Accommodation price calculation method and accommodation price calculation program

Abstract

To provide a method and program for calculating accommodation prices that can accurately estimate future monthly or annual sales figures for hotels, inns, and other accommodation facilities. [Solution] A method for calculating accommodation prices using a computer, which performs the following steps (1) to (5): (1) A step to calculate the monthly average accommodation prices Psave, Pwave, and Ptave for each room type 11 available at a specific hotel 1a in a specific month of the year under specific accommodation conditions. (2) A step to calculate the monthly average accommodation price PMave for the total number of rooms at the specific hotel 1a in a specific month under specific accommodation conditions. (3) A step to obtain the accompaniment coefficient 14 for each room type 11 from a specific accompaniment coefficient database DB2. (4) A step to calculate the average accompaniment coefficient ave14 for the total number of rooms at the specific hotel 1a. (5) A step to calculate the monthly average accommodation price Padr1 for the number of people corresponding to the average accompaniment coefficient ave14 for the specific hotel 1a in a specific month under specific conditions.

Description

Technical Field

[0001] The present invention relates to a method for calculating accommodation prices and an accommodation price calculation program.

Background Art

[0002] Conventionally, the sound management and improvement of the profitability of accommodation facilities such as hotels and inns have been important issues. To solve these issues, the future sales amount of accommodation facilities is predicted (estimated). In accommodation facilities, the unit price (accommodation price) is set for each type of guest room. Therefore, by using factors such as the unit price for each type of guest room, the number of guests staying, and the number of guest rooms for each type of guest room provided by the accommodation facility, the approximate monthly or annual sales amount of the accommodation facility can be estimated.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in reality, due to factors such as the type of guest room and the accommodation period (season), the sales amount fluctuates. Therefore, it is difficult to estimate the future sales amount based on the simply set unit price. Also, even for the same type of guest room, the unit price to be set varies depending on the area (region) where the accommodation facility is located, the number of companions, the presence or absence of meals, etc. Since there are many factors that make up the sales amount and they can be uncertain fluctuating factors, it is very difficult to estimate the future sales amount of the entire accommodation facility.

[0005] In view of the above circumstances, the present invention is made, and an exemplary problem is to provide an accommodation price calculation method and an accommodation price calculation program that can accurately estimate the future monthly or annual sales amount of the entire accommodation facility in accommodation facilities such as hotels and inns. [Means for solving the problem]

[0006] To solve the above problems, the accommodation price calculation method, as an exemplary aspect of the present invention, has the following configuration.

[0007] Multiple accommodations are divided into multiple areas, and each of these areas contains multiple accommodations that are part of the aforementioned multiple accommodations. A method for calculating accommodation prices related to a specified facility, in a case where one area selected from among the aforementioned multiple areas is defined as a specified area, and one accommodation facility selected from among the aforementioned multiple accommodation facilities located within the specified area is defined as a specified facility, the method for calculating accommodation prices related to the specified facility is as follows: A method for calculating accommodation prices using a computer, which performs the following steps (1) to (5). (1) A process of calculating the average monthly accommodation price for each room type provided by the specified facility in a specific month of the year, for a specific number of people and under specific conditions, as an average specified accommodation price for multiple room types. (2) A step of calculating the monthly average accommodation price for the total number of rooms in the specified facility in the specified month, under the specified number of people and specified conditions, by apportioning the average specified accommodation price for each room type according to the proportion of the total number of rooms that each room type occupies, and summing them up, thereby obtaining a single overall average specified accommodation price. (3) A step of obtaining multiple companion coefficients for each room type as multiple room type specific companion coefficients from a specific companion coefficient database in which the room types and companion coefficients in the specified facility are mutually associated. (4) A step of calculating the average companion coefficient for the total number of rooms in the specified facility as a single overall average companion coefficient by apportioning the multiple room type specific companion coefficients according to the proportion of the total number of rooms in the specified facility that each room type occupies. (5) A step of calculating the monthly average accommodation price for the number of people corresponding to the overall average specific companion coefficient for the specific month of the specific facility, based on the overall average specific accommodation price and the overall average specific companion coefficient, as the first specific accommodation price.

[0008] Furthermore, a lodging price calculation program, as another exemplary aspect of the present invention, has the following configuration.

[0009] Multiple accommodations are divided into multiple areas, and each of these areas contains multiple accommodations that are part of the aforementioned multiple accommodations. A lodging price calculation program for calculating the lodging price associated with a specified facility, in a case where one area selected from among the aforementioned multiple areas is defined as a specified area, and one lodging facility selected from among the aforementioned multiple lodging facilities located within the specified area is defined as a specified facility, the program calculates the lodging price associated with the specified facility. A program for calculating accommodation prices that instructs a computer to perform the following steps (1) to (5). (1) A process of calculating the average monthly accommodation price for each room type provided by the specified facility in a specific month of the year, for a specific number of people and under specific conditions, as an average specified accommodation price for multiple room types. (2) A step of calculating the monthly average accommodation price for the total number of rooms in the specified facility in the specified month, under the specified number of people and specified conditions, by apportioning the average specified accommodation price for each room type according to the proportion of the total number of rooms that each room type occupies, and summing them up, thereby obtaining a single overall average specified accommodation price. (3) A step of obtaining multiple companion coefficients for each room type as multiple room type specific companion coefficients from a specific companion coefficient database in which the room types and companion coefficients in the specified facility are mutually associated. (4) A step of calculating the average companion coefficient for the total number of rooms in the specified facility as a single overall average companion coefficient by apportioning the multiple room type specific companion coefficients according to the proportion of the total number of rooms in the specified facility that each room type occupies. (5) A step of calculating the monthly average accommodation price for the number of people corresponding to the overall average specific companion coefficient for the specific month of the specific facility, based on the overall average specific accommodation price and the overall average specific average companion coefficient, as the first specific accommodation price.

[0010] Further objects or other features of the present invention will be revealed by preferred embodiments described below with reference to the accompanying drawings. [Effects of the Invention]

[0011] According to the present invention, it is possible to provide a method and program for calculating accommodation prices that can accurately estimate future monthly or annual sales figures for the entire accommodation facility, such as hotels and inns. [Brief explanation of the drawing]

[0012] [Figure 1] This is a schematic diagram showing how multiple hotels according to Embodiment 1 are located within multiple areas. [Figure 2] This is a schematic diagram of the overall configuration of the ADR estimation system for realizing the ADR estimation method according to Embodiment 1. [Figure 3] This is a flowchart illustrating the ADR estimation method according to Embodiment 1. [Figure 4] This is a data structure diagram of a specific hotel database. [Figure 5] This is a data structure diagram of the specific companion coefficient database. [Modes for carrying out the invention]

[0013] Embodiments of the present invention will be described in detail below with reference to the drawings.

[0014] [Embodiment 1] <Overall Structure> FIG. 1 is a schematic diagram showing the locations of a plurality of hotels (accommodation facilities) 1 to 3 according to Embodiment 1 of the present invention within a plurality of areas 10 to 30. The areas 10 to 30 are regions partitioned for each predetermined area. A plurality of hotels 1 are located within area 10, a plurality of hotels 2 are located within area 20, and a plurality of hotels 3 are located within area 30.

[0015] Each partition of the areas 10 to 30 may be arbitrarily set based on appropriate conditions. Generally, an area is set for each city or region, or a group of a plurality of hotels that are generally common in terms of the accommodation customer layer, purpose of use, set unit price, etc., such as a group being set as one area around a tourist destination. Also, the city or region may be divided into regions by a circle having a certain length of radius or a quadrilateral (such as a square or rectangle) having a certain length of side, and an area may be set for each divided circular area or rectangular area.

[0016] In addition, in the present Embodiment 1, regarding the accommodation price calculation method and the accommodation price calculation program of a specific hotel (specific facility) 1a among the plurality of hotels 1 located within a specific area 10a of the plurality of areas 10 to 30, an explanation will be given. Hereinafter, the accommodation price calculation method will also be referred to as the ADR estimation method, the accommodation price calculation system as a system for realizing the ADR estimation method will also be referred to as the ADR estimation system, and the accommodation price calculation program will also be referred to as the ADR estimation program. Here, ADR is price information known as the average daily rate of a guest room, and generally, it is a numerical value obtained by total sales amount / number of guest rooms. However, by considering various other factors, more detailed and accurate estimation is possible.

[0017] <System Configuration> Figure 2 is a schematic diagram of the overall configuration of the ADR estimation system S for realizing the ADR estimation method (accommodation price calculation method) according to this embodiment 1. The ADR estimation system S is substantially configured with a computer 5, which may have an input unit 6 such as a keyboard and mouse and an output unit 7 such as a display. The computer 5 may be connected to other computers 8 or internet sites 9, for example, via a network W such as the internet.

[0018] Computer 5 has a CPU (Arithmetic Processing Unit) 5a and memory 5b inside. The CPU 5a functions as the main part of computer 5, and when the ADR estimation program P (described later) is started, it executes various processes based on various calculations. Memory 5b functions as a storage device, and the ADR estimation program P is stored inside it. It may also be used to temporarily store various intermediate parameters based on the calculations of the CPU 5a, and to store various databases (specific hotel database DB1, specific companion coefficient database DB2, etc.) (described later).

[0019] <Operation Description> The following describes each step of the ADR estimation method executed when the ADR estimation program P according to this embodiment 1 is started. Figure 3 is a flowchart for explaining the ADR estimation method. Although Figure 3 shows up to (S.8), in embodiment 1 the series of processes is completed up to (S.5), so the process up to (S.5) will be explained here. Processes from (S.6) to (S.8) can be added separately as appropriate to the ADR estimation method.

[0020] First, we identify a specific hotel, designated as Hotel 1a, for which we want to estimate the ADR, that is, for which we want to calculate the accommodation price equivalent to the average room rate (S.0). Hotel 1a is located within a specific area 10a, which is one area selected from among 10 to 30 areas, and is identified as Hotel 1a from among multiple hotels 1 within specific area 10a.

[0021] Figure 4 is a data structure diagram of the specific hotel database DB1, in which data related to a specific hotel 1a is interconnected. Within the specific hotel database DB1, the room types 11, the number of rooms for each room type 12, and the accommodation prices 13 set for each room type of the specific hotel 1a are interconnected. Note that although Figure 4 only shows the accommodation prices 13 for January, February, and March (specific months), in reality, information on accommodation prices 13 for April and beyond may also be stored and interconnected.

[0022] Here, room type 11 refers to the different room types, such as a single room (one single bed), a double room (one double bed), or a twin room (two single beds). The accommodation price 13 set for each room may be, for example, the price per night set by the accommodation facility.

[0023] If information such as accommodation prices 13 can be obtained directly from specific hotel 1a, that information may be stored in the specific hotel database DB1. If information cannot be obtained directly from specific hotel 1a, accommodation prices 13 may be stored in the specific hotel database DB1 based on information obtained, for example, from the homepage of specific hotel 1a's website. Furthermore, if information such as accommodation prices 13 has not yet been set, for example, because specific hotel 1a is not yet open, estimated price information 13 may be stored in the specific hotel database DB1 based on information from other hotels 1 in the area 10 where specific hotel 1a is located.

[0024] In Embodiment 1, the accommodation price 13 is set as the price for "2 people, 1 night, room only" for any room type 11. Of course, this condition may be set to other conditions as appropriate. Here, if the accommodation price 13 does not fluctuate within a month, one price information is sufficient, but if it fluctuates within a month depending on busy or slow seasons, the daily accommodation prices 13 may be stored in the specific hotel database DB1.

[0025] (1st step) After a specific hotel 1a is identified, the computer 5 performs a process (hereinafter referred to as the first process) to calculate the average monthly accommodation price for each room type 11 available at the specific facility for a specific number of people and under specific conditions in a specific month of the year, as an average specific accommodation price for multiple room types (S.1).

[0026] In this embodiment 1, "specific number of people and specific conditions" means "the conditions of '2 people, 1 night, room only'" (here, this "specific number of people and specific conditions" will be simply referred to as "specific accommodation conditions"). "Specific month within the year" is any month that serves as the basis for executing this first step.

[0027] For example, if the accommodation price in the specific hotel database DB1 is for March, the specific month can be set to March, and if the accommodation price in the specific hotel database DB1 is for October, the specific month can be set to October. As will be described later, when estimating the ADR for months other than the specific month, or estimating the annual average ADR, the information of which month the specific month is is used.

[0028] Furthermore, a concrete example of the calculation process in the first step can be explained as follows: The accommodation price for a specific month (for example, March) at a specific hotel 1a under specific accommodation conditions is Single room accommodation price: Ps Double room rates: Pw Price for a twin room: Pt Let's assume that this is the case. If we denote the daily accommodation prices for the month in question (March 1st to March 31st) with subscripts 1 to 31, then the daily accommodation prices for a single room under specific accommodation conditions for a specific month are: Day 1: Ps1 Day 2: PS2 · · 15th: PS15 · · 30th: PS30 31st: PS31 This is the result.

[0029] Therefore, the average specific accommodation price Psave for a single room type in a specific month is: Psave = Σ(Ps1~Ps31) / 31 The average specific accommodation price (Pwave) for double rooms in a specific month is: Pwave = Σ(Pw1~Pw31) / 31 The average specific accommodation price Ptave for twin rooms in a specific month is: Ptave = Σ(Pt1~Pt31) / 31 This is the result. Here, Σ(X1~X31) means the sum (total value) of the numbers from X1 to X31 in order. This number 31 changes depending on the number of days in a particular month; if the month is February, it will be 28 or 29, and if the month is April, June, September, or November, it will be 30.

[0030] (2nd process) The computer 5 performs a process (hereinafter referred to as the second process) in which the average specific accommodation price Psave, Pwave, and Ptave for each room type 11 are allocated proportionally to the proportion of the total number of rooms in the specific hotel 1a that corresponds to the room type 11, and then summed up, thereby calculating the monthly average accommodation price for the total number of rooms in the specific hotel 1a under specific accommodation conditions in a specific month as a single overall average specific accommodation price (S.2).

[0031] In the second step, the average monthly accommodation price (overall average specific accommodation price) for the entire number of rooms under specific accommodation conditions in the specific hotel 1a during the specific month (March) is calculated using the average specific accommodation price for each room type 11 calculated in the first step above. The number of rooms 12 for each room type 11 in the specific hotel 1a is, Number of single rooms: Ns Number of double rooms: Nw Number of twin rooms: Nt Total number of rooms: NT = Ns + Nw + Nt In that case, the overall average specific accommodation price PMave for specific hotel 1a under specific accommodation conditions in a specific month is: PMave={(Psave×Ns)+(Pwave×Nw)+(Ptave×Nt)} / NT This is the result.

[0032] (3rd step) The computer 5 performs the following step (hereinafter referred to as the third step) (S.3): obtaining multiple accompaniment coefficients for each room type 11 as multiple room type specific accompaniment coefficients from the specific accompaniment coefficient database DB2, in which room types 11 and accompaniment coefficients at a specific hotel 1a are interconnected.

[0033] Figure 5 is a data structure diagram of the specific occupancy coefficient database DB2 for specific hotel 1a. Within the specific occupancy coefficient database DB2, occupancy coefficients 14 are associated with each room type 11 that specific hotel 1a has. Here, the occupancy coefficient 14 is a numerical value that indicates the actual number of people staying in the corresponding room type 11, and is the average number of users per night over a predetermined period (e.g., 1 month, 6 months, 1 year, etc.).

[0034] For example, even if a double room is intended for two people, there may be days when only one person uses it, or days when three people use it with an extra bed. Similarly, even if a single room is intended for one person, there may be days when two people use it with an extra bed. Thus, the companion coefficient 14 is calculated based on the actual number of people using each room type 11 for a one-night stay.

[0035] For example, if, out of 10 days, there were 3 days with one person, 5 days with two people, and 2 days with three people, the companion coefficient of 14 would be {(1×3)+(2×5)+(3×2)} / 10=1.9. Also, if, out of 10 days, there were 2 days with one person, 6 days with two people, and 2 days with no use, the companion coefficient of 14 would be {(1×2)+(2×6)+(0×2)} / 10=1.4.

[0036] In this way, the companion coefficient 14 for each room type 11 is obtained from the specific companion coefficient database DB2 constructed for specific hotel 1a, as the single room companion coefficient s14, the double room companion coefficient w14, and the twin room companion coefficient t14 for each room type 11. These single room companion coefficient s14, double room companion coefficient w14, and twin room companion coefficient t14 for specific hotel 1a are collectively referred to as the specific companion coefficient for each room type.

[0037] Furthermore, this companion coefficient 14 may be an average value over a month, in which case it can be conceived as the companion coefficient 14 for a specific month (or the companion coefficient 14 for months other than the specific month). Of course, it may also be an average value over a year, or the average value of cumulative data from the time of opening to the present.

[0038] Furthermore, the occupancy coefficient 14 may be a value based on the actual performance of the specific hotel 1a itself, but if, for example, the specific hotel 1a is not yet open and does not have performance data, the occupancy coefficient 14 of a similar hotel in the vicinity may be applied by analogy. In other words, the occupancy coefficient 14 may be calculated based on the actual performance data of some or all of several hotels 1 within area 10, or some or all of several hotels 2, 3 including areas 20, 30, etc., outside of area 10, and may be used to estimate the specific occupancy coefficients s14, w14, t14 of the room type of the specific hotel 1a.

[0039] (4th step) The computer 5 performs a process (hereinafter referred to as the fourth step) in which it calculates the average companion coefficient for the total number of rooms in the specified hotel 1a by allocating and summing up the multiple room type specific companion coefficients s14, w14, and t14 in proportion to the proportion of the total number of rooms in the specified hotel 1a that each corresponding room type 11 occupies (S.4).

[0040] In the fourth step, based on the room type specific companion coefficients s14, w14, and t14 obtained in the third step, and the information on the number of rooms 12 for each room type 11 that the specific hotel 1a has, the average companion coefficient for the total number of rooms in the specific hotel 1a is calculated as the overall average specific companion coefficient ave14. That is, ave14 is, ave14={(s14×Ns)+(w14×Nw)+(t14×Nt)} / NT This is calculated as follows. This overall average specific companion coefficient ave14 is a value obtained by averaging the companion coefficient 14 for each room type by the total number of rooms, and in principle, there is one value for each specific hotel 1a. Of course, if the companion coefficient 14 fluctuates from month to month, and the companion coefficient 14 for a specific month and the companion coefficient 14 for other months are obtained separately in the third step, then there may be multiple overall average specific companion coefficients ave14 for each month for a specific hotel 1a.

[0041] (5th step) Based on the overall average specific accommodation price PMave and the overall average specific companion coefficient ave14, the computer 5 performs the process (hereinafter referred to as the fifth step) of calculating the monthly average accommodation price for the number of people corresponding to the overall average specific companion coefficient ave14 for a specific month (March) at a specific hotel 1a as the first specific accommodation price (hereinafter referred to as the fifth step) (S.5).

[0042] The overall average specific accommodation price PMave is the monthly average accommodation price for specific hotel 1a in a specific month under specific accommodation conditions. Here, the specific accommodation conditions include the condition of "2 people" as the specific number of people. The first specific accommodation price Padr1 is the accommodation price corresponding to the number of people indicated by the overall average specific companion coefficient ave14. Therefore, when the specific number of people under the specific accommodation conditions is M, the first specific accommodation price Padr1 is: Padr1 = PMave × ave14 / M This is the result. In this embodiment 1, the specific number of people M = 2.

[0043] As explained above, by starting the ADR estimation program P, the computer 5 (i.e., its main component, the CPU 5a) executes the above five steps while referring to the specific hotel database DB1 and the specific occupancy coefficient database DB2, which are constructed in memory 5b or in a storage device configured inside another computer 8. As a result, the first specific accommodation price Padr1, based on the number of people using the overall average specific occupancy coefficient ave14 for specific conditions (1 night, room only) in a specific month at a specific hotel 1a, is estimated as highly reliable numerical data. This first specific accommodation price Padr1 can be said to be the so-called monthly ADR for a specific month and under specific conditions at a specific hotel 1a.

[0044] [Embodiment 2] When the ADR estimation program P according to Embodiment 2 is started, in addition to the five steps described in Embodiment 1, the following sixth step is also executed.

[0045] (6th step) The computer 5 performs a process (hereinafter referred to as the sixth step) to calculate the second specific accommodation price for the number of people corresponding to the overall average specific companion coefficient ave14 under specific conditions in months other than the specific month (for example, October), based on the monthly average accommodation price in a specific month (March) and the monthly average accommodation price in months other than the specific month (for example, October) of the specific hotel 1a or other hotel 1 in the specific area 10a other than the specific hotel 1a, under specific accommodation conditions, as the second specific accommodation price (hereinafter referred to as the sixth step) (S.6).

[0046] In Embodiment 2, the monthly fluctuation database DB3 for the specific hotel 1a is stored in memory 5b or in an internal storage device such as another computer 8. Figure 2 shows an example where the monthly fluctuation database DB3 is stored inside another computer 8. The monthly fluctuation database DB3 stores the accommodation prices 13 for specific accommodation conditions at the specific hotel 1a on a monthly basis throughout the year. The accommodation prices 13 in the monthly fluctuation database DB3 may be actual price data or standardized ratio values ​​based on a specific month. In addition, the accommodation prices 13 for each month for each room type 11 may be stored, or the overall average specific accommodation price PMave for each month for the entire number of rooms at the specific hotel 1a may be stored. Furthermore, the monthly fluctuation database DB3 does not necessarily have to contain the accommodation prices 13 for the specific hotel 1a, but may contain information on the monthly accommodation prices 13 of other hotels of the same type, for example, some or all of several other hotels 1 within a specific area 10a.

[0047] Using the accommodation price 13 in this monthly fluctuation database DB3, it is possible to estimate the second specific accommodation price Padr2 for months other than the specific month under specific conditions for a specific hotel 1a. That is, the second specific accommodation price Padr2 is Padr2 = Padr1 × Accommodation price for months other than the specified month / Accommodation price for the specified month This calculation process allows for the simple and highly accurate estimation of the second specific accommodation price Padr2 for months other than the specific month. For example, if the specific month is March and the other month is October, the second specific accommodation price Padr2 for October can be estimated simply and highly accurately based on the first specific accommodation price Padr1 for March. It is possible to choose whether to use the accommodation price 13 in the monthly fluctuation database DB3 as the accommodation price for each room type 11, or as the overall average specific accommodation price PMave, and whether to use information from specific hotel 1a or information from hotel 1 other than specific hotel 1a. The calculation load and estimation accuracy will vary depending on which information is used. This second specific accommodation price Padr2 can be considered the so-called monthly ADR for a single month under specific conditions in months other than the specific month at specific hotel 1a.

[0048] [Embodiment 3] When the ADR estimation program P according to Embodiment 3 is started, in addition to the six steps described in Embodiment 2, the following seventh step is also executed.

[0049] (7th step) The computer 5 performs a process (hereinafter referred to as the seventh process) to calculate the third specific accommodation price for the number of people corresponding to the overall average specific companion coefficient ave14 at specific hotel 1a under specific conditions, based on the monthly average accommodation price at specific hotel 1a or hotel 1 other than specific hotel 1a within specific area 10a under specific accommodation conditions (S.7).

[0050] In Embodiment 3, the estimation of the second specific accommodation price Padr2 in Embodiment 2 is performed for all months except the specific month. As a result, the monthly average accommodation price for the number of people corresponding to the overall average specific companion coefficient ave14 under specific conditions for the specific hotel 1a is estimated for the specific month and all other months, i.e., for all 12 months of the year. Then, by summing these 12 accommodation prices and calculating the average, the third accommodation price Padr3 under specific conditions for the specific hotel 1a is estimated as highly reliable numerical data. This third accommodation price Padr3 can be said to be the annual average ADR for the specific hotel 1a.

[0051] [Differentiation] Furthermore, the ADR estimation method executed by activating the ADR estimation program P may further include the following eighth step.

[0052] (8th step) The computer 5 performs the process of updating the companion coefficient 14 corresponding to room type 11 in the specific companion coefficient database DB2 based on the accommodation record of room type 11 (hereinafter referred to as the eighth step) (S.8).

[0053] The companion coefficient 14 in the specific companion coefficient database DB2 may be a fixed value calculated from the accommodation record at specific hotel 1a or another hotel 1 other than specific hotel 1a. However, in the modified example, the companion coefficient 14 may be updated periodically or continuously based on past and new accommodation records.

[0054] Although preferred embodiments of the present invention have been described above, the present invention is not limited thereto, and various modifications and changes are possible within the scope of its essence. For example, the present invention includes the following aspects.

[0055] [Purpose 1] Multiple accommodations are divided into multiple areas, and each of these areas contains multiple accommodations that are part of the aforementioned multiple accommodations. A method for calculating accommodation prices related to a specified facility, in a case where one area selected from among the aforementioned multiple areas is defined as a specified area, and one accommodation facility selected from among the aforementioned multiple accommodation facilities located within the specified area is defined as a specified facility, the method for calculating accommodation prices related to the specified facility is as follows: A method for calculating accommodation prices using a computer, which performs the following steps (1) to (5). (1) A process of calculating the average monthly accommodation price for each room type provided by the specified facility in a specific month of the year, for a specific number of people and under specific conditions, as an average specified accommodation price for multiple room types. (2) A step of calculating the monthly average accommodation price for the total number of rooms in the specified facility in the specified month, under the specified number of people and specified conditions, by apportioning the average specified accommodation price for each room type according to the proportion of the total number of rooms that each room type occupies, and summing them up, thereby obtaining a single overall average specified accommodation price. (3) A step of obtaining multiple companion coefficients for each room type as multiple room type specific companion coefficients from a specific companion coefficient database in which the room types and companion coefficients in the specified facility are mutually associated. (4) A step of calculating the average companion coefficient for the total number of rooms in the specified facility as a single overall average companion coefficient by apportioning the multiple room type specific companion coefficients according to the proportion of the total number of rooms in the specified facility that each room type occupies. (5) A step of calculating the monthly average accommodation price for the number of people corresponding to the overall average specific companion coefficient for the specific month of the specific facility, based on the overall average specific accommodation price and the overall average specific companion coefficient, as the first specific accommodation price.

[0056] [Purpose 2] The above method for calculating accommodation prices may be further performed by a computer, including step (6) below. (6) A step of estimating a second specific accommodation price for the number of people corresponding to the overall average specific companion coefficient for months other than the specific month at the specific facility or accommodation facility within the specific area, based on the monthly average accommodation price for the specific month at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility

[0057] [Purpose 3] The above method for calculating accommodation prices may be further performed by a computer, including step (7) below. (7) A step of estimating the annual average accommodation price for the number of people corresponding to the overall average specific companion coefficient of the specific facility under the specific conditions, based on the average monthly accommodation price for the specific facility or accommodation within the specific area under the specific number of people and the specific conditions, as the third specific accommodation price.

[0058] [Purpose 4] The above method for calculating accommodation prices may be further performed by a computer, including step (8) below. (8) A step of updating the companion coefficient corresponding to the room type in the specified companion coefficient database based on the actual occupancy record of that room type.

[0059] [Purpose 5] Multiple accommodations are divided into multiple areas, and each of these areas contains multiple accommodations that are part of the aforementioned multiple accommodations. A lodging price calculation program for calculating the lodging price associated with a specified facility, in a case where one area selected from among the aforementioned multiple areas is defined as a specified area, and one lodging facility selected from among the aforementioned multiple lodging facilities located within the specified area is defined as a specified facility, the program calculates the lodging price associated with the specified facility. A program for calculating accommodation prices that instructs a computer to perform the following steps (1) to (5). (1) A process of calculating the average monthly accommodation price for each room type provided by the specified facility in a specific month of the year, for a specific number of people and under specific conditions, as an average specified accommodation price for multiple room types. (2) A step of calculating the monthly average accommodation price for the total number of rooms in the specified facility in the specified month, under the specified number of people and specified conditions, by apportioning the average specified accommodation price for each room type according to the proportion of the total number of rooms that each room type occupies, and summing them up, thereby obtaining a single overall average specified accommodation price. (3) A step of obtaining multiple companion coefficients for each room type as multiple room type specific companion coefficients from a specific companion coefficient database in which the room types and companion coefficients in the specified facility are mutually associated. (4) A step of calculating the average companion coefficient for the total number of rooms in the specified facility as a single overall average companion coefficient by apportioning the multiple room type specific companion coefficients according to the proportion of the total number of rooms in the specified facility that each room type occupies. (5) A step of calculating the monthly average accommodation price for the number of people corresponding to the overall average specific companion coefficient for the specific month of the specific facility, based on the overall average specific accommodation price and the overall average specific companion coefficient, as the first specific accommodation price. [Explanation of Symbols]

[0060] ave14: Overall average specific companionship coefficient DB1: Specific Hotel Database DB2: Database of Specific Accompanying Coefficients DB3: Monthly Variable Database M: Specific number of people Ns: Number of single rooms in a specific hotel Nw: Number of double rooms in a specific hotel Nt: Number of twin rooms in a specific hotel NT: Total number of rooms in a specific hotel P: ADR Estimation Program (Accommodation Price Calculation Program) Padr1: First Specific Accommodation Price Padr2: Second Specific Accommodation Price PMave: Overall average price of a specific hotel under specific accommodation conditions in a specific month. Ps: Accommodation price for a single room at a specific hotel in a specific month under specific accommodation conditions. Psave: Average specific accommodation price for single rooms by room type in a specific month Pw: Price of a double room at a specific hotel in a specific month under specific accommodation conditions. Pwave: Average specific accommodation price for double rooms in a specific month by room type Pt: Accommodation price for a twin room at a specific hotel in a specific month under specific accommodation conditions Ptave: Average specific accommodation price for twin rooms in a specific month by room type S: ADR Estimation System (Accommodation Price Calculation System) s14, w14, t14: Room type specific accompaniment coefficient W: Network 1-3: Hotel (accommodation) 1a: Designated hotels (designated facilities) 5: Computer 5a: CPU (Arithmetic Processing Unit) 6: Input section 7: Output section 8: Other computers 10-30: Area 10a: Specific area 11: Room Type 12: Number of rooms 13: Accommodation price 14: Companionship Coefficient

Claims

1. Multiple accommodations are divided into multiple areas, and each of these areas contains multiple accommodations that are part of the aforementioned multiple accommodations. A method for calculating accommodation prices in which, when one area selected from among the aforementioned multiple areas is defined as a specific area, and one accommodation facility selected from among the aforementioned multiple accommodation facilities located within the specific area is defined as a specific facility, the accommodation price associated with the specific facility is calculated, A method for calculating accommodation prices using a computer, which performs the following steps (1) to (5). (1) A process of calculating the average monthly accommodation price for each room type provided by the specified facility in a specific month of the year, for a specific number of people and under specific conditions, as an average specified accommodation price for multiple room types. (2) A step of calculating the monthly average accommodation price for the total number of rooms in the specified facility in the specified month, for the specified number of people and under the specified conditions, by apportioning the average specified accommodation price for each room type according to the proportion of the total number of rooms that each room type occupies, and summing them up. (3) A step of obtaining multiple companion coefficients for each room type as multiple room type specific companion coefficients from a specific companion coefficient database in which the room types and companion coefficients in the specified facility are mutually associated. (4) A step of calculating the average companion coefficient for the total number of rooms in the specified facility as a single overall average companion coefficient by apportioning the multiple room type specific companion coefficients according to the proportion of the total number of rooms in the specified facility that each room type occupies. (5) A step of calculating the monthly average accommodation price for the number of people corresponding to the overall average specific companion coefficient under the specific conditions in the specific month of the specific facility, based on the overall average specific accommodation price and the overall average specific companion coefficient, as the first specific accommodation price.

2. The method for calculating accommodation prices according to claim 1, further comprising performing the following step (6) by computer. (6) A step of estimating a second specific accommodation price for the number of people corresponding to the overall average specific companion coefficient for months other than the specific month at the specific facility or accommodation facility within the specific area, based on the average monthly accommodation price for the specific month at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility at the specific facility

3. The method for calculating accommodation prices according to claim 1, further comprising performing the following step (7) by computer. (7) A step of estimating the annual average accommodation price for the number of people corresponding to the overall average specific companion coefficient of the specific facility under the specific conditions, based on the average monthly accommodation price for the specific facility or accommodation within the specific area under the specific number of people and the specific conditions, as the third specific accommodation price.

4. The method for calculating accommodation prices according to any one of claims 1 to 3, further comprising performing the following step (8) by computer. (8) A step of updating the companion coefficient corresponding to the room type in the specified companion coefficient database based on the actual occupancy record of that room type.

5. Multiple accommodations are divided into multiple areas, and each of these areas contains multiple accommodations that are part of the aforementioned multiple accommodations. In a case where one area selected from the aforementioned multiple areas is defined as a specific area, and one accommodation facility selected from the aforementioned multiple accommodation facilities located within the specific area is defined as a specific facility, a lodging price calculation program for calculating the lodging price associated with the specific facility, A program for calculating accommodation prices that causes a computer to perform the following steps (1) to (5). (1) A process of calculating the average monthly accommodation price for each room type provided by the specified facility in a specific month of the year, for a specific number of people and under specific conditions, as an average specified accommodation price for multiple room types. (2) A step of calculating the monthly average accommodation price for the total number of rooms in the specified facility in the specified month, for the specified number of people and under the specified conditions, by apportioning the average specified accommodation price for each room type according to the proportion of the total number of rooms that each room type occupies, and summing them up. (3) A step of obtaining multiple companion coefficients for each room type as multiple room type specific companion coefficients from a specific companion coefficient database in which the room types and companion coefficients in the specified facility are mutually associated. (4) A step of calculating the average companion coefficient for the total number of rooms in the specified facility as a single overall average companion coefficient by apportioning the multiple room type specific companion coefficients according to the proportion of the total number of rooms in the specified facility that each room type occupies. (5) A step of calculating the monthly average accommodation price for the number of people corresponding to the overall average specific companion coefficient under the specific conditions in the specific month of the specific facility, based on the overall average specific accommodation price and the overall average specific companion coefficient, as the first specific accommodation price.

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