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Christian Engel

Wissenschaftlicher Mitarbeiter
location_on
IWI-HSG
52-6028
apartment
Müller-Friedbergstrasse 8
9000 St Gallen
mail
phone
+41 71 224 3363

Forschungsgebiete


  • Cognitive Automation
  • Management Künstlicher Intelligenz
  • Weitere Forschungsgebiete


  • Datengetriebene Geschäftsmodelle
  • Datengetriebene Dienstleistungen
  • Publikationen


    Artificial Intelligence (AI) provides organizations with vast opportunities of deploying AI for competitive advantage such as improving processes, and creating new or enriched products and services. However, the failure rate of projects on implementing AI in organizations is still high, and prevents organizations from fully seizing the potential that AI exhibits. To contribute to closing this gap, we seize the unique opportunity to gain insights from five organizational cases. In particular, we empirically investigate how the unique characteristics of AI – i.e. experimental character, context sensitivity, black box character, and learning requirements – induce challenges into project management, and how these challenges are addressed in organizational (socio-technical) contexts. This shall provide researchers with an empirical and conceptual foundation for investigating the cause-effect relationships between the characteristics of AI, project management, and organizational change. Practitioners can benchmark their own practices against the insights to increase the success rates of future AI implementations.

    Mehr
    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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    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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    Smart Personal Assistants (SPA) fundamentally influence the way individuals perform tasks, use services and interact with organizations. They thus bear an immense economic and societal potential. However, a lack of trust - rooted in perceptions of uncertainty and risk - when interacting with intelligent computer agents can inhibit their adoption. In this paper, we conduct a systematic literature review to investigate the state of knowledge on trust in SPAs. Based on a concept-centric analysis of 50 papers, we derive three distinct research perspectives that constitute this nascent field: user interface-driven, interaction-driven, and explanation-driven trust in SPAs. Building on the results of our analysis, we develop a research agenda to spark and guide future research surrounding trust in SPAs. Ultimately, this paper intends to contribute to the body of knowledge of trust in artificial intelligence-based systems, specifically SPAs. It does so by proposing a novel framework mapping out their relationship.

    Mehr
    Artificial Intelligence (AI) is considered being a disruptive force for existing companies and a promising avenue towards competitive advantage. A myriad of companies started investing in AI initiatives. However, a significant number of AI projects is not successfully deployed. Taking a closer look at financial service organizations, we aim at contributing to closing the gap between understanding the potential of AI and proactively leveraging the latter. We draw on affordance theory and socio-technical systems (STS) theory to identify the required socio-technical changes to actualize affordances of AI in financial service organizations. We present preliminary findings from a multiple case study approach with five financial service organizations based on rigorous interview coding that yields first insights into AI affordances. Building up on this, we will prioritize and structure future in-depth case studies to investigate how to orchestrate AI-induced changes in STS for actualizing AI affordances.

    Mehr
    Design Science (DS) has become an established research paradigm in Information Systems (IS) research. However, existing research still considers it as a challenge to publish DS contributions in top IS journals, due to the rather strict guidelines that DS publications are expected to follow. Against this backdrop, we intend to emphasize the myriad of configurations and empirically describe the status-quo of DS publications in IS. Based on a Systematic Literature Review (SLR) and a conceptually derived analysis frame, we empirically analyze DS papers published in the AIS Senior Scholars’ Basket. Thereby, we intend to contribute conceptually and descriptively to the knowledge base of DS, by providing insights based on empirical evidence to aid and guide the discussion towards the advancement of the field. Overall, this shall lay the descriptive foundation for creating prescriptive knowledge on DS in IS by proposing and opening future research avenues.

    Mehr
    The potential created by ongoing developments in data and analytics permeates a multitude of research areas, such as the field of Service Innovation. In this paper, we conduct a Systematic Literature Review (SLR) to investigate the integration of data and analytics as an analytical unit into the field of Service Innovation – referred to as Data-Driven Service Innovation (DDSI). Overall, the SLR reveals three main research perspectives that span the research field of Data-Driven Service Innovation: Explorative DDSI, validative DDSI, and generative DDSI. This integrated theoretical framework describes the distinct operant roles of data analytics for Service Innovation, and thus contributes to the body of knowledge in the field of DDSI by providing three unified lenses, which researchers can use to describe and locate their existing and future research endeavors in this ample field. Building up on the insights from the SLR, a research agenda is proposed in order to trigger and guide further discussions and future research surrounding DDSI. Ultimately, this paper aims at contributing to the body of knowledge of Service Innovation in general and Data-Driven Service Innovation in particular by presenting a three-dimensional research space model structuring DDSI towards its advancement.

    Mehr
    The abundance of data accompanied by advances in analytics technologies increasingly drive companies to introduce analytics-based services, i.e. customer-facing services in which data and analytics help customers make decisions. Despite its growing application in practice, theoretical and conceptual work on analytics-based services is still scarce. In this paper, we develop a taxonomy of analytics-based services unveiling their conceptually grounded and empirically validated characteristics. Applying an established taxonomy building method, we draw upon an analysis of 85 use cases of analytics-based services. The results of an expert evaluation indicate both the usefulness and robustness of our taxonomy. The developed taxonomy of analytics-based services contributes in two ways: First, we add to the descriptive knowledge on this new service type, establish a common language among researchers and equip them with the means to analyze analytics-based services in a structured manner-thus laying the foundation for a deeper theorizing process in the future. Second, we provide a concrete conceptualization of analytics-based services for practitioners for initial guidance in new service development.

    Mehr
    Design Science (DS) has become an established research paradigm in Information Systems (IS) research. However, existing research still considers it as a challenge to publish DS contributions in top IS journals, due to the rather strict guidelines that DS publications are expected to follow. Against this backdrop, we intend to emphasize the myriad of configurations and empirically describe the status-quo of DS publications in IS. Based on a Systematic Literature Review (SLR) and a conceptually derived analysis frame, we empirically analyze DS papers published in the AIS Senior Scholars’ Basket. Thereby, we intend to contribute conceptually and descriptively to the knowledge base of DS, by providing insights based on empirical evidence to aid and guide the discussion towards the advancement of the field. Overall, this shall lay the descriptive foundation for creating prescriptive knowledge on DS in IS by proposing and opening future research avenues.

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    Ausbildung


    • 2018 - M.Sc., Wirtschaftsingenieurwesen @ Karlsruher Institut für Technologie (KIT)
    • 2016 - Auslandssemester @ University of Connecticut (UCONN), USA
    • 2015/16 - Stanford ME310 Design Thinking Class als Teil des Sugar-Netzwerks
    • 2015 - B.Sc., Wirtschaftsingenieurwesen @ Karlsruher Institut für Technologie (KIT) 

    Awards


    • 2021 Bestes Minitrack-Paper und nominiert für Best Paper Award bei Hawaii International Conference on System Sciences (HICSS 2021) 

    Mitgliedschaften


    • Association for Information Systems (AIS)
    • Swiss Chapter of the Association for Information Systems (CHAIS)