Team

Leonardo Banh

Wissenschaftlicher Mitarbeiter

Leonardo Banh, M. Sc.

Raum:
R09 R02 H42
Telefon:
+49 201 18-34023
E-Mail:
X.509 Cert:
Nutzerzertifikat auf DFN.de
Sprechstunde:
Flexibel - Anmeldung per Email
Social Media:
LinkedIn
Adresse:
Universität Duisburg-Essen, Campus Essen
Fakultät für Wirtschaftswissenschaften
Lehrstuhl für Wirtschaftsinformatik und Softwaretechnik
Universitätsstr. 9
45141 Essen
Autorenprofile:
Google Scholar
ResearchGate

Lebenslauf:

Berufserfahrung

  • Seit September 2022: Wissenschaftlicher Mitarbeiter am Lehrstuhl für Wirtschaftsinformatik und Softwaretechnik (Lehrstuhlinhaber: Prof. Dr. Stefan Eicker) an der Universität Duisburg-Essen
  • Mai 2021 - August 2022: Wissenschaftliche Hilfskraft am Lehrstuhl für Wirtschaftsinformatik und Softwaretechnik (Lehrstuhlinhaber: Prof. Dr. Stefan Eicker) an der Universität Duisburg-Essen
  • Oktober 2018 - März 2022: Studentische Hilfskraft Erstsemesterbetreuung im Mentoring der Fakultät für Wirtschaftswissenschaften an der Universität Duisburg-Essen
  • Januar 2018 - Februar 2021: Werkstudent bei der HSBC Deutschland

Studium

  • Oktober 2019 - August 2022: Studium der Wirtschaftsinformatik (M. Sc.) an der Universität Duisburg-Essen
    • Masterarbeit: "Assuring Steel Quality with Artificial Intelligence - A Semantic Segmentation Approach"
  • Februar 2021 - Juli 2021: Auslandssemester an der Instituto Superior Técnico, Lissabon
  • Oktober 2016 - Januar 2020: Studium der Wirtschaftsinformatik (B. Sc.) an der Universität Duisburg-Essen
    • Bachelorarbeit: "Enhancing Communication in Collaborative Multi-User Virtual Reality Environments"

Forschungsgebiete:

  • Generative AI
  • Künstliche Intelligenz, insb. Machine Learning und Deep Learning

Publikationen:

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  • Strobel, Gero; Banh, Leonardo: What Did the Doctor Say? Empowering Patient Comprehension with Generative AI. In: AIS (Hrsg.): ECIS 2024 Research Papers. Paphos, Cyprus 2024. VolltextBIB DownloadDetails

    As global challenges, such as pandemics, population growth and widespread illnesses, continue to rise, healthcare systems are facing greater strain, resulting in a shortage of resources and increased demands for medical care. Effective communication between healthcare professionals and patients is essential for the provision of good services to prevent confusion and induced anxiety of patients, particularly when medical jargon is employed and not understood. Generative AI (GAI) presents a chance to transform healthcare communication by providing language processing capabilities that enhance patient-centered services. This paper examines how GAI-based conversational agents for explaining medical jargon in healthcare should be designed. We derived eleven design principles from a systematic literature review and evaluated them with nine clinical cardiological scenarios through a prototypical instantiation of an LLM-based conversational agent. The results provide insights for researchers and healthcare providers in form of prescriptive design knowledge to improve patient communication using GAI.

  • Strobel, Gero; Banh, Leonardo; Möller, Frederik; Schoormann, Thorsten: Exploring Generative Artificial Intelligence: A Taxonomy and Types. In: Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS). Hawaii, USA 2024. VolltextBIB DownloadDetails

    Generative Artificial Intelligence (GAI) is a prevalent topic in recent research and business, seemingly taking the position of a disruptive technology that has the potential to significantly transform industries ranging from productivity (e.g., ChatGPT-4) to creativity (e.g., DALL-E). While the emerging scientific discussion on GAI covers a variety of fields and issues, such as privacy, accuracy, and application scenarios, this paper sheds light on the business side of GAI by investigating the morphologic nature of start-ups and incumbents leveraging GAI. Based on the structured analysis of 100 real-world instances, we report on a taxonomy of GAI applications and services that advances our practical understanding, strengthens the distinguishability, as well as adds clarity to the discourse of GAI potentials. We provide an initial framework and five types of GAI, namely Generator, Reimaginator, Synthesizer, Assistant, and Enabler, that are informed by the core characteristics of the technology paradigm.

  • Banh, Leonardo; Strobel, Gero: Generative artificial intelligence. In: Electronic Markets, Jg. 33 (2023) Nr. 63. doi:10.1007/s12525-023-00680-1BIB DownloadDetails

    Recent developments in the field of artificial intelligence (AI) have enabled new paradigms of machine processing, shifting from data-driven, discriminative AI tasks toward sophisticated, creative tasks through generative AI. Leveraging deep generative models, generative AI is capable of producing novel and realistic content across a broad spectrum (e.g., texts, images, or programming code) for various domains based on basic user prompts. In this article, we offer a comprehensive overview of the fundamentals of generative AI with its underpinning concepts and prospects. We provide a conceptual introduction to relevant terms and techniques, outline the inherent properties that constitute generative AI, and elaborate on the potentials and challenges. We underline the necessity for researchers and practitioners to comprehend the distinctive characteristics of generative artificial intelligence in order to harness its potential while mitigating its risks and to contribute to a principal understanding.

  • Strobel, Gero; Schoormann, Thorsten; Banh, Leonardo; Möller, Frederik: Artificial Intelligence for Sign Language Translation – A Design Science Research Study. In: Communications of the Association for Information Systems, Jg. 53 (2023) Nr. 3. doi:10.17705/1CAIS.05303VolltextBIB DownloadDetails

    Although our digitalized society is able to foster social inclusion and integration, there are still numerous communities having unequal opportunities. This is also the case with deaf people. About 750,000 deaf people only in the European Union and over 4 million people in the United States face daily challenges in terms of communication and participation, such as in leisure activities but more importantly in emergencies too. To provide equal environments and allow people with hearing handicaps to communicate in their native language, this paper presents an AI-based sign language translator. We adopted a transformer neural network capable of analyzing over 500 data points from a person’s gestures and face to translate sign language into text. We have designed a machine learning pipeline that enables the translator to evolve, build new datasets, and train sign language recognition models. As proof of concept, we instantiated a sign language interpreter for an emergency call with over 200 phrases. The overall goal is to support people with hearing inabilities by enabling them to participate in economic, social, political, and cultural life.

  • Muschkiet, Michel; Wulfert, Tobias; Woroch, Robert; Strobel, Gero; Banh, Leonardo: Unleashing the digital building bricks - A smart service taxonomy for retail. In: Electronic Markets, Jg. 2023 (2023) Nr. 33. doi:10.1007/s12525-023-00666-zVolltextBIB DownloadDetails

    The increasing online competition, associated changes in customer behaviors, and effects of the pandemic in recent years have led to increasing retail store closures. This development has given rise to a downward spiral in terms of a decreasing attractiveness of local shopping places and a further reduction of stores. Research has recognized that smart services can unleash the potential to compensate for the competitive disadvantages of physical retailers by combining tailored physical and digital offerings to enhance customer-oriented value creation. However, most approaches are limited to in-store services without addressing the wider shopping experience in retail surroundings. Therefore, this paper provides a classification framework for smart services in retail evaluated against 163 use cases, as well as six service archetypes. This work contributes to understanding relevant service design elements and proposes applying the idea of a holistic customer experience to service design in physical retail environments.

  • Banh, Leonardo; Strobel, Gero: The Sound of Progress: Investigating the Representation of Artificial Intelligence in Music. In: AiS (Hrsg.): Wirtschaftsinformatik 2023 Proceedings. Paderborn, Germany 2023. VolltextBIB DownloadDetails

    The role of artificial intelligence in daily life is constantly advancing and has become an important topic of discussion. With music and its lyrics being a vehicle to express topics of society, this paper investigates how artificial intelligence is perceived by musicians and reflected in their songs. By analyzing the lyrics of over 1,200 songs over three decades, this work applies sentiment analysis to extract polarities and emotions. The results provide insights into how musicians view and reflect the impact of artificial intelligence on society and how this is reflected in their song texts. The findings show an increase in songs mentioning artificial intelligence-related terms, with a trend of more songs implying negativity, such as anger. However, minor increases in positive emotions indicate musicians' ambivalent views on hopes and fear of artificial intelligence.

  • Wulfert, Tobias; Woroch, Robert; Strobel, Gero; Schoormann, Thorsten; Banh, Leonardo: Unboxing the Role of E-Commerce Ecosystems to Address Grand Challenges. In: AIS (Hrsg.): ECIS 2023 Research Papers. Kristiansand, Norway 2023. VolltextBIB DownloadDetails

    The modern world is confronted with grand challenges, such as those codified by the United Nations’ Sustainable Development Goals. As single organizations are often not capable of addressing a broad set of goals on their own, they are increasingly concerned with creating ecosystems. This is also the case in the domain of e-commerce. Owners of focal platforms in e-commerce ecosystems have the power to implement sustainability initiatives and therefore need to be equipped with an overview of possible initiatives and actionable guidance. To unbox how e-commerce ecosystem participants consider sustainability, we conducted a multi-case study with 99 initiatives collected from sustainability reports. We found that (1) sustainability initiatives particularly focus on reducing inequality and managing climate change as well as (2) manufacturers, sellers, and service providers are the most involved ecosystem participants. Based on our findings, we (3) synthesized six categories of sustainability initiatives as measurements.

Vorträge:

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  • Banh, Leonardo: The Sound of Progress: Investigating the Representation of Artificial Intelligence in Music, 18. Internationale Tagung Wirtschaftsinformatik, 19.09.2023, Paderborn, Germany. Details

    The role of artificial intelligence in daily life is constantly advancing and has become an important topic of discussion. With music and its lyrics being a vehicle to express topics of society, this paper investigates how artificial intelligence is perceived by musicians and reflected in their songs. By analyzing the lyrics of over 1,200 songs over three decades, this work applies sentiment analysis to extract polarities and emotions. The results provide insights into how musicians view and reflect the impact of artificial intelligence on society and how this is reflected in their song texts. The findings show an increase in songs mentioning artificial intelligence-related terms, with a trend of more songs implying negativity, such as anger. However, minor increases in positive emotions indicate musicians' ambivalent views on hopes and fear of artificial intelligence.

Lehrveranstaltungen:

Begleitete Abschlussarbeiten:

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  • Machine Learning-gestützte Prozessautomatisierung von Transportmanagementsystemen - Eine Design Science Research Studie (Masterarbeit Wirtschaftsinformatik, in Bearbeitung)
  • An Affordance Perspective on Generative AI in Enterprise Architecture (Masterarbeit Wirtschaftsinformatik, in Bearbeitung)
  • Harnessing Large Language Models in Conversational Recommender Systems: Towards a Conceptual Framework (Masterarbeit Wirtschaftsinformatik, in Bearbeitung)
  • Vertrauen in Mensch-KI-Kollaboration: Analyse der Einflussfaktoren für KI-Assistenten im Steuerrecht (Masterarbeit Wirtschaftsinformatik, in Bearbeitung)
  • Embracing Change: Scenarios, Attitudes, and Key Factors for Generative AI Integration in Human Resource Processes (Masterarbeit Wirtschaftsinformatik, in Bearbeitung)
  • Generative KI im Geschäftsprozessmanagement: Implikationen bei der Transformation von Geschäftsprozessen (Bachelorarbeit Wirtschaftsinformatik, in Bearbeitung)
  • Strategien und Herausforderungen zur Mitarbeitenden-Sensibilisierung bei der Implementierung von generativer KI im HR (Bachelorarbeit Wirtschaftsinformatik, in Bearbeitung)
  • Leveraging Generative AI to Empower Self-Learning in Higher Education: A Design Science Research Study (Masterarbeit Wirtschaftsinformatik, in Bearbeitung)
  • Generative KI in der digitalen Kommunikation: Analyse der Risiken, Herausforderungen und Auswirkungen auf Unternehmen und Social Media (Bachelorarbeit Wirtschaftsinformatik, in Bearbeitung)
  • Advancing Behavioural Research in the Era of Generative AI: Employing Large Language Models-based Generative Agents to Simulate Human Behaviour (Bachelorarbeit Wirtschaftsinformatik, in Bearbeitung)
  • Daten als Grundlage für die Versorgungssicherheit: Eine qualitative Studie über die Vorhersage der Volatilität erneuerbarer Energien (Masterarbeit Wirtschaftsinformatik, 2024)
  • Automated ESG Assessment of Companies based on Sentiment Analysis of News Articles (Masterarbeit Wirtschaftsinformatik, 2024)
  • Developing Design Principles for an AI-based Physical Therapy Rehabilitation Tool - A Design Science Research Study (Masterarbeit Wirtschaftsinformatik, 2023)
  • Transformation Recruiting: Erforschung des Einsatzes generativer KI im Bereich der Personalakquise (Bachelorarbeit Wirtschaftsinformatik, 2023)
  • Evaluation von Einsatzmöglichkeiten der Natural Language Generation im Online-Marketing (Bachelorarbeit Wirtschaftsinformatik, 2023)

Mitgliedschaften:

  • Alumni der Fakultät für Wirtschaftswissenschaften der Universität Duisburg-Essen

Inneruniversitäre Funktionen:

  • Stellvertretendes Vorstandsmitglied des Instituts für Informatik und Wirtschaftsinformatik (ICB) der Fakultät Wirtschaftswissenschaften (Oktober 2022 - Oktober 2023)
  • (Beratendes) Mitglied der Berufungskommission Betriebswirtschaftslehre für die Nachfolge Prof. Dr. Nienhüser - Lehrstuhl für Arbeit, Personal und Organisation (November 2020 - September 2022)
  • Mitglied der Habilitationskommission für Dr. Heiko Hoßfeld (Januar 2022 - September 2022)

Weitere Funktionen:

  • Reviewer für die 18. Internationale Tagung der Wirtschaftsinformatik (WI) 2023
  • Reviewer für die 57th Hawaii International Conference on System Sciences (HICSS) 2024 (2x)
  • Reviewer für die 32nd European Conference on Information Systems (ECIS) 2024 (2x)
  • Reviewer für die 19. Internationale Tagung der Wirtschaftsinformatik (WI) 2024 (3x)
  • Reviewer für die 45th International Conference on Information Systems (ICIS) 2024 (2x)