Robots in the Hospitality Industry

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With the development of technology, more and more hotels are beginning to change their business management mode. For example, many hotels have saved their housekeeping supervisor and other positions through intelligent clients which in order to save the management cost of the hotel. This is a labor dependent industry that heavily relies on skilled labor force and a flexible workforce to cope with seasonal fluctuations. Also, face the challenges of finding and retaining talented employees (Murray, Elliot, Simmonds, Madeley & Taller, 2017). The skilled labor shortage was the biggest challenge in the hospitality industry. It is more serious in some emerging nations because they can’t produce enough graduates to serve the growing industry (Thailand, 2014). Not only new graduate, but skilled trainers in hotel are also in short supply. Since hospitality and tourism service interactions are often cross-cultural. There is a greater cultural and social gap between hospitality employees and customers they serve in some poor developing countries. Such employees have more to learn including things considered basic in developed societies such as language, social, communication and interpersonal skills and etiquette rules (Maumbe & Wyk, 2011). As to solve these problems, robots will be gradually introduced to hospitality industry in the future. This essay discusses the impact of robots on the guest experience, hotel operations and processes and data analytics in hospitality industry.

The presence of robots in the hospitality industry can bring different customer experience for guests. Compared to employees, service robots have ability to work 24 hours per day, almost no breaks and respond immediately. This can be the most different between service robots and employees as a service robot is able to serve guests at any time rather than shift working like employees. Service robots can reduce the conflict between employees and guest, they are free from human error and fatigue and respond to their service environment in a highly reliable manner (Wirtz, Patterson & Kunz et al., 2018). Since a service robot will be connected to CRM system and identify customers at the same time, then they can provide customized services on a pro-rata basis under guests demand or requirement. In addition, the system of service robots can be designed to be impartial which means have no biases by race, gender and social status and so on unless so programmed (e.g. for special handling of more 'valuable' customers) (Wirtz, Patterson & Kunz et al., 2018). Service robots seems more like a new service concept which is compared to traditional customer service in hospitality industry, these new technologies enable hotels to adapt to changing circumstances and differentiate themselves from their competitors, and customers can meet new service or values created by hotels in their self-service technology for their target customers through satisfying their curiosity and enjoyment (Kuo, Cheng & Tseng, 2017).

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However, service is mainly through emotional communication, robots still can’t achieve to the same level as human in this regard. The genuine emotions response of robots is not determined by themselves (Ojha, Williams & Johnston, 2018). Therefore, service robots will not be able to feel and express their real emotions. Even though they can mimic the expression of emotional reactions, for example, they can use facial expressions and body language to communicate with guests (Wirtz, Patterson & Kunz et al., 2018). In spite of this, the emotion expressed by a robot just keeps on the surface, it is likely to be noticed by customers, but they are less likely to respond to the emotions displayed by robots because deep inside customers may understand that these emotions are not real (Tung & Au, 2018). Moreover, service robots are unlikely to feel the meaning of emotions expressed by human, unlike employees who can distinguish guests emotional state from the manner of his behavior or tone of their express as employees have their own perceives ability to deal with different situations in different ways. So, the most important thing about service is emotional communication, as such it still has to back to the essence of human being in the end during the whole process.

During the process of hotel operations and processes, hospitality has a high turnover rate and high training required due to the development of the hospitality market, cater to market service need in different period. Employees require training in order to achieve a goal that they need an in-depth understanding of the customer and service processes to deliver good customer services to guests and organizations. That is, people need to learn a routine and also need to remember relevant information about their responsibility and understand how to use IT system. This takes times and cost.

On the contrary, robots do not need to learn as humans do. Robots may be part of a visible and customer-facing part of a large integrated service system, including basic knowledge and CRM systems. Accessing knowledge and information can be done instantaneously in a variety of forms. For instance, a service robot can learn through update coding knowledge, pattern recognition and “training” of AI thereby systematically comparing millions of scenes and determining the cause of action based on the distance to a given optimal result, and then, machine learning methods that using computer power to determine the best solution by playing millions of scenarios in a structured environment (Wirtz, Patterson & Kunz et al., 2018). Furthermore, each individual service robot can work immediately that only need to update the same system for all of robots. This id benefit to hospitality industry to reduce their training cost, improve their business operations, and promote the distribution, integration organization and delivery of their products and services through technology (Law & Daniel et al., 2013).

In the other hand, since service robots are set by programming system, so they might not be able to change according to the situation such as handle emergency or contingency. They only follow the standard and programmatic knowledge. They can’t work outside their plans without moral values and emotions. Compared to humans, robots lack of potential creativity, they performed programming and could not make mistakes or make correct judgments. If they are not familiar with a situation, they can’t make a decision and they also can’t subdivide or handle errors. Human insight depends on the cognitive process of knowledge, which is indispensable for real-time experience and observation. However, AI machines for mobile application development are different and follow the wisdom of robot programming. Unlike humans, a robot does store a lot of information, but it doesn't access and analyze data as humans do.

Additionally, the emergence of robot system failure would be inevitable when it occurs during the service process. “Although the morality of robots is a somewhat philosophical topic, it does have real-world implications for a future in which robots in the real-world cause accidents. Who is to blame? The robot? The developer? The owner?” (Murphy, Gretzel & Pesonen, 2019). As Tung and Au (2018) mentioned that one of service robot user felt insecurity which extends from robotic error. The robot in their room suddenly operated late at night so they had to power off when sleeping. Due to the concept of service robot is still relatively novel in hospitality environment, and some people are likely to be worried about the initial idea of sharing and interacting with robots. Thus, hotel operator needs to consider customers’ sense of discomfort when robots operate in the same physical space (Thung & Au, 2018).

Data collection and data analytic can a competitive strength of robots which compared to humans. Service robots enable to collect and store customer’s information together in their whole system when they are providing services. They do not need to spend a long time to do data analysis and some visualization works. Meanwhile, service robots are likely to perform data analysis through the built-in program at the same time, including record customer behavior characteristics, personal information, etc. Services robot detects the surrounding physical environment through sensors and then collect data and information automatically (Chien & Lin et al., 2018). Then offer they would offer more optimized service plans for customers that according to the result of the analysis, these all can be done in a short time. Thereby benefit to customer service satisfaction rate. Ref

Data protection is one of the driving forces behind security privacy, but ‘fair perception’ practices go beyond personal data, not to mention sensitive personal data. Humans not only protect others' own data but also protect their business ideas, scientific or technological discoveries or personal skills (Schafer & Edwards, 2017). If there is no justifiable reason to get information, this will invade the privacy of the individual (Holder et al., 2016).

Since robots can not only store data, but also connect to and retrieve data from other sources, and record everything in minutiae detail. Several security risks are able to be caused by robots. For example, sensitive data may be stored in the cloud where criminals can access data and use them to blackmail users (Holder et al., 2016). In addition, the robot may be hacked and remotely accessed, causing physical damage and damage to the home space. For a person's life, behavior and preferences are monitored so closely, documented and may be accessed by anyone (Wirtz, Patterson & Kunz et al., 2018). So, the ability of robots to store data may also be their vulnerability.

Nowadays, in some ways, robots are still not a substitute for humans like in housekeeping department. Artificial intelligence is in the auxiliary position in service industry because the consciousness of people in the service industry is indispensable. The database can be the basic thing of artificial intelligence. The real emotional can only be transmitted by employees. Since current intelligent robots still have many deficiencies, they can’t replace workforce completely. Robots might do not have ability to understand or handle something which is more specific or complicates and then expresses it. Moreover, robots only follow their program instructions when they are working, unlike humans who have a brain to thinking. It is necessary to know that communication between people is emotional, and this kind of emotion often help people to solve problems and bring good service experience to customers. For example, if people communicate with customer support, people can feel that person's attitude whether warm or friendly, people can feel the attitude through their conversation such as pitch or tone, this is what the robot can’t give.

For the development, if hospitality in the future, service robots cannot completely replace employees in hospitality, because the consciousness of people in the service industry is indispensable. It can’t be denied that there are works like some folding placement and inventory management in hotel will be the future direction of robot development. Even though interaction is still surrounded by people, but there is no denying that low-end and complicated labor work can be replaced by service robots. Therefore, services robots can work with human in the same environment. As for hotel analytics, robots are likely to collect and classify data automatically, but they may have difficult to have unique insights which rely on a long-time experience to do that. Consequently, the advantage of artificial intelligence in automation can help employees to save their time on low-level work (such as collect many data from difference area) which in order to allow people have enough time to focus on more creative and innovative work.

References

  1. Chien, S. Y., Lin, Y. L., Lee, P. J., Han, S., Lewis, M., & Sycara, K. (2018). Attention Allocation for Human Multi-Robot Control: Cognitive Analysis Based on Behavior Data and Hidden States. International Journal of Human - Computer Studies, 117(C), 30–44. doi: 10.1016/j.ijhcs.2018.03.005.
  2. Holder, C., Khurana, V., Harrison, F., & Jacobs, L. (2016). Robotics and Law: key legal and regulatory implications of the robotics age (Part 1 of 2), Computer Law & Security Review, 32(3), 383-402.
  3. Kuo, C. M., Chen, L. C., & Tseng, C. Y. (2017). Investigating an Innovative Service with Hospitality Robots. International Journal of Contemporary Hospitality Management, 29(5), 1305–1321. doi: 10.1108/IJCHM-08-2015-0414.
  4. Law, R., Leung, D., Au, N., & Lee, H. “andy” (2013). Progress and Development of Information Technology in the Hospitality Industry: Evidence from Cornell Hospitality Quarterly. Cornell Hospitality Quarterly, 54(1), 10–24. doi: 10.1177/1938965512453199.
  5. Maumbe, K., & Wyk, C. (2011). Addressing the Skills Shortage Problem of the South African Tourism and Hospitality Industry: An Evaluation of the Effectiveness of the 2007/2008 SA Host Training Program in the Western Cape Province. Urban Forum, 22(4), 363–377. doi: 10.1007/s12132-011-9115-z.
  6. Murray, W. C., Elliot, S., Simmonds, K., Madeley, D., & Taller, M. (2017). Human Resource Challenges in Canada’s Hospitality and Tourism Industry. Worldwide Hospitality and Tourism Themes, 9(4), 391–401. doi: 10.1108/WHATT-04-2017-0022.
  7. Murphy, J., Gretzel, U., & Pesonen, J. (2019). Marketing Robot Services in Hospitality and Tourism: The Role of Anthropomorphism. Journal of Travel & Tourism Marketing, 1–12. doi: 10.1080/10548408.2019.1571983.
  8. Ojha, S., Williams, M.-A., & Johnston, B. (2018). The Essence of Ethical Reasoning in Robot-Emotion Processing. International Journal of Social Robotics, 10(2), 211–223. https://doi.org/10.1007/s12369-017-0459-y
  9. Schafer, B., & Edwards, L. (2017). “I Spy, with My Little Sensor”: Fair Data Handling Practices for Robots Between Privacy, Copyright and Security. Connection Science, 29(3), 200–209. doi /10.1080/09540091.2017.1318356.
  10. Tung, V. W. S., & Au, N. (2018). Exploring Customer Experiences with Robotics in Hospitality. International Journal of Contemporary Hospitality Management, 30(7), 2680–2697. doi.org/10.1108/IJCHM-06-2017-0322.
  11. Thailand: Hospitality Industry in Southeast Asia Has All Operators to Work Together to Tackle Skilled Labour Shortage. (2014, January 30). Asia News Monitor. Retrieved from http://search-proquest-com.ezproxy.library.edu.au/docview/1492240885?accountid=14723
  12. Wirtz, J., Patterson, P.G., Kunz, W.H., Gruber, T., Lu, V, N., Paluch, S., & Martins, A. (2018). Brave New World - Service Robots in the Front Line. Journal of Service Management 29 (5), 907-931.
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Robots in the Hospitality Industry. (2022, October 28). Edubirdie. Retrieved December 22, 2024, from https://edubirdie.com/examples/robots-in-the-hospitality-industry/
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