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Analysis on the Number of Hotel Delivery Robots Based on Queuing Theory

Author(s)

Ruining Zhang, Yi Li, Xiao Hu

Affiliation(s)

Chongqing University of Posts and Telecommunications, Chongqing, China

Abstract

The purpose of this paper is to investigate the problem of order queue congestion caused by random arrival of orders during peak hours when hotels use robots for delivery, to optimize customer waiting time. This can determine the optimal number of robots while ensuring service quality and controlling the total cost of robots. This study selects a four-star hotel in South Korea as a case study and constructs a cost model for the order queuing system during peak hours based on queuing theory. This model comprehensively measures the application effectiveness of different numbers of robots by calculating the waiting cost per unit time of customers and the total cost per unit time of robots. To meet the diverse needs of different hotels in cost control and service quality, the model also introduces different weights, which can adjust for the differences in cost and service quality preferences of different hotel types. The research results indicate that as the number of robots increases, the total system cost shows a trend of first decreasing and then increasing. In the initial stage, adding robots can effectively reduce customer waiting time and thus lower overall waiting costs. However, when the number of robots reaches a certain critical value, the total system cost will begin to rise, mainly due to the increase in costs caused by too many robots. By identifying the lowest point of system cost and researching the optimal number of robots, the best balance between service quality and cost expenditure has been achieved. This study not only provides theoretical support for hotel managers to develop robot quantity scheduling plans during peak hours, but also promotes the application and development of robot delivery services in the hotel industry to a certain extent.

Keywords

Hotel Robots; Queuing Theory; Number of Robots; Robot Delivery; Random Orders

References

[1] Sobolewski Stanley Douglas. Room service principles and practices: An exploratory study. University of Nevada, Las Vegas, 2012: 1-179. [2] Powell Patricia Hunter, and Diane Watson. Service unseen: The hotel room attendant at work. International Journal of Hospitality Management, 2006, 25(2): 297-312. [3] Bowen John, and Elizabeth Whalen. Trends that are changing travel and tourism. Worldwide Hospitality and Tourism Themes, 2017, 9(6): 592-602. [4] Çakar Kadir, Şehmus Aykol. Understanding travellers’ reactions to robotic services: a multiple case study approach of robotic hotels. Journal of Hospitality and Tourism Technology, 2021, 12(1): 155-174. [5] Guan Xinhua, Gong Jinhong, Li Mingjie, Tzung-Cheng Huan. Exploring key factors influencing customer behavioral intention in robot restaurants. International Journal of Contemporary Hospitality Management, 2022, 34(9): 3482-3501. [6] Ivanov Stanislav, Craig Webster, and Katerina Berezina. Robotics in tourism and hospitality. Handbook of e-Tourism, 2022: 1873-1899. [7] Kim Seongseop (Sam), Jungkeun Kim, Frank Badu-Baiden, Marilyn Giroux, Youngjoon Choi.Preference for robot service or human service in hotels? Impacts of the COVID-19 pandemic. International Journal of Hospitality Management, 2021, 93: 102795. [8] Lin Ingrid Y., Anna S. Mattila. The value of service robots from the hotel guest’s perspective: A mixed-method approach. International Journal of Hospitality Management, 2021, 94: 102876. [9] Ivanov, Stanislav Hristov, and Craig Webster. Adoption of robots, artificial intelligence and service automation by travel, tourism and hospitality companies-a cost-benefit analysis. Artificial Intelligence and Service Automation by Travel, Tourism and Hospitality Companies-A Cost-Benefit Analysis, 2017, October: 19-21. [10] Qiu Hailian, Li Minglong, Shu Boyang, Bai Billy. Enhancing hospitality experience with service robots: the mediating role of rapport building. Journal of Hospitality Marketing & Management, 2020, 29(3): 247-268. [11] Ali Bayad Jamal, Bayar Gardi, Baban Jabbar Othman, Shahla Ali Ahmed, Nechirwan Burhan Ismael, Pshdar Abdalla Hamza, Hassan Mahmood Aziz. Hotel Service Quality: The Impact of Service Quality on Customer Satisfaction in Hospitality. International Journal of Engineering, Business and Management, 2021, 5(3): 14-28. [12] Lee Woojin, Sung Il Kwag, and Young Dae Ko. Optimal capacity and operation design of a robot logistics system for the hotel industry. Tourism Management, 2020, 76: 103971. [13] Lee Woojin, and Young Dae Ko. Operation policy of multi-capacity logistic robots in hotel industry. International Journal of Contemporary Hospitality Management, 2021, 33(5): 1482-1506. [14] Liu Jiahao, Gu Tao, Liao Zhixue. Operation design of a robot logistics system considering demand fluctuations in the hotel industry. International Journal of Contemporary Hospitality Management, 2024, 36(1): 113-135. [15] Yaduvanshi, Deepak, Ashu Sharma, and PrafulVijay More. Application of Queuing Theory to Optimize Waiting-Time in Hospital Operations. Operations and Supply Chain Management: An International Journal, 2019: 165-174. [16] Mpeta Kolentino N., Otsile R. Selaotswe. Application of Queuing Theory to Analyse an ATM Queuing System//Intelligent Computing & Optimization: Proceedings of the 4th International Conference on Intelligent Computing and Optimization 2021 (ICO2021) 3. Springer International Publishing, 2022: 888-892. [17] Habbache Fares, Messaoud Amir Maiza. Queue management system (QMS) as a recent trend in improving service's quality. Economic Researcher Review, 2021, 9(1): 66-81.