Search Results (19)

The end of the pandemic has been officially declared; however, the requirement to ensure hygienic living conditions in tourist accommodations remains a top priority for all hotel establishments and a prerequisite for every customer. Our systematic review studied the level of effectiveness of existing technological means and practices in order to limit COVID-19 infections and to protect customers from other factors aggravating their health, focusing on hotel restaurants. The PRISMA-S method was used. Database research (ABI/INFORM, ProQuest, Scopus EBSCO Business Source Premier, CBCA Business, Pubmed, and Embase) was undertaken between 6/2020 and 4/2024 with keywords comprising “hotels restaurants”, “health and safety”, “effectiveness/efficacy”, “primary analysis”, secondary analysis”, etc. In total, 1110 articles were initially identified, but eventually, 20 papers were selected comprising customer-level questionnaires, systematic reviews, and expert opinions/surveys. Different criteria were used for study assessment according to the type of study. So far, only a very limited number of studies have focused on the effectiveness of different health and safety measures in hotel restaurants. Even though the studies focusing on AI, robotics, and further technological means for enhancing customer satisfaction and the overall level of cleanliness are quite limited, the constant investment of hotels and restaurants in new technologies appears to be a one-way road. Full article

The experience economy of service robots in the restaurant industry was researched in the present study. The dimensions of the experience economy, which include esthetics, entertainment, education, and escapism, were assessed based on customer demographics. Additionally, this study explored how the four sub-dimensions of the experience economy affects word-of-mouth intentions. The study analyzed 292 surveys. Significant differences in the experience economy were found in terms of gender, education, and monthly income, according to the statistical results. Lastly, the results of the regression analysis revealed that the experience economy’s sub-dimensions have a positive effect on word-of-mouth intentions. This is the first study to examine the experience economy of robot services, and thus, it provides theoretical contributions and practical suggestions for the restaurant industry. Full article

To lessen the spread of COVID-19 and other dangerous bacteria and viruses, contactless distribution of different items has gained widespread popularity. In order to complete delivery tasks at a catering facility, this paper explores the development of an autonomous mobile robot. The robot, in particular, plans its path and maintains smooth and flexible mobility using a Time Elastic Band (TEB) motion control method and an upgraded Dijkstra algorithm. On the open-source AI platform of iFLYTEK, a voice recognition module was trained to recognize voice signals of different tones and loudness, and an image recognition capability was attained using YOLOv4 and SIFT. The UCAR intelligent vehicle platform, made available by iFLYTEK, served as the foundation for the development of the mobile robot system. The robot took part in China’s 16th National University Student Intelligent Car Race, an experimental demonstration test of the developed mobile robotics. The results of the experiments and task tests demonstrated that the proposed robot architecture was workable. In addition, we designed and put together a mobile robot utilizing components from the Taobao website. Compared to UCAR, this robot is less expensive and has the flexibility to be used in a variety of real-world settings. Full article

In this study, an automated tableware tidying-up robot system was developed to tidy up tableware in a self-service restaurant with a large amount of tableware. This study focused on sorting and collecting tableware placed on trays detected by an RGB-D camera. Leftover food was also treated with this robot system. The RGB-D camera efficiently detected the position and height of the tableware and whether there was leftover food or not by image processing. A parallel arm and robot hand mechanism was designed to realize the advantages of a low cost and high processing speed. Two types of rotation mechanisms were designed to realize the function of throwing away leftover food. The effectiveness of the camera detection system was verified through the experiments of tableware and leftover food detection. The effectiveness of the prototype robot and the rotation assist mechanism was verified through the experiments of grasping tableware, throwing away leftover food by two types of rotating mechanisms, collecting multiple tableware, and the sorting of overlapping tableware with multiple robots. Full article

Due to the workforce shortage caused by the declining birth rate and aging population, robotics is one of the solutions to replace humans and overcome this urgent problem. This paper introduces a deep learning-based object detection algorithm for empty-dish recycling robots to automatically recycle dishes in restaurants and canteens, etc. In detail, a lightweight object detection model YOLO-GD (Ghost Net and Depthwise convolution) is proposed for detecting dishes in images such as cups, chopsticks, bowls, towels, etc., and an image processing-based catch point calculation is designed for extracting the catch point coordinates of the different-type dishes. The coordinates are used to recycle the target dishes by controlling the robot arm. Jetson Nano is equipped on the robot as a computer module, and the YOLO-GD model is also quantized by TensorRT for improving the performance. The experimental results demonstrate that the YOLO-GD model is only 1/5 size of the state-of-the-art model YOLOv4, and the $mAP$ of YOLO-GD achieves 97.38%, 3.41% higher than YOLOv4. After quantization, the YOLO-GD model decreases the inference time per image from 207.92 ms to 32.75 ms, and the $mAP$ is 97.42%, which is slightly higher than the model without quantization. Through the proposed image processing method, the catch points of various types of dishes are effectively extracted. The functions of empty-dish recycling are realized and will lead to further development toward practical use. Full article

This study was designed to understand the relationships among the experience economy, brand attitude, and brand loyalty based on the type of service providers, such as robot servers and human servers in the restaurant industry. The data were collected from 296 people who experienced robot servers and from 294 people who experienced human servers and was analyzed through structural equation modeling (SEM), which indicated that the four sub-dimensions of the experience economy: education, entertainment, esthetics, and escapism, positively affect brand attitude, which in turn has a significant positive impact on brand loyalty. In addition, statistical differences were found with the average value of the six constructs based on the type of service providers, such as robot servers and human servers. Full article

Personalization and localization are important when developing social robots for different sectors, including education, industry, healthcare or restaurants. This allows for an adjustment of robot behaviors according to the needs, preferences or personality of an individual when referring to personalization or to the social conventions or the culture of a country when referring to localization. However, there are different models that enable personalization and localization presented in the current literature, each with their advantages and drawbacks. This work aims to help researchers in the field of social robotics by reviewing and analyzing different papers in this domain. We specifically focus our review by exploring different robots that employ distinct models for the adaptation of the robot to its environment. Additionally, we study an array of methods used to adapt the nonverbal and verbal skills of social robots, including state-of-the-art techniques in artificial intelligence. Full article

Regulating the curbside usage of delivery vehicles and ride-hailing services as well as micromobility has been a challenge in the last years, a challenge which might worsen with the increase of autonomous vehicles. The contribution of the research outlined in this paper is an evaluation method of the land use of on-demand meal delivery services such as Deliveroo and UberEats. It evaluates the effect parking policies, operating strategy changes, and scheduling options have on the land consumption of bicycle couriers and sidewalk automated delivery robots (SADRs). Various operating strategies (i.e., shared fleets and fleets operated by restaurants), parking policies (i.e., parking at the restaurant, parking at the customer or no parking) and scheduling options (i.e., one meal per vehicle, multiple meals per vehicle) are simulated and applied to New York City (NYC). Additionally, the time-area requirements of on-demand meal delivery services are calculated based on GPS traces of Deliveroo and UberEats riders in two UK cities. The simulation in the paper shows that SADRs can reduce the time-area requirements by half compared with bicycle couriers. The effect of operating strategy changes and forbidding vehicles to park at the customer’s home is small. Delivering multiple meals in one tour halves the time-area requirements. The time-area requirements based on GPS traces is around 300 m²·min per order. The study allows policymakers to learn more about the land use of on-demand meal delivery services and how these can be influenced. Hence, they can adjust their policy strategies to ensure that on-demand meal delivery services are provided in a way that they use land effectively, reduce external costs, improve sustainability and benefit everyone. Full article

As various types of robots increasingly influence consumers’ service experiences, companies need to consider how to be competitive in this new artificial intelligence and service automation business environment. However, only limited studies have investigated the factors involved in consumer behaviors toward robot restaurant visitors and their impacts. This study integrates trust, the perceived risk, and satisfaction with the well-known Technology Acceptance Model’s (TAM) original constructs (perceived usefulness, perceived ease of use, and acceptance) in the robot service restaurant setting. A scenario-based online survey was performed on 338 respondents. Structural equational modeling shows the direct impact of PU (perceived usefulness) and the indirect impact of PEOU (perceived ease of use) on consumers’ revisit intention to robot restaurants. Trust significantly increases PU and PEOU toward a service robot, and increased trust in robot service decreases the perceived risk as well as increases satisfaction. Further, perceived risk decreases satisfaction and revisit intention. The study provides useful information for hospitality marketers to acknowledge how consumers accept robot service and better understand the key drivers of robot restaurant revisit intention. Full article

This research empirically tested a theoretical model by defining senior customers’ intentions to use robot service restaurants emerging in South Korea. Non-face-to-face services have become increasingly important for seniors. Therefore, restaurant marketers should cater to senior customers’ needs by sustaining robot service restaurants. The study analyzed 243 questionnaires to verify the reliability and validity of the measurement items. The research hypotheses were examined using structural equation modeling (SEM). The suggested model comprised three stages: motivated consumer innovativeness (MCI), perceived value, and planned behavior (attitude, intention to use). The results revealed that senior customers’ perceived values positively influenced attitude and were enhanced by hedonically MCI (hMCI) and socially MCI. Moreover, the hedonic and social elements of motivation improved the attitude and usage intentions of robot service restaurants for senior customers. However, these relationships differed in terms of the income level of the customer groups. For the low-income senior-level group, hMCI was more influential on the perceived value. This study is meaningful because it analyzes the effect of MCI of seniors on the perceived value of robot service restaurants, which are growing rapidly in South Korea. It has empirically proved the moderating effect of different income groups, providing practical implications. Full article

“Hello, I’m the TERMINATOR, and I’ll be your server today”. Diners might soon be feeling this greeting, with Optimus Prime in the kitchen and Wall-E then sending your order to C-3PO. In our daily lives, a version of that future is already showing up. Robotics companies are designing robots to handle tasks, including serving, interacting, collaborating, and helping. These service robots are intended to coexist with humans and engage in relationships that lead them to a better quality of life in our society. Their constant evolution and the arising of new challenges lead to an update of the existing systems. This update provides a generic vision of two questions: the advance of service robots, and more importantly, how these robots are applied in society (professional and personal) based on the market application. In this update, a new category is proposed: catering robotics. This proposal is based on the technological advances that generate new multidisciplinary application fields and challenges. Waiter robots is an example of the catering robotics. These robotic platforms might have social capacities to interact with the consumer and other robots, and at the same time, might have physical skills to perform complex tasks in professional environments such as restaurants. This paper explains the guidelines to develop a waiter robot, considering aspects such as architecture, interaction, planning, and execution. Full article

Although innovative robotic technology plays an important role in the restaurant industry, there is not much research on it. Thus, this study tried to identify how to form behavioral intentions using the concept of perceived innovativeness in the context of robotic restaurants for the first time. A research model comprising 12 hypotheses is evaluated using structural equation modeling based on a sample of 418 subjects in South Korea. The data analysis results show that perceived innovativeness is an important predictor of the customers’ attitude, which in turn has a significant effect on desire. In addition, desire exerts a positive influence on intentions to use and willingness to pay more. Lastly, perceived risk moderates the relationships between (1) desire and intentions to use and (2) desire and willingness to pay more. Based on the above statistical results, important theoretical and managerial implications are presented. Full article

Restaurants have been using robots to meet the increasing consumer demand for food customization and safety and contactless service operations. This study identified the antecedent factors influencing a customer’s attitude and acceptance intention toward a robot barista. To this end, we conducted a questionnaire survey from 10 to 24 January 2020, on a sample of 317 Korean consumers who purchased coffee prepared by a robot barista. We based the analysis on the following determinant factors of the extension of the technology acceptance model (ETAM): perceived enjoyment, perceived usefulness, need for interaction, perceived risk, and perceived innovativeness. The results showed that perceived usefulness had the highest impact on acceptance intention, followed by perceived enjoyment and the need for interaction. Perceived usefulness and innovativeness positively influenced acceptance intention. These results confirmed the significance of the determinant factors in inducing customers’ attitude and acceptance intention toward a robot barista. This study extends the research on the application of artificial intelligence and the fourth industrial revolution technologies in the food service industry, and hence contributes toward the preparations for the post-Covid-19 period. It also offers practical implications for sustainable coffee shop management. Full article

The popularity and application of artificial intelligence (AI) are increasing rapidly all around the world—where, in simple terms, AI is a technology which mimics the behaviors commonly associated with human intelligence. Today, various AI applications are being used in areas ranging from marketing to banking and finance, from agriculture to healthcare and security, from space exploration to robotics and transport, and from chatbots to artificial creativity and manufacturing. More recently, AI applications have also started to become an integral part of many urban services. Urban artificial intelligences manage the transport systems of cities, run restaurants and shops where every day urbanity is expressed, repair urban infrastructure, and govern multiple urban domains such as traffic, air quality monitoring, garbage collection, and energy. In the age of uncertainty and complexity that is upon us, the increasing adoption of AI is expected to continue, and so its impact on the sustainability of our cities. This viewpoint explores and questions the sustainability of AI from the lens of smart and sustainable cities, and generates insights into emerging urban artificial intelligences and the potential symbiosis between AI and a smart and sustainable urbanism. In terms of methodology, this viewpoint deploys a thorough review of the current status of AI and smart and sustainable cities literature, research, developments, trends, and applications. In so doing, it contributes to existing academic debates in the fields of smart and sustainable cities and AI. In addition, by shedding light on the uptake of AI in cities, the viewpoint seeks to help urban policymakers, planners, and citizens make informed decisions about a sustainable adoption of AI. Full article

Robots have been reportedly seen serving food in several restaurants in many parts of the world. New ventures have been deploying mechanical partners which promote the growth in service robotics. However, robots are considerably incompetent when it comes to beverage and soup delivery. The physical challenge behind the clumsy motion of these machines is found to be its jerky motion control. Jerk control solutions are widely studied in a constrained environment but not well introduced in dynamic environments. In this paper, we will begin by examining developed kinematics solutions, open-source packages from Robot Operating System and the constraints of motion planning. The proposed solution in this paper provides a quick system response with jerk limits using spline velocity profiles. The solution will introduce the concepts of a state machine design that enables the robot to behave and move reactively; effectively balancing its desired velocity and position without spilling a drop of customer satisfaction. Experiments have proven that robots can move at higher velocity without any crashing, spilling, or docking issues. The smooth velocity control proposed will improve the capabilities of waiter robot and service operations in restaurants. Full article