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A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels
Author(s) -
Ming Xu,
Yan Jiao,
Xiaoming Li,
Qingfeng Cao,
Xiaoyang Wang
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0128574
Subject(s) - reservation , duration (music) , service provider , business , profit (economics) , reputation , computer science , operations research , marketing , service (business) , profit margin , margin (machine learning) , stackelberg competition , environmental economics , computer network , microeconomics , economics , art , social science , literature , machine learning , sociology , engineering
This paper presents a multi-period optimization model for high margin and zero salvage products in online distribution channels with classifying customers based on number of products required. Taking hotel customers as an example, one is regular customers who reserve rooms for one day, and the other is long term stay (LTS) customers who reserve rooms for a number of days. LTS may guarantee a specific amount of demand and generate opportunity income for a certain number of periods, meanwhile with risk of punishment incurred by overselling. By developing an operational optimization model and exploring the effects of parameters on optimal decisions, we suggest that service providers should make decisions based on the types of customers, number of products required, and duration of multi-period to reduce the loss of reputation and obtain more profit; at the same time, multi-period buying customers should buy products early. Finally, the paper conducts a numerical experiment, and the results are consistent with prevailing situations.

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