JP7316562B2 - Information provision device and information provision method - Google Patents

Description

TECHNICAL FIELD The present invention relates to an information providing apparatus and an information providing method, and more particularly to a technique for increasing room sales opportunities and improving profitability in accommodation facilities.

Accommodation facilities such as hotels and Japanese inns, in addition to selling rooms on their own websites, are outsourcing sales to so-called OTAs in order to broaden sales opportunities. One of the intentions of the lodging facility is to increase sales opportunities in this way so as to raise the booking curve as early as possible, that is, to achieve and maintain full occupancy as early as possible.

As such conventional technology related to revenue management of accommodation facilities, for example, a communication device that communicates with other devices via a network, a room sales price related to a prescribed accommodation facility and other accommodation facilities other than the prescribed accommodation facility and a customer evaluation value from at least one of the websites of each of the plurality of net agents, the site controller contracted with the prescribed accommodation facility, and the official website operated by each accommodation facility itself for a prescribed period of time. and based on the acquired information, another accommodation facility that is a competing facility that has a customer evaluation value close to the predetermined accommodation facility within a predetermined range, or a nearby accommodation facility of the predetermined accommodation facility and is specified from a predetermined terminal Identify other accommodation facilities that are competing facilities that have received the above and their room sales prices for each net agent's website or for each official website, and the customer evaluation value of the specified competing facilities and the customer evaluation of the predetermined accommodation facility Depending on the range and direction of deviation from the value, the room sales price of the prescribed accommodation facility or the competing facility on the website of the relevant net agent or the official website is raised or lowered by a prescribed percentage, and the price is sent to the prescribed accommodation facility. and notification of the proposed price to the terminal of the prescribed accommodation facility, or the proposed price to the relevant net agent or a prescribed server of the official website of the prescribed accommodation facility at the relevant WEB site and a computing device that performs at least one of a setting instruction to set the room sales price (see Patent Literature 1).

In addition, a reservation reception method for an accommodation facility in which a terminal device is connected via the Internet to a server device built on the Internet to accept reservations for accommodation facilities, wherein the number of rooms to be used in advance and the number of rooms in each room a step of receiving and storing the input of the total number of nights, which is the sum of the number of nights, a step of receiving an input of a start date of stay and the number of nights for each guest room corresponding to the number of rooms stored; A step of referring to a guest room inventory database for room inventory corresponding to the number of nights stayed, and if there is room inventory corresponding to the accommodation start date and the number of nights accepted, adding the number of nights received to the total number of nights stored in advance. A reservation acceptance method for an accommodation facility, comprising: a step of allocating; and a step of establishing a reservation when a pre-stored total number of nights is equal to the number of nights allocated (see Patent Document 2). are also proposed.

JP 2016-27461 A JP 2007-172190 A

There are many cases in which revenue managers of lodging facilities easily accept such reservations without a solid basis in terms of profitability, partly because they believe that if there are reservations for group guests, it will be easier for them to reach full occupancy early.

However, considering the profitability of the accommodation facility, it is necessary to be careful about accepting group reservations. In other words, while reservations for such group customers often include requests for discounts, the fact that the number of rooms sold at one time and the total amount of sales appear to be large can result in a significant decline in profitability. .

For example, if a guest room with a fixed maximum number is filled with group guests with low unit prices as early as half a year or a year before the date of stay, good customers with high unit prices that would otherwise have been acquired ( and its reservation request) occurs during the relevant period, there will be a situation where you have to refuse. In other words, there is a high risk of losing those good customers. Moreover, it is difficult to grasp such a situation unless one has knowledge in advance, and it becomes difficult to see the situation in which the profit of the accommodation facility during the relevant period is worse than before accepting group reservations.

Therefore, it is extremely important to accurately determine whether or not to accept group reservations, while taking into consideration the profitability of the accommodation facility, and to increase opportunities for room sales and improve profitability accordingly. SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide a technique for increasing room sales opportunities and improving profitability in accommodation facilities.

The information providing device of the present invention for solving the above problems is a storage device that holds a history DB containing information on past room sales at accommodation facilities, and receives group reservation information from a predetermined device, and receives the group reservation information. A process of extracting from the history DB information on past reservation transitions for the same period as the indicated accommodation period, and predicting, by a predetermined algorithm, the transitions in the guest room sales situation for each acceptance or rejection of the group reservation based on the information on the reservation transitions. and a process of calculating a predicted value of the total sales amount at the accommodation facility for each acceptance or non-acceptance of the group reservation based on the transition of the guest room sales situation for each of the acceptance or non-acceptance obtained in the prediction, and the prediction and an arithmetic device for executing a process of outputting value information to a predetermined terminal.

In the above-described information providing device, if the estimated value of the total sales amount when the group reservation is accepted is smaller than the estimated value of the total sales amount when the group reservation is not accepted, It may be configured such that a message to that effect is output to the terminal.

Further, in the information providing apparatus described above, the arithmetic unit estimates, as a condition for accepting the group reservation, a room sales price based on the transition of the room sales situation when the group reservation is not accepted, and the terminal may be output to

Further, in the above-described information providing device, the computing device sets the room sales price as the lower limit of the room sales price when accepting the group reservation, and the requested amount of the room sales price indicated by the group reservation information is equal to the room sales price. If the price falls below the lower price limit, the group reservation should be rejected, and if the requested room sales price indicated by the group reservation information exceeds the room price lower limit, the group reservation should be accepted. and outputting the result of any of the determinations to the terminal.

Further, in the information providing device described above, the computing device may calculate the room sales price of the accommodation facility in the past at the same time as the predetermined group reservation inquiry time indicated by the information for the predetermined period held in the history DB. , Room sales prices of other accommodation facilities, and machine learning with input of the occupancy rate of the said accommodation facilities are executed in advance, and the time of inquiry of the group reservation that received the above information, the other accommodation facilities at the time of receiving the above The room selling price may be estimated according to the room selling price and the occupancy rate of the accommodation facility.

Further, in the above-described information providing device, the computing device, in the machine learning, in the past, when the accommodation facility refused a predetermined group reservation and other accommodation facilities accepted, the room sales price of the accommodation facility, Machine learning is further executed with the room sales price of the other accommodation facility and the occupancy rate of the accommodation facility as input, and the timing of group reservation inquiry when the information is received and the room sales of the other accommodation facility at the time of receiving the information Depending on the price and the occupancy rate of the accommodation facility, the room sales price may be estimated differently depending on whether or not the group reservation is accepted.

Further, in the information providing method of the present invention, the information processing device has a storage device that holds a history DB containing information on past room sales at the accommodation facility, receives group reservation information from a predetermined device, and processes the group reservation. extract from the history DB the reservation transition information related to the past at the same time as the lodging period indicated by the information, and based on the reservation transition information, change the room sales status by acceptance or rejection of the group reservation by a predetermined algorithm. A process of predicting and a process of calculating an expected value of the total sales amount at the accommodation facility for each acceptance or rejection of the group reservation based on the progress of the guest room sales situation for each acceptance or rejection obtained by the prediction. , and a process of outputting the information of the predicted value to a predetermined terminal.

In the above-described information providing method, if the estimated total sales amount when the information processing device accepts the group reservation is smaller than the estimated total sales amount when the group reservation is not accepted. , a message to that effect may be output to the terminal.

Further, in the above-described information providing method, the information processing device, as a condition for accepting the group reservation, estimates a room sales price based on the transition of the room sales situation when the group reservation is not accepted, You can also output to the terminal.

Further, in the above-described information providing method, the information processing device sets the room sales price as the lower limit of the room sales price when accepting the group reservation, and the requested amount of the room sales price indicated by the group reservation information is If the price falls below the minimum sales price, the group reservation should be rejected, and if the requested room sales price indicated by the group reservation information exceeds the minimum sales price, the group reservation should be accepted. It may be determined, and the result of any of the determinations may be output to the terminal.

Further, in the above-described information providing method, the information processing apparatus holds room sales of the accommodation facility in the past at the same time as a predetermined group reservation inquiry time indicated by the information for a predetermined period held in the history DB. Machine learning is performed in advance with price, room sales price of other accommodation facilities, and the occupancy rate of the accommodation facility as input, and the time of group reservation inquiry when the information is received, other accommodation facilities at the time of the reception and the occupancy rate of the accommodation facility, the room sales price may be estimated.

Further, in the above-described information providing method, when the information processing device performs the machine learning, in the past, when the accommodation facility refused a predetermined group reservation and another accommodation facility accepted it, the room sales price of the accommodation facility , the sales price of the room of the other accommodation facility, and the occupancy rate of the accommodation facility are further executed by machine learning, and the time of inquiry of the group reservation at which the information is received, the guest room of the other accommodation facility at the time of the reception Depending on the sales price and the occupancy rate of the accommodation facility, the room sales price may be estimated differently depending on whether the group reservation is acceptable.

According to the present invention, it is possible to increase opportunities for room sales and improve profitability in accommodation facilities.

It is a network block diagram containing the information provision apparatus of this embodiment. It is a figure which shows the hardware structural example of the information provision apparatus in this embodiment. It is a figure which shows the data structural example of log|history DB of this embodiment. It is a figure which shows the data structural example of evaluation information DB of this embodiment. It is a figure which shows the flow example of the information provision method in this embodiment. It is a figure which shows the example 1 of a screen in this embodiment. It is a figure which shows the example 2 of a screen in this embodiment. FIG. 11 is a diagram showing a screen example 3 according to the embodiment;

--- Network configuration ---

Embodiments of the present invention will be described in detail below with reference to the drawings. FIG. 1 is a network configuration diagram including an information providing apparatus 100 of this embodiment. The information providing device 100 shown in FIG. 1 is a computer device that aims to increase room sales opportunities and improve profitability in accommodation facilities.

More specifically, the information providing device 100 can be assumed to be, for example, a server device operated by a predetermined operator affiliated with various accommodation facilities, but is not limited to this. For example, it may be a device operated by an OTA (Online Travel Agent).

On the other hand, the information providing apparatus 100 of the present embodiment outputs and presents information as a processing result to an accommodation provider (accommodation facility terminal 400 of the accommodation facility terminal 400) contracted to receive the service provided by the information providing apparatus 100. is. Of course, it is not limited to this, and it is also possible to assume terminals and systems of other various business operators as information output targets.

Therefore, the information providing device 100 is communicably connected to the accommodation terminal 400 provided by each accommodation company (and the OTA net agent server 300 from which information can be collected) via an appropriate network 10 such as the Internet.

In addition, the above-mentioned lodging business makes a contract with the above-mentioned OTA, that is, a net agent, for the purpose of selling the rooms of its own lodging facility (which can also include the concept of selling accommodation plans), and sells the rooms of its own lodging facility to this net agent. shall be outsourced.

However, this is merely an example for explanation, and may include a form in which a lodging company sells rooms on its own website. In any case, the type of sales site is not limited.

In addition, the information providing apparatus 100 of the present embodiment provides sales performance (room sales price (including the value of ), word-of-mouth information from customers, evaluation results that aggregate evaluations by each customer regarding the accommodation facility (e.g., number of stars, total evaluation score out of 5), etc., etc., at regular intervals Obtained from the net agent server 300 . These pieces of information may be acquired not only from the net agent server 300 but also from the accommodation terminal 400 of each accommodation facility.

Further, the net agent server 300 operated by the above-mentioned net agent is a server that distributes a WEB site that sells rooms entrusted by each lodging company.

This net agent server 300 receives a reservation request for an accommodation facility (and its package product, etc.) from the user terminal 200 of the customer who sells the guest rooms, and executes reservation processing for the accommodation facility and accompanying inventory management processing. . In addition, posts of word-of-mouth information about the accommodation facility, evaluation scores for each item such as service, guest room, location, and meals, and overall scores for the accommodation facility are accepted.

In addition, the net agent server 300 aggregates the scores and the like of the above-mentioned evaluation submissions and publishes them on the website in a simple form such as the number of stars or a 5-level evaluation.

Note that the user terminal 200 is a terminal that accesses the above-described WEB site according to the customer's operation, and performs a reservation request, that is, a purchase process, etc. for a room that is on sale. Specifically, general information processing terminals capable of network communication, such as PCs, smartphones, and tablet terminals, are assumed. Customers who operate the user terminal 200 can be assumed to be those who want to arrange personal trips or business trips for themselves or their families, as well as business operators who manage group trips. Of course, in the present embodiment, description will be given focusing on a person who makes a group reservation as a customer who operates the user terminal 200 described above.

Further, the accommodation facility terminal 400 is a terminal operated by an accommodation company, and serves as a terminal that receives useful information regarding acceptance or rejection of a group reservation from the information providing device 100 and outputs the information on a display or the like. Specifically, general information processing terminals capable of network communication, such as PCs, smartphones, and tablet terminals, are assumed.
--- Hardware configuration ---

Further, the hardware configuration of the information providing apparatus 100 of this embodiment is as shown in FIG. The information providing device 100 includes at least a storage device 101 , a memory 103 , an arithmetic device 104 and a communication device 105 .
Among them, the storage device 101 is composed of an appropriate non-volatile storage element such as an SSD (Solid State Drive) or a hard disk drive.
Also, the memory 103 is composed of a volatile memory element such as a RAM.

Arithmetic device 104 is a CPU that reads program 102 stored in storage device 101 into memory 103 and executes it, performs overall control of the device itself, and performs various determinations, calculations, and control processes.

Also, the communication device 105 can be assumed to be a network interface card that connects to an appropriate network 10 such as the Internet and handles communication processing with other devices such as the user terminal 200 , the net agent server 300 and the accommodation facility terminal 400 .

In addition to the configuration described above, the information providing apparatus 100 also includes an input device such as a keyboard and a mouse for accepting key input and voice input from the user, and an output device such as a display for displaying data processed by the arithmetic unit 104. may be

Note that the storage device 101 has at least a machine learning engine 110 in the program 102 for implementing the functions necessary for the information providing device of this embodiment. The details of this machine learning engine 110 will be described later.

In addition to the program 102 described above, the storage device 101 also stores at least a history DB 125 and an evaluation information DB 126 . Details of the history DB 125 and the evaluation information DB 126 will be described later.
--- Data structure example ---
Next, the database used by the information providing apparatus 100 of this embodiment will be described. FIG. 3 shows an example of the history DB 125 in this embodiment.
The history DB 125 is a database that accumulates sales results for each predetermined period regarding each accommodation facility.

The data structure includes a project ID that uniquely identifies each project, a facility ID that indicates the accommodation facility that is the target of the project, the reservation acceptance period, the target period (accommodation period), whether the reservation is accepted, the sales unit price (= It is a set of records in which data such as room sales price indicated in the reservation request), sales amount, lodger attributes (group/individual, nationality, number of people, representative, handling agent, etc.) are associated.

Also, FIG. 4 shows an example of the evaluation information DB 126 in this embodiment. The evaluation information DB 126 in this embodiment is a database in which evaluation results acquired from each customer and aggregated on the website of the above-mentioned net agent server 300 regarding each accommodation facility are accumulated.

The data structure is a record that associates data such as the evaluation period, total score, and evaluation score for each item (e.g. service, guest room, location, meal) with the facility ID that uniquely identifies each accommodation facility as a key. is a collection of
--- Flow example ---

The actual procedure of the information providing method according to this embodiment will be described below with reference to the drawings. Various operations corresponding to the information providing method described below are realized by a program that the information providing apparatus 100 reads out to a memory or the like and executes. This program is composed of codes for performing various operations described below.

FIG. 5 is a diagram showing a flow example of an information providing method according to this embodiment. In this case, the information providing apparatus 100 first receives group reservation information (group reservation request) from the user terminal 200 or the net agent server 300, or acquires it from the history DB 125 of its own storage device 101 ( s10).

Subsequently, the information providing apparatus 100 provides information on the reservation transition of the accommodation facility regarding the past at the same time as the accommodation period indicated by the group reservation information obtained in the above s10 (“target period” in the record of the history DB 125). , is extracted from the history DB 125 (s11).

In this case, the information providing apparatus 100 selects the facility ID (the ID of the accommodation facility for which the group reservation was made), the date when the request for the group reservation was received, and the corresponding accommodation period. A record is searched for in the history DB 125 using the date as a key. As a result, it is possible to extract the records of the reservations received for the accommodation facility during the period from the reservation acceptance time to the lodging time.

Then, the information providing apparatus 100 generates a so-called booking curve from the records extracted as described above. For the method of generating such a booking curve itself, existing technology shall be used as appropriate. The generation of this booking curve corresponds to the extraction of reservation transition information.

Subsequently, the information providing apparatus 100 predicts, by a predetermined algorithm, the transition of the room sales status for each group reservation, based on the reservation transition information obtained in s11, that is, the booking curve (s12).

The algorithm described above in the present embodiment assumes the machine learning engine 110 as an example, although not particularly limited. In this case, the machine learning engine 110 generates reservations for the accommodation facility, the type of reservation (individual/group), acceptability, and acceptability at various times (e.g., months, seasons, national holiday seasons, etc.). is used as learning data to learn the transition pattern of the room sales situation when a certain group reservation is accepted or rejected.

In addition, the information providing apparatus 100 determines whether or not the group reservation to be processed this time (information obtained in s10) can be accepted or not, based on the transition of the room sales status by acceptance or non-acceptance obtained in the prediction in s12. An expected total sales amount at another accommodation facility is calculated (s13).

In this case, the information providing apparatus 100 accepts the group reservation at the time of reception, that is, deletes the guest room inventory for the group reservation, and rejects the group reservation to maintain the guest room inventory. Calculation is performed with two patterns of assumptions.

In the calculation on the premise that the group reservation is accepted, the information providing device 100 calculates the sales amount accompanying the group reservation (multiplying the sales unit price by the number of people indicated by the lodger attribute) and the period from the reception time to the target time (group Another reservation newly accepted and its sales amount (with the reduction in room inventory for the reservation) multiplied by the median or average unit selling price) to calculate the above-mentioned forecast value.

In addition, in the calculation on the premise that the group reservation is rejected, the information providing device 100 does not include the sales amount associated with the group reservation in the calculation, and during the period from the reception time to the target time Another reservation newly accepted and its sales amount (the cumulative number of reservations indicated by the booking curve, the median and average number of guests per reservation and the median and average sales unit price in the relevant period) multiplied values) to calculate the expected value above.
Of course, such a calculation method and its concept are only examples, and other methods (such as the already-described machine learning engine 110) may be adopted as appropriate.

In addition, the information providing apparatus 100 sends the information (see screen 600 in FIG. 6) of the estimated total sales amount at the accommodation facility calculated for each acceptance or rejection of the group reservation in s13 to the accommodation facility terminal 400 described above. output (s14) and terminate the process.

As shown in FIG. 6, when outputting such information, the information providing device 100 changes the estimated value of the total sales amount when the group reservation is accepted to the estimated total sales amount when the group reservation is not accepted. If the value is smaller than the value, if the information 601 to that effect is clearly displayed, it is easy to support the judgment of the revenue manager of the accommodation facility.
<Further Form Example 1>

In addition, as a condition for accepting a group reservation, the information providing device 100 estimates a room sales price 701 (see screen 700 in FIG. 7) based on the transition of the room sales situation when the group reservation is not accepted, It is preferable to output to the accommodation facility terminal 400 . This estimation of the room sales price (room unit sales price) is performed, for example, by dividing the expected total sales amount calculated in s13 by the number of reservations based on the above-described booking curve.

It goes without saying that the machine learning engine 110 can also be used to estimate the room selling price (unit room selling price). In that case, the information providing apparatus 100 displays the room sales price of the accommodation facility and the room sales of other accommodation facilities in the past at the same time as the predetermined group reservation inquiry time indicated by the information for the predetermined period held in the history DB 125 Machine learning is executed in advance by giving the machine learning engine 110 the price and the occupancy rate of the accommodation facility as learning data. Then, the time when the group reservation information to be considered is received, that is, the reception time (inquiry time), the room sales price of other accommodation facilities at the time of receiving the information, and the occupancy rate of the accommodation facility, are machine-learned. This information is input to the engine 110 to estimate the room sales price.

In addition, the information providing device 100 sets the above-mentioned room selling price as the lower limit of the room selling price when accepting the group reservation, and the requested amount of the room selling price indicated by the information of the group reservation is below the lower limit of the room selling price. In this case, it is more preferable to determine that the group reservation should be rejected and output information 801 to that effect (see screen 800 in FIG. 8). Of course, if the requested room sales price indicated by the group reservation information exceeds the minimum room sales price, it is determined that the group reservation should be accepted, and information to that effect is output.
<Further Form Example 2>

In addition, when the information providing device 100 performs machine learning in the machine learning engine 110, in the past, when the above-mentioned accommodation facility refuses a predetermined group reservation and another accommodation facility accepts, the room sales price of the accommodation facility, Machine learning may be further performed using the room sales prices of other accommodation facilities and the occupancy rates of the accommodation facilities as learning data.

Among the information given as learning data, the value of the "facility ID" column of each record in the history DB 125 is different for the information when the above-mentioned accommodation facility refuses a predetermined group reservation and another accommodation facility accepts it. However, in the record pair with the same value in the ``guest attribute'' column, the ``reservation acceptance availability'' column identifies records where one is ``n'' (i.e., rejection) and the other is ``y'' (i.e., acceptance). shall be That is, it identifies records in which a group reservation was rejected at one accommodation and accepted at another.

In that case, the information providing device 100 receives the group reservation to be considered (inquiry time), the room sales price of other accommodation facilities at the time of the reception, and the occupancy rate of the accommodation facility. 110 to estimate different room sales prices depending on whether the group reservation is accepted or not. In this case, as the other accommodation facilities, it is preferable to specify in advance those accommodation facilities that have similar overall scores in the evaluation information DB 127 within a predetermined range, ie, competing accommodation facilities, as processing targets.

The room sales price estimated in this way will not be calculated if a group reservation that has changed from refusal to acceptance between lodging facilities as a result is taken from the lodging facility to another competing lodging facility, that is, if the lodging facility refuses the group reservation. In addition, it can suggest an increase (expected sales increase) or decrease in sales prices due to changes in demand on the same day that increase throughout the relevant region.

Although the best mode for carrying out the present invention has been specifically described above, the present invention is not limited to this, and can be variously modified without departing from the scope of the invention.

According to this embodiment, it is possible to accurately determine whether or not to accept reservations from groups of guests while taking into account the profitability of the accommodation facility, thereby increasing opportunities for room sales and improving profitability accordingly. .

10 Network 100 Information Providing Device 101 Storage Device 102 Program 103 Memory 104 Arithmetic Device 105 Communication Device 110 Machine Learning Engine 125 History DB
126 Evaluation information DB
200 User terminal 300 Net agent server 400 Accommodation facility terminal

Claims (12)

A storage device that holds a history DB containing information on past room sales at accommodation facilities;
Receiving group reservation information from a predetermined device, extracting from the history DB information on reservation transitions in the past at the same period as the lodging period indicated by the group reservation information, and based on the reservation transition information, based on the group reservation information A process of predicting, by a predetermined algorithm, changes in room sales status by acceptance or non-acceptance, and said lodging by acceptance or non-acceptance of said group reservation based on the transition of room sales status by acceptance obtained by said prediction. A computing device that executes a process of calculating an expected value of the total sales amount at the facility and a process of outputting the information of the expected value to a predetermined terminal;
An information providing device comprising: The computing device is
If the expected total sales amount when the group reservation is accepted is smaller than the expected total sales amount when the group reservation is not accepted, that fact is output to the terminal.
2. An information providing apparatus according to claim 1, characterized by: The computing device is
As a condition for accepting the group reservation, a room sales price is estimated based on the transition of the room sales situation when the group reservation is not accepted, and is output to the terminal.
3. The information providing apparatus according to claim 2, characterized by: The computing device is
The above-mentioned room sales price shall be the minimum room sales price when accepting the said group reservation, and if the requested amount of the room sales price indicated by the group reservation information is below the said minimum room sales price, the group reservation shall be refused. If the requested room sales price indicated by the group reservation information exceeds the minimum room sales price, it is determined that the group reservation should be accepted, and the result of any of the above judgments is output to the terminal. is to
4. The information providing device according to claim 3, characterized by: The computing device is
The room sales price of the accommodation facility, the room sales price of other accommodation facilities, and the price of the accommodation facility in the past at the same time as the predetermined group reservation inquiry time indicated by the information for the predetermined period held in the history DB Machine learning with the occupancy rate as input is performed in advance, and the timing of the group reservation inquiry that received the information, the room sales price of other accommodation facilities at the time of the reception, and the occupancy rate of the accommodation facility , which estimates the room sales price,
4. The information providing device according to claim 3, characterized by: The computing device is
In the machine learning, in the past, when the accommodation facility refused a predetermined group reservation and another accommodation facility accepted it, the room sales price of the accommodation facility, the room sales price of the other accommodation facility, and the accommodation facility Machine learning is further performed with the occupancy rate as input, and the time of inquiry for the group reservation that received the information, the room sales price of other accommodation facilities at the time of receiving the information, and the occupancy rate of the accommodation facility. Estimates the room sales price that varies depending on whether group reservations are accepted,
6. The information providing device according to claim 5, characterized by: The information processing device
Equipped with a storage device that holds a history DB containing information on past room sales at the accommodation facility,
Receiving group reservation information from a predetermined device, extracting from the history DB information on reservation transitions in the past at the same period as the lodging period indicated by the group reservation information, and based on the reservation transition information, based on the group reservation information A process of predicting, by a predetermined algorithm, changes in room sales status by acceptance or non-acceptance, and said lodging by acceptance or non-acceptance of said group reservation based on the transition of room sales status by acceptance obtained by said prediction. A process of calculating an expected value of the total sales amount at the facility, and a process of outputting the information of the expected value to a predetermined terminal;
An information provision method characterized by executing The information processing device
If the expected total sales amount when the group reservation is accepted is smaller than the expected total sales amount when the group reservation is not accepted, outputting that fact to the terminal;
8. The information providing method according to claim 7, characterized by: The information processing device
As a condition for accepting the group reservation, estimate a room sales price based on the transition of the room sales situation when the group reservation is not accepted, and output to the terminal;
9. The information providing method according to claim 8, characterized by: The information processing device
The above-mentioned room sales price shall be the minimum room sales price when accepting the said group reservation, and if the requested amount of the room sales price indicated by the group reservation information is below the said minimum room sales price, the group reservation shall be refused. If the requested room sales price indicated by the group reservation information exceeds the minimum room sales price, it is determined that the group reservation should be accepted, and the result of any of the above judgments is output to the terminal. do,
10. The information providing method according to claim 9, characterized by: The information processing device
The room sales price of the accommodation facility, the room sales price of other accommodation facilities, and the price of the accommodation facility in the past at the same time as the predetermined group reservation inquiry time indicated by the information for the predetermined period held in the history DB Machine learning with the occupancy rate as input is performed in advance, and the timing of the group reservation inquiry that received the information, the room sales price of other accommodation facilities at the time of the reception, and the occupancy rate of the accommodation facility , estimating the room sales price;
10. The information providing method according to claim 9, characterized by: The information processing device
In the machine learning, in the past, when the accommodation facility refused a predetermined group reservation and another accommodation facility accepted it, the room sales price of the accommodation facility, the room sales price of the other accommodation facility, and the accommodation facility Machine learning is further performed with the occupancy rate as input, and the time of inquiry for the group reservation that received the information, the room sales price of other accommodation facilities at the time of receiving the information, and the occupancy rate of the accommodation facility. estimating a different room sales price depending on the acceptance or rejection of group bookings;
12. The information providing method according to claim 11, characterized by: