Now showing 1 - 10 of 17
  • Publication
    The Rise of Generative AI in Low Code Development Platforms – An Analysis and Future Directions
    ( 2024-01-06) ;
    Ernestine Dickhaut
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    This study investigates the relationship between Generative AI (GenAI) and Low Code Development Platforms (LCDPs), providing preliminary insights into Gen's transformative potential in this context. It is based on expert interviews and provides insight into the changing landscape of LCDPs influenced by GenAI. The findings highlight the promising benefits of GenAI in LCDPs, such as increased efficiency and decreased errors, while also emphasizing the importance of human oversight and collaboration. The findings also highlight the importance of interpersonal skills in IT, even in an increasingly automated environment. While the economic efficiency and broader implications of GenAI are still being investigated, the study lays the groundwork for future research in this rapidly evolving domain.
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  • Publication
    Faster, Cheaper, Better? Analyzing how Lowcode Developoment Platforms drive Bottom-Up Innovation
    ( 2023) ;
    Dominic Germann
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    Ernestine Dickhaut
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    Recent years have seen a growing adoption of Low Code Development Platforms (LCDPs) in organizations. The increasing affinity for technology development across all user groups, consumerization of development, and advancing digitalization are opening up a new target group for the low code movement. This change in software development allows bottom-up user innovators within a company to leverage their domain knowledge and quickly deploy much-needed digital services. However, a clear understanding of this paradigm of software development in organizations and the influence on end-user acceptance is still missing. In this paper, we present the results of an interview study conducted with 18 LCDP experts and discuss the implications of our findings, highlighting the role of LCDPs and context in bottom-up innovation as well as user-centricity. Our research contributes to the literature on LCDPs and offers valuable insights for organizations looking to leverage their workforce's innovative potential.
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  • Publication
    An Investigation of Why Low Code Platforms Provide Answers and New Challenges
    ( 2023-01-06) ;
    Dickhaut, Ernestine
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    Although the idea of low code development is not new, the market for these oftentimes platform-based development approaches is exponentially growing. Especially factors such as increasing affinity for technology development across all user groups, consumerization of development, and advancing digitalization are opening a new target group for the low code movement. The broad application possibilities of low code, as well as the benefits, are therefore getting more important for businesses. Especially for small and medium-sized enterprises (SMEs), low code constitutes a promising avenue to survive and succeed in the rapidly changing world. However, a clear understanding regarding the application of this paradigm of software development in SMEs is still missing. To provide a coherent understanding of the phenomenon low code in SMEs, we review extant literature and conduct interviews, identifying potential application domains and conceptualizing the benefits and challenges of low code from a holistic perspective.
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  • Publication
    What to Learn Next? Designing Personalized Learning Paths for Re-&Upskilling in Organizations
    ( 2023-01-06) ;
    Leonie Freise
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    Ulrich Bretschneider
    The fast-paced acceleration of digitalization requires extensive re-&upskilling, impacting a significant proportion of jobs worldwide. Technology-mediated learning platforms have become instrumental in addressing these efforts, as they can analyze platform data to provide personalized learning journeys. Such personalization is expected to increase employees’ empowerment, job satisfaction, and learning outcomes. However, the challenge lies in efficiently deploying these opportunities using novel technologies, prompting questions about the design and analysis of generating personalized learning paths in organizational learning. We, therefore, analyze and classify recent research on personalized learning paths into four major concepts (learning context, data, interface, and adaptation) with ten dimensions and 34 characteristics. Six expert interviews validate the taxonomy’s use and outline three exemplary use cases, undermining its feasibility. Information Systems researchers can use our taxonomy to develop theoretical models to study the effectiveness of personalized learning paths in intra-organizational re-&upskilling.
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  • Publication
    Artificial Socialization? How Artificial Intelligence Applications Can Shape A New Era of Employee Onboarding Practices
    ( 2023-01-06) ;
    Fabio, Donisi
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    Onboarding has always emphasized personal contact with new employees. Excellent onboarding can extend employee retention and improve loyalty. Even in a physical setting, the onboarding process is demanding for both the newcomer and the onboarding organization. Remote work, in contrast, has made this process even more challenging by forcing a rapid shift from offline to online onboarding practices. Organizations are adopting new technologies like artificial intelligence (AI) to support work processes, such as hiring processes or innovation facilitation, which could shape a new era of work practices. However, it has not been studied how AI applications can or should support onboarding. Therefore, our research conducts a literature review on current onboarding practices and uses expert interviews to evaluate AI's potential and pitfalls for each action. We contribute to the literature by presenting a holistic picture of onboarding practices and assessing potential application areas of AI in the onboarding process.
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    Requirements for AI-based Teammates: A Qualitative Inquiry in the Context of Creative Workshops
    ( 2022-01-04) ;
    Siemon, Dominik
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    de Vreede, Triparna
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    de Vreede, Gert-Jan
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    Oeste-Reiß, Sarah
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    Innovation requires organizations to tap into the knowledge and creativity of teams. However, teams are confronted with massive amounts of data and information, necessitating a broad set of knowledge, methodologies, and approaches to solve problems and innovate. Consequently, team composition has become a critical challenge. Recent advances in artificial intelligence (AI) may assist in addressing this challenge. As AI is permeating both business and private sectors, organizational teams may be augmented with AI team members. However, given the nascent nature of this phenomenon, little is known about the specific roles and requirements for such AI teammates. Within an interview study we discover common challenges in teams and identify recurring capability gaps of participants and behaviors that negatively impact the team's collective performance. Based on our findings, we propose requirements for AI-based teammates to address these gaps and support beneficial collaboration between humans and AI in teams.
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    Examining the Antecedents of Creative Collaboration with an AI Teammate
    ( 2022-12-14)
    Siemon, Dominik
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    de Vreede, Triparna
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    Oeste-Reiß, Sarah
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    de Vreede, Gert Jan
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    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.
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  • Publication
    Why Do We Turn to Virtual Companions? A Text Mining Analysis of Replika Reviews
    ( 2022)
    Siemon, Dominik
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    Strohmann, Timo
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    Khosrawi-Rad, Bijan
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    de Vreede, Triparna
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    Meyer, Michael
    Many people globally experience the feeling of loneliness and struggle with its consequences. A modern way to deal with this loneliness and lack of companionship is to use empathetic and emotional conversational agents. Often referred to as virtual companions, these agents can engage in human-like conversations with their users and build relationships with them through modern artificial intelligence technologies. One established service of such virtual companions is Replika, which we investigate in this study to explore what users expect to gain from long-term interactions with virtual companions and what they tend to talk about with them. Using a text mining approach and 119,831 reviews of the Replika service, we analyze users' sentiments, emotions, and topics. Our results show that users interact with virtual companions to cope with their loneliness and, especially, to address their mental well-being. Furthermore, Replika users have a joyful and beneficial experience during long-term interaction with such virtual companions.