Edona Elshan
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Dr.
Last Name
Elshan
First name
Edona
Email
edona.elshan@unisg.ch
Phone
+41 71 224 3304

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  • Publication
    Examining the Antecedents of Creative Collaboration with an AI Teammate
    ( 2022-12-14)
    Siemon, Dominik
    ;
    Elshan, Edona
    ;
    de Vreede, Triparna
    ;
    Oeste-Reiß, Sarah
    ;
    de Vreede, Gert Jan
    ;
    Ebel, Philipp
    With the advent of artificial intelligence (AI), individuals are increasingly teaming up with AI-based systems to enhance their creative collaborative performance. When working with AI-based systems, several aspects of team dynamics need to be considered, which raises the question how humans’ approach and perceive their new teammates. In an experimental setting, we investigate the influence of social presence in a group ideation process with an AI-based teammate and examine its effects on the motivation to contribute. Our results show a multi-mediation model in which social presence indirectly influences whether human team members are motivated to contribute to a team with AI-based teammates, which is mediated by willingness to depend and team-oriented commitment.
    Type: conference paper
    Journal: International Conference on Information Systems (ICIS)
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/107975
  • Publication
    Opening the Black Box of Music Royalties with the Help of Hybrid Intelligence
    ( 2021-01)
    Elshan, Edona
    ;
    Engel, Christian
    ;
    Ebel, Philipp
    The ever-increasing complexity of the music industry and the intensified resentment of artists towards collecting societies call for a transformation and a change of behavior within the music ecosystem. This article introduces a hybrid intelligence system, that ameliorates the current situation by combining the intelligence of humans and machines. This study proposes design requirements for hybrid intelligence systems in the music industry. Using a design science research approach, we identify design requirements both inductively from expert interviews and deductively from theory and present a first prototypical instantiation of a respective hybrid intelligence system. Overall, this shall enrich the body of knowledge of hybrid intelligence research by transferring its concepts into a new context. Furthermore, the identified design requirements shall serve as a foundation for researchers and practitioners to further explore and design hybrid intelligence in the music industry and beyond.
    Type: conference paper
    Journal: Hawaii International Conference on System Sciences (HICSS)
    DOI: 10.24251/HICSS.2021.671
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/110755