Now showing 1 - 10 of 18
  • 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
    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 33
  • Publication
    Designing Conversational Evaluation Tools: A Comparison of Text and Voice Modalities to Improve Response Quality in Course Evaluations
    (Association for Computing Machinery, 2022-11-11) ; ; ;
    Käser, Tanja
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    Koedinger, Kenneth R.
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    Conversational agents (CAs) provide opportunities for improving the interaction in evaluation surveys. To investigate if and how a user-centered conversational evaluation tool impacts users' response quality and their experience, we build EVA - a novel conversational course evaluation tool for educational scenarios. In a field experiment with 128 students, we compared EVA against a static web survey. Our results confirm prior findings from literature about the positive effect of conversational evaluation tools in the domain of education. Second, we then investigate the differences between a voice-based and text-based conversational human-computer interaction of EVA in the same experimental set-up. Against our prior expectation, the students of the voice-based interaction answered with higher information quality but with lower quantity of information compared to the text-based modality. Our findings indicate that using a conversational CA (voice and text-based) results in a higher response quality and user experience compared to a static web survey interface.
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    Scopus© Citations 2
  • Publication
    Voice bots on the frontline: Voice-based interfaces enhance flow-like consumer experiences & boost service outcomes
    Voice-based interfaces provide new opportunities for firms to interact with consumers along the customer journey. The current work demonstrates across four studies that voice-based (as opposed to text-based) interfaces promote more flow-like user experiences, resulting in more positively-valenced service experiences, and ultimately more favorable behavioral firm outcomes (i.e., contract renewal, conversion rates, and consumer sentiment). Moreover, we also provide evidence for two important boundary conditions that reduce such flow-like user experiences in voice-based interfaces (i.e., semantic disfluency and the amount of conversational turns). The findings of this research highlight how fundamental theories of human communication can be harnessed to create more experiential service experiences with positive downstream consequences for consumers and firms. These findings have important practical implications for firms that aim at leveraging the potential of voice-based interfaces to improve consumers' service experiences and the theory-driven ''conversational design'' of voice-based interfaces.
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    Scopus© Citations 17
  • Publication
    Towards Developing Trust-Supporting Design Features for AI-Based Chatbots in Customer Service
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    Hausch, Michael
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    Bruhin, Olivia
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    Chatbots are predicted to play a key role in customer service based on recent advances in the area of Artificial Intelligence (AI). However, a lack of user trust impedes the wide- spread adaption of AI-based chatbots. Still, there is a lack of systematically derived design knowledge concerning user trust in those agents. In this short paper, we report on the first steps of our design science research project on which design principles are relevant for building trust in chatbots. Based on trust literature and user interviews, we propose preliminary requirements and design principles for trust-enhancing design features for chatbots in customer service. Furthermore, we present a first instantiation of those principles. These insights will support researchers and practitioners to better understand how user trust in chatbots can be systematically built to increase adoption and usage.
  • Publication
    Challenges and Good Practices in Conversational AI-Driven Service Automation
    Conversational AI offers novel opportunities for companies to automate customer interactions. However, many companies grapple with effectively implementing conversational AI. Utilizing an engaged, consortium-based research approach, we examine the unique challenges faced by six companies in the insurance and banking sector while implementing conversational AI solutions and identify best practices to address these challenges. Finally, drawing upon the lessons learned, we offer guidance for developing conversational AI capabilities and fostering conversational AI success stories.
  • Publication
    How Conversational Agents Relieve Teams from Innovation Blockages
    Innovation is one of the most important antecedents of a company's competitive advantage and long-term survival. Prior research has alluded to teamwork being a primary driver of a firm's innovation capacity. Still, many firms struggle with providing an environment that supports innovation teams in working efficiently together. Thereby, a team's failure can be attributed to several factors, such as inefficient working methods or a lack of internal communication that leads to so-called innovation blockages. There are a number of approaches that are targeted at supporting teams to overcome innovation blockages, but they mainly focus on the collaboration process and rarely consider the needs and potentials of individual team members. In this paper, we argue that Conversational Agents (CAs) can efficiently support teams in overcoming innovation blockages by enhancing collaborative work practices and, specifically, by facilitating the contribution of each individual team member. To that end, we design a CA as a team facilitator that provides nudges to reduce innovation blocking actions according to requirements we systematically derived from scientific literature and practice. Based on a rigorous evaluation, we demonstrate the potential of CAs to reduce the frequency of innovation blockages. The research implications for the development and deployment of CAs as team facilitators are explored.
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  • Publication
    “I Will Follow You!” – How Recommendation Modality Impacts Processing Fluency and Purchase Intention
    ( 2022-12-09)
    Schwede, Melanie
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    Hammerschmidt, Maik
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    Although conversational agents (CA) are increasingly used for providing purchase recommendations, important design questions remain. Across two experiments we examine with a novel fluency mechanism how recommendation modality (speech vs. text) shapes recommendation evaluation (persuasiveness and risk), the intention to follow the recommendation, and how modality interacts with the style of recommendation explanation (verbal vs. numerical). Findings provide robust evidence that text-based CAs outperform speech-based CAs in terms of processing fluency and consumer responses. They show that numerical explanations increase processing fluency and purchase intention of both recommendation modalities. The results underline the importance of processing fluency for the decision to follow a recommendation and highlight that processing fluency can be actively shaped through design decisions in terms of implementing the right modality and aligning it with the optimal explanation style. For practice, we offer actionable implications on how to make effective sales agents out of CAs.
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  • Publication
    Alexa, are you still there? Understanding the Habitual Use of AI-Based Voice Assistants
    ( 2021-12)
    Grünenfelder, Janay Ilya
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    Voice assistants are a novel class of information systems that fundamentally change human–computer interaction. Although these assistants are widespread, the utilization of these information systems is oftentimes only considered on a surface level by individuals. In addition, prior research has focused predominantly on initial use instead of looking deeper into post-adoption and habit formation. In consequence, this paper reviews how the notion of habit has been conceptualized in relation to biographical utilization of voice assistants and presents findings based on a qualitative study approach. From a perspective of post-adoption users, the study suggests that existing habits persist, and new habits hardly ever form in the context of voice assistant utilization. This paper outlines four key factors that help explain voice assistant utilization behavior and furthermore provides practical implications that help to ensure continued voice assistant use in the future.
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  • Publication
    Voice as a Contemporary Frontier of Interaction Design
    Voice assistants’ increasingly nuanced and natural communication bears new opportunities for user experiences and task automation, while challenging existing patterns of human-computer interaction. A fragmented research field, as well as constant technological advancements, impede a common apprehension of prevalent design features of voice-based interfaces. As part of this study, 86 papers across domains are systematically identified and analysed to arrive at a common understanding of voice assistants. The review highlights perceptual differences to other human-computer interfaces and points out relevant auditory cues. Key findings regarding those cues’ impact on user perception and behaviour are discussed along with the three design strategies 1) personification, 2) individualization and 3) contextualization. Avenues for future research are lastly deducted. Our results provide relevant opportunities to researchers and designers alike to advance the design and deployment of voice assistants.
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