Price presentation device, method, and program

Abstract

An input unit 20 receives an input of the date and time for using a resource. A price determination unit 30 determines a plurality of prices according to the priority indicating the degree to which the resource that has variable available capacity can be preferentially used at the received date and time. An output unit 40 outputs a plurality of prices for the resource according to the priority.

Description

Price display device, method and program

[0001] The present invention relates to a price quote device, a price quote method, and a price quote program for quoting prices when reserving resources.

[0002] Various methods are known for dynamically setting prices for services and products based on the balance between supply and demand. For example, Patent Document 1 describes a seat reservation device that takes demand into account. The seat reservation device described in Patent Document 1 takes into account that the price of a seat reservation varies depending on the type of seat and the length of the period (remaining period) from the time the reservation is made to the time it ends, and sets the price so as to maximize the total sales amount while taking into account changes in demand.

[0003] International Publication No. 2023 / 100315

[0004] On the other hand, when reserving seats on an airplane, since it is not assumed that the airplane's capacity will change, the seat reservation device described in Patent Document 1 does not assume that the number of seats for sale will change. Therefore, it is difficult for the seat reservation device described in Patent Document 1 to set prices that will increase the total amount (total sales amount) in a situation where the amount of available resources changes.

[0005] Therefore, the present invention aims to provide a price quote device, a price quote method, and a price quote program that can quote resource prices in a way that further increases profits even in situations where the amount of available resources changes.

[0006] The price presentation device according to the present invention is characterized by comprising an accepting means for accepting input of the date and time of resource use, a price determination means for determining a plurality of prices according to a priority indicating the degree to which a resource whose available capacity changes can be preferentially used at the accepted date and time, and an output means for outputting a plurality of resource prices according to the priority.

[0007] The price presentation method according to the present invention is characterized by accepting input of the date and time of resource use, determining multiple prices according to a priority indicating the degree to which a resource whose available capacity changes can be preferentially used at the accepted date and time, and outputting multiple resource prices according to the priority.

[0008] The price presentation program according to the present disclosure is characterized in that it causes a computer to execute a reception process for receiving input of the date and time at which a resource will be used, a price determination process for determining multiple prices according to a priority indicating the degree to which a resource whose available capacity changes can be preferentially used at the received date and time, and an output process for outputting multiple prices of the resource according to the priority.

[0009] According to the present invention, resource prices can be presented to increase profits even in situations where the amount of available resources changes.

[0010] Fig. 1 is a block diagram showing an example of the configuration of an embodiment of a reservation reception system according to the present invention. Fig. 2 is a block diagram showing an example of the configuration of an embodiment of a price quote device according to the present invention. Fig. 3 is an explanatory diagram showing an example of a method for setting prices according to predicted flight availability. Fig. 4 is an explanatory diagram showing an example in which a price determination unit is realized as an online optimization system. Fig. 5 is an explanatory diagram showing an example of a method for determining multiple prices using a price model. Fig. 6 is a flowchart showing an example of the operation of the price quote device.

[0011] This invention assumes a situation in which reservations are accepted for resources whose available capacity changes depending on the environment and situation. Hereinafter, the amount of available resources may be referred to simply as capacity. As a specific example, this embodiment assumes a situation in which reservations are accepted for resources whose capacity changes.

[0012] In such a situation, resource reservations are accepted from users assuming that the maximum capacity will be available when the resource is used, but when the resource is actually used, the capacity may decrease due to weather changes or other reasons, and the resource may not be available to all users who have made reservations. In this case, users who have made reservations with higher priority will be given priority in using the resource.

[0013] In other words, in this embodiment, priority indicates the degree to which resources can be used preferentially when capacity changes and the resources available within a specified period are limited, and the higher the priority, the more likely the resources can be used with a higher service rate.

[0014] For example, when reserving an airplane, there is a concept of preferentially using resources, such as priority boarding, which is a reservation method for using resources under more favorable conditions than other users. However, when using an airplane, there is no concept that only some users can use the airplane and other users cannot. Therefore, the priority in the present invention is a different concept from the priority use in seat reservations described in Patent Document 1, for example.

[0015] The content of a resource can be arbitrary as long as its capacity (e.g., service rate) changes depending on the environment and situation. Examples of resources include space-time used by flying cars or eVTOLs (electric vertical take-off and landing aircraft), drones, automobiles, ships, etc. Specifically, resources include air roads called corridors, or sections of expressways. Alternatively, resources may include ground take-off and landing sites (vertiports) for flying cars, or parking lots for automobiles. The capacity of these may decrease depending on weather and other conditions. Furthermore, using a resource includes not only situations in which a user uses the resource themselves (e.g., using a flying car), but also situations in which a user allows another device to use the resource (e.g., flying a drone).

[0016] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0017] 1 is a block diagram showing an example of the configuration of an embodiment of a reservation reception system according to the present invention. The reservation reception system 1 of this embodiment includes a price presentation device 100 and an input / output device 200.

[0018] The input / output device 200 is a device that accepts resource reservations from users and displays prices presented by the price presentation device 100. The input / output device 200 is realized by, for example, a tablet.

[0019] 2 is a block diagram showing an example of the configuration of an embodiment of a price quote device according to the present invention. The price quote device 100 of this embodiment includes a storage unit 10, an input unit 20, a price determination unit 30, and an output unit 40.

[0020] The storage unit 10 stores various information used when the price estimation unit 30 (described later) determines the price. The storage unit 10 is realized by, for example, a magnetic disk.

[0021] The input unit 20 accepts input of the date and time of resource utilization input by the user via the input / output device 200. The content of the accepted date and time is a specific time or a time period having a certain range, and is determined according to the object for which the price determination unit 30, which will be described later, determines the price.

[0022] The price determination unit 30 determines the price for using the resource at the date and time of receipt. As described above, in this embodiment, it is assumed that the capacity of the available resource changes at the date and time of receipt. Therefore, the price determination unit 30 determines a price according to the degree to which the resource can be used preferentially (i.e., priority). Furthermore, in this embodiment, the price determination unit 30 determines multiple prices in stages according to the priority. Note that the priority and priority range for which the price is to be determined are predetermined by an administrator or the like.

[0023] A specific method by which the price determination unit 30 determines the price according to the priority will be described below.

[0024] In the first method, a rule for determining the price is set such that the higher the predicted service rate of the resource of the priority level for the accepted date and time, the higher the price is set. In the first method, the price determination unit 30 determines the price based on this rule.

[0025] 3 is an explanatory diagram showing an example of a method for setting prices according to the predicted flight availability. In the example shown in Fig. 3, when the weather is fine during operation, resources can be used up to a capacity of 15, when the weather is cloudy during operation, resources can be used up to a capacity of 10, and when the weather is rainy during operation, resources can be used up to a capacity of 5.

[0026] In this way, when the resource capacity changes due to the weather, the predicted in-service rate also changes statistically. Therefore, in the example shown in Figure 3, the predicted in-service rate for the highest priority (first class seats) is 95%, the predicted in-service rate for the next highest priority (second class seats) is 90%, and the predicted in-service rate for the third highest priority (third class seats) is 80%.

[0027] The example shown in Figure 3 shows that the rules set prices in stages: 10,000 yen for first-class seats, 8,000 yen for second-class seats, and 6,000 yen for third-class seats. The predicted service rates shown in Figure 3 can be determined based on future weather conditions, so they can also be said to be determined based on the results of weather forecasts. For example, if it is almost certain that heavy rain will reduce capacity to zero, the predicted service rate for the highest priority will also be almost 0%. Furthermore, if clear skies are certain, the predicted service rate can exceed 95% even for the third priority. The prices can also be said to be determined taking into account the predicted capacity during operation.

[0028] In this embodiment, priority is given to users who have made reservations with higher priority, so availability is determined based on the capacity determined at the time of operation and in accordance with priority. For example, in the example shown in Figure 2, if the weather is cloudy at the time of operation, the resource capacity is 10, so users who have reserved first-class and second-class seats can use the resource.

[0029] Since the predicted service rate changes from time to time depending on the forecasted weather, the prices illustrated in FIG. 3 may be recalculated and updated over time.

[0030] The second method is to determine the price by online optimization based on demand. In this case, the price determination unit 30 may be realized as an online optimization system. Figure 4 is an explanatory diagram showing an example in which the price determination unit 30 is realized as an online optimization system.

[0031] The online optimization system 130 illustrated in FIG. 4 includes a learning unit 31, a prediction unit 32, an optimization unit 33, and a trial unit 34.

[0032] The learning unit 31 uses training data including the circumstances under which the resource was used in the past and the demand at that time to learn a model (hereinafter referred to as a demand forecasting model) that predicts resource demand relative to price. In this embodiment, the training data includes future information that may affect the resource capacity. FIG. 4 shows an example in which the learning unit 31 learns a resource demand forecasting model using data d11 including various resource information (port, weather environment, y time slot x days from now, z day of the week) and predicted service rate, and training data d13 including demand d12 at that time.

[0033] In the example shown in Figure 4, the future information that may affect the resource capacity is the predicted in-service rate. Note that, instead of the predicted in-service rate, information that affects the predicted in-service rate (for example, weather predicted based on a weather forecast) may be used. Furthermore, it is expected that the higher the predicted in-service rate of each priority, the higher the price that will be determined.

[0034] The learning unit 31 may learn the demand forecasting model by any method and in any form. For example, the learning unit 31 may learn a demand model that indicates the relationship between the demand quantity D(t, p(t)) when the price is p(t) at the timing t, as described in Patent Document 1.

[0035] The prediction unit 32 predicts demand for resources by applying the data d11 related to resources for which reservations are accepted from users to the demand prediction model generated by the learning unit 31. Then, the optimization unit 33 optimizes the predicted demand forecast to derive a price distribution. For example, the optimization unit 33 may derive a price distribution in which the total demand amount is equal to or less than the capacity and the expected value of profit is maximized.

[0036] The trial unit 34 then performs a trial (simulation) based on the price distribution to determine multiple prices for using the resource. That is, the optimization unit 33 and the trial unit 34 optimize the price based on the predicted demand, thereby determining multiple prices for using the resource.

[0037] The third method is to determine the price using a price model created by an external system (not shown in FIG. 1) that predicts the optimal price. Compared to the second method, this method is more effective when past data (price data) has been accumulated.

[0038] The pricing model assumed in this embodiment is a model that is trained using training data including the situation and price of past resource usage, and uses information obtained from the data indicating the situation as an explanatory variable and price as a target variable. This training data also includes future information that may affect the resource capacity (for example, future weather) and the predicted service rate of the priority.

[0039] 5 is an explanatory diagram showing an example of a method by which the price determination unit 30 determines multiple prices using a price model. The example shown in Fig. 5 shows that a regression predictor y = f(x) is generated using information such as port features, airspace features, weather / predicted weekly efficiency features, and time features as explanatory variables as past data used in learning the price model, with the price for using a resource as the objective variable.

[0040] The price determination unit 30 determines the price by applying data d21 including various resource information (port, weather environment, time slot y after x days, z day of the week) and predicted service rate to this regression predictor. In the third method, it is expected that the higher the predicted service rate, the higher the price will be.

[0041] The output unit 40 outputs multiple resource prices according to priority. For example, as illustrated in Fig. 3, the output unit 40 may output three types of prices for first to third class seats according to priority along with information indicating the priority. The content output by the output unit 40 is presented to the user via the input / output device 200.

[0042] The input unit 20, the price determination unit 30, and the output unit 40 are realized by a processor (for example, a CPU (Central Processing Unit)) of a computer that operates according to a program (a code conversion program).

[0043] For example, the program may be stored in the storage unit 10 of the price quote device 100, and the processor may read the program and operate as the input unit 20, the price determination unit 30, and the output unit 40 in accordance with the program. Also, the functions of the price quote device 100 may be provided in a Software as a Service (SaaS) format.

[0044] The input unit 20, the price determination unit 30, and the output unit 40 may each be realized by dedicated hardware. Some or all of the components of each device may be realized by general-purpose or dedicated circuits, processors, etc., or a combination of these. These may be configured by a single chip, or by multiple chips connected via a bus. Some or all of the components of each device may be realized by a combination of the above-mentioned circuits, etc., and a program.

[0045] Furthermore, when some or all of the components of the price quote device 100 are realized by multiple information processing devices, circuits, etc., the multiple information processing devices, circuits, etc. may be centrally or decentralized. For example, the information processing devices, circuits, etc. may be realized as a client-server system, a cloud computing system, or the like, in a form in which each is connected via a communication network.

[0046] Next, the operation of the price quote device 100 of this embodiment will be described. Fig. 6 is a flowchart showing an example of the operation of the price quote device 100 of this embodiment. The input unit 20 accepts input of the date and time when a resource will be used (step S11). The price determination unit 30 determines multiple prices according to priority (step S12). Then, the output unit 40 outputs multiple prices of the resource according to priority (step S13).

[0047] As described above, in this embodiment, the input unit 20 accepts input of the date and time when the resource will be used, the price determination unit 30 determines multiple prices according to the priority, and the output unit 40 outputs multiple resource prices according to the priority. Therefore, resource prices can be presented in a way that further increases profits even in situations where the amount of available resources changes.

[0048] For example, the shorter the time before using a resource (for example, from a few hours to a few tens of minutes), the easier it is to grasp changes in the environment and situation, so it is thought that more favorable adjustments can be made by accepting reservations just before the resource is used.On the other hand, if demand exceeds the resource capacity just before the resource is used, congestion and delays are expected to occur.

[0049] Therefore, it is preferable to narrow down the demand roughly in advance (for example, several days in advance) so that the demand can be adjusted in advance. On the other hand, if there is a possibility that the capacity may change due to the influence of weather, etc., it is difficult to narrow down the demand in advance using general methods.

[0050] On the other hand, in this embodiment, the price determination unit 30 determines multiple prices according to priority, so even if capacity changes, it is possible to balance demand and accept appropriate reservations even at an advance stage.

[0051] Although the present invention has been described above with reference to the embodiments and examples, the present invention is not limited to the above-described embodiments and examples. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

[0052] 1 Reservation acceptance system 10 Storage unit 20 Input unit 30 Price determination unit 40 Output unit 100 Price presentation device 200 Input / output device

Claims

1. A price presentation device comprising: a receiving means for receiving input of a date and time for using a resource; a price determination means for determining a plurality of prices according to a priority indicating the degree to which a resource whose available capacity changes can be preferentially used at the received date and time; and an output means for outputting a plurality of prices of the resource according to the priority.

2. The price display device according to claim 1, wherein the price determination means determines a plurality of prices such that the higher the service rate of the resource priority, the higher the price is set.

3. The price display device according to claim 2, wherein the price determination means determines a plurality of prices so that the prices become higher in stages as the in-service rate increases.

4. A price display device as claimed in any one of claims 1 to 3, wherein the price determination means determines multiple prices based on a rule that the higher the predicted resource capacity at the date and time of receipt, the higher the priority is set, and the higher the priority, the higher the price is set.

5. A price presentation device as claimed in any one of claims 1 to 3, wherein the price determination means predicts the demand for the resource at the date and time of receipt using a demand prediction model learned based on the situation when the resource was used in the past and the demand at that time, and determines multiple prices for using the resource by optimizing the price based on the predicted demand, wherein the situation includes future information that may affect the capacity of the resource.

6. A price display device as claimed in any one of claims 1 to 3, wherein the price determination means learns from training data including the circumstances under which the resource was used in the past and the price at that time, and determines multiple prices for using the resource at the received date and time using a price model which is a model with information obtained from the data indicating the circumstances as explanatory variables and price as the objective variable, and wherein the circumstances include future information that may affect the capacity of the resource.

7. The price display device according to claim 5 or 6, wherein the future information that may affect the capacity of the resource is a predicted service rate or a predicted weather.

8. A price display method comprising: receiving input of a date and time for using a resource; determining a plurality of prices according to a priority indicating the degree to which a resource whose available capacity changes can be preferentially used at the received date and time; and outputting a plurality of prices for the resource according to the priority.

9. A price display program for causing a computer to execute the following: a reception process for receiving input of the date and time for using a resource; a price determination process for determining a plurality of prices according to a priority indicating the degree to which a resource whose available capacity changes can be preferentially used at the received date and time; and an output process for outputting a plurality of prices for the resource according to the priority.