Personality factors and acceptability of socially assistive robotics in teachers with and without specialized training for children with disability

Personality factors can be predictors of acceptability and intention to use new technologies, especially regarding education and care fields in the whole lifespan. The aim of this study was to evaluate the predictive factors and attitudes of curricular and specialized teachers towards socially assistive robotics and the intention to use robots in teaching activities. In our research, we investigated the impact of the personality factors measured with the Big Five Questionnaire, on acceptability questionnaires derived by Eurobarometer and by the model Unified Theory of the Acceptance and Use of Technology (UTAUT), administered respectively before and after showing the possible uses of the robot NAO in education and teaching. The study was conducted in four schools, participants were 114 teachers (52.07 ± 8.22), aged 26 to 68 years, of the primary and middle school level. The results highlight the primary role of the personality factors Openness to Experience and Extraversion for promoting the acceptability and reduce the prejudicial reject regarding the use of educational and assistive robotic technologies. In conclusion, for using at best robotics in education, teachers need to receive appropriate training - also on the basis of their attitudes and personality traits - to learn how to plan their educational activities integrating the robotics tool

Using chatbots in e-retailing: how to mitigate perceived risk and enhance the flow experience

Purpose: Chatbots represent an undeniable player between online retailers and customers as they boost operational efficiency and bring cost savings to businesses while offering convenience for customers in terms of timing and immediacy. However, as chatbots represent a new-born online touchpoint in retailing, especially when it comes to online pre-purchase and purchase experience, this study examines whether and how effort expectation, facilitating condition, performance expectancy, social influence, trust, perceived risk and flow affect consumers' intention to use chatbots for online shopping. The purpose of this paper is to address this issue. Design/methodology/approach: A total of 226 respondents participated in an online survey. Participants were asked to try a new online service and interact with a chatbot designed using Chatfuel, a platform within the Facebook Messenger setting. Structural equation modelling was used to test the proposed research model regarding the intention to use chatbots. Findings: This study discusses the importance of offering useful and trustworthy conversational agents for online shopping and argues and explains the insignificant paths amongst other studied factors and intention to use chatbots concluding with the need to explore more drivers for such contemporary technologies. Moreover, the findings indicate that trust turns out to be an important predictor of behavioural intention towards chatbots, in addition to its role in mitigating perceived risk and enhancing flow experience. Originality/value: Given the lack of empirical evidence related to chatbots applied for business purposes, this paper fills a gap in this research field and provides a deeper understanding of what leverages consumers' intention to use chatbots for online shopping.Chatbots, E-Retailing, Flow, Social Influence, Trust, Perceived Riskinfo:eu-repo/semantics/acceptedVersio

A systematic review of attitudes, anxiety, acceptance, and trust towards social robots

As social robots become more common, there is a need to understand how people perceive and interact with such technology. This systematic review seeks to estimate people’s attitudes toward, trust in, anxiety associated with, and acceptance of social robots; as well as factors that are associated with these beliefs. Ninety-seven studies were identified with a combined sample of over 13,000 participants and a standardized score was computed for each in order to represent the valence (positive, negative, or neutral) and magnitude (on a scale from 1 to − 1) of people’s beliefs about robots. Potential moderating factors such as the robots’ domain of application and design, the type of exposure to the robot, and the characteristics of potential users were also investigated. The findings suggest that people generally have positive attitudes towards social robots and are willing to interact with them. This finding may challenge some of the existing doubt surrounding the adoption of robotics in social domains of application but more research is needed to fully understand the factors that influence attitudes

Supporting active and healthy aging with advanced robotics integrated in smart environment

The technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is the integration of service robotics for optimising social services and improving quality of life of the elderly population. This chapter aims to underline the barriers of the state of the art, furthermore the authors present their concrete experiences to overcome these barriers gained at the RoboTown Living Lab of Scuola Superiore Sant'Anna within past and current projects. They analyse and discuss the results in order to give recommendations based on their experiences. Furthermore, this work highlights the trend of development from stand-alone solutions to cloud computing architecture, describing the future research directions

iRobot : conceptualising SERVBOT for humanoid social robots

Services are intangible in nature and, as a result, it is often difficult to measure the quality of the service. The service is usually delivered by a human to a human customer and the service literature shows SERVQUAL can be used to measure the quality of the service. However, the use of social robots during the pandemic is speeding up the process of employing social roots in frontline service settings. An extensive review of the literature shows there is a lack of an empirical model to assess the perceived service quality provided by a social robot. Furthermore, the social robot literature highlights key differences between human service and social robots. For example, scholars have highlighted the importance of entertainment and engagement in the adoption of social robots in the service industry. However, it is unclear whether the SERVQUAL dimensions are appropriate to measure social robots’ service quality. This master’s project will conceptualise the SERVBOT model to assess a social robot’s service quality. It identifies reliability, responsiveness, assurance, empathy, and entertainment as the five dimensions of SERVBOT. Further, the research will investigate how these five factors influence emotional and social engagement and intention to use the social robot in a concierge service setting. To conduct the research, a 2 x 1 (CONTROL vs SERVBOT) x (Concierge) between-subject experiment was undertaken and a total of 232 responses were collected for both stages. The results indicate that entertainment has a positive influence on emotional engagement when service is delivered by a human concierge. Further, assurance had a positive influence on social engagement when a human concierge provided the service. When a social robot concierge delivered the service, empathy and entertainment both influenced emotional engagement, and assurance and entertainment impacted social engagement favourably. For both CONTROL (human concierge) and SERVBOT (social robot concierge), emotional and social engagement had a significant influence on intentions to use. This study is the first to propose the SERVBOT model to measure social robots’ service quality. The model provides a theoretical underpinning on the key service quality dimensions of a social robot and gives scholars and managers a method to track the service quality of a social robot. The study also extends the literature by exploring the key factors that influence the use of social robots (i.e., emotional and social engagement)

Accessibility requirements for human-robot interaction for socially assistive robots

Mención Internacional en el título de doctorPrograma de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: María Ángeles Malfaz Vázquez.- Secretario: Diego Martín de Andrés.- Vocal: Mike Wal

Human-Machine Communication: Complete Volume. Volume 6

his is the complete volume of HMC Volume 6

Mutual shaping in the design of socially assistive robots: A case study on social robots for therapy

This paper offers a case study in undertaking a mutual shaping approach to the design of socially assistive robots. We consider the use of social robots in therapy, and we present our results regarding this application, but the approach is generalisable. Our methodology combines elements of user-centered and participatory design with a focus on mutual learning. We present it in full alongside a more general guide for application to other areas. This approach led to valuable results concerning mutual shaping effects and societal factors regarding the use of such robots early in the design process. We also measured a significant shift in participant robot acceptance pre-/post-study, demonstrating that our approach led to the two-way sharing and shaping of knowledge, ideas and acceptance

A socially assistive robot for long-term cardiac rehabilitation in the real world

What are the benefits of using a socially assistive robot for long-term cardiac rehabilitation? To answer this question we designed and conducted a real-world long-term study, in collaboration with medical specialists, at the Fundacion Cardioinfantil-Instituto de Cardiologia clinic (Bogota, Colombia) lasting 2.5 years. The study took place within the context of the outpatient phase of patients' cardiac rehabilitation programme and aimed to compare the patients' progress and adherence in the conventional cardiac rehabilitation programme (control condition) against rehabilitation supported by a fully autonomous socially assistive robot which continuously monitored the patients during exercise to provide immediate feedback and motivation based on sensory measures (robot condition). The explicit aim of the social robot is to improve patient motivation and increase adherence to the programme to ensure a complete recovery. We recruited 15 patients per condition. The cardiac rehabilitation programme was designed to last 36 sessions (18 weeks) per patient. The findings suggest that robot increases adherence (by 13.3%) and leads to faster completion of the programme. In addition, the patients assisted by the robot had more rapid improvement in their recovery heart rate, better physical activity performance and a higher improvement in cardiovascular functioning, which indicate a successful cardiac rehabilitation programme performance. Moreover, the medical staff and the patients acknowledged that the robot improved the patient motivation and adherence to the programme, supporting its potential in addressing the major challenges in rehabilitation programmes

A Meta-Analysis of Human Personality and Robot Acceptance in Human-Robot Interaction

Human personality has been identified as a predictor of robot acceptance in the human robot interaction (HRI) literature. Despite this, the HRI literature has provided mixed support for this assertion. To better understand the relationship between human personality and robot acceptance, this paper conducts a meta-analysis of 26 studies. Results found a positive relationship between human personality and robot acceptance. However, this relationship varied greatly by the specific personality trait along with the study sample’s age, gender diversity, task, and global region. This meta-analysis also identified gaps in the literature. Namely, additional studies are needed that investigate both the big five personality traits and other personality traits, examine a more diverse age range, and utilize samples from previously unexamined regions of the globe.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/165339/1/Esterwood et al. 2021 (one column).pdfDescription of Esterwood et al. 2021 (one column).pdf : Preprint one column versionSEL