Social Influence in Customer-Robot Interactions

This paper focuses on social influence in customer-robot interactions. Drawing on social impact theory and the computers-are-social-actors (CASA) paradigm, we argue that customers\u27 reluctance to provide information to a service robot decreases when other customers exhibit high information disclosure. The effect of demonstrated information disclosure on customers\u27 reluctance to provide information is enhanced by the application of social norms. The results also show that social influence is stronger in customer-robot interactions than in customer-employee interactions. This article demonstrates the potential of social influence to reduce reluctance towards service robots, which has both theoretical and managerial implications. We extend existing research on the imitation of robot behavior with the imitation of user behavior, and discuss the ethical implications of customers mindlessly following other customers in customer-robot interactions

Customer Responses to (Im)Moral Behavior of Service Robots - Online Experiments in a Retail Setting

Service robots play an increasingly important role in the service sector. Drawing on moral psychology research, moral foundations theory as well as the computers-as-social-actors (CASA) paradigm, this experimental study containing of four online experiments examines the extent to which the moral or immoral behavior of a service robot affects customer responses during a service interaction. This study contributes to design science by defining, conceptualizing and operationalizing morality of service robots and developing a corresponding vignette as basis to manipulate (im)moral robotic behavior in a retail setting. To investigate possible effects of the robot’s appearance, we tested our hypotheses with two different robots, i.e., a humanoid robot and an android robot. Results from the online experiment indicate that the (im)moral behavior of service robots at the customer interface has a significant effect on customers’ trust and customers’ ethical concerns towards the robot

Facial emotion expressions in human-robot interaction: A survey

Facial expressions are an ideal means of communicating one's emotions or intentions to others. This overview will focus on human facial expression recognition as well as robotic facial expression generation. In case of human facial expression recognition, both facial expression recognition on predefined datasets as well as in real time will be covered. For robotic facial expression generation, hand coded and automated methods i.e., facial expressions of a robot are generated by moving the features (eyes, mouth) of the robot by hand coding or automatically using machine learning techniques, will also be covered. There are already plenty of studies that achieve high accuracy for emotion expression recognition on predefined datasets, but the accuracy for facial expression recognition in real time is comparatively lower. In case of expression generation in robots, while most of the robots are capable of making basic facial expressions, there are not many studies that enable robots to do so automatically.Comment: Pre-print version. Accepted in International Journal of Social Robotic

Customer Responses to (Im)Moral Behavior of Service Robots - Online Experiments in a Retail Setting

Service robots play an increasingly important role in the service sector. Drawing on moral psychology research, moral foundations theory as well as the computers-as-social-actors (CASA) paradigm, this experimental study containing of four online experiments examines the extent to which the moral or immoral behavior of a service robot affects customer responses during a service interaction. This study contributes to design science by defining, conceptualizing and operationalizing morality of service robots and developing a corresponding vignette as basis to manipulate (im)moral robotic behavior in a retail setting. To investigate possible effects of the robot’s appearance, we tested our hypotheses with two different robots, i.e., a humanoid robot and an android robot. Results from the online experiment indicate that the (im)moral behavior of service robots at the customer interface has a significant effect on customers’ trust and customers’ ethical concerns towards the robot

Good Robot, Bad Robot: Customer Responses to Norm-Compliant and Norm-Violating Service Robots

Service robots that interact with customers have penetrated various industries. With a basis in social identity theory, this study examines how customers respond to frontline service robots (FSRs) by investigating norm-compliant versus norm-violating behaviors compared with similar behaviors by human frontline employees (FLEs). In experimental studies, a black sheep effect occurs, such that customers downgrade norm-violating FLE behaviors more than similar behaviors by FSRs. They also upgrade norm-compliant behaviors by human FLEs more than those of FSRs. In service failures, this effect manifests as greater anger and frustration toward the FLE. We establish the underlying mechanism driving the black sheep effect: customers assign FSRs to an outgroup but categorize FLEs to their social ingroup, across different service encounters and independent of interaction frequency

Facial Emotion Expressions in Human-Robot Interaction: A Survey

Facial expressions are an ideal means of communicating one's emotions or intentions to others. This overview will focus on human facial expression recognition as well as robotic facial expression generation. In the case of human facial expression recognition, both facial expression recognition on predefined datasets as well as in real-time will be covered. For robotic facial expression generation, hand-coded and automated methods i.e., facial expressions of a robot are generated by moving the features (eyes, mouth) of the robot by hand-coding or automatically using machine learning techniques, will also be covered. There are already plenty of studies that achieve high accuracy for emotion expression recognition on predefined datasets, but the accuracy for facial expression recognition in real-time is comparatively lower. In the case of expression generation in robots, while most of the robots are capable of making basic facial expressions, there are not many studies that enable robots to do so automatically. In this overview, state-of-the-art research in facial emotion expressions during human-robot interaction has been discussed leading to several possible directions for future research

How does technology readiness affect the transfer of innovation between the professional domain and the private domain? A longitudinal study

Many researchers have studied innovation in terms of either employee innovation or user innovation, but much less is known about the transfer of innovative behavior between the professional and private domains. This quantitative empirical study investigates the relationship between the development of innovations by user innovators in the private domain and the transfer of the innovation to the professional domain and vice versa. Focusing on technology readiness as a moderator on the relationship between the transfer of innovation and innovative behavior in the other domain, we address the importance of digitization for innovations. The study is relied on the spillover theory and conducted as a longitudinal online survey consists of three consecutive waves over a period of four months. The result of the study demonstrates that employee innovation in the professional domain has an impact on innovative behavior in the private domain and, in reverse causality, user innovation in the private domain has an impact on innovative behavior in the professional domain. The relationship between these spillover effects and innovative behavior is strengthened by the technology readiness of innovators

Implications from Responsible Human-Robot Interaction with Anthropomorphic Service Robots for Design Science

Accelerated by the COVID-19 pandemic, anthropomorphic service robots are continuously penetrating various domains of our daily lives. With this development, the urge for an interdisciplinary approach to responsibly design human-robot interaction (HRI), with particular attention to human dignity, privacy, compliance, and transparency, increases. This paper contributes to design science, in developing a new artifact, i.e., an interdisciplinary framework for designing responsible HRI with anthropomorphic service robots, which covers the three design science research cycles. Furthermore, we propose a multi-method approach by applying this interdisciplinary framework. Thereby, our finding offer implications for designing HRI in a responsible manner

Responsible Human-Robot Interaction with Anthropomorphic Service Robots: State of the Art of an Interdisciplinary Research Challenge

Anthropomorphic service robots are on the rise. The more capable they become and the more regular they are applied in real-world settings, the more critical becomes the responsible design of human-robot interaction (HRI) with special attention to human dignity, transparency, privacy, and robot compliance. In this paper we review the interdisciplinary state of the art relevant for the responsible design of HRI. Furthermore, directions for future research on the responsible design of HRI with anthropomorphic service robots are suggested