Limits...
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 with accepting LTS.
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pone.0128574.g002: Room sale statuses with accepting LTS.

Mentions: The room sale status at the ending date of LTS without accepting LTS is presented in Fig 1(b). Rooms on dates 3 and T-3 are sold out; by contrast, rooms are available on the other days. By comparing the two statuses in Figs 1(b) and 2, we find that these available rooms will incur opportunity losses, as Fig 2 shows. The marginal profit of each sold room is considerable, and the unit variable cost is lower than the high fixed cost [8]. Specifically, (1) for date T-3, the room sale statuses under two situations are the same by simply reserving n rooms for the LTS customer instead of regular customers. (2) For dates 1, 4, T-4, and T-1, the hotel will lose some regular customers, but LTS customers will replenish the empty rooms. (3) For date T-2 and T, the hotel will expand the room sales and not lose any regular customer.


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 with accepting LTS.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0128574.g002: Room sale statuses with accepting LTS.
Mentions: The room sale status at the ending date of LTS without accepting LTS is presented in Fig 1(b). Rooms on dates 3 and T-3 are sold out; by contrast, rooms are available on the other days. By comparing the two statuses in Figs 1(b) and 2, we find that these available rooms will incur opportunity losses, as Fig 2 shows. The marginal profit of each sold room is considerable, and the unit variable cost is lower than the high fixed cost [8]. Specifically, (1) for date T-3, the room sale statuses under two situations are the same by simply reserving n rooms for the LTS customer instead of regular customers. (2) For dates 1, 4, T-4, and T-1, the hotel will lose some regular customers, but LTS customers will replenish the empty rooms. (3) For date T-2 and T, the hotel will expand the room sales and not lose any regular customer.

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.