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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 161 to 163 of 163 (0.025 seconds)Spelling suggestions: "subject:"chatbot."" "subject:"chatbots.""
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Agent for Interactive Student Assistance: A Study of an Avatar-Based Conversational Agent's Impact on Student Engagement and Recruitment at BGSU's College of TechnologyOrwick Ogden, Sherri L. 28 October 2011 (has links)
No description available.
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Contextualizing Customer Feedback: A Research-through-Design Approach - Alternative Approaches and Dialogical Engagement in Survey DesignSvensson, Rasmus January 2023 (has links)
Providing context behind customer feedback remains a challenge for company’s who rely on approaching Customer Experience (CX) through standardized Customer Satisfaction (CS) metrics like Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), and Customer Effort Score (CES). Practical guidelines for monitoring CS throughout the customer journey are limited, creating a gap in academic research. This study addresses this gap by offering practical guidelines for CS, actionable insights, and alternative survey design strategies within the context of invoicing. Utilizing a Research-through-Design (RtD) approach guided by the Double Diamond design model, the study consists of four phases: Discover, Define, Develop, and Deliver. From a service design perspective using qualitative methods, the study acquires and analyzes both organizational and customer insights. Synthesized empirical findings emphasize the need for a more comprehensive approach that targets specific phases of the customer journey utilizing a more customer- centric approach, paving the way for alternative methods that reaches beyond just simply measuring CS. Introducing the concept of a personal companion, the study presents a dialogical approach where surveys are experienced as ongoing interactions rather mere tasks. By highlighting the importance of contextualization, alternative survey approaches, and a dialogical approach, this research aims to guide company’s in managing customer feedback strategies.
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Introducing Generative Artificial Intelligence in Tech Organizations : Developing and Evaluating a Proof of Concept for Data Management powered by a Retrieval Augmented Generation Model in a Large Language Model for Small and Medium-sized Enterprises in Tech / Introducering av Generativ Artificiell Intelligens i Tech Organisationer : Utveckling och utvärdering av ett Proof of Concept för datahantering förstärkt av en Retrieval Augmented Generation Model tillsammans med en Large Language Model för små och medelstora företag inom TechLithman, Harald, Nilsson, Anders January 2024 (has links)
In recent years, generative AI has made significant strides, likely leaving an irreversible mark on contemporary society. The launch of OpenAI's ChatGPT 3.5 in 2022 manifested the greatness of the innovative technology, highlighting its performance and accessibility. This has led to a demand for implementation solutions across various industries and companies eager to leverage these new opportunities generative AI brings. This thesis explores the common operational challenges faced by a small-scale Tech Enterprise and, with these challenges identified, examines the opportunities that contemporary generative AI solutions may offer. Furthermore, the thesis investigates what type of generative technology is suitable for adoption and how it can be implemented responsibly and sustainably. The authors approach this topic through 14 interviews involving several AI researchers and the employees and executives of a small-scale Tech Enterprise, which served as a case company, combined with a literature review. The information was processed using multiple inductive thematic analyses to establish a solid foundation for the investigation, which led to the development of a Proof of Concept. The findings and conclusions of the authors emphasize the high relevance of having a clear purpose for the implementation of generative technology. Moreover, the authors predict that a sustainable and responsible implementation can create the conditions necessary for the specified small-scale company to grow. When the authors investigated potential operational challenges at the case company it was made clear that the most significant issue arose from unstructured and partially absent documentation. The conclusion reached by the authors is that a data management system powered by a Retrieval model in a LLM presents a potential path forward for significant value creation, as this solution enables data retrieval functionality from unstructured project data and also mitigates a major inherent issue with the technology, namely, hallucinations. Furthermore, in terms of implementation circumstances, both empirical and theoretical findings suggest that responsible use of generative technology requires training; hence, the authors have developed an educational framework named "KLART". Moving forward, the authors describe that sustainable implementation necessitates transparent systems, as this increases understanding, which in turn affects trust and secure use. The findings also indicate that sustainability is strongly linked to the user-friendliness of the AI service, leading the authors to emphasize the importance of HCD while developing and maintaining AI services. Finally, the authors argue for the value of automation, as it allows for continuous data and system updates that potentially can reduce maintenance. In summary, this thesis aims to contribute to an understanding of how small-scale Tech Enterprises can implement generative AI technology sustainably to enhance their competitive edge through innovation and data-driven decision-making.
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