Publication Type
Journal Article
Version
submittedVersion
Publication Date
7-2021
Abstract
The limousine service in luxury hotels is an integral component of the whole customer journey in the hospitality industry. One of the largest hotels in Singapore manages a fleet of both in-house and outsourced vehicles around the clock, serving 9,000 trips per month on average. The need for vehicles may scale up rapidly, especially during special events and festive periods in the country. The excess demand is met by having additional outsourced vehicles on standby, incurring millions of dollars of additional expenses per year for the hotel. Determining the required number of limousines by hour of the day is a challenging service capacity planning problem. In this paper, a recent transformational journey to manage this problem for the hotel is introduced, having driven up to S$3.2 million of savings per year while improving the service level. The approach builds on widely available open-source statistical and spreadsheet optimization tools, along with robotic process automation, to optimize the schedule of the hotel's fleet of limousines and drivers and to support decision making for planners and controllers to cultivate sustained business value.
Keywords
demand forecasting, scheduling, process automation, hospitality
Discipline
Finance and Financial Management | Operations and Supply Chain Management
Research Areas
Quantitative Finance
Publication
INFORMS Journal on Applied Analytics
Volume
51
Issue
4
First Page
280
Last Page
296
ISSN
2644-0865
Identifier
10.1287/inte.2021.1079
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Citation
LIU, Peng; CHEN, Ying; and TEO, Chung-Piaw.
Limousine service management: Capacity planning with predictive analytics and optimization. (2021). INFORMS Journal on Applied Analytics. 51, (4), 280-296.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/7044
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1287/inte.2021.1079
Included in
Finance and Financial Management Commons, Operations and Supply Chain Management Commons