Updated:

Generic Dimensionality of Hospitality Essay

Exclusively available on Available only on IvyPanda® Made by Human No AI

Despite poor reception during the initial years of the introduction of robot technologies to the hospitality industry, there is a growing trend in the customer preference for roboservice. The initial spike in the preference was caused by the restrictive measures of pandemic which seemed to have influenced cultural values of the customers developing a new trend. Consequently, due to the cost-savings, performance and authenticity of robots in service, their implementation is a recommended course for development of the industry and attracting new customers. Even though some may argue that maintenance and cyber-security protection would be an issue, the benefits of the technology outweigh potential risks.

Introduction

It is crucial today to make the most of all available resources. Digitalization or automation is brought to the sector to accomplish such growth in many industries because of the minimal maintenance and enhanced performance. Roboservice, the use of robots in the hospitality business, is replacing humans in roles formerly held by bellhops, receptionists, luggage porters, and delivery personnel. Many hotels throughout the globe are beginning to upgrade their offerings by adopting this new technology. Famous hotel chains, including Hilton, Aloft, Yotel, and Henn na, are just a few examples. Although early acceptance of robots in hospitality was bad since customers preferred a person, their popularity has surged by a large magnitude following and throughout the epidemic. As a result, it is important to consider how digitization relates to introducing robots into the hospitality industry.

Robots are undeniably becoming standard hotel staff members. Robots that carry out mundane tasks are becoming standard in many hospitality establishments. With more and more companies realizing the benefits that robots may bring to the hospitality industry, this is a developing trend. The number of persons who have benefited from robotic services has increased since 2017. Trejos (2016) cites studies and research showing that robots increase employment significantly in the hotel business. Also, the hotel sector is the first place where human-robot interaction was widely used (Trejos, 2016). According to the research presented here, the manufacturing sector is the frontrunner when it comes to adopting robots, and humans will soon be obsolete.

This paper will proceed in the following manner:

  1. The literature review will focus on the reasons for the increasing popularity of robotics in the industry.
  2. Three subsections will be dedicated to the analysis of the benefits and demerits of the service robots’ presence in the hotel. Each subsection would include one distinct argument, a counterargument that readers may find, and a rebuttal explanation to demonstrate how their opposition should not be concerned.
  3. The paper will draw a conclusion based on the arguments provided.

Literature Review

Because of the mutual benefit that results from the exchange of hospitality between host and guest, the success of any hospitality business relies on the “hospitableness” of its employees (Kim et al., 2021). Human connection and the care and concern shown toward staff members are cornerstones of the hospitality industry (Golubovskaya et al., 2017). In the context of human values and connection, hospitality is represented through hotels. Numerous factors, including the friendliness, patience, and emotional display of hotel staff members toward guests, the warmth of their greetings, and the serenity of the rooms they provide, all contribute to the quality of guests’ overall stays (Hwang et al., 2015; Lashley & Morrison, 2000).

People who stay in hotels tend to favor personalized treatment, highlighting the importance of personal interactions where guests may freely express their appreciation or displeasure. The impulse to converse with hotel staff members indicates a desire for individualized and exceptional service (Ariffin, 2013).

By increasing efficiency and lowering labor costs, service robots are predicted by scientists to become a major platform for service sector productivity growth. This presumption received attention and ignited a heated debate on using service robots in the hospitality business among hotel owners, shareholders, employees, visitors, industry groups, suppliers, government agencies, and academic institutions (Tnooz, 2016). The debate about the technological status and lack of humanization in artificially intelligent service robots is highlighted here.

Hotel service robots will only be useful if they have a high level of autonomy and human-robot interaction (HRI) (Tung & Au, 2018). Savioke’s Relay, which is installed in various hotels and is responsible for a large portion of the delivery service’s operations exhibits, has a certain HR§I. Relays connected with cameras and sensors can detect room numbers, letting them traverse congested corridors and access the elevator without clashing with other items. In order for customers to get their ordered food and amenities, Relay will automatically open its lid once it has arrived at its destination. Instead of leaving tips, customers at Relay are encouraged to rate the service through a digital screen in an effort to improve it. As soon as Relay’s system software detects affirmative user input, it will begin to shake violently.

Numerous studies have demonstrated that when it comes to interaction quality and the actual service environment, humans are preferred over robots. However, risk perception has a considerable role in consumer decision-making regarding their selection of tourist merchandise. There is a range of customer-related dangers in the hotel sector, including personal health, social, financial, and performance risks. In particular, the gravity of the COVID-19 threat may cause guests to have different impressions of a robot-managed hotel (Galoni et al., 2020).

In light of the pandemic, Jiang and Wen (2019) have predicted a rise in the need for hotel service robots. The very contagious character of COVID-19 might make guests nervous and affect their opinion of hotels served by robots. Guests will be more amenable to hotels staffed by robots because they perceive a lesser risk of transmission from robots. Kim et al. (2021) found that as a result of the COVID-19 epidemic, people started preferring robot services over human ones, signaling a shift in the prevailing choice paradigm.

Discussion

Primary Advantages of Robotics in Hospitality

Chatbots, delivery robots, robot concierges, conveyor restaurants, and self-service information/check-in kiosks are just a few examples of RAISA that have found their way into the travel, tourist, and hospitality sectors. A growing body of research in the hospitality industry, informed by studies in robotics that tout the benefits of anthropomorphism on user engagement (Broadbent, 2017), shows that making service robots more human-like increases consumers’ desire to employ them. Researchers have shown that when people give service robots human traits, they have a more favorable impression of them and are more likely to want to adopt them (Lin et al., 2020).

Furthermore, customers have higher expectations for service quality when humanoid service robots are involved (Lin & Mattila, 2021). According to research by Zhu and Chang (2019), when consumers attribute human traits to robot chefs, they have higher expectations for the quality of their meals. An even more intriguing finding is that customers have higher expectations for service robots when they appear like people. When engaging with humanoid service robots, for instance, customers gave the robots higher marks for providing satisfactory service when they mimicked human speech patterns and idioms (Lu et al., 2021). The findings suggest that if hotel management includes human-like characteristics in service robots, they may increase customer happiness.

Diverse Applications in the Field

The robot assists restaurant guests who want advice or assistance. The robot is a Watson-enabled robot concierge that utilizes Way Blazer and Watson’s expertise (Kuo, Chen, & Tseng, 2017, p. 1305). Ideally, the robot assists individuals in deciding where to go, where to eat, and how to find everything on the premises. The robot serves as a test since the corporation intends to incorporate its features into its offices. The firm is still determining whether to bring Connie to additional properties at this time. Connie’s primary purpose was to eliminate consumer obstacles, such as waiting in line while the human staff answered (Trejos, 2016).

Additionally, it was intended to enhance operations on the site. It was intended to surprise and excite faithful consumers primarily. In an ideal world, the robot’s purpose is not to reduce personnel but to provide an efficient working environment (Kuo, Chen, & Tseng, 2017, p. 1315). The robot answers over 100 unique inquiries and concerns at the front desk. In addition, it effectively handles calls and expedites the visitor check-in process.

When a consumer requests instructions, Connie directs them in the appropriate path. Additionally, its eyes change color according to the conditions. As it expresses perplexity, comprehension, confusion, and other emotions, it illuminates differently to convey its emotions. Through its capacity to detect, learn, and experience, the robot has been able to learn about the environment thanks to cognitive computing technology (Kuo, Chen, & Tseng, 2017, p. 1318). The robot responds to visitors using gestures and body language; for instance, when asked where the elevator is, it indicates that it is located down the corridor to the left. Additionally, it points left and down the hall.

Limitations to Implementation

In addition to the usage of AI-enabled technologies, what other options may be explored to expand the capabilities of service robots in the hotel industry? In light of Wirtz et al., who mapped customer demands to robot capabilities, it is obvious that, in the first instance, hospitality may be seen as a job with low analytical-cognitive complexity and high emotional complexity. In light of the restrictions provided by robots in their first phase of service, their assignment will tend to favor humans. Therefore, robot interactions in frontline hospitality services should be deemed inadequate since they often fail to match the qualities of human-oriented perception and exhibit high degrees of impersonality — these services will continue to be provided primarily by humans.

Another school of thought in the hospitality literature, based on the narrative of Mori et al. (2012), contends that the human-likeness of service robots has no impact or even a negative one on the business. Customers have a bias towards humanoid service robots because they believe they lack interpersonal skills, despite the fact that this is a key factor in determining whether or not a guest will be satisfied with their service experience (Hu et al., 2021). In the event of a service failure, customers are less likely to accept an apology from a service robot than they would from a human worker (Hu et al., 2021). Furthermore, studies have shown that customers are less likely to engage with a service robot if it seems too human (Yu, 2020). Managers in the hotel industry need to proceed with caution when introducing humanoid service robots, especially for jobs requiring extensive communication with consumers.

Conclusion

Robotic service providers, defined as system-based autonomous and adaptive interfaces that engage, communicate, and give service to an organization’s clients, are the cutting edge of customer service technology right now (Wirtz et al., 2018, p. 4). As a result of the widespread fear of contracting an infectious illness via casual conversation, the hospitality sector has seen an increase in the use of service robots. Indicating limited social interaction and lowering the perceived danger of virus transmission, the use of service robots may improve the likelihood that a customer would visit a business (Wan et al., 2020). Consumers are more likely to choose hotels operated by robots because of fear for their safety (Kim et al., 2021). This provides support for the hypothesis that the hotel service robots industry will expand at a rapid clip in the future.

Consumers’ divergent reactions to humanoid service robots point to the influence of extraneous circumstances. Individual consumer characteristics, such as openness to new ideas, and environmental variables, such as high foot traffic, may be distinguished among the many influences. Examples of demographics that are more likely to have positive views of humanoid service robots include those who are more technologically savvy, less averse to change, and who value convenience above human connection in service interactions (Hu et al., 2021). Customers also prefer service robots when they have a strong incentive for social disengagements, such as when there is a fear of infectious illness or when the place is overly congested with other people (Kim et al., 2021).

References

Ariffin, A. A. M. (2013). Generic dimensionality of hospitality in the hotel industry: A host–guest relationship perspective. International Journal of Hospitality Management, 35, 171-179.

Broadbent, E. (2017). Interactions with robots: The truths we reveal about ourselves. Annual Review of Psychology, 68, 627-652.

Choi, Y., Choi, M., Oh, M., & Kim, S. (2020). Service robots in hotels: understanding the service quality perceptions of human-robot interaction. Journal of Hospitality Marketing & Management, 29(6), 613-635.

Galoni, C., Carpenter, G. S., & Rao, H. (2020). Disgusted and afraid: Consumer choices under the threat of contagious disease. Journal of Consumer Research, 47(3), 373-392.

Golubovskaya, M., Robinson, R.N. & D. Solnet. (2017). The meaning of hospitality: do employees understand? International Journal of Contemporary Hospitality Management, 29(5), pp. 1282-1304.

Hu, Y., Min, H., & Su, N. (2021). How sincere is an apology? Recovery satisfaction in a robot service failure context. Journal of Hospitality & Tourism Research, 45(6), 1022-1043.

Hwang, J., Han, H., & Kim, S. (2015). How can employees engage customers? Application of social penetration theory to the full-service restaurant industry by gender. International Journal of Contemporary Hospitality Management, 27(6), 1117-1134.

Jiang, Y., & Wen, J. (2020). Effects of COVID-19 on hotel marketing and management: a perspective article. International Journal of Contemporary Hospitality Management, 32(8), pp. 2563-2573

Kim, S. S., Kim, J., Badu-Baiden, F., Giroux, M., & Choi, Y. (2021). Preference for robot service or human service in hotels? Impacts of the COVID-19 pandemic. International Journal of Hospitality Management, 93, 102795.

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), pp. 1305-1321. Web.

Lashley, C., & Morrison, A. J. (Eds.). (2000). Franchising hospitality services. Routledge.

Lin, H., Chi, O. H., & Gursoy, D. (2020). Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing & Management, 29(5), 530-549.

Lin, I. Y., & Mattila, A. S. (2021). The Value of Service Robots from the Hotel Guest’s Perspective: A Mixed-Method Approach. International Journal of Hospitality Management, 94, 102876.

Mori, M., MacDorman, K. F., & Kageki, N. (2012). The uncanny valley [from the field]. IEEE Robotics & Automation Magazine, 19(2), 98-100.

Trejos, N. (2016). . Web.

Tung, V. W. S., & Au, N. (2018). Exploring customer experiences with robotics in hospitality. International Journal of Contemporary Hospitality Management, 30, pp. 2680–2697. Web.

Wan, L. C., Chan, E. K., & Luo, X. (2020). . Annals of Tourism Research. Web.

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 frontline. Journal of Service Management.

Yu, C. E. (2020). Humanlike robots as employees in the hotel industry: Thematic content analysis of online reviews. Journal of Hospitality Marketing & Management, 29(1), 22-38.

Zhu, D. H., & Chang, Y. P. (2019). Robot with humanoid hands cooks food better?: Effect of robotic chef anthropomorphism on food quality prediction. International Journal of Contemporary Hospitality Management, 32(3), 1367-1383.

More related papers Related Essay Examples
Cite This paper
You're welcome to use this sample in your assignment. Be sure to cite it correctly

Reference

IvyPanda. (2023, December 11). Generic Dimensionality of Hospitality. https://ivypanda.com/essays/generic-dimensionality-of-hospitality/

Work Cited

"Generic Dimensionality of Hospitality." IvyPanda, 11 Dec. 2023, ivypanda.com/essays/generic-dimensionality-of-hospitality/.

References

IvyPanda. (2023) 'Generic Dimensionality of Hospitality'. 11 December.

References

IvyPanda. 2023. "Generic Dimensionality of Hospitality." December 11, 2023. https://ivypanda.com/essays/generic-dimensionality-of-hospitality/.

1. IvyPanda. "Generic Dimensionality of Hospitality." December 11, 2023. https://ivypanda.com/essays/generic-dimensionality-of-hospitality/.


Bibliography


IvyPanda. "Generic Dimensionality of Hospitality." December 11, 2023. https://ivypanda.com/essays/generic-dimensionality-of-hospitality/.

If, for any reason, you believe that this content should not be published on our website, please request its removal.
Updated:
This academic paper example has been carefully picked, checked and refined by our editorial team.
No AI was involved: only quilified experts contributed.
You are free to use it for the following purposes:
  • To find inspiration for your paper and overcome writer’s block
  • As a source of information (ensure proper referencing)
  • As a template for you assignment
1 / 1