Technological breakthroughs, combined with the demographic challenges of an aging population and the aftermath of the COVID-19 pandemic, spur new business opportunities in the service robot industry. From a management perspective, these technologies are positively evaluated in terms of increasing productivity, new business opportunities, and financial benefits (Belanche et al., 2020). However, although automation and robotics have already gained attention in the tourism and hospitality industry, research on their use in restaurants and the customer's attitude toward these new service solutions is still limited (Berezina et al., 2019; Ivanov et al., 2019; Kuo et al., 2017).

In the hospitality and tourism sectors, service robots have become increasingly adopted by companies to facilitate frontline service to reduce human labor, improve efficiency and provide better customer experience. In addition, the COVID-19 pandemic has intensified consumers’ demand for service robots to reduce human contact. To better understand the impact of service robots in the service sector, researchers have been examining user behavior of different technologies. While prior empirical studies have mainly focused on utilitarian-based acceptance models, other perspectives, such as the interpersonal relations, have been largely overlooked. With the ubiquitous of social media, people become connected but alone, leading to negative effects on interpersonal relations.

The proliferation of service robots has led to a growing concern about the impact of these technological advancements on privacy. Despite the development, quantitative research on the influence mechanism of privacy concerns on service robot adoption intentions is still limited. This research explores the influencing mechanism and boundary conditions of the interaction effect between customer privacy concerns and service type on customers’ service robot adoption intentions.

An increasing number of companies are using service robots, such as physical robots and virtual chatbots, to interact with their customers. Service robots are autonomous agents with the purpose of providing services to customers by performing a variety of physical and nonphysical tasks (Joerling et al., 2019). Conceptual work has suggested that social robots will increasingly be used in the front line of service encounters (Gonzalez-Jimenez, 2018; Van Doorn et al., 2017). Real examples of the inclusion of these robots in retail settings already exist. For instance, some retailers use Softbank´s robot Pepper to greet and inform customers. Social robots such as Pepper can use their sensors and cameras to interpret customer reactions and adapt accordingly. Moreover, the robot can even make product recommendations based on the assessed customer´s mood, age, gender and, if available, purchase history (McKenna, 2018). Not surprisingly, there is a vast market potential associated with these robots, which is expected to grow to 87 billion by 2025 (BCG, 2017).

The rapid development of artificial intelligence technology has accelerated the promotion and application of service robot in the market. Although technology has provided service robot with increasingly autonomous functions, more research is needed on how service robot with different levels of autonomy affects customer satisfaction in the hospitality industry. Guided by affordance theory, the study examines whether service robot operational and decisional autonomy would have effects on customer satisfaction and explored explanatory mechanism. Adopting an experimental vignette method (EVM), the study reveals that direct effect of service robot operational autonomy and indirect effect of decisional autonomy on customer satisfaction, and functional affordance played a positive mediating role in the impact of service robot autonomy on customer satisfaction. This research extends and enriches the relevant literature on human-machine interaction and customer satisfaction research. Further, the study also provides marketing insights for enterprises to improve autonomous robot design and enhance customer relationships.

The costs associated with law enforcement have seen a sharp increase, driven by rising personnel costs and the growing demand for policing services (Gascón, 2010; Urban Institute, 2020). Considerable discussion has arisen about how science can potentially help law enforcement “do more with less”, and some scholars have suggested introducing new crime control technologies to address this problem (e.g., Roach, 2022; Weisburd & Neyroud, 2011). With the onset of the COVID-19 pandemic, police departments around the world had additional demand, as they were made responsible for overseeing and ensuring compliance with COVID protocols. As a response, some countries (e.g., Singapore and China; Barrett, 2021) resorted to employing service robots either alongside or in place of police officers to assist with COVID-related compliance tasks.

The use of artificial intelligence (AI) service robots is on the rise. With service frontlines gradually shifting to human–robot interactions, the question of whether AI robots should be humanlike or machinelike has emerged. While many firms use robots that resemble humans in their appearance and actions, others use machinelike robots, assuming that very humanlike robots may lead to uncanny valley effects. There is no consensus on whether the anthropomorphism of service robots facilitates or constrains consumers’ experiences. To fill this gap, this article examines when and how service companies should use anthropomorphic AI service robots.

This study attempts to analyze the economic impact of the service robot industry using Input-Output analysis, which is conducted based on Demand-driven model, the Leontief price model, the Backward and Forward Linkage Effects, and the Exogenous Methods. In a Demand-driven model analysis, we can conclude that the service robot industry contains characteristics of both the manufacturing industry and the service industry, which causes a positive impact on the overall industry by compensating for the weaknesses of the two industries. The Leontief price analysis indicates when wages in the service robot industry increase, prices related to robot manufacturing also increase. Also, when profits in the service robot industry increase, prices related to service provision increase, too. The Backward and Forward Linkage Effects analysis shows that the service robot industry is highly sensitive to the current economic condition and has a great influence on the service industry. The service robot industry can highlight the aspect of service characteristics when the manufacturing industry is in recession and vice versa. In addition, the service robot industry can be regarded as a value-adding and domestic economy promoting industry which utilizes knowledge of information and communication technologies. It is important to foster the service robot industry in South Korea, which is in economic recession to provide an opportunity to stimulate the growth of both service and robot industries.

The experimental study investigates whether customers perceive a service robot as apparently more deep acting than surface acting and whether these perceptions differ for interactions with human service employees and humanoid service robots. Moreover, the role of gender within these service interactions is examined.

Prior social robotics research has shown that robot design influences if people perceive a robot as friendly, trustworthy, or safe (Castro-Gonzalez et al., 2016; Rosenthal-Von Der Pütten & Krämer, 2014). Meanwhile, recent conceptual work has suggested that social robots will increasingly be used in the front line of service encounters (Gonzalez-Jimenez, 2018; Van doorn et al., 2017). According to The International Journal of Social Robotics social robots are robots that can communicate and interact with humans, among themselves, and with the environment, within the cultural and social structure assigned to its role. Real examples of the inclusion of these robots in retail settings already exist. For instance, some retailers use Softbank´s robot Pepper to greet and inform customers. Social robots such as Pepper can use their sensors and cameras to interpret customer reactions and adapt accordingly. Moreover, the robot can even make product recommendations based on the assessed customer´s mood, age, gender and, if available, purchase history (McKenna, 2018). Not surprisingly, there is a vast market potential associated with these robots, which is expected to grow to 87 billion by 2025 (BCG, 2017).

첨단 기술, 네트워크 등의 발전과 지능기반 사회의 변화로 인 간형 로봇 개발이 활발하게 진행 중에 있다. 특히 일상생활에 서 인간과 자연스럽게 상호 작용할 수 있는 인간 지향적인 개 인서비스 로봇에 대한 연구가 중요해지고 있다. 하지만 국내의 개인서비스 로봇 연구를 살펴보면 기반기술 개발에 치중한 정 부의 지원과 연구로 인간이 진정으로 원하는 로봇의 기능이나 형태 등의 로봇 디자인에 대한 연구가 미흡한 실정이다. 이에 본 연구는 개인서비스 로봇 디자인 방향을 제시하는 것을 목적 으로 하며, 이를 위해서 로봇의 시장 요구사항 분석, 로봇 시장 트렌드 분석, 소비자 인식 및 요구 분석을 진행하였다. 그 결과 개인서비스 로봇이 인간의 일상생활에서 활용 가능한 기능 디 자인과 감성 디자인을 중심으로 개인서비스 로봇의 디자인을 위한 방향을 제시하였다. 이러한 결과를 통해서 본 연구는 개 인서비스 로봇의 콘셉트, 기능, 콘텐츠, 외형 등을 디자인하거 나 새로운 아이디어를 제안하는데 기여할 수 있을 것이다.

현재 진행되고 있는 대부분의 로봇 연구는 특정한 목적을 수행함에 있어서 기능적으로 안정적이고 원활한 움직임을 보이는 것과 더불어 사용자가 원하는 정보를 적절하게 전달하는 것에 초점을 맞춰 진행하고 있다. 본 논문에서는 로봇의 작업수행 상태가 아닌 외부로부터 입력 값이 없는 대기상태의 행동패턴을 제시하여 보다 자연스러운 인간-로봇 상호작용을 제시하고자 하였다. 로봇의 대기상태 행동패턴을 디자인함에 있어서 비디오 판독 방법을 선택하였고, 실제 서비스업에 종사하는 10명의 사람들을 비디오로 녹화하여 사람들과 상호작용이 없는 대기상태의 반복적인 행동패턴을 관찰하였다. 각각의 비디오 데이터로부터 총 21개의 반복적 행동을 기록하였고, 비슷한 항목들을 통합하여 최종적으로 11개의 행동패턴을 추출하였다. 추출된 패턴들 가운데 6개의 대표적인 행동들을 EEEX라는 로봇에 적합하도록 인코딩 작업을 하였고, 이것들이 사람들에게 올바르게 인식되는지를 확인하기 위하여 검증실험을 수행하였다. 사람들은 대부분의 로봇 행동패턴을 실험에서 의도한 바와 같이 인식하였으나 로봇의 하드웨어 특성상 몸과 팔의 움직임에서 약간의 혼동 요소가 있었다. 추후 실험을 통해 EEEX를 대형 마트의 입구에 실제로 배치하여 대기 중에 중립행동을 보일 때와 보이지 않을 때의 손님의 관심도 차이를 조사해보고자 한다.

정보통신기술의 발달과 함께 학습자에게 재미와 흥미를 통한 즐거운 교육환경을 제공하고자 다양한 방법이 시도 되고 있다. 에듀테인먼트와 게임기반학습 등에서 게임이나 로봇과 같은 기술을 교육에 활용하는 것은 좋은 예이다. 본 연구에서는 휴머노이드 로봇의 율동 생성을 위한 사용자 데이터 수집과 분석을 통한 지능형 율동 교육 시스템을 제안한다. 이를 위하여 사용자는 음악을 선택하고, 선택한 음악에 따라 율동 정보를 입력한다. 이러한 사용자의 로봇 활용 데이터는 분석을 통하여 지능화된 서비스를 위한 패턴의 역할을 한다. 분석 결과는 빈도에 기반을 두며, 과거 정보가 부족한 경우 FFT 유사도 비교 방법을 적용하였다. 제안하는 방법은 유치원 아이들을 대상으로 하는 실험을 통하여 유효함을 확인하였다.

In a large scale robot system, one of important problems is software integration, which involves three elements: modularity, reusability and stability. By these issues, the degree of convenience of system integration, its required time and the performance of the system stability can be determined. In addition, the convenience of system management can be determined by the degree of completion of service components. This paper explains the template based service component (TBSC) for the integration of service components in networked robot. The important characteristics of TBSC are automatical execution and recovery process by a PnP supporting robot framework, which helps a system operator to manage a robot system comfortably. For easy implementation and system stability, we provide a service component creator and a verification tool to developers.

This paper describe the riding robot system named by "RideBot" which is a riding robot like as a horse. In order to simulate the riding motions, we develope the saddle mechanism which can generate 3 DOF motions including pitch, roll, and bounce movement, and also we controlled the riding motions and the intention of horseman. To generate the riding motions with the bodily sensation, we developed Novel Washout Filter and the algorithms for motion control. And also, we developed some health care service for the health care of horseman. A body state index was proposed that evaluates the personal health state from both the measured physiological variables and the surveyed questions. The physiological variables such as weight, blood pressure, heart rate variability (HRV), accelerated state photoplethysmograph(APG), body fat, and happiness index were measured by the specially designed bio-handle system and survey questions. The efficiency of the proposed ride robot is evaluated in the experiments.

As expanding of service robots into the human life, the needs of robots are increased. The experts group forecasted that the robot market would grow rapidly in a short time, robot companies should compete with others for prior occupation in a market. In this research, we proposed a framework of robot identity design based on building methods of product identity and developed a case study. Identity is one of the strategies to distinguish from competitors through managing image united. It is possible to apply this identity approach on robot area, which was used for making image of companies, brands, and products. In general, identity has visual, invisual features, which can be classified into three elements; Robot Philosophy, Functional Affordance, Family Look. Robot philosophy means the vision or philosophy of a company through robot development, functional affordance is a character or role to serve and family look includes visual design elements like as shape, color, material, graphic, behavior etc. We suggest that this guide will be applied to build identity of following series of a model, models of same service group and all models of a company or commercial space.

Emotion interaction between human and robot is an important element for natural interaction especially for service robot. We propose a hybrid emotion generation architecture and detailed design of reactive process in the architecture based on insight about human emotion system. Reactive emotion generation is to increase task performance and believability of the service robot. Experiment result shows that it seems possible for the reactive process to function for those purposes, and reciprocal interaction between different layers is important for proper functioning of robot’s emotion generation system.

지능형 서비스 로봇은 인공지능 및 센서인터페이스 등의 다양한 기능과 IT기술의 접목으로 우리의 생활을 윤택하게 해줄 수 있는 인간 지향적인 성격으로 발전하고 있다. 또한 많은 분야에서 새로운 서비스 개발을 통해서 좀더 인간의 생활에 가까이 접근되어 지고 있다. 한편 국내 초등학교에서 초등교사는 학생 수의 과다로 능동적이기 보다는 수동적인 수업을 하고 있어서 학습 효율성이나 능률성이 떨어지고 있다. 이에 본 연구에서는 발전하고 있는 서비스 로봇 기술로 능