DESIGN FOR FAST REQUEST FULFILLMENT OR NATURAL INTERACTION? INSIGHTS FROM AN EXPERIMENT WITH A CONVERSATIONAL AGENT

Conversational agents continue to permeate our lives in different forms, such as virtual assistants on mobile devices or chatbots on websites and social media. The interaction with users through natural language offers various aspects for researchers to study as well as application domains for practitioners to explore. In particular their design represents an interesting phenomenon to investigate as humans show social responses to these agents and successful design remains a challenge in practice. Compared to digital human-to-human communication, text-based conversational agents can provide complementary, preset answer options with which users can conveniently and quickly respond in the interaction. However, their use might also decrease the perceived humanness and social presence of the agent as the user does not respond naturally by thinking of and formulating a reply. In this study, we conducted an experiment with N=80 participants in a customer service context to explore the impact of such elements on agent anthropomorphism and user satisfaction. The results show that their use reduces perceived humanness and social presence yet does not significantly increase service satisfaction. On the contrary, our findings indicate that preset answer options might even be detrimental to service satisfaction as they diminish the natural feel of human-CA interaction

User satisfaction of chatbot system

Abstract. The purpose of this study was to identify how the research trend of user satisfaction of chatbots in customer services is presented. As the recent raise of attention in chatbots system, especially in commercial use, the user satisfaction should be considered. The main research question was how is the topic of user satisfaction of chatbot system in customer service presented in the prior academic research? Therefore, it was distributed into 3 sub-questions; how did the amount of research change according to time? How and why did the researchers conduct the research? How did the existing literature evaluate the user satisfaction? Systematic mapping study research methodology was applied in the study. This research methodology considered the prior literature as primary studies then categorized them in order to get answer to research question. The results were how frequency the research had been published based on different scheme. 26 articles were involved as primary studies. The schemes included year of publication, research approach and user satisfaction evaluation approach. The main contribution of this study was to discover trend regarding user satisfaction of chatbot in customer service context. This would help structure academic research area and motivate future research as well as being a guidance for conducting new research. The studied proved that the topic was still received a lot of interest from researchers as number of literatures regarding topic were growing. However, the results also stated that there was still lacking of research in some area or in specific scheme. As this study’s goal is to discover the research trend in order to identify the research gap, the future research is encouraged regarding the gap identified as well as the improvement of this study

Exploring User Experience with a Conversational Agent to Treat Depression in Youth: A Think-Aloud Study

Conversational agents are a promising digital health intervention that can mitigate help-seeking barriers for youth with depression to receive treatment. Although studies have shown sufficient acceptance, feasibility, and promising effectiveness for adults, not much is known about how youth experience interacting with conversational agents to improve mental health. Therefore, we conducted an exploratory study with 15 youth with to collect data on their interaction with a conversational agent prototype using the think-aloud protocol. We coded the material from the think-aloud sessions using an inductive approach. Our findings provide insights into how youth with depression interacted with the prototype. Participants frequently and controversially discussed the conversational agent’s (1) personality and interaction style, (2) its functionality, and (3) the dialogue content with implications for the design of conversational agents to treat depression and future research

Machinelike or Humanlike? A Literature Review of Anthropomorphism in AI-Enabled Technology

Due to the recent proliferation of AI-enabled technology (AIET), the concept of anthropomorphism, human likeness in technology, has increasingly attracted researchers’ attention. Researchers have examined how anthropomorphism influences users’ perception, adoption, and continued use of AIET. However, researchers have yet to agree on how to conceptualize and operationalize anthropomorphism in AIET, which has resulted in inconsistent findings. A comprehensive understanding is thus needed of the current state of research on anthropomorphism in AIET contexts. To conduct an in-depth analysis of the literature on anthropomorphism, we reviewed 35 empirical studies focusing on conceptualizing and operationalizing AIET anthropomorphism, and its antecedents and consequences. Based on our analysis, we discuss potential research gaps and offer directions for future research

You are an Idiot! – How Conversational Agent Communication Patterns Influence Frustration and Harassment

Conversational Agents (CA) in the form of digital assistants on smartphones, chatbots on social media, or physical embodied systems are an increasingly often applied new form of user interfaces for digital systems. The human-like design of CAs (e.g., having names, greeting users, and using self-references) leads to users subconsciously reacting to them as they were interacting with a human. In recent research, it has been shown that this social component of interacting with a CA leads to various benefits, such as increased service satisfaction, enjoyment, and trust. However, numerous CAs were discontinued because of inadequate responses to user requests or only making errors because of the limited functionalities and knowledge of a CA, which can lead to frustration. Therefore, investigating the causes of frustration and other related emotions and reactions highly relevant. Against this background, this study investigates via an online experiment with 169 participants how different communication patterns influence user’s perception, frustration, and harassment behavior of an error producing CA

Working with ELSA – How an Emotional Support Agent Builds Trust in Virtual Teams

Virtual collaboration is an increasing part of daily life for many employees. Despite many advantages, however, virtual collaborative work can lead to a lack of trust among virtual team members, e.g., due to spatial separation and little social interaction. Previous findings indicated that emotional support provided by a conversational agent (CA) can impact human-agent trust and the perceived social presence. We developed an emotional support agent called ELSA and conducted a between-subject online experiment to examine how CAs can provide emotional support in order to increase the level of trust among colleagues in virtual teams. We found that human-agent trust positively influences the level of calculus-based trust among team members and increases team cohesion, whereas perceived anthropomorphism and social presence towards a CA seems to be less important for trust among team members

USER ACCEPTANCE OF SOCIAL ROBOTS: A SOCIAL RESPONSE PERSPECTIVE

Anthropomorphism of social robots has been argued to be an important factor that determines individuals’ usage of social robots. Little research on social robots has explained how the anthropomorphic design of social robots affects users’ social responses to social robots and how social responses further affect user acceptance of social robots. Drawing on the social response theory, we propose a conceptual model to examine user acceptance of social robots. Specifically, three anthropomorphic features (appearance, voice, and response) are proposed to trigger users’ social responses (perceived social presence and perceived humanness) to social robots, which lead to individuals’ intention to accept social robots. The proposed research model will be empirically tested with data collected among hotel customers via an online experiment. The current study aims to contribute to the social robot acceptance literature from the social response perspective

Adaptive Conversational Agents: Exploring the Effect of Individualized Design on User Experience

Conversational agents (CA) offer a range of benefits to firms and users, yet user experiences are often unsatisfying. An explanation might be that individual differences of users are only insufficiently addressed in today’s CA design. Drawing on communication accommodation theory, we develop a research model and study design to investigate how adapting CA design to users’ individual characteristics influences the user experience. In particular, we develop text-based CAs (i.e., chatbots) that are adapted to users’ rational/intuitive cognitive style or need for interaction, and compare the user experience to non-adapted CAs. Initial results from our pilot study (n=37) confirm that individualized CA design can enhance the user experience. We expect to contribute to the growing research field of adaptive CA design. Moreover, our results will provide guidance for developers on how to facilitate a pleasing user experience by adapting the CA design to users

Painting A Holistic Picture of Trust in and Adoption of Conversational Agents: A Meta-Analytic Structural Equation Modeling Approach

With their human-like nature, conversational agents (CAs) introduce a social component to human-computer interaction. Numerous studies have previously attempted to integrate this social component by incorporating trust into models such as the technology acceptance model (TAM) to decipher the adoption mechanisms related to CAs. Given the heterogeneity of these previous works, the aim of this paper is to integrate empirical evidence on the role and influence of trust within the nomological network of the TAM. For this purpose, we conduct a meta-analytic structural equation modeling approach based on 45 studies comprising k = 155 correlations, and N = 13,786 observations. Our findings highlight the multifaceted role of trust as a mediator transmitting the effects of the technology-related perceptions that drive the intention to use CAs. Our results present a comprehensive overview in a thriving research field that can guide both future theory building and the designs of more trustworthy CAs