Introduction
The term ‘social robot’ has become popular in the modern world and is almost being integrated into the modern day cultural constructs as usual. Lamers & Verbeek (2010) maintain that social technology is meant to invoke emotional attributes and to engage the human mind in a way that exceeds what is physical. Lamers & Verbeek (2010) argue that a robot is man’s effort at recreating his own self and it is with this semblance that the conceptualization of human-robot interaction has been captured. Dating back from the 18th century, inventors and scientists alike have been making numerous attempts at making the robotics idea come to life. Lamers & Verbeek (2010) continue to maintain that the 18th century was a markedly significant period in the quest for engineering and scientific supremacy. Following the concept of automatons, the 18th century presented an era of original art and impressions of humanoids that could do all creative human activities – drawing portraits, thinking critically, writing poems, and other forms of human essence (Minsky 1996, p. 26).
The apt relationship between humans and robots has been qualified as one that is of a friendly nature – social intelligence has been accredited to these robotic entities. As Lamers & Verbeek (2010) put it, robots invoke a sense of the need to attend to humans by satisfying their ‘needs’ as well as harnessing the gratified human nature, which is expressed by being thankful. Some of the already existent examples of robots meant to suit the human contentment nature are PLEO, a dinosaur-like Hong Kong robot that uses the methodic of artificial intelligence to learn its environment, PARO, a therapeutic robot resembling a harp seal, which replicates animal-assisted therapy only that it’s a robot, and Nexi, a Mobile Dexterous Social robot with human capabilities (Lamers & Verbeek 2011, p. 4).
All these examples are social robots definitive by their ability to communicate and have emotionally invoking exchanges with humans. Another postulation looks at robots as agents of embodiment whose belonging is of a heterogeneous nature.
Hospitality in General
Wood & Brotherton (2008) accredit the field of research on hospitality as a concept, to limited research efforts. Developmental conceptualization of hospitality as a discipline is by far an ongoing limitation while the systemic analytical disposition of hospitality alone is almost null. Wood & Brotherton (2008) maintain that the field research of hospitality management is as scattered as its hospitality counterpart. Wood & Brotherton (2008) try to avoid on the idealistic definition of hospitality and at the most average level of definition, hospitality still lacks both in conceptual rigidity, and in physical definitiveness. Overall, the broader reviews on matters hospitality are well captured in the social science literature as a derivative of philosophical writings, history, and sociological studies (Wood & Brotherton 2008, p. 4). Therefore, being that there is little literature to work with when it comes to hospitality, it can then be extrapolated that little exists in as far as social robotics literature is concerned.
Service industries such as hospitality and other more delicate ones like healthcare, have of late been flooding with robotics in general (Wood & Brotherton 2008, p. 5). Precision surgery, robotic arms for hoisting luggage, robot-assisted prosthetic technology, as well as personal robotic assistants have flooded the service industry to the helm. However, the idea of social robotics is a rather novel one and has seen the service industry marvel at this technological wonder (Wood & Brotherton 2008, p. 5). Robots with human capabilities are beginning to flood the service industry having some almost unfathomable capabilities integrated into the system’s robotic whole (Thomaz & Breazeal 2008, p. 725).
At the top of the social robotics food chain is perhaps artificial intelligence – the ability to cognitively harness stimuli from the surrounding environment and converting it into meaningful adaptive data (Cassimatis, et al. 2004, p. 17). Such interactive features have been integrated inside social robots to ensure that the human being has come as close as possible to inventing a mirror image of himself (Wood & Brotherton 2008, p. 6). This concept is quickly being integrated into the general service industry and has made numerous changes to the industry as a whole. Perhaps the most rigid of all advantages is that of higher output – with more accuracy and precision, robots can work at a faster rate than humans, and with minimal errors (Andrew 1984, p. 17). Additionally, in cases involving dangerous undertakings e.g. offloading heavy baggage from a conveyor, robots can take the risk and perform better than humans (Andrew 1984, p. 17). At an emotional level, the use of robots in the service industry invokes a feeling of excitement among the customers being that besides the monotonous human assistant, the digitalized social robot can perform as courteously and efficiently as its human equivalent (Karg, et al. 2011, p. 128).
Additionally, the robots eradicate the rather heavy budgetary payroll that the human workers in the hospitality sector will get (Romer, et al. 2005, p. 202). The robots will also work overtime with no complaints or due demands for increase in payment as the human assistants would. On the other hand, however, robots have the disadvantage of being less versatile than the human worker, e.g. in case a customer would want to have an extra undertaking done for him, the robot will not conform as it works as a program, and hence strictly follows a particular set of guidelines (Lee 1984, p. 5).
Human and Robot interactions
Most of the analytical ventures that have been done to find out more about the human-robot associative relationship are of a user-inclined nature.
The question of how the robots ought to be structurally and digitally designed, as well as what the user generally looks forward to, are the more used yardsticks in social robotics (Mutlu & Forlizzi 2008, p. 23). In most studies carried out, at least, the general user outcry is for a robot that has human-like appearances for a job that requires more social skills than power or accuracy of work (Taylor 1983, p. 16). It was also found that most people would much conveniently subjugate tasks of an especially socioeconomic nature, to a robot that is more human than it is machine (Bartneck & Forlizzi 2004, p. 32).
In a 2016 research paper, Yamaoka et al (2016) assess the advantages and disadvantages of having tele-operated robots to the levels of enjoyment they induce amongst the users. In their research, they hypothesized that people had filed reports of having lesser enjoyment from tele-operated robots as opposed to using the autonomous robots. In the actual experiment, they used a cooperative robotized system of a humanoid nature that had been previously launched and used. This system was meant to work with the non-verbal accentuations produced by human activities, and then it was supposed to report them to a dedicated feedback system. The non-verbal cues in this case were a derivative of previous findings based on the ideals of developmental psychology – a premise that substantiates the animate versus inanimate perceptions.
Additionally, assuming the person did not approach the robot, it would approach him and obtain initial contact, so called the agent state. The system in general, was a composition of a Robovie, humanoid robot, motion detection technology, and robot controls. Motion sensing was meant to capture the position of predetermined position markers on various parts of the robot body i.e. arms, head etc. It was also meant to capture the person’s predefined body parts and then trigger the robot control accordingly. Yamaoka et al (2016) instructed the participants to be aware of the interaction they were about to go into with the robots. The controls of the robot would be randomized to either human or program controlled. The participant was then given a chance to interact and experiment with the robot for a given amount of time after which it was randomly interrupted for an immediate questionnaire session. After the questionnaire session, the participant was given a choice of whether to continue with interactions with the robot, or to just stay and wait.
In this way, Yamaoka et al (2016) measured the level of enjoyment using the number of participatory subjects that were willing to voluntarily continue interacting with the robot, and for what amount of time they did it. The environment of experimentation was a 7/1/2 by 10 meters room with a participating sample total of 77 university level students, 50 of whom were men, and 27 were women. Each of the participants was paid for the partaking and due to the limitations encountered in term of motion capture, the interaction between the participants and the robot was restricted to a 2x2 meter floor area. The procedure had a set of steps where the first was a set of instructions which were issued just before beginning the experiment in form of a video tutorial. The participants then became actively involved with one on one first time interaction with the robot for 90 seconds before proceeding to fill in the questionnaire. Eventually, after all the steps were completed, the results were tallied and a one-channel analysis of variance was carried out.
It was revealed that the only significant difference was found in intelligence and none at all in autonomy. This result was proof that participants were largely associating the prevalent experimental differences in condition to the intelligence borne by the robot, and not to the robot’s autonomous system (Sato, et al. 1996, p. 188). The general impression among the participants as that the robot had a lower perceived level of intelligence when it was human-operated, rather than when it was self-controlled. Moreover, Yamaoka et al (2016) established that there was no significant difference in the general enjoyment condition as well the voluntary added time of interaction. This, then, was translated to a very minute effect size, so that, the conclusion could be that the awareness of the presence of an operator (or not) did not have an effect on enjoyment. In addition, Yamaoka et al (2016) also recorded a significant variance in the interaction attribution concept.
What this meant was that how people looked at operator presence in a subjective manner had no bearing on the knowledge that the operator was there or not. Yamaoka et al (2016) drew a conclusion that, on average, considering the nonverbal interactive nature between people and robots, the enjoyment harnessed by people was unaffected. However, people will have a subconscious awareness pointing towards the lesser intelligence of a tele-operated robot. About two thirds of any population will be convinced that they are interacting with the robot, while the remainder will be inclined to assume that they are interacting with a human behind a robot
Analytical View of Robotics in Hospitality
With this form of scientific conscience with regard to human perception towards robotic interventions, it can be presumed that the greater population of people will enjoy services offered by social robots.
Additionally, being that the service industry of hospitality is one that can oftentimes be overwhelmed with large number of people to serve in a limited amount of time, robotics represent a great effort in hastening the pace of service delivery. Bilgihan & Nejad (2015) hold that the idea of robotics in hospitality is one of the most potent future trend, citing a specific example of Henn-na hotel in the country of Japan whereby the use of robots is extensive. At the hotel’s reception, robots serve incoming customers and ferry their baggage to their respective rooms without any external control. This, as Bilgihan & Nejad (2015) put it, is the prime concept whose impact will cause a major development in the fields of economics, society and business alike. Bilgihan & Nejad (2015) continue to posit that, the idea of robotics in hospitality serves more than just the purpose of the accrued benefits.
Robotics is a befitting concept that allows all the member proprietors to brag and boast about what they own and what they represent as a company. Consumers will strive for such attributes as uniqueness, pride and the feeling of undivided attention when such a concept like robotics is brought to the limelight. Different reasons for adopting a concept vary according to different consumers – one consumer may implore robotics for resource saving, while another may make use of it for its environmental friendliness. With the many emerging trends in hospitality at par with technological advancements, it is pertinent that all hospitality providers be at their economic best. In an article by Chen (2010), the issue of pricing in hotels and keeping up with competitor trends has been highlighted. Chen (2010) raises a concern over what people normally go for between a hotel that offers relatively low prices, and one that offers prices that soar higher than competitor prices. To best analyze this problem, Chen (2010) further analyzes the factors that lead to the occurrence of the pricing framework: cost, the valuation tenets, and the elasticity defining the hotel.
Chen (2010) then posits that as far as cost is concerned, the labor as well as materials implored in the customer service table contribute the greatest. Chen (2010) then maintains that the pricing in hotels is an aftermath of costing, with a lag element induced in the former. However, being that hotels are part of the shorter production service industry, Chen (2010) then continues to show that the lags are therefore shorter there and hence not much effect comes to pricing relative to costing.
Personal Reflection
On a personal level, I would look forward to a hospitality industry where the robotic systems handle the tedious and bulky activities, as well as those less cryptic human-robot interaction activities e.g. customer ushering, swiping credit cards, and general one-on-one interaction. However, for the more complex undertakings e.g. problem solution, settling disputes, and assisting customers with complicated requests, the human should be the entity concerned (Yang & Lee 2007, p. 262). In other forms of service delivery also, whereby the human being interacts severally with machines, I would suggest an integration of both human and robot interaction to aid in service delivery. For instance, if ID verification for a customer involves cross-matching the customer’s face, and then running the ID’s serial number on a computer aided platform and then signing of verification documentation by both parties, the interaction can be split two ways. First, facial recognition and serial number checking can be done by the robot, and then the last phase involving signatures can be done by the customer and a human being. Conclusively, I would make a suggestion to the hospitality stakeholders, to integrate the robot-customer interaction into hotel rooms so that on demand, a customer can quickly get access to a robot for assistance at their doorstep.
Conclusion
Therefore, the ideals revolving around the use of social robotics in the hospitality scene is purely methodical and economically advantageous other than an element of anti-economic heaviness. Hospitality in general can benefit heavily from the ideals of this social robotics concept not paying specific regard to the cost that comes with it. Observing that many hotels world over, have with time turned to the idea of robotizing all service deliveries with proof of success, it can only be presumed that the hospitality realm is headed towards a robotic future.
References
Andrew, W., 1984. Hospitality education and the technological revolution. Journal of Hospitality & Tourism Research,, 8(2), pp. 15-21.
Bartneck, C. & Forlizzi, J., 2004. A design-centred framework for social human-robot interaction. s.l., s.n., pp. 31-33.
Bilgihan, A. & Nejad, M., 2015. Innovation in hospitality and tourism industries. Journal of Hospitality and Tourism Technology, 6(3).
Cassimatis, N., Trafton, J., Bugajska, M. & Schultz, A., 2004. Integrating cognition, perception and action through mental simulation in robots. Robotics and Autonomous Systems, 49(1), pp. 13-23.
Chen, J., 2010. Advances in Hospitality and Leisure, vol. 6. s.l.:Emerald Group Publishing.
De Ruyter, B., Saini, P., Markopoulos, P. & Van Breemen, A., 2005. Assessing the effects of building social intelligence in a robotic interface for the home. Interacting with computers, 17(5), pp. 522-541.
Goodrich, M. & Schultz, A., 2007. Human-robot interaction: a survey.. Foundations and trends in human-computer interaction, 1(3), pp. 203-275.
Karg, M., Sachenbacher, M. & Kirsch, A., 2011. Towards expectation-based failure recognition for human robot interaction. s.l., s.n., p. 128.
Lamers, M. & Verbeek, F. e., 2011. Human-Robot Personal Relationships: Third International Conference, HRPR 2010, Leiden, The Netherlands, June 23-24, 2010, Revised Selected Papers (Vol. 59). s.l.:Springer..
Lee, H., 1984. An economic model for evaluating robot applications - Master's thesis, s.l.: Ohio University.
Minsky, M., 1996. Will robots inherit the Earth?. s.l.:s.n.
Mutlu, B. & Forlizzi, J., 2008. Robots in organizations: the role of workflow, social, and environmental factors in human-robot interaction, s.l.: IEEE.
Romer, G., Stuyt, H. & Peters, A., 2005. Cost-savings and economic benefits due to the assistive robotic manipulator (ARM). 9th International Conference on Rehabilitation Robotics, pp. 201-204.
Sato, T., Nishida, Y. & Mizoguchi, H., 1996. Robotic room: Symbiosis with human through behavior media. Robotics and Autonomous Systems, 18(1), pp. 185-194.
Shoemaker, S. & Lewis, R., 1999. Customer loyalty: the future of hospitality marketing. International Journal of Hospitality Management, 18(4), pp. 345-370.
Taylor, J., 1983. R & D in human aspects of robotic technology.. Robotica, 1(1), pp. 15-17.
Thomaz, A. & Breazeal, C., 2008. Teachable robots: Understanding human teaching behavior to build more effective robot learners. Artificial Intelligence, 172(6), pp. 716-737.
Wood, R. & Brotherton, B. e., 2008. The SAGE handbook of hospitality management. s.l.:Sage.
Yamaoka, F., Kanda, T., Ishiguro, H. & Hagita, N., 2012. Human-robot interaction in social robotics. In: Is Interaction with Teleoperated Robots Less Enjoyable. s.l.:CRC Press, pp. 76-84.
Yang, H. P. A. & Lee, S., 2007. Gesture spotting and recognition for human–robot interaction. IEEE Transactions on Robotics, 23(2), pp. 256-270.
