack of usage. The study also suggests the most appropriate communication areas of AI chatbot application in higher education suggested by students. For this study, the unified theory of Acceptance and Use of technology 2 (UTAUT2) has been compiled with the qualitative data gathered from semi-structured interviews and questionnaire surveys. The study participants are university students from various countries (Sweden, Norway, Finland, Czech Republic). The findings showed three primary constructs: Performance expectancy (PE), Effort expectancy (EE), and a newly proposed construct, Nonjudgmental expectancy (NE), to significantly predict intention to use AI chatbot technology without education intentionality. Students suggested using AI chatbots for recap of course material, study material recommendation, and exam and requirements information.  Furthermore, this study provides a rationale behind AI chatbot acceptability based on students' generation characteristics. The results can guide universities to incorporate innovative solutions into their organization.

The aim of this work is to simplify access to information for citizens of the city of Brno and at the same time to innovate the way of communication between the citizen and his city. The problem is solved by creating a conversational agent - chatbot Kroko. Using artificial intelligence and a Czech language analyzer, the agent is able to understand and respond to a certain set of textual, natural language queries. The agent is available on the Messenger platform and has a knowledge base that includes data provided by the city council. After conducting an extensive user testing on a total of 76 citizens of the city, it turned out that up to 97\% of respondents like the idea of a city-oriented chatbot and can imagine using it regularly. The main finding of this work is that the general public can easily adopt and effectively use a chatbot. The results of this work motivate further development of practical applications of conversational agents.

The digitalization of society is a major trend that is currently transforming the businesslandscape (Parviainen et al., 2017, p. 63). Within this digital era, the AI chatbot hasemerged (Hsu & Lin, 2023, p. 2), enabling companies to provide high-quality customerservice 24/7. AI chatbots offer a range of benefits and possibilities that can be utilized invarious industries. There is evidence that AI chatbots have the potential to create loyalcustomers, making it a valuable tool for businesses. Therefore, this thesis investigateswhat AI chatbot attributes can relate to the two dimensions of customer loyalty amongGen Z.The purpose of this research is to help organizations to build relationships with customersand provide insight into which attributes of an AI chatbot can be used by companies tocreate value for customers. This to further facilitate their work of building customerloyalty. In this study, we utilize a framework to quantitatively measure AI chatbotsthrough various attributes, including Availability, Ease of Use, Accuracy of Response,Responsiveness, Assurance, and Empathy. Then the relationship of the attributes washypothesized together with the two dimensions of customer loyalty, attitudinal andbehavior loyalty. The questionnaires was distributed to Gen Z through snowball and self-selection sampling techniques. Through the online survey, 73 responses were collected totest the hypothesis. It was found that empathy has a significant relationship with bothdimensions of customer loyalty, and assurance has a significant relationship withattitudinal loyalty.We are convinced that this strengthens and reinforces the ongoing research on customerloyalty. Moreover, the study expands the quantitative work on AI chatbots by introducingand utilizing a framework to examine the attributes of AI chatbots in a general context.Furthermore, the thesis provides knowledge to companies that are currently working onor developing AI chatbots, of which attributes that should be prioritized to enhancecustomer loyalty. Our findings suggest that these attributes are assurance and empathy.

The success of software development projects heavily depends on effectively capturing and meeting stakeholders' requirements. However, involving multiple stakeholders with diverse backgrounds and objectives often leads to conflicts among these requirements. These conflicts represent inconsistencies in the system design, resulting in various challenges, including project delays, increased costs, and potential system failures. Previous research has primarily focused on identifying conflicts with algorithms or negotiation, while conversational AI's potential to detect conflicts in real-time has been neglected. This thesis study addresses the challenge of requirement conflicts by proposing a novel approach that leverages conversational AI in the form of a chatbot. The chatbot, developed using the Rasa platform, enables real-time detection of conflicts, focusing on three general types: duplicated (similar), incompatible, and contradictory requirements. During the study, the design science research method is employed to guide the chatbot's development. Further, an experiment is applied to evaluate the chatbot's performance compared with domain experts using four different datasets. The experiment results are presented using F1 scores, which calculate precision and recall for both the chatbot and the experts on each dataset. Overall, the chatbot scored 0.8, while the experts achieved a slightly higher score of 0.86. To determine if there was a statistically significant difference between the two performances, a Wilcoxon signed-rank test was conducted on the results. The analysis showed no significant difference in the F1 score between the chatbot and the experts, indicating the chatbot's feasibility and effectiveness in detecting conflicts. The contribution of this thesis study can advance requirements engineering by providing a user-friendly and efficient method for real-time conflict detection, enhancing the quality and overall success of software development projects.

Since the coronavirus pandemic in 2019, millions of people started to use online streaming and entertainment services during the lockdown. Streaming solutions such as OTT and IPTV has grown and boosted the live streaming and non-linear streaming revenue, by using new technologies and innovation such as Artificial Intelligence (AI) to improve the video quality, performance, and security of video streaming services. However, QoS and QoE guarantee and traffic management is still a challenge to many multimedia services and systems provided over the Internet. In this paper the analysis of a proposed user-friendly design will be discussed, describing how it can improve the management and troubleshooting experience. And in what way an AI knowledge-based agent can be used to improve and support the operators daily tasks and challenges. With an usability test, the results showed that the combination of an user-centered interface and AI-technology can improve the productivity in video troubleshooting and prevention of common issues. The user-centered design focuses on the user’s goal and needs, using interactive products to help the user achieve their goal. And the AI would assist the operators to identifying network congestion, stream quality, and much more.

Artificially intelligent chatbots are rapidly gaining popularity in customer service, and they can offer businesses benefits such as increased stock prices and low-cost, efficient service. However, customer trust and satisfaction with these chatbots are often low. Most current research focuses on which business benefits artificially intelligent systems can yield, and less focus lies on how to create satisfactory experiences for the customers. This study examines which chatbot characteristics that build customer trust and satisfaction, and identifies the types of inquiries where customers prefer artificially intelligent chatbots over human customer service agents. An online questionnaire was conducted with 47 participants, primarily 18-24-year-old females from Sweden, with a university degree and high comfort with modern technology. The data analysis, using the Wilcoxon signed-rank test and an investigation of the mean and median scores, revealed no characteristic was significantly more important for trust than for enhancing experience. However, anthropomorphism was indicated to have some importance for trust, though not statistically significant. Machine reading comprehension, perceived accuracy, and privacy concerns were found to be important for a positive customer experience. Participants preferred artificially intelligent chatbots over human customer service agents only for basic information inquiries. The findings support existing theories such as the service quality model and can provide guidance for businesses wanting to implement artificially intelligent chatbots in customer service.

樂齡商機因人口老化問題而持續受到關注，新聞媒體更是屢屢報導各國各界對樂齡市場龐大商機的預估，惟與現實生活對比後不難發現樂齡商品或服務甚為不足；故而在自身與年邁父母對樂齡服務的需求，觀察時下樂齡人口及其家庭可能面臨的問題與需求，便興起「樂齡服務平台」的念頭。 在客觀驗證目標族群樣貌後，因應多元而分散的特性，以及現今尚未成型的樂齡市場環境下，「樂齡服務平台」的商業模式必將面對足以開疆闢土、滿足需求的核心競爭力建構問題。是而考量樂齡族群的需求特色及痛點外，亦檢視個人的專業、經驗與人脈、資源範圍，遂鎖定可同時滿足多方條件考量的「AI ChatBot聊天機器人」科技運用，成為「樂齡人工智慧服務平台」構想起源。 由於現今台灣對於人工智慧「AI ChatBot聊天機器人」技術甚為陌生，再加上技術功能範疇複雜，故將藉由本篇論文探討研究的過程，鎖定此人工智慧平台之初步策略，客觀分析樂齡需求痛點，對照研究所得之「AI ChatBot聊天機器人」功能特色與運用限制是否得以滿足，並檢視平台本身建置「AI ChatBot聊天機器人」的能力是否足夠面對競爭，進而評估「樂齡人工智慧服務平台」核心競爭力與發展初步策略的適切性及完整度。

Syftet med denna studie är att undersöka hur användningen av AI-chatbotar hos Amazon påverkar kundnöjdheten. Metodvalet för denna studie är kvantitativ och baseras på data insamlad genom en enkätundersökning. Enkäten är utformad för att kvantifiera och analysera respondenternas åsikter, beteenden och demografiska variabler. Data analyseras med hjälp av SEM och AMOS. Studien har identifierat signifikanta samband mellan förtroende och kundnöjdhet samt uppfattad enkelhet och kundnöjdhet när det gäller Amazons AI-chatbot. Sambandet är positivt och ökad förtroende samt uppfattad enkelhet leder till ökad kundnöjdhet. / The purpose of this study is to investigate how the use of AI chatbots at Amazon affects customer satisfaction. The method chosen for this study is quantitative and is based on data collected through a survey. The survey is designed to quantify and analyze respondents' opinions, behaviors, and demographic variables. The data is analyzed using SEM and AMOS. The study has identified significant relationships between trust and customer satisfaction, as well as perceived simplicity and customer satisfaction regarding Amazon´s AI chatbot. The relationship is positive and increased trust and perceived ease of use leads to increased customer satisfaction.