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P351 - 7. Fachtagung Rechts- und Verwaltungsinformatik (RVI 2024)

https://dl.gi.de/handle/20.500.12116/44609
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Auflistung P351 - 7. Fachtagung Rechts- und Verwaltungsinformatik (RVI 2024) nach Schlagwort "Artificial Intelligence"

1 - 2 von 2
  • Student Paper
    AI-based chatbots as enabler for efficient external knowledge management in public administration
    (7. Fachtagung Rechts- und Verwaltungsinformatik (RVI 2024): Neue Wege der Zusammenarbeit und Vernetzung für digitale Transformation und Verwaltungsmodernisierung, 2024) Wiethölter, Jost; Kühl, Linus; Feldmann, Carsten
    This study addresses the pressing issue of staff shortages in German public administrations through the lens of digitalization, focusing on the potential of AI-based chatbots to solve this problem by replacing human labour. Employing a Design Science Research Process (DSRP) methodology, the research synthesizes theoretical foundations and regulatory frameworks to develop a robust chatbot concept. The artifact presented is a comprehensive architectural framework integrating user-centric design, linguistic processing, and regulatory compliance. The proposed artifact navigates complex federal structures and diverse IT infrastructures, promoting accessibility and inclusivity. Implications suggest enhanced efficiency and accessibility in public service delivery for potentially increasing citizen satisfaction and decreasing employee workload. The study underscores the importance of legal compliance and the evolving regulatory landscape in AI deployment. Future research will involve prototyping and evaluating the artifact's performance and applicability throughout the course of the DSRP, thus contributing to the advancement of digital transformation in public administrations.
  • Research Paper
    Turning Tenders into Tinder: How AI and Open Data can spark Bidding Matches
    (7. Fachtagung Rechts- und Verwaltungsinformatik (RVI 2024): Neue Wege der Zusammenarbeit und Vernetzung für digitale Transformation und Verwaltungsmodernisierung, 2024) Klassen, Gerhard; Bauer, Luca T.; Fritzsche, Robin; Kordyaka, Bastian; Weber,Sebastian; Niehaves, Björn
    Public procurement in Germany, accounting for 15% of GDP, is plagued by inefficiencies, high costs, and lack of transparency. This study investigates how Open Data can enhance competitive bidding and streamline the identification of suitable companies. Using the German public procurement market, we propose a web-based portal employing machine learning to automate tender and bidder matchmaking. Our methodology includes data collection, company profiling, and NLPbased similarity searches. Results indicate that integrating Open Data can increase competition, improve bid quality, and enhance procurement efficiency. This research provides a scalable framework for more transparent and effective public procurement practices, with potential applications in other regions and sectors.