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BISE 62(3) - June 2020

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  • Zeitschriftenartikel
    Virtual Assistance in Any Context
    (Business & Information Systems Engineering: Vol. 62, No. 3, 2020) Janssen, Antje; Passlick, Jens; Rodríguez Cardona, Davinia; Breitner, Michael H.
    Several domain-specific assistants in the form of chatbots have conquered many commercial and private areas. However, there is still a limited level of systematic knowledge of the distinctive characteristics of design elements for chatbots to facilitate development, adoption, implementation, and further research. To close this gap, the paper outlines a taxonomy of design elements for chatbots with 17 dimensions organized into the perspectives intelligence, interaction and context. The conceptually grounded design elements of the taxonomy are used to analyze 103 chatbots from 23 different application domains. Through a clustering-based approach, five chatbot archetypes that currently exist for domain-specific chatbots are identified. The developed taxonomy provides a structure to differentiate and categorize domain-specific chatbots according to archetypal qualities that guide practitioners when taking design decisions. Moreover, the taxonomy serves academics as a foundation for conducting further research on chatbot design while integrating scientific and practical knowledge.
  • Zeitschriftenartikel
    The Role of IS in the Conflicting Interests Regarding GDPR
    (Business & Information Systems Engineering: Vol. 62, No. 3, 2020) Jakobi, Timo; Grafenstein, Maximilian; Legner, Christine; Labadie, Clément; Mertens, Peter; Öksüz, Ayten; Stevens, Gunnar
  • Zeitschriftenartikel
    Interview with Omer Biran and Michael Halfmann on 'Conversational Agents at SAP'
    (Business & Information Systems Engineering: Vol. 62, No. 3, 2020) Pfeiffer, Jella
  • Zeitschriftenartikel
    User Assistance for Intelligent Systems
    (Business & Information Systems Engineering: Vol. 62, No. 3, 2020) Morana, Stefan; Pfeiffer, Jella; Adam, Marc T. P.
  • Zeitschriftenartikel
    Intelligent User Assistance for Automated Data Mining Method Selection
    (Business & Information Systems Engineering: Vol. 62, No. 3, 2020) Zschech, Patrick; Horn, Richard; Höschele, Daniel; Janiesch, Christian; Heinrich, Kai
    In any data science and analytics project, the task of mapping a domain-specific problem to an adequate set of data mining methods by experts of the field is a crucial step. However, these experts are not always available and data mining novices may be required to perform the task. While there are several research efforts for automated method selection as a means of support, only a few approaches consider the particularities of problems expressed in the natural and domain-specific language of the novice. The study proposes the design of an intelligent assistance system that takes problem descriptions articulated in natural language as an input and offers advice regarding the most suitable class of data mining methods. Following a design science research approach, the paper (i) outlines the problem setting with an exemplary scenario from industrial practice, (ii) derives design requirements, (iii) develops design principles and proposes design features, (iv) develops and implements the IT artifact using several methods such as embeddings, keyword extractions, topic models, and text classifiers, (v) demonstrates and evaluates the implemented prototype based on different classification pipelines, and (vi) discusses the results' practical and theoretical contributions. The best performing classification pipelines show high accuracies when applied to validation data and are capable of creating a suitable mapping that exceeds the performance of joint novice assessments and simpler means of text mining. The research provides a promising foundation for further enhancements, either as a stand-alone intelligent assistance system or as an add-on to already existing data science and analytics platforms.
  • Zeitschriftenartikel
    Designing Anthropomorphic Enterprise Conversational Agents
    (Business & Information Systems Engineering: Vol. 62, No. 3, 2020) Diederich, Stephan; Brendel, Alfred Benedikt; Kolbe, Lutz M.
    The increasing capabilities of conversational agents (CAs) offer manifold opportunities to assist users in a variety of tasks. In an organizational context, particularly their potential to simulate a human-like interaction via natural language currently attracts attention both at the customer interface as well as for internal purposes, often in the form of chatbots. Emerging experimental studies on CAs look into the impact of anthropomorphic design elements, so-called social cues, on user perception. However, while these studies provide valuable prescriptive knowledge of selected social cues, they neglect the potential detrimental influence of the limited responsiveness of present-day conversational agents. In practice, many CAs fail to continuously provide meaningful responses in a conversation due to the open nature of natural language interaction, which negatively influences user perception and often led to CAs being discontinued in the past. Thus, designing a CA that provides a human-like interaction experience while minimizing the risks associated with limited conversational capabilities represents a substantial design problem. This study addresses the aforementioned problem by proposing and evaluating a design for a CA that offers a human-like interaction experience while mitigating negative effects due to limited responsiveness. Through the presentation of the artifact and the synthesis of prescriptive knowledge in the form of a nascent design theory for anthropomorphic enterprise CAs, this research adds to the growing knowledge base for designing human-like assistants and supports practitioners seeking to introduce them into their organizations.
  • Zeitschriftenartikel
    Monetizing Online Content: Digital Paywall Design and Configuration
    (Business & Information Systems Engineering: Vol. 62, No. 3, 2020) Rußell, Robert; Berger, Benedikt; Stich, Lucas; Hess, Thomas; Spann, Martin