WO2020230736A1

WO2020230736A1 - Demand distribution device

Info

Publication number: WO2020230736A1
Application number: PCT/JP2020/018722
Authority: WO
Inventors: 謙司篠田; 将人山田; 佑介深澤; 木本　勝敏
Original assignee: 株式会社Ｎｔｔドコモ
Priority date: 2019-05-14
Filing date: 2020-05-08
Publication date: 2020-11-19
Also published as: JPWO2020230736A1

Abstract

The present invention addresses the problem of guiding a user more suitably. A demand distribution device 1 is provided with: an acquisition unit 12 that acquires demand information pertaining to a future excess or insufficiency in demand that can be accommodated by a facility; and a guidance unit 13 that, on the basis of the demand information acquired by the acquisition unit 12, guides a user from one facility, at which the demand that can be accommodated will be excessive at a future time of day, to one facility at which the demand that can be accommodated will be insufficient at a future time of day. The guidance unit 13 calculates the probability that a user will visit one facility at a future time of day and may guide the user on the basis of the calculated probability. The guidance unit 13 may guide a user on the basis of the probability that the user will visit one facility at a future time of day in which the demand that can be accommodated thereat will be excessive. When there are a plurality of facilities at which the demand that can be accommodated will be insufficient at a future time of day, the guidance unit 13 may guide the user on the basis of the probabilities that the user will visit each facility at that time of day.

Description

Demand disperser

One aspect of this disclosure relates to a demand distribution device that guides users from one facility to another.

Patent Document 1 below discloses a providing device that guides a user to a second facility by providing a coupon that can be used at the second facility to the user when the first facility is full.

Japanese Unexamined Patent Publication No. 2019-21321

However, the above-mentioned provided device guides the user when the first facility is full at the present time, and does not consider the future situation. Therefore, there is a problem that the user cannot be guided in consideration of the future situation.

Therefore, one aspect of the present disclosure is made in view of such a problem, and an object thereof is to provide a demand distribution device capable of guiding users more appropriately.

In order to solve the above problems, the demand distribution device according to one aspect of the present disclosure is based on the acquisition unit that acquires the demand information regarding the future excess / deficiency of the acceptable demand of the facility and the demand information acquired by the acquisition unit. It is provided with a guidance unit that guides the user from one facility whose acceptable demand exceeds one hour in the future to one facility whose acceptable demand is insufficient at one hour in the future.

According to such a demand diversifier, the acceptable demand is the future from one facility where the acceptable demand exceeds the future one hour based on the demand information regarding the future excess or deficiency of the acceptable demand of the facility. The user is guided to one facility that is short at one time. By adopting such a configuration, it is possible to guide the user in consideration of the future excess or deficiency of the acceptable demand of the facility, so that the user can be guided more appropriately.

According to one aspect of the present disclosure, the user can be guided more appropriately.

It is a system block diagram of the demand distribution system including the demand distribution device which concerns on embodiment of this invention. It is a conceptual diagram explaining the use example of the demand distribution apparatus which concerns on embodiment of this invention. It is a functional block diagram of the demand distribution apparatus which concerns on embodiment of this invention. It is a figure which shows the table example of an acceptable demand master. It is a figure which shows the table example of the acceptable demand data. It is a figure which shows the table example of the data for demand forecast learning. It is a figure which shows the table example of the demand forecast forecasting data. It is a figure which shows the table example of the demand information. It is a figure which shows the table example of the visit probability data. It is a figure which shows the table example of the visit probability data by area. It is a figure which shows the table example of the user position history data. It is a figure which shows the table example of the store position master. It is a figure which shows the table example of the delivery destination master. It is a figure which shows the graph example of the optimum amount graph. It is a figure which shows the table example of the coupon delivery history data. It is a figure which shows the table example of the user attribute data. It is a figure which shows the table example of the coupon delivery schedule data. It is a flowchart which shows the process executed by the demand distribution apparatus which concerns on embodiment of this invention. It is a hardware block diagram of the demand distribution apparatus which concerns on embodiment of this invention.

Hereinafter, the embodiment of the demand distribution device will be described in detail together with the drawings. In the description of the drawings, the same elements are designated by the same reference numerals, and duplicate description will be omitted. Further, the embodiments in the following description are specific examples of the present invention, and are not limited to these embodiments unless otherwise specified to limit the present invention.

FIG. 1 is a system configuration diagram of a demand distribution system 3 including a demand distribution device 1 according to the present embodiment. As shown in FIG. 1, the demand distribution system 3 includes a demand distribution device 1 and one or more mobile terminals 2. The demand distribution device 1 and each mobile terminal 2 are communicated with each other by a network such as a mobile communication network, and can transmit and receive information to and from each other.

The demand distribution device 1 is a computer device that guides a user from one facility whose acceptable demand exceeds one hour in the future to one facility whose acceptable demand is insufficient at one hour in the future. Demand is a desire that is backed by purchasing power for goods or services, or the social total amount of that desire. In the present embodiment, the demand is assumed to be the number of visitors, the sales amount, the number of units sold, etc. in a facility such as a store, but the demand is not limited to this. Excessive (excessive) acceptable demand means, for example, in a facility such as a store, the number of visitors exceeding the number of seats in the facility or the sales amount (based on the number of seats), which cannot be covered by the staff of the facility. The amount of money or the number of visitors, the number of items sold exceeds the number of products prepared at the facility, and so on. On the other hand, when the acceptable demand is insufficient (underestimated), for example, in a facility such as a store, the number of visitors or the sales amount (based on the number of seats) is smaller than the number of seats in the facility, and the staff of the facility is left over. The amount of sales or the number of visitors (which will be unheard of), the number of items sold will be less than the number of products prepared at the facility, and so on. The facility is assumed to be a commercial facility that provides demand, such as a store, a restaurant, and an event facility, but is not limited to this. Further, in the present embodiment, the term "facility" is used not only to indicate only a physical facility but also to include services provided by the facility. In the present embodiment, "store" may be appropriately read as "facility". The guidance of the user by the demand distribution device 1 is performed by the demand distribution device 1 transmitting information (instruction) to the mobile terminal 2 carried by the user. The details of the demand distribution device 1 will be described later.

The mobile terminal 2 is a computer device such as a mobile communication terminal or a laptop computer that performs mobile communication. In the present embodiment, a smartphone is assumed as the mobile terminal 2, but the present invention is not limited to this. The mobile terminal 2 is carried by the user of the mobile terminal 2. The mobile terminal 2 is provided with GPS (Global Positioning System), and acquires the current position information (latitude, longitude, etc.) of the mobile terminal 2 using GPS. The mobile terminal 2 may acquire the current position information based on the base station information without using GPS. The mobile terminal 2 may appropriately acquire the position information and appropriately transmit the acquired position information to the demand distribution device 1. The mobile terminal 2 may include other sensors and functions provided by a general smartphone.

The mobile terminal 2 receives information (instruction) from the demand distribution device 1 and outputs (displays) the received information to the user who carries the mobile terminal 2. The user takes some action based on the output information to generate some motivation. That is, the user is guided by the demand distribution device 1. In the present embodiment, it is assumed that the demand distribution device 1 guides the user to the facility by presenting the facility coupon (discount coupon) to the user via the mobile terminal 2, but the present embodiment is not limited to this. ..

FIG. 2 is a conceptual diagram illustrating a usage example of the demand distribution device 1. It is assumed that at time t, which is one time in the future, the facility S1 is predicted to exceed the acceptable demand (high demand is expected). Further, it is assumed that the facility S2 is predicted to lack acceptable demand (low demand is expected) at time t', which is one time in the future. The demand distribution device 1 guides the user from the facility S1 to the facility S2 to recommend a visit from the facility S1 to the facility S2 in consideration of the future excess or deficiency of the acceptable demand of the facility. Examples of the method of guiding the user by the demand distribution device 1 include distribution of a coupon for a store and / or a limited time, distribution of a coupon whose coupon amount is dynamically changed according to a situation, and the like. By guiding the user by the demand distribution device 1, for example, in the facility S1, from the state that "a lot of customers are likely to come (sweat) even though there are few staff" at time t, "customers are coming" at time t'. I was saved without coming too much. " In addition, for example, in facility S2, from the state of "there are many staff, but not many customers may come ..." at time t, "customers came and there were not many staff left" at time t'. ! ”. That is, the facility S1 and the facility S2 have a win-win relationship. The time t and the time t'may be different times or may be the same time. Further, the facility S1 and the facility S2 may be different facilities or may be the same facility.

Next, the details of the function of the demand distribution device 1 will be described. FIG. 3 is a functional block diagram of the demand distribution device 1. As shown in FIG. 3, the demand distribution device 1 includes a storage unit 10, a calculation unit 11, an acquisition unit 12, and an induction unit 13.

Each functional block of the demand forecasting device 1 is assumed to function in the demand forecasting device 1, but is not limited to this. For example, a part of the functional blocks of the demand forecasting device 1 is a computer device different from the demand forecasting device 1, and information is appropriately transmitted to and received from the demand forecasting device 1 in the computer device connected to the demand forecasting device 1 via a network. It may function while doing so. Further, some of the functional blocks of the demand forecasting device 1 may be omitted, a plurality of functional blocks may be integrated into one functional block, or one functional block may be decomposed into a plurality of functional blocks. Good.

Hereinafter, each functional block of the demand distribution device 1 shown in FIG. 3 will be described.

The storage unit 10 stores various data used in various processes performed by the demand distribution device 1. Various data stored by the storage unit 10 are appropriately referred to and updated by each functional block in various processes performed by the demand distribution device 1.

The calculation unit 11 calculates the demand information regarding the future excess or deficiency of the acceptable demand of the facility based on the future forecast resource and the forecast demand of the facility. The resource is a resource that the facility can provide, such as the staff (number) of the facility and the availability of the facility. An example of calculating the demand information by the calculation unit 11 will be described with reference to the table examples shown in FIGS. 4 to 8.

FIG. 4 is a diagram showing an example of a table of acceptable demand masters. The acceptable demand master is master data showing a threshold value of the number of staff and an acceptable demand (sales amount) at a certain date and time of a certain store. As shown in FIG. 4, the acceptable demand master includes the store (identifying store name), the date and time, the lower threshold of the number of staff at the date and time (the time on the date) of the store, and the threshold value. The threshold of the upper limit of the number of staff at the date and time of the store corresponds to the acceptable demand of the store at the date and time. The acceptable demand master is created in advance by the persons concerned in each store and is stored in advance by the storage unit 10.

FIG. 5 is a diagram showing an example of a table of acceptable demand data. Acceptable demand data is data showing acceptable demand (sales amount) at a certain date and time of a certain store. As shown in FIG. 5, the acceptable demand data includes the store (identifying store name), the date and time, and the planned number of staff (forecast of the future of the facility) at the relevant date and time (the relevant time on the relevant date) of the relevant store. (Resources) and the acceptable demand of the store at the date and time correspond. In the acceptable demand data, the planned number of staff and the acceptable demand are initially blank. First, the persons concerned at each store register the planned number of staff based on the shift schedule of the store. Next, the parties concerned at each store refer to the acceptable demand master to extract the acceptable demand that (mostly) corresponds to the store, the date and time, and the number of staff in the acceptable demand data, and the extracted acceptable acceptability. Register the demand. Acceptable demand data is stored by the storage unit 10.

FIG. 6 is a diagram showing an example of a table of data for demand forecast learning. The demand forecast learning data is learning data for generating a forecast model for forecasting demand (sales amount) at a certain date and time of a certain store, and is past data. As shown in FIG. 6, the data for demand forecast learning includes the store (identifying store name), the period, the number of people in the area 30 minutes before the period in the vicinity of the store, and the amount of rain in the vicinity of the store during the period. The air volume around the store during the period, the average sales of the same day of the week one year before the period (average sales of the same day of the week one year ago), and the three months of the period at the store. The average sales on the same day of the same week before (average sales on the same day of the same week three months ago) and the actual value of the sales amount for the relevant period at the store correspond. Rain volume and air volume are weather information, the average sales on the same day of the same week one year ago and the average sales on the same day of the same week three months ago are sales performance statistics, and the weather information and sales performance statistics are feature quantities for learning. .. The demand forecast learning data is created in advance by the persons concerned in each store and is stored in advance by the storage unit 10.

The calculation unit 11 generates a prediction model by learning using the demand forecast learning data, and stores the generated prediction model in the storage unit 10. The generated forecast model can calculate the forecast value of the sales amount at any timing.

FIG. 7 is a diagram showing an example of a table of data for forecasting demand forecast. The demand forecast forecast data is forecast data for forecasting the demand (sales amount) at a certain date and time of a certain store by applying it to a forecast model. The table contents of the demand forecast forecast data are the same as the table contents of the demand forecast learning data. For example, the person concerned at each store, as the feature amount for prediction, the amount of rain (acquired based on the weather forecast etc.) and the air volume (acquired based on the weather forecast etc.) related to the specified timing, one year ago the same week Register the same day sales average and the same week sales average three months ago, leave the sales amount forecast value (corresponding to the actual sales amount value in Fig. 6) blank, create demand forecast forecast data, and store the storage unit 10. To be stored by. Then, the calculation unit 11 applies the demand forecast forecast data stored by the storage unit 10 to the forecast model stored by the storage unit 10, so that the sales amount at the designated timing can be obtained (table in FIG. 7). It is predicted as the sales amount forecast value (future forecast demand of the facility) (on the far right of the example). The calculation unit 11 stores the demand forecast forecast data updated and registered with the predicted sales amount forecast value by the storage unit 10.

FIG. 8 is a diagram showing an example of a table of demand information. The demand information is calculated by the calculation unit 11 based on the acceptable demand data stored by the storage unit 10 and the demand forecast forecast data stored by the storage unit 10. More specifically, the calculation unit 11 acquires the acceptable demand of a certain store at a certain date and time in the acceptable demand data, and acquires the sales amount forecast value of the store at that date and time in the demand forecast forecast data. However, if the acquired sales amount forecast value is greater than or equal to a certain threshold for the acquired acceptable demand, it is judged to be exceeded (the excess / deficiency flag of the demand information is registered as "excess"), and the acquired acceptable value. If the forecast value of the sales amount acquired for the demand is less than a certain threshold, it is judged to be insufficient (the excess / insufficient flag of the demand information is registered as "insufficient"). The calculation unit 11 stores the calculated demand information in the storage unit 10.

The acquisition unit 12 acquires the demand information of the facility. The acquisition unit 12 may acquire the demand information of the facility calculated by the calculation unit 11. The acquisition unit 12 may acquire the demand information of the facility stored by the storage unit 10. The acquisition unit 12 may acquire the demand information of the facility from another device via the network. The acquisition unit 12 outputs the acquired demand information to the guidance unit 13.

Based on the demand information acquired (input) by the acquisition unit 12, the guidance unit 13 has a facility in which the acceptable demand exceeds one time in the future, and one in which the acceptable demand is insufficient in one time in the future. Guide users to the facility. For example, the guidance unit 13 guides the user from the A store to the B store based on the example of the demand information table shown in FIG.

The guidance unit 13 may guide the user so that one facility whose acceptable demand exceeds one time in the future guides the user so that the acceptable demand at that one time is not insufficient. The guidance unit 13 may guide the user so that one facility whose acceptable demand is insufficient at one time in the future guides the user so that the acceptable demand is not exceeded at that one time. For example, the guidance unit 13 counts the number of guided users, and prevents users from guiding more than a predetermined number.

The guidance unit 13 may guide the user by delivering the coupon to the user by limiting at least one of the target facility and the target time for using the coupon. For example, the guidance unit 13 distributes coupons that can be used only at facilities where acceptable demand is insufficient at one time in the future. Further, for example, when there is a facility where the acceptable demand is insufficient at one time in the future, the guidance unit 13 delivers a coupon that can be used only at the time around the one time.

The guidance unit 13 may calculate the probability (possibility) that the user will visit one facility at one time in the future, and guide the user based on the calculated probability. The probability that a user will visit a facility may be based on the distance between the user and the facility or the user's past travel history. Hereinafter, three specific examples of the processing of the induction unit 13 will be given.

[User selection]
The guidance unit 13 may guide the user based on the probability that the user will visit a facility whose acceptable demand exceeds one time in the future at that one time. Specifically, the guidance unit 13 calculates the probability of visiting the facility at time t for each user, and has a high probability (probability higher than a predetermined probability) and high demand (acceptable demand exceeds). Priority is given to coupon distribution to users who are expected to visit the facility (facility S1). The guidance unit 13 calculates the probability of visiting the facility so that the user's current position is smaller when the distance to the facility S1 is farther and higher when the user's current position is closer. Alternatively, the guidance unit 13 predicts the future route of the user and calculates the probability of visiting the facility based on the distance from the facility S1 at time t. In addition, the guidance unit 13 calculates in advance the probability of each area being in the area after a predetermined time starting from a certain position based on the past route / area information acquired from the user, and the calculated area presence is in each area. Predict future routes by referring to category probabilities.

The data used by the guidance unit 13 in the processing of this specific example will be described with reference to FIGS. 9 to 13. Each data is appropriately acquired from the mobile terminal 2 and other devices by the guidance unit 13, the demand distribution device 1, or a person related to each store, is appropriately created, and is stored by the storage unit 10.

FIG. 9 is a diagram showing an example of a table of visit probability data. The visit probability data is data showing the probability that a user visits a store at a certain time on a certain day of the week. As shown in FIG. 9, the visit probability data corresponds to the user ID that identifies the user, the day of the week, the time, and the probability that the user visits the store after a certain time on the day of the week for each store. attached.

FIG. 10 is a diagram showing a table example of visit probability data by area. The area-specific visit probability data is data in which the user's current area is further associated with the visit probability data. As shown in FIG. 10, the area-specific visit probability data includes the user ID that identifies the user, the day of the week, the time, the current area of the user, and the area that is located in the current area for each store. It corresponds to the probability that the user will visit the store after a certain time on the day of the week.

FIG. 11 is a diagram showing an example of a table of user position history data. The user position history data is data indicating the user's position history. As shown in FIG. 11, the user position history data has a user ID that identifies the user, a date and time, and a latitude and longitude in which the user is located at the date and time.

FIG. 12 is a diagram showing an example of a table of the store position master. The store location master is master data indicating the location of the store. As shown in FIG. 12, in the store location master, the store name that identifies the store corresponds to the latitude and longitude in which the store is located.

FIG. 13 is a diagram showing an example of a table of the delivery destination master. The delivery destination master is master data indicating the delivery destination of the user. As shown in FIG. 13, the delivery destination master has a user ID that identifies a user and a delivery destination (email address) of the user.

[Determination of guidance destination]
If there are a plurality of facilities whose acceptable demand is insufficient at one time in the future, the guidance unit 13 may guide the user based on the probability that the user will visit each facility at that one time. Specifically, when there are a plurality of guidance destination facilities from the facility (facility S1) whose acceptable demand exceeds, the guidance unit 13 determines by any or a combination of the following three methods.
(1) Acquire the current position of each user and guide the user to a store closer to the user.
(2) Calculate the future route of each user and guide the user to the nearest store at the time to be guided.
(3) Calculate the guidance cost for each user to each facility, and guide with the combination that minimizes the guidance cost. The induction cost is determined, for example, by [[Method 2]] of [Amount determination] described later.

In the processing of this specific example, the guidance unit 13 uses the above-mentioned visit probability data, area-specific visit probability data, user position history data, store position master, and the like.

[Amount determination]
The guidance unit 13 may guide the user by delivering the coupon based on the degree of reaction of the user to the past delivery of the coupon to the user. The guidance unit 13 may guide the user by delivering a coupon to the user based on the probability that the user will visit at one time in the future when the acceptable demand is insufficient at one time in the future.

Specifically, the guidance unit 13 calculates in advance how much and how many users responded to the coupon amount from the number of coupon distributions, the coupon amount, and the number of responders accumulated in advance. Based on the calculation result, determine the optimum amount for the number of people you want to guide this time. Further, the guidance unit 13 may individually determine the coupon amount for each user by the following method 1 or method 2.

[[Method 1]]
The coupon amount is determined according to the distance to the facility and the arrival time of each user at the time of coupon distribution.

[[Method 2]]
For each user or for each group of users with the same attribute information (sex age, food and drink lovers, museum lovers, etc.), calculate in advance how much and how much they responded to the distance to the facility. Determine the coupon amount. FIG. 14 is a diagram showing a graph example of the optimum amount graph. As shown in FIG. 14, in a graph in which the x-axis shows the distance from the facility to the user and the y-axis shows the coupon amount, the optimum amount for each user group is shown as a function, and in the corresponding function, at a certain time. By inputting the position of the user, the optimum amount for the user can be determined.

The data used by the guidance unit 13 in the processing of this specific example will be described with reference to FIGS. 15 to 17. Each data is appropriately acquired from the mobile terminal 2 and other devices by the guidance unit 13, the demand distribution device 1, or a person related to each store, is appropriately created, and is stored by the storage unit 10.

FIG. 15 is a diagram showing an example of a table of coupon distribution history data. The coupon distribution history data is data showing the history of the situation when the coupon is distributed and the reaction of the user. As shown in FIG. 15, the coupon distribution history data includes a coupon ID that identifies the coupon, a distribution date and time that the coupon was distributed, a distribution user that identifies the user who distributed the coupon, and a discount amount (or coupon) of the coupon. Content), the destination store (identifying store name) that guided the user with the coupon, the distance and required time of the distribution user to the destination store, and whether or not the distribution user opened the coupon. There is a correspondence between whether or not the coupon has been opened and whether or not the distribution user has used the coupon.

FIG. 16 is a diagram showing an example of a table of user attribute data. The user attribute data is data indicating the attributes of the user. As shown in FIG. 16, in the user attribute data, a user ID that identifies a user, a gender of the user, an age of the user, and a hobby / preference of the user are associated with each other.

FIG. 17 is a diagram showing a table example of coupon distribution schedule data. The coupon distribution schedule data is data indicating a schedule in which the guidance unit 13 actually distributes the coupon. As shown in FIG. 17, the coupon distribution schedule data includes a coupon ID that identifies the coupon, a distribution date and time that the coupon is scheduled to be distributed, a distribution user that identifies the user to whom the coupon is distributed, and a discount for the coupon. Correspondence between the amount (or coupon content), the destination store that guides the distribution user by the coupon (coupon available store), and the guidance destination time that guides the distribution user by the coupon (coupon available time zone) attached.

The guidance unit 13 uses the information of the coupon distribution history data and the user attribute data to relate the coupon amount (or coupon content) to the probability of visiting the facility for the entire user, for each user, or for each user attribute. Is calculated, the amount and amount of coupons to be distributed are determined, and registered in the coupon distribution schedule data.

Subsequently, the processing of the demand distribution method in the demand distribution device 1 will be described with reference to the flowchart shown in FIG. First, the calculation unit 11 calculates the demand information of the facility based on the future forecast resource and the forecast demand of the facility (step S1). Next, the acquisition unit 12 acquires the demand information of the facility calculated in S1 (step S2). Next, based on the demand information acquired in S2 by the guidance unit 13, one facility whose acceptable demand exceeds one hour in the future, and one facility whose acceptable demand is insufficient in one hour in the future. The user is guided to (step S3). Note that S1 can be omitted, and in that case, the demand information stored in advance is acquired in S2, or the demand information is acquired from another device.

Next, the operation and effect of the demand distribution device 1 configured as in the present embodiment will be described.

According to the demand distribution device 1 of the present embodiment, the acquisition unit 12 acquires the demand information regarding the future excess / deficiency of the acceptable demand of the facility, and the guidance unit 13 uses the demand information acquired by the acquisition unit 12. Based on this, the user is guided from one facility where the acceptable demand exceeds one hour in the future to one facility where the acceptable demand is insufficient at one hour in the future. As a result, the user can be guided in consideration of the future excess or deficiency of the acceptable demand of the facility, so that the user can be guided more appropriately. Therefore, the demand can be more reliably balanced.

Further, according to the demand distribution device 1 of the present embodiment, the guidance unit 13 calculates the probability that the user will visit one facility at one time in the future, and the user is guided based on the calculated probability. As a result, for example, a user who has a higher probability of visiting a facility whose acceptable demand exceeds a predetermined time is guided to another facility, or an acceptable demand is insufficient in a future time. It is possible to guide users to the facility with a higher probability of visiting the facility than a predetermined standard, so that the demand can be more reliably balanced.

Further, according to the demand distribution device 1 of the present embodiment, the probability that the user visits one facility is based on the distance between the user and the one facility or the past movement history of the user. As a result, the probability can be calculated more accurately.

Further, according to the demand distribution device 1 of the present embodiment, the guidance unit 13 guides the user based on the probability that the user visits one facility whose acceptable demand exceeds one time in the future at that one time. To. This ensures that demand can be balanced more reliably, for example, by directing users who have a higher probability of visiting a facility whose acceptable demand exceeds a certain time in the future to another facility. The user can be guided.

Further, according to the demand distribution device 1 of the present embodiment, when there are a plurality of facilities whose acceptable demand is insufficient at one time in the future by the guidance unit 13, the user visits each facility at that one time. The user is guided based on the probability of doing so. As a result, it is possible to guide the user to a facility having a higher probability, so that the demand can be more reliably balanced.

Further, according to the demand distribution device 1 of the present embodiment, the guidance unit 13 guides the user by delivering the coupon based on the degree of reaction of the user to the past delivery of the coupon to the user. As a result, the coupon can be distributed so that the user reacts more reliably to the coupon, and thus the user can be guided so that the demand can be more reliably balanced.

Further, according to the demand distribution device 1 of the present embodiment, the guidance unit 13 delivers a coupon based on the probability that the user will visit one facility where the acceptable demand is insufficient at one time in the future. The user is guided by performing to the user. As a result, the user can be more reliably guided to the facility where the acceptable demand is insufficient at one time in the future, so that the demand can be more reliably balanced.

Further, according to the demand distribution device 1 of the present embodiment, the guidance unit 13 guides the user by delivering the coupon that limits at least one of the target facility and the target time for using the coupon. As a result, the user can be more reliably guided to the target facility and / or the target time, so that the demand can be more reliably balanced.

Further, according to the demand distribution device 1 of the present embodiment, the guidance unit 13 guides the user to the demand that can be accepted at one time by one facility whose acceptable demand exceeds one time in the future. Users are guided so that there is no shortage, or one facility that is short of acceptable demand at one time in the future guides users so that the acceptable demand is not exceeded at that one time. Will be done. As a result, demand can be balanced more reliably.

Further, according to the demand distribution device 1 of the present embodiment, the calculation unit 11 calculates the demand information of the facility based on the future forecast resource and the forecast demand of the facility, and the acquisition unit 12 calculates the facility. The calculated demand information of the facility is acquired. As a result, demand information can be calculated and acquired at any time, so that demand can be balanced in a more timely manner.

Here, as a background of one aspect of this disclosure, there was a request to adjust the operation of staff based on the demand forecast and reduce the human burden on restaurants and event facilities. In other words, it was valuable to be able to maximize the use of resources allocated to stores one day and improve operational efficiency. As an existing technology, there is a technology for grasping users who are in the vicinity of a facility and delivering a coupon that encourages a visit to a predetermined facility in consideration of the availability of the facility. However, the recommendation is based only on the current availability, not on the congestion and availability of facilities after a predetermined time from the current time. Therefore, when there is a large demand after a predetermined time, there is a possibility that the human resources of the facility will be tight. On the contrary, if there are few visits to the facility after the specified time, it may not be possible to utilize human resources. That is, the future demand forecast cannot be taken into consideration.

The demand distribution device 1 of the present embodiment performs store demand balancing by coupon distribution, or coupon distribution and demand balancing based on demand forecast, and the facility status (vacancy status, staffing number of staff) of each facility. ) To calculate the acceptable demand (number of people, sales, etc.). Next, demand forecasts are made using visit records, weather information, population information, etc. at multiple facilities, and whether it can exceed or fall below acceptable demand at each time is calculated. Based on whether or not the acceptable demand of each facility is exceeded, the facility S1 where high demand is expected at time t to the facility S2 (when S2 = S1) where low demand is expected at time t'(may be t = t'). Distribute store / time-limited coupons to users to encourage visits to (some).

In addition, the demand distribution device 1 of the present embodiment includes acceptable demand calculation, demand forecast, extraction of stores expected to be over-demand and stores expected to be under-demand, extraction of users to be guided, extraction of destination stores, determination of coupon amount (contents), and coupon distribution. May be performed in order (some processes can be omitted, some processes can be replaced).

Further, the demand distribution device 1 of the present embodiment may perform the following processing in the intermediate processing (some processing can be omitted, and some processing can be replaced).
(1) Acquire various types of information such as sales information, weather information, and population information.
(2) Perform feature calculation and create a regression table.
(3) Infer the sales amount.
(4) Acquire the store status (time, number of staff, etc.).
(5) Calculate acceptable demand from the store status.
(6) Excessive / insufficient stores are discriminated from the acceptable demand and the inferred sales amount.

The demand distribution device 1 as described above can realize demand balancing by shifting the visit time or the visit facility (= space-time) in consideration of the future demand forecast.

Note that the block diagram used in the explanation of the above embodiment shows a block for each functional unit. These functional blocks (components) are realized by any combination of at least one of hardware and software. Further, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized by using one device that is physically or logically connected, or directly or indirectly (for example, by two or more devices that are physically or logically separated). , Wired, wireless, etc.) and may be realized using these plurality of devices. The functional block may be realized by combining the software with the one device or the plurality of devices.

Functions include judgment, decision, judgment, calculation, calculation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, solution, selection, selection, establishment, comparison, assumption, expectation, and assumption. There are broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, assigning, etc., but only these. I can't. For example, a functional block (constituent unit) that functions transmission is called a transmitting unit or a transmitter. As described above, the method of realizing each of them is not particularly limited.

For example, the demand distribution device 1 in the embodiment of the present disclosure may function as a computer that processes the demand distribution method of the present disclosure. FIG. 19 is a diagram showing an example of the hardware configuration of the demand distribution device 1 according to the embodiment of the present disclosure. The demand distribution device 1 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, and the like.

In the following explanation, the word "device" can be read as a circuit, device, unit, etc. The hardware configuration of the demand distribution device 1 may be configured to include one or more of the devices shown in the figure, or may be configured not to include some of the devices.

For each function in the demand distribution device 1, the processor 1001 performs an operation by loading predetermined software (program) on hardware such as the processor 1001 and the memory 1002, and controls communication by the communication device 1004 or a memory. It is realized by controlling at least one of reading and writing of data in the 1002 and the storage 1003.

The processor 1001 operates, for example, an operating system to control the entire computer. The processor 1001 may be configured by a central processing unit (CPU: Central Processing Unit) including an interface with peripheral devices, a control device, an arithmetic unit, a register, and the like. For example, the above-mentioned calculation unit 11, acquisition unit 12, guidance unit 13, and the like may be realized by the processor 1001.

Further, the processor 1001 reads a program (program code), a software module, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes according to these. As the program, a program that causes a computer to execute at least a part of the operations described in the above-described embodiment is used. For example, the calculation unit 11, the acquisition unit 12, and the guidance unit 13 may be realized by a control program stored in the memory 1002 and operating in the processor 1001, and may be realized in the same manner for other functional blocks. Although it has been described that the various processes described above are executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. Processor 1001 may be implemented by one or more chips. The program may be transmitted from the network via a telecommunication line.

The memory 1002 is a computer-readable recording medium, and is composed of at least one such as a ROM (Read Only Memory), an EPROM (Erasable Programmable ROM), an EPROM (Electrically Erasable Programmable ROM), and a RAM (Random Access Memory). May be done. The memory 1002 may be referred to as a register, a cache, a main memory (main storage device), or the like. The memory 1002 can store a program (program code), a software module, or the like that can be executed to implement the wireless communication method according to the embodiment of the present disclosure.

The storage 1003 is a computer-readable recording medium, and is, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (for example, a compact disk, a digital versatile disk, or a Blu-ray). It may consist of at least one (registered trademark) disk), smart card, flash memory (eg, card, stick, key drive), floppy (registered trademark) disk, magnetic strip, and the like. The storage 1003 may be referred to as an auxiliary storage device. The storage medium described above may be, for example, a database, server or other suitable medium containing at least one of memory 1002 and storage 1003.

The communication device 1004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, or the like. The communication device 1004 includes, for example, a high frequency switch, a duplexer, a filter, a frequency synthesizer, and the like in order to realize at least one of frequency division duplex (FDD: Frequency Division Duplex) and time division duplex (TDD: Time Division Duplex). It may be composed of. For example, the above-mentioned calculation unit 11, acquisition unit 12, guidance unit 13, and the like may be realized by the communication device 1004.

The input device 1005 is an input device (for example, a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives an input from the outside. The output device 1006 is an output device (for example, a display, a speaker, an LED lamp, etc.) that outputs to the outside. The input device 1005 and the output device 1006 may have an integrated configuration (for example, a touch panel).

Further, each device such as the processor 1001 and the memory 1002 is connected by the bus 1007 for communicating information. The bus 1007 may be configured by using a single bus, or may be configured by using a different bus for each device.

In addition, the demand distribution device 1 includes hardware such as a microprocessor, a digital signal processor (DSP: Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), and an FPGA (Field Programmable Gate Array). It may be configured by, and a part or all of each functional block may be realized by the hardware. For example, processor 1001 may be implemented using at least one of these hardware.

The notification of information is not limited to the mode / embodiment described in the present disclosure, and may be performed by using another method.

Each aspect / embodiment described in the present disclosure includes LTE (Long Term Evolution), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), and 5G (5th generation mobile communication). system), FRA (Future Radio Access), NR (new Radio), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)) )), LTE 802.16 (WiMAX®), IEEE 802.20, UWB (Ultra-WideBand), Bluetooth®, and other systems that utilize suitable systems and have been extended based on these. It may be applied to at least one of the next generation systems. Further, a plurality of systems may be applied in combination (for example, a combination of at least one of LTE and LTE-A and 5G).

The order of the processing procedures, sequences, flowcharts, etc. of each aspect / embodiment described in the present disclosure may be changed as long as there is no contradiction. For example, the methods described in the present disclosure present elements of various steps using exemplary order, and are not limited to the particular order presented.

The input / output information and the like may be saved in a specific location (for example, memory), or may be managed using a management table. Input / output information and the like can be overwritten, updated, or added. The output information and the like may be deleted. The input information or the like may be transmitted to another device.

The determination may be made by a value represented by 1 bit (0 or 1), by a boolean value (Boolean: true or false), or by comparing numerical values (for example, a predetermined value). It may be done by comparison with the value).

Each aspect / embodiment described in the present disclosure may be used alone, in combination, or switched with execution. Further, the notification of predetermined information (for example, the notification of "being X") is not limited to the explicit one, but is performed implicitly (for example, the notification of the predetermined information is not performed). May be good.

Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described in the present disclosure. The present disclosure may be implemented as an amendment or modification without departing from the purpose and scope of the present disclosure, which is determined by the description of the scope of claims. Therefore, the description of this disclosure is for purposes of illustration only and does not have any restrictive meaning to this disclosure.

Software is an instruction, instruction set, code, code segment, program code, program, subprogram, software module, whether called software, firmware, middleware, microcode, hardware description language, or another name. , Applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, etc. should be broadly interpreted to mean.

In addition, software, instructions, information, etc. may be transmitted and received via a transmission medium. For example, a website that uses at least one of wired technology (coaxial cable, fiber optic cable, twist pair, digital subscriber line (DSL: Digital Subscriber Line), etc.) and wireless technology (infrared, microwave, etc.) When transmitted from a server, or other remote source, at least one of these wired and wireless technologies is included within the definition of transmission medium.

The information, signals, etc. described in this disclosure may be represented using any of a variety of different techniques. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be voltage, current, electromagnetic waves, magnetic fields or magnetic particles, light fields or photons, or any of these. It may be represented by a combination of.

Note that the terms explained in the present disclosure and the terms necessary for understanding the present disclosure may be replaced with terms having the same or similar meanings.

The terms "system" and "network" used in this disclosure are used interchangeably.

In addition, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, relative values from predetermined values, or using other corresponding information. It may be represented. For example, the radio resource may be one indicated by an index.

The names used for the above parameters are not limited in any respect.

The terms "determining" and "determining" used in this disclosure may include a wide variety of actions. "Judgment" and "decision" are, for example, judgment (judging), calculation (calculating), calculation (computing), processing (processing), derivation (deriving), investigation (investigating), search (looking up, search, inquiry). (For example, searching in a table, database or another data structure), confirming (ascertaining) may be regarded as "judgment" or "decision". In addition, "judgment" and "decision" are receiving (for example, receiving information), transmitting (for example, transmitting information), input (input), output (output), and access. (Accessing) (for example, accessing data in memory) may be regarded as "judgment" or "decision". In addition, "judgment" and "decision" mean that "resolving", "selecting", "choosing", "establishing", "comparing", etc. are regarded as "judgment" and "decision". Can include. That is, "judgment" and "decision" may include that some action is regarded as "judgment" and "decision". Further, "judgment (decision)" may be read as "assuming", "expecting", "considering" and the like.

The terms "connected", "coupled", or any variation thereof, mean any direct or indirect connection or connection between two or more elements, and each other. It can include the presence of one or more intermediate elements between two "connected" or "combined" elements. The connection or connection between the elements may be physical, logical, or a combination thereof. For example, "connection" may be read as "access". As used in the present disclosure, the two elements use at least one of one or more wires, cables and printed electrical connections, and, as some non-limiting and non-comprehensive examples, the radio frequency domain. Can be considered to be "connected" or "coupled" to each other using electromagnetic energies having wavelengths in the microwave and light (both visible and invisible) regions.

The phrase "based on" as used in this disclosure does not mean "based on" unless otherwise stated. In other words, the statement "based on" means both "based only" and "at least based on".

Any reference to elements using designations such as "first", "second", etc. as used in this disclosure does not generally limit the quantity or order of those elements. These designations can be used in the present disclosure as a convenient way to distinguish between two or more elements. Thus, references to the first and second elements do not mean that only two elements can be adopted, or that the first element must somehow precede the second element.

The "means" in the configuration of each of the above devices may be replaced with "part", "circuit", "device" and the like.

When "include", "including" and variations thereof are used in the present disclosure, these terms are as comprehensive as the term "comprising". Is intended. Furthermore, the term "or" used in the present disclosure is intended not to be an exclusive OR.

In the present disclosure, if articles are added by translation, for example a, an and the in English, the disclosure may include that the nouns following these articles are in the plural.

In the present disclosure, the term "A and B are different" may mean "A and B are different from each other". The term may mean that "A and B are different from C". Terms such as "separate" and "combined" may be interpreted in the same way as "different".

1 ... Demand distribution device, 2 ... Mobile terminal, 3 ... Demand distribution system, 10 ... Storage unit, 11 ... Calculation unit, 12 ... Acquisition unit, 13 ... Guidance unit.

Claims

An acquisition department that obtains demand information on future excesses and deficiencies of acceptable demand for facilities,
Guidance to guide the user from one facility where the acceptable demand exceeds one hour in the future to one facility where the acceptable demand is insufficient at one hour in the future based on the demand information acquired by the acquisition unit. Department and
A demand distribution device equipped with.
The guidance unit calculates the probability that the user will visit one facility at one time in the future, and guides the user based on the calculated probability.
The demand distribution device according to claim 1.
The probability that a user will visit a facility is based on the distance between the user and the facility or the user's past travel history.
The demand distribution device according to claim 2.
The guidance unit guides the user based on the probability that the user will visit a facility whose acceptable demand exceeds the future time.
The demand distribution device according to any one of claims 1 to 3.
When there are a plurality of facilities whose acceptable demand is insufficient at one time in the future, the guidance unit guides the user to each facility based on the probability that the user will visit at that one time.
The demand distribution device according to any one of claims 1 to 4.
The guidance unit guides the user by delivering the coupon based on the degree of reaction of the user to the past delivery of the coupon to the user.
The demand distribution device according to any one of claims 1 to 5.
The guidance unit guides the user by delivering a coupon to the user based on the probability that the user will visit the facility at one time in the future when the acceptable demand is insufficient.
The demand distribution device according to any one of claims 1 to 6.
The guidance unit guides the user by delivering a coupon that limits at least one of the target facilities and the target time for using the coupon.
The demand distribution device according to any one of claims 1 to 7.
The guide portion
A facility whose acceptable demand exceeds one hour in the future guides the user so that the acceptable demand is not insufficient at that one hour, or
A facility that lacks acceptable demand at one time in the future guides the user so that the acceptable demand is not exceeded at that one time.
The demand distribution device according to any one of claims 1 to 8.
Further equipped with a calculation unit that calculates the demand information of the facility based on the future forecast resources and the forecast demand of the facility.
The acquisition unit acquires the demand information of the facility calculated by the calculation unit.
The demand distribution device according to any one of claims 1 to 9.