Edona Elshan
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Elshan
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Edona
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edona.elshan@unisg.ch
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+41 71 224 3304

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Publication

An Investigation of Why Low Code Platforms Provide Answers and New Challenges

2023-01-06 , Elshan, Edona , Dickhaut, Ernestine , Ebel, Philipp

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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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.

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Moving Beyond Rule-Based Automation: A Method for Assessing Cognitive Automation Use Cases

2021-12 , Engel, Christian , Elshan, Edona , Ebel, Philipp

Facilitated by Artificial Intelligence technology, cognitive automation means to front and back offices what the pervasive automation through physical machinery and robots meant to production plants. Thus, we can automate tasks and processes that were unimaginable to be automated one decade ago. However, organizational adoption of cognitive automation is way below its possibilities, as this novel class of automation technology is perceived to be risky by organizations. This demands structured approaches for assessing the suitability of use cases for cognitive automation. Following the Design Science Research paradigm, we develop a method for assessing cognitive automation use cases. This enables practitioners to make more informed decisions on selecting, specifying, and embedding cognitive automation use cases in their organizations. For researchers, the method serves as a conceptual frame, which they can adapt to guide their empirical research or to use it for developing future decision support to shape the future of work.

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Assessing the Reusability of Design Principles in the Realm of Conversational Agents

2022-06 , Elshan, Edona , Engel, Christian , Ebel, Philipp Alexander , Siemon, Dominik

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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.

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Let's Team Up: Designing Conversational Agents as Teammates

2020-12 , Elshan, Edona , Ebel, Philipp

The success of projects is, amongst others, highly depended on the team members skillset and ability to collaborate. Hence, education has to undergo a change to keep up with the shift in the compositions of skills and knowledge needed for students. To overcome scalability issues, we propose to develop Timmy-a conversational agents (CAs) that acts as a team member. As there is a lack of concrete design knowledge concerning CAs as peers in teams, we conduct a design science research project. Based on requirements from scientific literature and expert interviews, we develop a concise set of design principles for designing CAs in peer roles in educational settings. Furthermore, we present an initial proof of concept evaluation. These insights will support researchers and practitioners to understand better how CAs can be systematically built to ameliorate the collaborative skill of students in teamwork settings.

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Requirements for AI-based Teammates: A Qualitative Inquiry in the Context of Creative Workshops

2022-01-04 , Elshan, Edona , Siemon, Dominik , de Vreede, Triparna , de Vreede, Gert-Jan , Oeste-Reiß, Sarah , Ebel, Philipp

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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Deploying a Model for Assessing Cognitive Automation Use Cases: Insights from Action Research with a Leading European Manufacturing Company

2021-01 , Engel, Christian Thomas , Elshan, Edona , Ebel, Philipp

Cognitive automation moves beyond rule-based automation and thus imposes novel challenges on organizations when assessing the automation potential of use cases. Thus, we present an empirically grounded and conceptually operationalized model for assessing cognitive automation use cases, which consists of four assessment dimensions: data, cognition, relationship, and transparency requirements. We apply the model in a real-world organizational context in the course of an action research project at the customer service department of ManuFact AG, and present unique empirical insights as well as the impact the application of the model had on the organization. The model shall help practitioners to make more informed decisions on selecting use cases for cognitive automation and to plan respective endeavors. For research, the identified factors affecting the suitability of a use case for cognitive automation shall deepen our understanding of cognitive automation in particular, and AI as the driving force behind cognitive automation in general.

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