Towards a Taxonomy of Platforms for Conversational Agent Design

Software that interacts with its users through natural language, so-called conversational agents (CAs), is permeating our lives with improving capabilities driven by advances in machine learning and natural language processing. For organizations, CAs have the potential to innovate and automate a variety of tasks and processes, for example in customer service or marketing and sales, yet successful design remains a major challenge. Over the last few years, a variety of platforms that offer different approaches and functionality for designing CAs have emerged. In this paper, we analyze 51 CA platforms to develop a taxonomy and empirically identify archetypes of platforms by means of a cluster analysis. Based on our analysis, we propose an extended taxonomy with eleven dimensions and three archetypes that contribute to existing work on CA design and can guide practitioners in the design of CA for their organizations

On Conversational Agents in Information Systems Research: Analyzing the Past to Guide Future Work

Conversational agents (CA), i.e. software that interacts with its users through natural language, are becoming increasingly prevalent in everyday life as technological advances continue to significantly drive their capabilities. CA exhibit the potential to support and collaborate with humans in a multitude of tasks and can be used for innovation and automation across a variety of business functions, such as customer service or marketing and sales. Parallel to the increasing popularity in practice, IS researchers have engaged in studying a variety of aspects related to CA in the last few years, applying different research methods and producing different types of theories. In this paper, we review 36studies to assess the status quo of CA research in IS, identify gaps regarding both the studied aspects as well as applied methods and theoretical approaches, and propose directions for future work in this research area

Examining Applicability of Uncanny Valley Hypothesis: A Large-Scale Study

Despite a growing interest in applying the uncanny valley hypothesis (UVH) in IS studies, there is a paucity of knowledge on the applicability of UVH and its strength. By summarizing a set of attitudinal variables popularized in the extant IS literature on AI robots, this study examined the strength and applicability of UVH on a large, objectively chosen sample of 80 real-world robots face against these variables. We demonstrate that while robot anthropomorphism does affect users’ attitudes toward the robot, its effects do not necessarily follow a UV pattern, and it has a very limited explanatory power toward users’ attitudinal responses. In addition, robot anthropomorphism has a much stronger linear-like association with a perceived social presence than with the commonly used response variable of perceived likability. Our results offer insights into understanding the applicability and strength of the uncanny valley effect and the impacts of robot anthropomorphism on users’ perceptions

Design Requirements for AI-based Services Enriching Legacy Information Systems in Enterprises: A Managerial Perspective

Information systems (IS) have been introduced in enterprises for decades to generate business value. Historically systems that are deeply integrated into business processes and not replaced remain vital assets, and thus become legacy IS (LISs). To secure the future success, enterprises invest in innovative technologies such as artificial intelligence-based services (AIBSs), enriching LISs and assisting employees in the execution of work-related tasks. This study develops design requirements from a managerial perspective by following a mixed-method approach. First, we conducted ten interviews to formulate requirements to design AIBSs. Second, we evaluated their business value using an online survey (N = 101). The results indicate that executives consider design requirements as relevant that create strategic advancements in the short term. With the help of our findings, researchers can better understand where further in-depth studies are needed to refine the requirements. Practitioners can learn how AIBSs generate business value when enriching LISs

Is it COVID or a Cold? An Investigation of the Role of Social Presence, Trust, and Persuasiveness for Users\u27 Intention to Comply with COVID-19 Chatbots

The COVID-19 pandemic challenged the existing healthcare system by demanding potential patients to self-diagnose and self-test a potential virus contraction. In this process, some individuals need help and guidance. However, the previous modus-operandi to go to a physician is no longer viable because of the limited capacity and danger of spreading the virus. Hence, digital means had to be developed to help and inform individuals at home, such as conversational agents (CA). The human-like design and perceived social presence of such a CA are central to attaining users’ compliance. Against this background, we surveyed 174 users of a commercial COVID-19 chatbot to investigate the role of perceived social presence. Our results provide support that the perceived social presence of chatbots leads to higher levels of trust, which are a driver of compliance. In contrast, perceived persuasiveness seems to have no significant effect

Supporting Inclusive Learning Using Chatbots? A Chatbot-Led Interview Study

Supporting student academic success has been one of the major goals for higher education. However, low teacher-to-student ratio makes it difficult for students to receive sufficient and personalized support that they might want to. The advancement of artificial intelligence (AI) and conversational agents, such as chatbots, has provided opportunities for assisting learning for different types of students. This research aims at investigating the opportunities and requirements of chatbots as an intelligent helper to facilitate equity in learning. We developed a chatbot as an experimental platform to investigate the design opportunities of using chatbots to support inclusive learning. Through a chatbot-led user study with 215 undergraduate students, we found chatbots provide the opportunity to support students who are disadvantaged, with diverse life environments, and with varied learning styles. This could be achieved through an accessible, interactive, and confidential way

Instrument Development for R-Service Quality: A Literature Review

Motivated by a paucity of knowledge on the measurement of robotic service (r-service) quality, the current study strives to review the existing literature on r-service quality, with a focus on the potential methodological issues of developing measurement instruments and identifying the dimensionality of r-service quality. With a content analysis of 55 articles, this study identifies several methodological limitations of existing studies in developing measurement scales of r-service quality. This review reveals that dimensions of r-service quality are prone to be contingent on specific con-texts of service industry and service type. Several common dimensions regarding evaluating r-service are identified, including tangibility, responsiveness, reliability, empathy, assurance, ease of use/usability, usefulness, anthropomorphism, perceived intelligence, and social presence. This study is the first systematic literature review on r-service quality dimensionality

Follow Me If You Want to Live - Understanding the Influence of Human-Like Design on Users’ Perception and Intention to Comply with COVID-19 Education Chatbots

Following recommendations and complying with behavioral attitudes is one major key in overcoming global pandemics, such as COVID-19. As the World Health Organization (WHO) highlights, there is an increased need to follow hygiene standards to prevent infections and in reducing the risk of infections transmissions (World-Health-Organization, 2021). This urgent need offers new use cases of digital services, such as conversational agents that educate and inform individuals about relevant counter measurements. Specifically, due to the increased fatigue in the population in the context of COVID-19, (Franzen and Wöhner, 2021), CAs can play a vital role in supporting and attaining user’s behavior. We conducted an experiment (n=116) to analyze the effect of a human-like-design CA on the intention to comply. Our results show a significant impact of a human-like design on the perception of humanness, source credibility, and trust, which are all (directly or indirectly) drivers of the intention to comply

“Look Closer” Anthropomorphic Design and Perception of Anthropomorphism in Conversational Agent Research

Conversation agents have been attracting increased attention in IS research and increased adoption in practice. They provide an AI-driven conversation-like interface and tap into the anthropomorphism bias of its users. There has been extensive research on improving this effect for over a decade since increased anthropomorphism leads to increased service satisfaction, trust, and other effects on the user. This work examines the current state of research regarding anthropomorphism and anthropomorphic design to guide future research. It utilizes a modified structured literature analysis to extract and classify the examined constructs and their relationships in the hypotheses of current literature. We provide an overview of current research, highlighting focus areas. Based on our results, we formulate several open research questions and provide the IS community with directions for future research