Acceptance Of Robots Research Articles

Do You Want Me?: Exploring Differences in Consumer Home Robot Preferences, Perceptions, and Purchase Intent

While research in human-robot interaction is beginning to focus on the acceptance of domestic robots, there is little research on the potential adoption of these agents. Technology adoption is a complex phenomenon requiring not only positive perceptions of technology but also its value, along with product desire strong enough to lead to desired adoption behavior. Adoption of innovations also occurs in phases, from early adopters to mainstream consumers, then laggards. While the characteristics of technology early adopters generally have been researched extensively, there is no previous work that seeks to validate some of these variables for domestic robots specifically, and which draws from HRI research to further amend them. In this work, we determine how various consumer and robot characteristics affect assessments of home robot liking, privacy concerns, and purchasing intent. We find that five main consumer characteristics are associated with robot early adopters, and that surprisingly, income has a negative correlation with purchasing intent, specifically for the companion robot. We further compare predicted product liking to purchasing intent, showing that although robot acceptance is reasonably high for those in the mainstream, purchasing intent is low. For all market segments, perceptions of high price accounted for about 20-30% of the variance in intended purchasing, intended use 6-7%, belief in performance as advertised 4-6%, and design 3%. While privacy concerns were not influential to purchasing intentions held by early adopters, they were to mainstream users and laggards.

Robot Transparency and Employees’ Acceptance: The Roles of Trust and Anthropomorphism

Robots are more and more widely used in work scenes, but few studies have discussed the influence of robots on front-line employees. This study aims to investigate whether the transparency and anthropomorphism of robots affect employees’ acceptance of robots and its influencing mechanism from the perspective of social identity. We test our hypotheses in two studies. Study 1 examined the main effect of robot transparency on employee’s acceptance and the mediating role of human–robot trust, while Study 2 further examined the main and mediating effects, as well as the moderating role of robot anthropomorphism. The findings revealed that that robot transparency positively affects employee’s acceptance, cognition-based trust mediates the relationship, and the mediating effect of affect-based trust is not significant. Robot anthropomorphism moderates the relationship between transparency and cognition-based trust, it also moderates the mediating effect of cognition-based trust between transparency and employee’s acceptance.

Robot Acceptance and Service Quality in Food Delivery: An Expanded TAM-based Study

This study aimed to identify determinants of customer acceptance regarding services provided by autonomous delivery robots. It proposes an integrative model that combines the technology acceptance model (TAM) with aspects of service quality (SQ), user satisfaction, and personal innovativeness. Therefore, this study’s unique approach lies in integrating multiple theoretical frameworks – SERVQUAL, TAM, and user satisfaction models – to provide a holistic understanding of the determinants of food delivery robot service (FDRS) acceptance, which has not been extensively explored in previous research. Analyzing data from 1181 actual users from the United States, the investigation employed structural equation modeling to find that SQ positively affects TAM determinants, which, in turn, influence user satisfaction. This study provided evidence that FDRS adoption is significantly influenced by SQ, which shapes user perceptions and societal attitudes toward FDRS. Furthermore, the results revealed that personal innovativeness not only directly influences user satisfaction but also moderates the relationship between perceived usefulness and user satisfaction.

Human–robot interactions and experiences of staff and service robots in aged care

The rise of robotics in aged care is transforming how older adults are cared for, addressing staff shortages and workload. Daily interactions with staff and residents highlight an urgent need to better understand and improve human–robot interactions. This study investigates how 34 staff interacted with 10 service robots in a regional Australian aged care facility over 5 years, focusing primarily on their experience with service robots that transported meals and laundry. Guided by the Almere model, the research employs a qualitative case study approach, drawing on observations, focus groups, and interviews with management, industry leaders, and frontline staff. Findings are categorised into Emotional Reactions, Human–Robot Interaction and Collaboration, Social License and Environmental Dynamics. Results indicate conditional acceptance of service robots with scepticism about the service robots’ reliability and practical utility. Our study highlights the importance of a supportive environment, robust infrastructure and adequate training for successful robotic adoption. It also argues for engaging diverse multi-tiered stakeholders in investigating, designing, and implementing robotics in aged care, emphasising the role of social behaviours and interactions for what we propose as functional social service robots.

AI-Enabled Service Continuance: Roles of Trust and Privacy Risk

ABSTRACT Despite extensive research on AI-enabled services, most studies have focused on behavioral and adoption intentions, often overlooking factors influencing continued usage. The post-adoption behavior of AI-enabled services remains underexplored. This study addresses this gap by developing and validating a comprehensive model that integrates parasocial relationship theory, trust-commitment theory, and key constructs from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the Service Robot Acceptance Model (sRAM). Data from 356 users in Oman, a developing country, provide insights into AI-enabled service acceptance in daily life. The findings reveal that performance expectancy, hedonic motivation, and social influence positively impact engagement and continuance intentions, with perceived accuracy and innovativeness also playing significant roles. Additionally, the study establishes the moderating effect of perceived privacy risk on several hypotheses, thereby advancing the understanding of AI service continuance.

The acceptance of robots in the orthopedic joint replacement operating room.

Robotic surgery has seen substantial growth over the years and continues to show promise, with recent implementation into orthopedic surgery. There is limited literature available on patient attitudes and comfort level with robotic compared with conventional surgery. We aimed to develop an understanding of patient views on robot-assisted knee replacement to help the development of patient education materials and facilitate successful implementation. A qualitative, descriptive methodology was used. Included participants were those who had undergone total knee replacement in the last 5 years. Participants completed an online semistructured interview assessing their past experiences and their fears and assumptions about robotic surgery. An inductive thematic analysis was completed to organize and present the major themes. Four overarching themes described the areas patients focused on: advancements in surgery, perception of robotic surgery and surgeons, reliability, and patient education materials. Major subthemes included the proven reliability of robots, safety fears, and efficacy. Some participants' fear centred around robot autonomy. Greater comfort with the use of robots would occur if patients were given information about the role of the robot before surgery. Patient education materials can help alleviate fears and prevent misperceptions about robot-assisted knee replacement. Materials should include themes of surgical advancements and how surgeons interact with these advancements, level of robot autonomy, and the reliability and safety of the robot.

How do older adults react to social robots’ offspring-like voices

Social robots are being developed as a technological solution to alleviate older adults' loneliness due to separation from their offspring. This study explores how and why offspring-like voices affect older adults' acceptance of social robots from an auditory perspective, which differ from the visual aspects of human–robot interactions. Three scenario-based studies are conducted among a large number of cognitively intact older adults. Our findings reveal a positive correlation between the offspring-like voices of social robots and older adults’ acceptance of the robots. Further, social identity served as a psychological mechanism mediating the effect of offspring-like voices on the acceptance of older adults, whereas spatial distance acted as a positive moderator of these direct and indirect effects. Notably, older adults were more willing to accept social robots with grandchildren-like voices. These insights offer theoretical contributions to the literature on social identity theory and the similarity attraction paradigm, as well as practical implications for social robot design and development, thereby contributing to the evolving landscape of human–robot interaction acceptance.

EXPLORING KEY DRIVERS OF FRONTLINE SERVICE ROBOT ACCEPTANCE IN THAI RETAIL SERVICE CONTEXT: A QUALITATIVE STUDY

This qualitative study explores the factors associated to the acceptance of frontline service robots (FSRs) in the context of retail services in Thailand. In-depth interviews were conducted with a sample of 30 participants who had direct experience with FSRs. The data was analyzed using thematic analysis. The findings revealed five key elements associated with the acceptance of FSRs: individual heterogeneity factors, functional elements, social-emotional elements, psychological comfort elements, and value elements. The research findings revealed five key elements associated with the acceptance of FSR: 1) Individual heterogeneity factors, which refers to the perception of an individual's technological capability; 2) Functional elements, which includes the efficiency of service delivery and command reception of the FSR; 3) Social-emotional elements, which involves the facial expressions and tone of voice of the FSR; 4) Psychological comfort elements, which positive feelings of mental ease and reliability; and 5) Value elements, which pertains to the perceived value in the service delivery provided by the FSR. The study indicated that individuals who chose to interact with FSRs exhibited high self-efficacy, low technology anxiety, and a high level of customer innovativeness. Additionally, it was found that functional attributes, such as providing quick and accurate services, along with social and emotional aspects, including facial expressions and polite manners, were related to perceived utilitarian value, hedonic value, and psychological comfort, all of which associated the acceptance of FSRs.

Service robot acceptance: agenda for tourism and hospitality research

Purpose This study aims to provide insights and guidance for future research on service robot acceptance in the tourism and hospitality (T&H) domain through a comprehensive literature review. Design/methodology/approach A total of 249 journal articles, retrieved from the Scopus and Web of Science databases, were reviewed using an inductive analysis method. Findings Since its emergence in 2008, the topic of robot acceptance has gained significant attention, especially after 2019. The research assesses the current state of research, methodologies used, theoretical foundations and antecedents influencing acceptance. Five categories of antecedents affecting acceptance were systematically identified: robot design factors, individual/organisational factors, situational factors, appraisal factors and affective factors. Originality/value This study provides a comprehensive overview of the current landscape of service robot acceptance research. It offers insights and theoretical directions to advance research in the T&H domain.

Patient acceptance of medical service robots in the medical intelligence era: an empirical study based on an extended AI device use acceptance model

In the era of medical intelligence, there are still few studies focusing on medical service robots from a user experience perspective. Guided by the model of artificial intelligence (AI) device use acceptance (AIDUA), this article develops a theoretical model to explain patients’ intention to use medical service robots at hospitals. The proposed model specifically distinguished the dimensions of anthropomorphic attributes of service robots and further introduces two variables, perceived empathy and interaction experience, as a way to construct a three-stage psychological mechanism for patient acceptance of robots. 400 questionnaires from Chinese patients were collected offline and analyzed using structural equation modeling (SEM). The results revealed that the four attributes of anthropomorphism play a differential influence in performance expectations and effort expectations, but all positively contribute to empathy, which in turn positively affects interaction quality. Interaction quality, performance expectations, and effort expectations all influence patients’ emotions, thus having an impact on patients’ intentions to accept service robots. The findings from this study will assist the healthcare sector in upgrading medical service robots, which will improve patient acceptance of these robots.

Teleoperated Communication Robot: A Law Enforcement Perspective

The goal of this paper is to investigate the use of communication robots as tools to increase the safety of first responders (specifically, law enforcement officers) during social interactions or first-response situations. This paper functions as the first stage of our investigation into communication robots for use by first responders. The law enforcement officers (LEOs) in our study were provided with a mobile communication robot to determine if such robots could be of use in the public domain for the benefit of both civilians and LEOs. As part of our study, LEOs participated in training sessions where they worked with non-weaponized teleoperated communication robots and completed pretest-posttest surveys. The surveys captured LEOs’ perceptions and attitudes towards the robot and examined the impact of robot design features on LEOs’ acceptance of the communication robot. This paper discusses the significance and potential use of communication robots as tools in the future of law enforcement. Our future works include conducting additional studies involving affected stakeholders (e.g., citizen communities) and assessing/mitigating any potential negative impact of communication robots.

Augmenting Consumer Acceptance of Robot-Assisted Technologies in Retail Industry: An Interdisciplinary Approach

Since they have been incorporated into retail, robots have been discussed more frequently in academic publications and public debate. Customers in retail sector, as well as workers will be resistant to the rising employment of robots as their capabilities increase and they are employed to supplement or replace human labour. "Interdisciplinary" denotes a technique that amalgamates knowledge and methodologies from several academic or professional domains to attain a thorough comprehension of a particular subject or matter. As robots and AI become more common in society, this study examines the public's attitudes towards their use in retail. Consumer perceptions of retail robots are examined using consumer psychology and technology attitudes literature. To fill the research gap, 393 retailers' responses on service robot deployment in retail contexts are analyzed, with an emphasis on the East region. Service robot attitudes vary based on aspects such as robot benefits, social skills, and technology attitudes. Cluster analysis divides respondents into "high techies" and "high touches," depending on their service robot acceptance. The regression study clarifies how numerous factors affect retail robot-assisted service perceptions. Retailers and policymakers can learn from the survey that consumer opinion is significant for the future integration of robots in retail.

6-DOFs Robot Placement Based on the Multi-Criteria Procedure for Industrial Applications

Robot acceptance is rapidly increasing in many different industrial applications. The advancement of production systems and machines requires addressing the productivity complexity and flexibility of current manufacturing processes in quasi-real time. Nowadays, robot placement is still achieved via industrial practices based on the expertise of the workers and technicians, with the adoption of offline expensive software that demands time-consuming simulations, detailed time-and-motion mapping activities, and high competencies. Current challenges have been addressed mainly via path planning or robot-to-workpiece location optimization. Numerous solutions, from analytical to physical-based and data-driven formulation, have been discussed in the literature to solve these challenges. In this context, the machine learning approach has proven its superior performance. Nevertheless, the industrial environment is complex to model, generating extra training effort and making the learning procedure, in some cases, inefficient. The industrial problems concern workstation productivity; path-constrained minimal-time motions, considering the actuator’s torque limits; followed by robot vibration and the reduction in its accuracy and lifetime. This paper presents a procedure to find the robot base location for a prescribed task within the robot’s workspace, complying with multiple criteria. The proposed hybrid procedure includes analytical, physical-based, and data-driven modeling to solve the optimization problem. The contribution of the algorithm, for a given user-defined task, is the search for the best robot base location that enables the target points, maximizing the manipulability, avoiding singularities, and minimizing energy consumption. Firstly, the established method was verified using an anthropomorphic robot that considers different levels of a priori kinematics and system dynamics knowledge. The feasibility of the proposed method was evaluated through various simulations for small- and medium-sized robots. Then, a commercial offline program was compared, considering three scenarios and fourteen robots demonstrating an energy reduction in the 7.6–13.2% range. Moreover, the unknown joint dependency in real robot applications was investigated. From 11 robot positions for each active joint, a direct kinematic was appraised with an automatic DH scheme that generates the 3D workspace with an RMSE lower than 65.0 µm. Then, the inverse kinematic was computed using an ANN technique tuned with a genetic algorithm showing an RMSE in an S-shape task close to 702.0 µm. Finally, three experimental campaigns were performed with a set of tasks, repetitions, end-effector velocity, and payloads. The energy consumption reduction was observed in the 12.7–22.9% range. Consequently, the proposed procedure supports the reduction in workstation setup time and energy saving during industrial operations.

Explanation of time perspectives in adopting AI service robots under different service settings

This study bridges a gap in AI acceptance literature by integrating Time Perspective Theory with the Technology Acceptance Model by examining how time orientations influence AI acceptance in various service settings. The results show that past-positive, present-hedonistic, and future time perspectives impact individuals' privacy concerns and their recognition of AI's utilitarian and hedonic benefits. Conversely, past-negative and present-fatalistic perspectives show negligible effects. The study highlights distinct patterns in credence versus experience services, with future-oriented and present-hedonistic individuals favoring AI's benefits in hospitals over restaurants, and past-positive individuals valuing hedonic benefits more in restaurant settings. These orientations affect perceived usefulness and ease of use, with privacy concerns significantly influencing ease of use. The findings offer significant theoretical and practical implications, underscoring the nuanced role of time perspectives in AI service robot acceptance across different environments.

Influence of robot anthropomorphism on consumer attitudes toward restaurants and service providers

We conducted this study to investigate the influence of robot anthropomorphism on consumers’ attitudes toward restaurants and service providers, focusing on the moderating effects of robot social roles and consumer autonomy. The results of Study 1 revealed that anthropomorphic robots fostered more positive attitudes toward restaurants and service robots than non-anthropomorphic robots when consumers viewed restaurant advertisements. The results of Study 2 revealed that consumers also exhibited more positive attitudes toward anthropomorphic robots compared to non-anthropomorphic robots when picturing restaurant dining experiences. Furthermore, when non-anthropomorphic robots were assigned partner roles and consumers were given the option to choose their servers, attitudes toward these robots improved. Collectively, these findings suggest that anthropomorphism in robots can lead to more positive attitudes, and the acceptance of non-anthropomorphic robots can be enhanced through greater consumer autonomy and the assignment of partner roles. These results provide insight into AI service marketing strategies.

Human-Robot Intimacy: Acceptance of Robots as Intimate Companions.

Depictions of robots as romantic partners for humans are frequent in popular culture. As robots become part of human society, they will gradually assume the role of partners for humans whenever necessary, as assistants, collaborators, or companions. Companion robots are supposed to provide social contact to those who would not have it otherwise. These companion robots are usually not designed to fulfill one of the most important human needs: the one for romantic and intimate contact. Human-robot intimacy remains a vastly unexplored territory. In this article, we review the state-of-the-art research in intimate robotics. We discuss major issues limiting the acceptance of robots as intimate partners, the public perception of robots in intimate roles, and the possible influence of cross-cultural differences in these domains. We also discuss the possible negative effects human-robot intimacy may have on human-human contact. Most importantly, we propose a new term "intimate companion robots" to reduce the negative connotations of the other terms that have been used so far and improve the social perception of research in this domain. With this article, we provide an outlook on prospects for the development of intimate companion robots, considering the specific context of their use.

Consumer acceptance of social robots in domestic settings: A human-robot interaction perspective

Consumer acceptance of social robots in retail and service settings is an emerging field in marketing research. Social Home Robots (e.g., Jibo, Cozmo, and Kuri) serving various groups in domestic settings show significant retail and consumer service potential. However, most current research focuses on social robots that serve older or disabled individuals in domestic settings, leaving a gap in understanding consumer acceptance of Social Home Robots, particularly across different cultures. From the Human-Robot Interaction perspective, this article examines consumers' intentions to use Social Home Robots through a sequential mixed-method approach. Our findings indicate that consumers' intentions to use these robots are primarily influenced by key factors in Human-Robot Interaction: belief in social robot benefits, concern about privacy risks, trust, the robots' overall anthropomorphic design, and consumers' self-construal tendency. Furthermore, trust mediates the relationships between belief in social support, privacy concerns, independent self-construal, and usage intention. This study explores consumer acceptance of social robots serving diverse groups rather than special groups in domestic settings, contributing to the literature on social/service robots. It also offers business guidelines for designing and marketing Social Home Robots in retail.

Students’ Perceptions of Workplace Robots in the Republic of Serbia

Research Question: The key research question is what the key positive and negative perceptions of students from the Republic of Serbia regarding workplace robots are. Motivation: Academics, practitioners, and decision-makers are more and more interested in the impact of new technological solutions in the field of robotics on organizations and their functioning. Ongoing technological advancements have accelerated the adoption and use of robots in the workplace. As a result, organizations that plan to introduce robots should consider all effects on employees, both positive and negative. Idea: The main idea is to examine and analyse the perceptions and attitudes of students from the Republic of Serbia regarding robots at the workplace. The results of this study regarding students' perceptions and attitudes towards robots in the workplace are crucial for the future of work and job design. Data: Data were collected via online questionnaire consisting of five profile questions and 13 statements organized in two five-point Likert scales. From January to March 2023, the questionnaire was completed by 164 students from the Republic of Serbia. Tools: The collected answers were analysed using the Statistical Package for Social Sciences – SPSS, version 21.0. (Armonk, NY: IBM Corporation). The Cronbach's Alpha coefficient, Kolmogorov-Smirnov test, descriptive statistics, student t-test and one-way ANOVA test was used for data analysis. Findings: Research results showed that most respondents believe that robots can do dangerous jobs that humans cannot, that robots can free humans from routine and monotonous jobs, and that humans will have more time for creative tasks. Robots in the workplace, on the other hand, will have some negative consequences. Many respondents agree that working with robots without people would make them feel lonely; robots would not know how to react in some unexpected circumstances; and they are not as flexible and mobile as humans. Contribution: The findings of this study could make a significant contribution to a better understanding of students’ attitudes towards robots in the workplace and they may help decision makers, employers, leaders, and managers on how to increase workplace acceptance of robots.

What Will the Delivery Robots Bring Us Tomorrow?

ABSTRACTAutonomous delivery robots offer a promising solution to the challenges of last mile logistics, a crucial topic in times of increasing logistics volume, environmental concern, and ongoing urbanization. This study investigates the acceptance of such robots in various application scenarios for last mile delivery in Germany. A first, quantitative, study investigating the overall acceptance of autonomous delivery robots for the primary predominant usage scenarios of meal and package delivery tested an adapted technology acceptance model via a structural equation model. A second, qualitative, study was conducted to better understand possible future use cases for these robots included semistandardized interviews with 14 individuals and employed a qualitative content structuring analysis method for data analysis. The results of Study 1 confirm that performance expectancy and effort expectancy influence the acceptance of delivery robots, with performance expectancy and behavioral intention being significantly higher for the package than for meal deliveries. However, in both cases, the average intention to use these robots only slightly exceeded the scale mean. Study 2 reveals that autonomous delivery robots are perceived as more convenient than existing alternatives in grocery and pharmaceutical delivery and return processing. The further application of emergency situations, such as illness or the risk of infection, also emerged from the data; even respondents who generally reject the idea of such robots would still use them in such exceptional situations. These results should be considered in the further development of autonomous delivery robot systems.

Towards smooth mobile robot deployments in dynamic human environments

AbstractRecently, there has been great interest in deploying autonomous mobile robots in airports, malls, and hospitals to complete a range of tasks such as delivery, cleaning, and patrolling. The rich context of these environments gives rise to highly unstructured motion that is challenging for robots to anticipate and adapt to. This results in uncomfortable and unsafe human–robot encounters, poor robot performance, and even catastrophic failures that hinder robot acceptance. Such observations have motivated my work on social robot navigation, the problem of enabling robots to navigate in human environments while accounting for human safety and comfort. In this article, I highlight prior work on expanding the classical autonomy stack with mathematical models and algorithms designed to contribute towards smoother mobile robot deployments in complex environments.