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A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels.

Xu M, Jiao Y, Li X, Cao Q, Wang X - PLoS ONE (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: College of Tourism and Service Management, Nankai University, Tianjin, 300074, China.

ABSTRACT
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.

No MeSH data available.


Room sale statuses without accepting LTS.
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pone.0128574.g001: Room sale statuses without accepting LTS.

Mentions: Generally, multi-item buying, such as 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. To clearly describe the problem, we take hotels industry as an example, and consider a scenario under which the LTS customer intends to reserve n rooms for T day before T0 days from the start time of LTS. As Fig 1(a) shows, at the reservation time for LTS, all of the rooms on the third day have been sold; meanwhile, rooms are available on other days. The hotel should consider the room sale status at the reservation time for LTS and predict the room sale status after the ending date of LTS. The consideration of these times facilitates the comparison of expected profits during LTS according to two situations.


A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels.

Xu M, Jiao Y, Li X, Cao Q, Wang X - PLoS ONE (2015)

Room sale statuses without accepting LTS.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493130&req=5

pone.0128574.g001: Room sale statuses without accepting LTS.
Mentions: Generally, multi-item buying, such as 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. To clearly describe the problem, we take hotels industry as an example, and consider a scenario under which the LTS customer intends to reserve n rooms for T day before T0 days from the start time of LTS. As Fig 1(a) shows, at the reservation time for LTS, all of the rooms on the third day have been sold; meanwhile, rooms are available on other days. The hotel should consider the room sale status at the reservation time for LTS and predict the room sale status after the ending date of LTS. The consideration of these times facilitates the comparison of expected profits during LTS according to two situations.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: College of Tourism and Service Management, Nankai University, Tianjin, 300074, China.

ABSTRACT
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.

No MeSH data available.