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This paper investigates the reasons for the differences in customers' acceptance of service robots (CASR) in actual experience and credence service settings for the following two aspects: (1) different antecedents affecting CASR and (2) different customer perceptions of their own characteristics (role clarity and ability) and service robot characteristics (anthropomorphism and ability).

The data were collected using online surveys in an experience service setting (Hotel, N = 426) and a credence service setting (Hospital, N = 406). Differences in experience and credence service settings were examined using two statistical methods, namely, PLS-SEM to test the differences in antecedents affecting CASR and independent-samples t-tests to test the differences in customer perceptions of their own characteristics and service robot characteristics.

The results indicate that customers in an experience (vs credence) service setting have stronger positive attitudes toward and a greater intention to use service robots. Further, this paper finds there are two key reasons for the differences in CASR. The first is different antecedents. Perceived usefulness is positively influenced by the anthropomorphism of a service robot and customer ability in the experience service setting, but is influenced not in the credence service setting. Conversely, service robot autonomy positively relates to perceived ease of use in the credence service setting, but does not in the experience service setting. The second reason for CASR differences is different customer perceptions. Customers' ability and perceived ease of use are higher, while their perception of anthropomorphism of the service robot is lower in the experience (vs credence) service setting.

This study helps explain why there are differences in the CASR in different settings and presents two perspectives: (1) antecedents' affecting CASR and (2) customer perceptions of their own as well as service robot characteristics.

The robot has passed through a development period, and is now entering an era in which robots are being utilised by industry in production. In Japan, about 1500 robots are used on production lines and more than 50 robot makers are supplying their products to the market. Many users have completed trials with industrial robots, and have reached the situation in which repeat orders are being sent to robot manufacturers as a potential way of improving productivity. Many of the robot makers have completed the initial development of their products, and in future will be promoting their sales to reap the benefits of these developments.

This research empirically investigates how service employees' ratings of technology readiness (TRI), negative attitudes towards robots (NARS), Big Five personality traits (BFI) and emotional demands (ED) affect their willingness to work with service robots (WTW).

One set of data is collected from 410 service employees expected to work with service robots in Study 1. Another set of field data is collected from 102 employees working with service robots in Study 2. Hierarchical regression is used to test hypotheses about the impact of technology readiness, negative attitudes towards robots and Big Five personality traits on WTW. Additionally, the interactions of emotional demands in the workplace are analysed.

TRI-optimism and TRI-insecurity significantly affect WTW in Study 2 but are nonsignificant in Study 1. The impacts of NARS-emotions in interaction with robots and NARS-interaction with robots situations on WTW are significant in Study 1 but nonsignificant in Study 2. Moreover, BFI-neuroticism negatively affected WTW in Study 1, while these effects were nonsignificant in Study 2. Finally, emotional demands significantly interact with three of eleven dimensions of IVs in Study 1, but all interactions are nonsignificant in Study 2.

This research provides a guiding framework for service companies to screen employees expected to cowork with service robots, to enhance newly hired employees' WTW and to improve existing employees' WTW.

Integrating the characteristics of service employees, service robots and jobs into a theoretical framework, this research is the first to empirically examine the effects of service employees' several critical characteristics (technology readiness, negative attitudes towards robots and Big Five personality) on WTW and the moderation of job characteristics (emotional demands).

The purpose of this paper is to achieve the optimal system design of a four-wheel mobile robot on transmission line maintenance, as the authors know transmission line mobile robot is a kind of special robot which runs on high-voltage cable to replace or assist manual power maintenance operation. In the process of live working, the manipulator, working end effector and the working environment are located in the narrow space and with heterogeneous shapes, the robot collision-free obstacle avoidance movement is the premise to complete the operation task. In the simultaneous operation, the mechanical properties between the manipulator effector and the operation object are the key to improve the operation reliability. These put forward higher requirements for the mechanical configuration and dynamic characteristics of the robot, and this is the purpose of the manuscript.

Based on the above, aiming at the task of tightening the tension clamp for the four-split transmission lines, the paper proposed a four-wheel mobile robot mechanism configuration and its terminal tool which can adapt to the walking and operation on multi-split transmission lines. In the study, the dynamic models of the rigid robot and flexible transmission line are established, respectively, and the dynamic model of rigid-flexible coupling system is established on this basis, the working space and dynamic characteristics of the robot have been simulated in ADAMS and MATLAB.

The research results show that the mechanical configuration of this robot can complete the tightening operation of the four-split tension clamp bolts and the motion of robot each joint meets the requirements of driving torque in the operation process, which avoids the operation failure of the robot system caused by the insufficient or excessive driving force of the robot joint torque.

Finally, the engineering practicability of the mechanical configuration and dynamic model proposed in the paper has been verified by the physical prototype. The originality value of the research is that it has double important theoretical significance and practical application value for the optimization of mechanical structure parameters and electrical control parameters of transmission line mobile robots.

Collaboration between frontline employees (FLEs) and frontline robots (FLRs) is expected to play a vital role in service delivery in these increasingly disrupted times. Firms are facing the challenge of designing effective FLE-FLR collaborations to enhance customer experience. This paper develops a framework to explore the potential of FLE-FLR collaboration through the lens of interdependence in customer service experience and advances research that specifically focuses on employee-robot team development.

This paper uses a conceptual approach rooted in the interdependence theory, team design, management, robotics and automation literature.

This paper proposes and defines the Frontline employee – Frontline robot interdependence (FLERI) concept based on three structural components of an interdependent relationship – joint goal, joint workflow and joint decision-making authority. It also provides propositions that outline the potential impact of FLERI on customer experience and employee performance, and outline several boundary conditions that could enhance or inhibit those effects.

Managerial insights into designing an employee-robot team in service delivery are provided.

This study is the first to propose a novel conceptual framework (FLERI) that focuses on the notion of human-robot collaboration in service settings.

This review scopes evidence on the use of social robots for older adults with depressive symptoms, in the scenario of smart cities, analyzing the age-related depression specificities, investigated contexts and intervention protocols' features.

Studies retrieved from two major databases were selected against inclusion and exclusion criteria. Studies were included if used social robots, included older adults over 60, and reported depressive symptoms measurements, with any type of research design. Papers not published in English, published as an abstract or study protocol, or not peer-reviewed were excluded.

28 relevant studies were included, in which PARO was the most used robot. Most studies included very older adults with neurocognitive disorders living in long-term care facilities. The intervention protocols were heterogeneous regarding the duration, session duration and frequency. Only 35.6% of the studies had a control group. Finally, only 32.1% of the studies showed a significant improvement in depression symptoms.

Despite the potential for using social robots in mental health interventions, in the scenario of smart cities, this review showed that their usefulness and effects in improving depressive symptoms in older adults have low internal and external validity. Future studies should consider factors as planning the intervention based on well-established supported therapies, characteristics and needs of the subjects, and the context in which the subjects are inserted.

The abilities and limitations of today's industrial robots are reviewed and compared to similar human parameters. The robot abilities were determined from a survey of 282 current robot models. This discussion is held within the general framework of a skills analysis approach to robot task performance.

Service robots have increasingly been utilized in retail settings, yet empirical research on how frontline employees (FLEs) might deal with this new reality remains scarce. This mixed-methods study aims to examine how FLEs expect physical service robots to impact job characteristics and affect their job engagement and well-being.

First, explorative interviews (Study 1; N = 32) were conducted to investigate how FLEs currently experience job characteristics and how they believe robots might impact these job characteristics and job outcomes. Next, a survey (Study 2; N = 165) examined the relationship between job characteristics that retail FLEs expect to be impacted by robots and their own well-being and job engagement.

While the overall expectations for working with robots are mixed, retail FLEs expect that working with robots can alleviate certain job demands, but robots cannot help to replenish their job resources. On the contrary, most retail FLEs expect the pains and gains associated with robots in the workspace to cancel each other out, leaving their job engagement and well-being unaffected. However, of the FLEs that do anticipate that robots might have some impact on their well-being and job engagement, the majority expect negative effects.

This study is unique in addressing the trade-off between expected benefits and costs inherent to job demands-resources (JD-R) theory while incorporating a transformative service research (TSR) lens. By integrating different streams of research to study retail FLEs' expectations about working with robots and focusing on robots' impact on job engagement and well-being, this study offers new insights for theory and practice.

Due to dynamic model is the basis of realizing various robot control functions, and it determines the robot control performance to a large extent, this paper aims to improve the accuracy of dynamic model for n-Degree of Freedom (DOF) serial robot.

This paper exploits a combination of the link dynamical system and the friction model to create robot dynamic behaviors. A practical approach to identify the nonlinear joint friction parameters including the slip properties in sliding phase and the stick characteristics in presliding phase is presented. Afterward, an adaptive variable-step moving average method is proposed to effectively reduce the noise impact on the collected data. Furthermore, a radial basis function neural network-based friction estimator for varying loads is trained to compensate the nonlinear effects of load on friction during robot joint moving.

Experiment validations are carried out on all the joints of a 6-DOF industrial robot. The experimental results of joint torque estimation demonstrate that the proposed strategy significantly improves the accuracy of the robot dynamic model, and the prediction effect of the proposed method is better than that of existing methods.

The proposed method extends the robot dynamic model with friction compensation, which includes the nonlinear effects of joint stick motion, joint sliding motion and load attached to the end-effector.

Service robots are now an integral part of people's living and working environment, making service robots one of the hot topics for service researchers today. Against that background, the paper reviews the recent service robot literature following a Theory-Context-Characteristics-Methodology (TCCM) approach to capture the state of art of the field. In addition, building on qualitative input from researchers who are active in this field, the authors highlight where opportunities for further development and growth lie.

The paper identifies and analyzes 88 manuscripts (featuring 173 individual studies) published in academic journals featured on the SERVSIG literature alert. In addition, qualitative input gathered from 79 researchers who are active in the service field and doing research on service robots is infused throughout the manuscript.

The key research foci of the service robot literature to date include comparing service robots with humans, the role of service robots' look and feel, consumer attitudes toward service robots and the role of service robot conversational skills and behaviors. From a TCCM view, the authors discern dominant theories (anthropomorphism theory), contexts (retail/healthcare, USA samples, Business-to-Consumer (B2C) settings and customer focused), study characteristics (robot types: chatbots, not embodied and text/voice-based; outcome focus: customer intentions) and methodologies (experimental, picture-based scenarios).

The current paper is the first to analyze the service robot literature from a TCCM perspective. Doing so, the study gives (1) a comprehensive picture of the field to date and (2) highlights key pathways to inspire future work.