Now showing 1 - 10 of 22
  • Publication
    How to leverage anthropomorphism for chatbot service interfaces: The interplay of communication style and personification
    (Elsevier, 2023-09-19)
    Although chatbots are oftentimes used in customer service encounters, interactions are oftentimes perceived as not satisfactory. One key aspect for designing chatbots is the use of anthropomorphic design elements. In this experimental study, we examine the two anthropomorphic chatbot design elements of personification, which includes a human-like appearance, and social orientation of communication style, which means a more sensitive and extensive communication. We tested the influence of the two design elements on social presence, satisfaction, trust and empathy towards a chatbot. First, the results show a significant influence of both anthropomorphic design elements on social presence. Second, our findings illustrate that social presence influences trusting beliefs, empathy, and satisfaction. Third, social presence acts as a mediator for both anthropomorphic design elements for satisfaction with a chatbot. Our implications provide a better understanding of anthropomorphic chatbot design elements when designing chatbots for short-term interactions, and we offer actionable implications for practice that enable more effective chatbot implementations.
    Scopus© Citations 1
  • Publication
    The Role of AI-Based Artifacts’ Voice Capabilities for Agency Attribution
    The pervasiveness and increasing sophistication of artificial intelligence (AI)-based artifacts within private, organizational, and social realms change how humans interact with machines. Theorizing about the way humans perceive AI-based artifacts is crucial to understanding why and to what extent humans deem these as competent for, i.e., decision-making, yet has traditionally taken a modality-agnostic view. In this paper, we theorize about a particular case of interaction, namely that of voice-based interaction with AI-based artifacts. The capabilities and perceived naturalness of such artifacts, fueled by continuous advances in natural language processing, induce users to deem an artifact as able to act autonomously in a goal-oriented manner. We argue that there is a positive direct relationship between the voice capabilities of an artifact and users’ agency attribution, ultimately obscuring the artifact’s true nature and competencies. This relationship is further moderated by an artifact’s actual agency, uncertainty, and user characteristics.
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  • Publication
    Charting the Evolution and Future of Conversational Agents: A Research Agenda Along Five Waves and New Frontiers
    (Springer Nature, 2023-04-20)
    Schöbel, Sofia
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    Benner, Dennis
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    Saqr, Mohammed
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    Conversational agents (CAs) have come a long way from their first appearance in the 1960s to today's generative models. Continuous technological advancements such as statistical computing and large language models allow for an increasingly natural and effortless interaction, as well as domain-agnostic deployment opportunities. Ultimately, this evolution begs multiple questions: How have technical capabilities developed? How is the nature of work changed through humans' interaction with conversational agents? How has research framed dominant perceptions and depictions of such agents? And what is the path forward? To address these questions, we conducted a bibliometric study including over 5000 research articles on CAs. Based on a systematic analysis of keywords, topics, and author networks, we derive "five waves of CA research" that describe the past, present, and potential future of research on CAs. Our results highlight fundamental technical evolutions and theoretical paradigms in CA research. Therefore, we discuss the moderating role of big technologies, and novel technological advancements like OpenAI GPT or BLOOM NLU that mark the next frontier of CA research. We contribute to theory by laying out central research streams in CA research, and offer practical implications by highlighting the design and deployment opportunities of CAs.
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    Scopus© Citations 9
  • Publication
    How to Achieve Ethical Persuasive Design: A Review and Theoretical Propositions for Information Systems
    ( 2022-12-29)
    Benner, Dennis
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    Schöbel, Sofia
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    Persuasive system design (PSD) is an umbrella term for designs in information systems (IS) that can influence people’s attitude, behavior, or decision making for better or for worse. On the one hand, PSD can improve users’ engagement and motivation to change their attitude, behavior, or decision making in a favorable way, which can help them achieve a desired outcome and, thus, improve their wellbeing. On the other hand, PSD misuse can lead to unethical and undesirable outcomes, such as disclosing unnecessary information or agreeing to terms that do not favor users, which, in turn, can negatively impact their wellbeing. These powerful persuasive designs can involve concepts such as gamification, gamblification, and digital nudging, which all have become prominent in recent years and have been implemented successfully across different sectors, such as education, e-health, e-governance, e-finance, and digital privacy contexts. However, such persuasive influence on individuals raises ethical questions as PSD can impair users’ autonomy or persuade them towards a third party’s goals and, hence, lead to unethical decision-making processes and outcomes. In human-computer interaction, recent advances in artificial intelligence have made this topic particularly significant. These novel technologies allow one to influence the decisions that users make, to gather data, and to profile and persuade users into unethical outcomes. These unethical outcomes can lead to psychological and emotional damage to users. To understand the role that ethics play in persuasive system design, we conducted an exhaustive systematic literature analysis and 20 interviews to overview ethical considerations for persuasive system design. Furthermore, we derive potential propositions for more ethical PSD and shed light on potential research gaps.
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  • Publication
    Understanding the Design Elements Affecting User Acceptance of Intelligent Agents: Past, Present and Future
    Intelligent agents (IAs) are permeating both business and society. However, interacting with IAs poses challenges moving beyond technological limitations towards the human-computer interface. Thus, the knowledgebase related to interaction with IAs has grown exponentially but remains segregated and impedes the advancement of the field. Therefore, we conduct a systematic literature review to integrate empirical knowledge on user interaction with IAs. This is the first paper to examine 107 Information Systems and Human-Computer Interaction papers and identified 389 relationships between design elements and user acceptance of IAs. Along the independent and dependent variables of these relationships, we span a research space model encompassing empirical research on designing for IA user acceptance. Further we contribute to theory, by presenting a research agenda along the dimensions of the research space, which shall be useful to both researchers and practitioners. This complements the past and present knowledge on designing for IA user acceptance with potential pathways into the future of IAs.
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    Scopus© Citations 28
  • Publication
    Improving Students Argumentation Learning with Adaptive Self-Evaluation Nudging
    Recent advantages from computational linguists can be leveraged to nudge students with adaptive self evaluation based on their argumentation skill level. To investigate how individual argumentation self evaluation will help students write more convincing texts, we designed an intelligent argumentation writing support system called ArgumentFeedback based on nudging theory and evaluated it in a series of three qualitative and quaxntitative studies with a total of 83 students. We found that students who received a self-evaluation nudge wrote more convincing texts with a better quality of formal and perceived argumentation compared to the control group. The measured self-efficacy and the technology acceptance provide promising results for embedding adaptive argumentation writing support tools in combination with digital nudging in traditional learning settings to foster self-regulated learning. Our results indicate that the design of nudging-based learning applications for self-regulated learning combined with computational methods for argumentation self-evaluation has a beneficial use to foster better writing skills of students.
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    Scopus© Citations 5
  • Publication
    Enhancing argumentative writing with automated feedback and social comparison nudging
    The advantages offered by natural language processing (NLP) and machine learning enable students to receive automated feedback on their argumentation skills, independent of educator, time, and location. Although there is a growing amount of literature on formative argumentation feedback, empirical evidence on the effects of adaptive feedback mechanisms and novel NLP approaches to enhance argumentative writing remains scarce. To help fill this gap, the aim of the present study is to investigate whether automated feedback and social comparison nudging enable students to internalize and improve logical argumentation writing abilities in an undergraduate business course. We conducted a mixed-methods study to investigate the impact of argumentative writing on 71 students in a field experiment. Students in treatment group 1 completed their assignment while receiving automated feedback, whereas students in treatment group 2 completed the same assignment while receiving automated feedback with a social comparison nudge that indicated how other students performed on the same assignment. Students in the control group received generalized feedback based on rules of syntax. We found that participants who received automated argumentation feedback with a social comparison nudge wrote more convincing texts with higher-quality argumentation compared to the two benchmark groups (p < 0.05). The measured self-efficacy, perceived ease of use, and qualitative data provide valuable insights that help explain this effect. The results suggest that embedding automated feedback in combination with social comparison nudges enables students to increase their argumentative writing skills by triggering psychological processes. Receiving only automated feedback in the form of in-text argumentative highlighting without any further guidance appears not to significantly influence students’ writing abilities when compared to syntactic feedback.
    Scopus© Citations 11
  • Publication
    Value Co-Creation in Smart Services: A Functional Affordances Perspective on Smart Personal Assistants
    (Assoc. of Information Systems, 2020-03-09)
    Knote, Robin
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    In the realm of smart services, smart personal assistants (SPAs) have become a popular medium for value co-creation between service providers and users. The market success of SPAs is largely based on their innovative material properties, such as natural language user interfaces, machine-learning-powered request handling and service provision, and anthropomorphism. In different combinations, these properties offer users entirely new ways to intuitively and interactively achieve their goals and, thus, co-create value with service providers. But how does the nature of the SPA shape value co-creation processes? In this paper, we look through a functional affordances lens to theorize about the effects of different types of SPAs (i.e., with different combinations of material properties) on users' value co-creation processes. Specifically, we collected SPAs from research and practice by reviewing scientific literature and web resources, developed a taxonomy of SPAs' material properties, and performed a cluster analysis to group SPAs of a similar nature. We then derived 2 general and 11 cluster-specific propositions on how different material properties of SPAs can yield different affordances for value co-creation. With our work, we point out that smart services require researchers and practitioners to fundamentally rethink value co-creation as well as revise affordances theory to address the dynamic nature of smart technology as a service counterpart.
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  • Publication
    Designing Pedagogical Conversational Agents for Achieving Common Ground
    ( 2023)
    Antonia Tolzin
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    Anita Körner
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    Ernestine Dickhaut
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    Ralf Rummer
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    As educational organizations face difficulties in providing personalized learning material or individual learning support, pedagogical conversational agents (PCAs) promise individualized learning for students. However, the problem of conversational breakdowns of PCAs and consequently poor learning outcomes still exist. Hence, effective and grounded communication between learners and PCAs is fundamental to improving learning processes and out-comes. As understanding each other and the conversational grounding is crucial for conversations between humans and PCAs, we propose common ground theory as a foundation for designing a PCA. Conducting a design science research project, we propose theory-motivated design principles and instantiate them in a PCA. We evaluate the utility of the artifact with an experimental study in higher education to inform the subsequent design iterations. We contribute design knowledge on conversational agents in learning settings, enabling researchers and practitioners to develop PCAs based on common ground research in education and providing avenues for future research. Thereby, we can secure further understanding of learning processes based on grounding communication.
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    Scopus© Citations 1
  • Publication
    Disentangling Trust in Voice Assistants - A Configurational View on Conversational AI Ecosystems
    ( 2023) ; ;
    Bevilacqua, Tatjana
    Voice assistants’ (VAs) increasingly nuanced and natural communication via artificial intelligence (AI) opens up new opportunities for the experience of users, providing task assistance and automation possibilities, and also offer an easy interface to digital services and ecosystems. However, VAs and according ecosystems face various problems, such as low adoption and satisfaction rates as well as other negative reactions from users. Companies, therefore, need to consider what contributes to user satisfaction of VAs and related conversational AI ecosystems. Key for conversational AI ecosystems is the consideration of trust due to their agentic and pervasive nature. Nonetheless, due to the complexity of conversational AI ecosystems and different trust sources involved, we argue that we need a more detailed understanding about trust. Thus, we propose a configurational view on conversational AI ecosystems that allows us to disentangle the complex and interrelated factors that contribute to trust in VAs. We examine with a configurational approach and a survey study, how different trust sources contribute to the outcomes of conversational AI ecosystems, i.e., in our case user satisfaction. The results of our study show four distinct patterns of trust source configurations. Vice versa, we show how trust sources contribute to the absence of the outcome, i.e., user satisfaction. The derived implications provide a configurative theoretical understanding for the role of trust sources for user satisfaction that provides practitioners useful guidance for more trustworthy conversational AI ecosystems.
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