JP2023006011A - Information processing program and information processing apparatus - Google Patents

Abstract

To provide an information processing program and an information processing apparatus configured to make a suggestion in consideration of increase of income for each of multiple landlords and increase of sales for each of multiple tenants, when the multiple tenants can select the multiple landlords.SOLUTION: An information processing apparatus 1 includes: sales prediction means 102 which predicts sales of each tenant in a real estate of each landlord for a designated period, on the basis of landlord information 111 including at least real estate information of one or more landlords and tenant information 112 including at least business information of the multiple tenants; rent calculation means 103 for calculating rents of each of the real estates, on the basis of the landlord information 111, the tenant information 112, and the sales of each tenant predicted by the sales prediction means 102; and output means 104 which outputs predicted sales of the tenants in each of the real estates of the landlords and the rents of the real estates of the landlords.SELECTED DRAWING: Figure 2

Description

The present invention relates to an information processing program and an information processing apparatus.

2. Description of the Related Art As a conventional technology, an information processing apparatus has been proposed for determining contract terms between a shopkeeper and a landlord in a shopping center or the like consisting of a plurality of shops (see, for example, Patent Document 1).

The information processing device disclosed in Patent Document 1 is a shopping center, a department store, and a station building, each of which consists of a plurality of shops, and which is related to a tenant (tenant, lessee) and a landlord (lessor), and is capable of handling a plurality of contract conditions. It has a database in which the (borrower's) sales efficiency by industry and business type is associated, and determines the contract conditions based on the sales efficiency by business type and business type of the tenant (borrower). By making a contract between the tenant (tenant) and the landlord according to the determined contract conditions, the tenant (tenant) who does not reach the set sales amount will have a higher rent burden, and on the contrary, the tenant (tenant) who exceeds the ) will reduce the rent burden, so each tenant (lessee) will make sales efforts, which will lead to an increase in sales for the entire tenant (lessee). fee revenue will increase.

JP-A-2002-99606

However, according to the information processing apparatus described above, in the relationship between a landlord (lessor) and a plurality of tenants (lessees), that is, one landlord (lessor) and a plurality of stores that wish to open a store in the landlord's shopping center, etc. In the relationship with the child (tenant), an increase in sales and tenant fees may be expected, but in situations where multiple tenants (tenants) can choose multiple landlords (lessors) It cannot be said that it is a structure that can realize an increase in tenant fees and an increase in sales for each of multiple tenants (lessees).

An object of the present invention is to provide an information processing program and an information processing device that make proposals in a situation where a plurality of borrowers can select a plurality of lenders, considering an increase in income of each of the plurality of lenders and an increase in sales of each of the plurality of borrowers. That's what it is.

One aspect of the present invention provides the following information processing program and information processing apparatus in order to achieve the above object.

[1] a computer,
a prediction means for predicting the sales of each lessor's property in a specified period based on lessee information including at least real estate information of one or more lessors and lessee information including at least business information of lessees; ,
a rent calculation means for calculating the rent of the real estate of each of the landlords based on the landlord information, the landlord information, and the sales of the landlord predicted by the prediction means;
An information processing program for functioning as an output means for outputting the sales forecast of the said lessee in each lessor's real estate and the rent of each said lessor's real estate.
[2] The information processing program according to [1], wherein the rent calculation means calculates a rent for each predetermined unit period.
[3] The output means predetermines the output order of the rent of the real estate of each of the lenders to the sales forecast of the lender, the rent of the real estate of the lender, or the sales forecast of the lender and the rent of the real estate of the lender. The information processing program according to [1] or [2], wherein the weighted sums are output in ascending or descending order.
[4] The information processing according to any one of [1] to [3] above, wherein the landlord information includes at least one of location, area, property of building, attributes of passers-by, business category to be treated preferentially, and rental price. program.
[5] The information processing program according to any one of [1] to [4], wherein the borrower information includes at least one of industry, customer attributes, and sales.
[6] The output means outputs the real estate of each of the lenders in a unit time so as to increase or decrease the sales of the borrower, the rent of the real estate of the lender, and the sum of the sales of the borrower and the rent of the real estate of the lender. The information processing program according to any one of [1] to [5], which generates and outputs a schedule for using the real estate of the borrower by combining each.
[7] The prediction means learns based on at least one of the business data of the borrower and external information, and predicts the sales of the borrower in the real estate of each lender based on the learning result of the learning. The information processing program according to any one of [1] to [6].
[8] The prediction means divides the real estate into sections so that the total sales or total rent of a plurality of tenants increases or decreases, The information processing program according to any one of [1] to [7], which predicts the sales of .
[9] The rent calculation means divides the real estate into sections so that the total sales or the total rent of a plurality of lessees increases or decreases, and calculates the rent for the divided sections [1] to [8] The information processing program according to any one of the above.
[10] Predicting the sales of each lessor's property in a specified period based on lessee information including at least real estate information of one or more lessors and lessee information including at least business information of the lessee; a predictive means;
rent calculation means for calculating the rent of the real estate of each of the landlords based on the landlord information, the landlord information, and the sales of the landlord predicted by the prediction means;
An information processing apparatus having a sales forecast of the borrower in the real estate of each lender and an output means for outputting the rent of the real estate of each of the lenders.

According to the invention according to claim 1 or 10, in a situation where a plurality of borrowers can select a plurality of lenders, it is possible to make a proposal considering the increase in income of each of the plurality of lenders and the increase in sales of each of the plurality of borrowers.
According to the second aspect of the invention, it is possible to calculate the rent for each predetermined unit period.
According to the invention of claim 3, the output order of the rent of each lender's real estate is weighted in advance to the sales forecast of the lender, the rent of the real estate of the lender, or the sales forecast of the lender and the rent of the real estate of the lender. The sums can be output in ascending or descending order.
According to the fourth aspect of the invention, at least one of the position, area, property of the building, attributes of passers-by, preferential business category, and rental price can be included.
According to the invention of claim 5, at least one of the type of industry, customer attributes, and sales can be included.
According to the invention of claim 6, each lender's real estate is combined for each unit time so as to increase or decrease the tenant's sales, the lender's real estate rent, and the sum of the borrower's sales and the lender's real estate rent. can generate a schedule for using the tenant's property.
According to the invention of claim 7, learning is performed based on at least one of the business data of the borrower and external information, and the sales of each lender's real estate are predicted based on the learning result of the learning. can be done.
According to the invention of claim 8, the real estate is divided into sections so that the total sales or total rent of multiple lessees increases or decreases, and each lessee in the real estate of each lessor during the period specified for the divided sections sales can be predicted.
According to the ninth aspect of the invention, it is possible to divide the real estate into sections so that the total sales or the total rent of a plurality of tenants increases or decreases, and to calculate the rent for the divided sections.

FIG. 1 is a schematic diagram showing an example of the configuration of an information processing system according to an embodiment. FIG. 2 is a block diagram illustrating a configuration example of an information processing apparatus according to an embodiment; FIG. 3 is a schematic diagram showing a configuration example of lender information. FIG. 4 is a schematic diagram showing a configuration example of borrower information. FIG. 5 is a schematic diagram showing a configuration example of customer information. FIG. 6 is a schematic diagram showing a configuration example of a screen displayed on the borrower's terminal. FIG. 7 is a schematic diagram showing a configuration example of a screen displayed on the borrower's terminal. FIG. 8 is a schematic diagram showing a configuration example of a screen displayed on the borrower's terminal. FIG. 9 is a schematic diagram showing a configuration example of a screen displayed on the lender's terminal. FIG. 10 is a flowchart for explaining the proposal/operation operation. FIG. 11 is a flow chart for explaining the schedule management operation. FIG. 12 is a flow chart for explaining the lender's operational operation.

[Embodiment]
(Configuration of information processing system)
FIG. 1 is a schematic diagram showing an example of the configuration of an information processing system according to an embodiment.

This information processing system 5 comprises an information processing device 1, terminals 2a, 2b, 2c operated by lenders 4a, 4b, 4c, . Operated terminals 3a, 3b . . . and terminals 6a, 6b, 6c . . . operated by customers 7a, 7b, 7c . Borrowers 5a, 5b, ... are, for example, real estate 8a, 8b, 8c, ... through mobile shops 30a, 30b, ... and sell to customers 7a, 7b, 7c, .... , borrowers 5a, 5b, . Note that the real estate 8a, 8b, 8c may be outdoor public land or may be indoors including buildings. Moreover, the real estate 8a, 8b, and 8c may be partitioned in advance, or may not be partitioned. In addition, the borrowers 5a, 5b, ... do not necessarily have mobile shops 30a, 30b, .... Alternatively, tenants in the building may be used. Moreover, the lessees 5a, 5b, .

The information processing apparatus 1 is a server-type information processing apparatus, and operates in response to requests from terminals 2a, 2b, 2c, . . , terminals 3a, 3b, . It includes electronic components such as a CPU (Central Processing Unit) and a flash memory that have functions for processing information.

Terminals 2a, 2b, 2c, . . , terminals 3a, 3b, .., terminals 6a, 6b, 6c, . It has electronic parts such as CPU and flash memory.

The network 4 is a communication network capable of high-speed communication, and is, for example, a wired or wireless communication network such as an intranet or LAN (Local Area Network).

As an example, the information processing device 1 operates in response to requests from the terminals 2a, 2b, 2c, . . . , the terminals 3a, 3b, . Predict sales when operating in real estate 8a, 8b, 8c, ... of landlords 4a, 4b, 4c, ..., calculate rent based on the predicted sales, and tenants 5a, 5b, ... operate business with this information. propose real estate suitable for In addition, it proposes management of real estate 8a, 8b, 8c, . . . to lenders 4a, 4b, 4c, . A detailed description will be given below.

(Configuration of information processing device)
FIG. 2 is a block diagram showing a configuration example of the information processing device 1 according to the embodiment.

The information processing apparatus 1 is composed of a CPU and the like, controls each part and executes various programs, a storage part 11 composed of a storage medium such as a flash memory and stores information, and a network. and a communication unit 12 for communicating with the outside.

By executing an information processing program 110, which will be described later, the control unit 10 executes the lessor information registration means 100, the lessee information registration means 101, the sales prediction means 102, the rent calculation means 103, the output means 104, the external information acquisition means 105, the learning It functions as means 106, reservation means 107, and the like.

The lender information registration means 100, in response to requests from the terminals 2a, 2b, 2c, ..., the lender's name, contact information, details of the real estate to be rented (real estate information), weather, preferential treatment/business type/genre (business information), rental price, etc. are received and stored in the storage unit 11 as the landlord information 111 .

The borrower information registration means 101 receives information such as the borrower's name, contact information, business type/genre (business information), customer attribute data, sales scale, etc., in response to requests from the terminals 3a, 3b, . . . , and stored in the storage unit 11 .

The sales prediction means 102 predicts the sales of each lender's real estate in a specified period based on the lender information 111, the borrower information 112, the external information 116, and the learning result information 118, and stores the sales as predicted sales information 114 in the storage unit. 11.

The rent calculation means 103 calculates the rent of each landlord's real estate based on the landlord information 111, the tenant information 112, the external information 116, and the sales of the tenant predicted by the sales prediction means 102, and stores the rent as proposed rent information 115 in the storage unit. 11.

The output means 104 outputs the information such as the lessor information 111, the lessee information 112, the predicted sales information 114, the proposed rent information 115, etc., together with other information as necessary, to the terminals 2a, 2b, 2c, ..., terminals 3a, 3b. . . , terminals 6a, 6b, 6c, .

The external information acquisition means 105 acquires information such as weather, traffic data, people flow data, business data, etc. from the outside via the communication unit 12 and stores them in the storage unit 11 as external information 116 and business information 117 .

The learning means 106 learns the prediction operation of the sales prediction means 102 based on the external information 116, sales information 117, etc., and updates the learning result information 118. FIG.

The reservation means 107 stores a reservation for real estate in the storage unit 11 as reservation information 119 in accordance with the content of requests received from the terminals 3a, 3b, . . . .

The storage unit 11 stores an information processing program 110 that causes the control unit 10 to operate as each means 100 to 106 described above, landlord information 111, lessee information 112, customer information 113, predicted sales information 114, proposed rent information 115, external information 116, Stores sales information 117, learning result information 118, reservation information 119, and the like.

FIG. 3 is a schematic diagram showing a configuration example of the lender information 111. As shown in FIG.

The lender information 111 includes the lender ID for identifying the lender, the name of the lender, the contact information of the lender, the location information of the real estate owned by the lender, the area, indoor/outdoor, public/private property/restricted area, etc. , passerby attribute data (real estate information) of passersby passing through the non-moving area, weather as history and forecast, business type/genre (business information) that the landlord wants to give preferential treatment/attraction, and basic rental price of real estate and other information.

In addition, as passerby attribute data, age, gender ratio, age, traction by gender (an index of the ratio of those who were interested in the passerby and led to purchasing behavior), age, Consumption by gender, other attributes of passers-by, individual/group ratio, earphone wearing rate, walking speed distribution, action purpose ratio such as business, casual, sightseeing, customer consumption trends (past consumption data), payment methods trends (cash, credit, mobile payments, etc.).

In addition, the basic rental price includes basic fixed rent, basic sales-linked rent linked to the lessee's sales, and the lessee's target sales per unit time.

FIG. 4 is a schematic diagram showing a configuration example of the borrower information 112. As shown in FIG.

The borrower information 112 includes information such as the borrower ID for identifying the borrower, the name of the borrower, the contact information of the borrower, the business type/genre (business information) of the borrower, the customer attribute data of the borrower, and the basic sales scale. have.

In addition, as customer attribute data, customer age, gender ratio, traction by age and gender, consumption amount by age and gender, customer consumption trends (past consumption data), payment method trends (cash, credit, etc.) mobile payments, etc.).

FIG. 5 is a schematic diagram showing a configuration example of the customer information 113. As shown in FIG.

The customer information 113 includes information such as customer ID for identifying the customer, customer name, customer contact information, personal identification information, business usage history indicating the borrower used by the customer, range of action, movement route data, etc. have

(Operation of information processing device)
Next, the operation of the present embodiment will be described separately for (1) preparation operation, (2) proposal/operation operation, and (3) learning operation.

(1) Preparatory operation First, as a preparatory operation for operating the information processing system, the lenders 4a, 4b, 4c, . . . , 8b, 8c . . . (real estate information) are input by operating terminals 2a, 2b, 2c . The terminals 2 a , 2 b , 2 c . . . transmit the input information to the information processing device 1 .

The lender information registration means 100 of the information processing device 1, in response to requests from the terminals 2a, 2b, 2c, ..., the lender's name, contact information, details of the real estate to be rented (real estate information), weather, preferential treatment / business to be attracted Information such as type/genre, rental price, etc. is received and stored in the storage unit 11 as lessor information 111 . The real estate 8a, 8b, 8c, . It may be registered. If the real estate is registered as a whole without division, it is possible to propose an appropriate division of the real estate to the lessee in the proposal/management operation described later.

Next, the lessees 5a, 5b, . . . who desire to receive real estate 8a, 8b, 8c, . do. The terminals 3a, 3b, . . . transmit the input information to the information processing device 1. FIG.

The borrower information registration means 101 of the information processing device 1 receives information such as the borrower's name, contact information, business type/genre, customer attribute data, sales volume, etc. in response to requests from the terminals 3a, 3b, etc., and stores the borrower information. 112 is stored in the storage unit 11 .

In addition, the external information acquisition means 105 of the information processing apparatus 1 acquires the customer's name, contact information, usage status, activity range, etc. from the terminals 6a, 6b, 6c operated by the customers 7a, 7b, 7c, . Then, the customer information 113 is stored in the storage unit 11 .

In addition, the external information acquisition means 105 of the information processing apparatus 1 acquires information such as weather, traffic, and population density from a weather server, a traffic server, a people flow server, etc. (not shown) via the communication unit 12, and obtains external information 116. , and stored in the storage unit 11 .

(2) Proposal/operation operation (2-1) Reservation by tenant First, tenants 5a, 5b, . . . operate terminals 3a, 3b, . The terminals 3a, 3b, . . . request the information processing apparatus 1 for sales forecast and rent.

FIG. 10 is a flowchart for explaining the proposal/operation operation.

When the sales forecasting means 102 of the information processing device 1 receives the sales forecast and the request for the rent (S1; Yes), it acquires the lessor information 111, the lessee information 112, and the external information 116 (S2). Using the learning result information 118, the borrower's sales for each lender's real estate in the period designated based on the data is predicted (S3) and stored in the storage unit 11 as predicted sales information 114. FIG. The learning result information 118 is generated and updated by "(3) learning operation" described later.

Specifically, the sales prediction means 102 predicts sales using the learning result information 118 with the average sales scale of the business, the passerby attribute of the real estate, and the customer attribute of the business as feature quantities, and the sales impact as the result quantity. do. In addition, the sales forecasting means 102, based on the degree of similarity with the attributes of other tenants who have made reservations in the surrounding real estate, if there is a risk of scramble for a certain demand, reflects that fact in the sales forecast. , to display a warning. Moreover, the sales forecasting means 102 forecasts based on the learning result information 118 having a learning strategy of minimizing a loss function that takes into consideration the sales tendency constant (brand power) of each business.

In addition, the rent calculation means 103 of the information processing device 1 calculates the rent of each lessor's real estate based on the lessee information 111, the lessee information 112, the external information 116, and the lessee's sales predicted by the sales prediction means 102. (S4), it is stored in the storage unit 11 as the proposed rent information 115. FIG. The basic rent calculation consists of a basic fixed rent and a basic sales-linked rent that is added according to the forecasted sales, but is not limited to this. may be set based on the rent of other properties (including those traded outside of this system), or may be charged based on the number of customers who have received the service (when forecasting rent, the number of customers is the number of sales Estimated by the forecasting means 102. The actual rent is calculated based on the actual value.).

Specifically, the rent calculation means 103 calculates the rent using an economic model (dynamic pricing of obsolete products) based on the predicted amount of the sales-linked rent, the basic rental price, the degree of attention, the contract rate, and the target sales. Calculate In addition, the rent calculation means 103 sets the degree of preferential treatment (positive, zero, or negative) of the business operator by comparing the use designation/use restriction of the property, the welcome genre, and the normal average of assumed sales, and the degree of preferential treatment Based on this, preferential rent may be offered in addition to the regular rent. In addition, the preferential rent can be set to lower the usage barrier, for example, by setting the fixed rate low and the variable rent high.

The output means 104 of the information processing device 1 rearranges the information such as the lessor information 111, the lessee information 112, the predicted sales information 114, the proposed rent information 115, etc., together with other information as necessary, in order of priority to be described later. (S5), and output as information to be displayed on the display units of the terminals 3a, 3b, . . . (S6).

The terminals 3a, 3b, .

FIG. 6 is a schematic diagram showing a configuration example of a screen displayed on the borrower's terminal.

_The screen 104a is displayed on the display screens of the terminals 3a, 3b, . , a display area _104a3 for selectively displaying the contents of the proposed rent information 115 _, and an operation button _104a4 for reserving the use of the real estate at the selected rent. Also, the contents of the predicted sales information 114 may be displayed together with the average data of the tenant's business and the average sales distribution of other companies' businesses in the same real estate. In addition, a set of fixed rent (price) and sales-linked rent (percentage) may be proposed and a simulation of sales and rent may be presented. Furthermore, if there is a variable setting that improves sales efficiency, such as when the time slot is changed, that information may also be presented. Moreover, you may display the factor which came to estimate sales.

Note that the details of the real estate displayed in the display area 104a- ₁ are given priority to either the sales forecast displayed in the display area 104a- ₂ or the rent displayed in the display area 104a- ₃ in step S5 described above. Sorted or the sum of both with predetermined weighting is preferably displayed in the order of maximum (ascending order, descending order) (not limited to maximum, so as to increase or decrease from the current state or average value etc. ).

The borrowers 5a, 5b, . . . check the display _screens of the terminals 3a, 3b, . The terminals 3a, 3b, .

The reservation means 107 of the information processing apparatus 1 receives requests from the terminals 3a, 3b, . Based on the reservation information 119, the lessees 5a, 5b, .

(2-2) Confirmation of sales during business Next, the lessees 5a, 5b, . . The terminals 3a, 3b, . The business information may be input by the borrower 5a, 5b, etc. (data input, scanning of handwritten ledger, etc.), for example, purchase history data of POS (Point of Sale) installed in the store, store or It may be acquired from images of marketing cameras (not shown) installed in the area.

The external information acquisition means 105 of the information processing apparatus 1 acquires business information such as sales, and stores it in the storage unit 11 as business information 117 .

Next, borrowers 5a, 5b, . . . operate terminals 3a, 3b, . The terminals 3a, 3b, . . . request the information processing apparatus 1 for sales forecast.

The output means 104 of the information processing device 1 outputs the information such as the lender information 111, the borrower information 112, the predicted sales information 114, the external information 116, the sales information 117, etc., together with other information as necessary, to the terminals 3a, 3b. … output as information for display on the display unit. In addition, the output means 104 analyzes the sales information 117 by converting the customer attributes and traction data by time zone by video analysis of the marketing camera, linking the customer attribute data to the purchase history data of the POS, etc. You may make it output as a feedback to.

The terminals 3a, 3b, .

FIG. 7 is a schematic diagram showing a configuration example of a screen displayed on the borrower's terminal.

_The screen 104b is displayed on the display screens of the terminals 3a, 3b, . a display area _104b3 that displays the sales information 117 _, which is the sales history _, and the predicted sales information 114 after the current time using a graph or the like; It has a display area 104b4 for displaying information 116 and a display area _104b5 for displaying sales information 117. FIG.

The display area 104b- ₃ displays forecasted sales information 114 predicted by the sales forecasting means 102 in consideration of, for example, the flow of people due to the weather displayed in the display area 104b- ₄ , changes in purchase intentions, and the like. It should be noted that when the weather deteriorates, processing may be performed to receive an application and reduce or exempt the fixed rent during the period of bad weather.

The borrowers 5a, 5b, . . . confirm the display screens of the terminals 3a, 3b, . For example, if rain forecast predicts that sales will drop in a certain time period, the lessees 5a, 5b, . The terminals 3a, 3b, .

The reservation means 107 of the information processing apparatus 1 receives requests from the terminals 3a, 3b, . . . and changes the reservation contents of the reservation information 119.

(2-3) Schedule Management Further, the borrowers 5a, 5b, . . . operate the terminals 3a, 3b, . The terminals 3a, 3b, . . . request the information processing apparatus 1 to manage schedules.

FIG. 11 is a flow chart for explaining the schedule management operation.

Further, when the sales forecasting means 102 and the rent calculating means 103 of the information processing device 1 receive the schedule management request of the terminals 3a, 3b, . . . (S11; Yes), they Information 118 is acquired (S12), and based on the acquired information, the borrower's sales for each lender's real estate in a specified period are predicted (S13), and stored in the storage unit 11 as predicted sales information 114.

In addition, the rent calculation means 103 of the information processing device 1 calculates the rent of each lessor's real estate based on the lessee information 111, the lessee information 112, the external information 116, and the lessee's sales predicted by the sales prediction means 102. ( S<b>14 ), it is stored in the storage unit 11 as the proposed rent information 115 .

The output means 104 of the information processing device 1 outputs the information such as the lessor information 111, the lessee information 112, the predicted sales information 114, the proposed rent information 115, etc., together with other information as necessary, to the past lessees 5a, 5b, . . . Considering the business information 117 and the reservation information 119, real estate is selected in each time period, and a reservation schedule for using the real estate is created (S15) and output to the borrowers 5a, 5b, . . . (S16).

In addition, the combination of real estate in all time periods maximizes the income of each landlord so that, for example, the sum of predicted sales is maximized and the sum of proposed rents is minimized (or maximized). so that the difference between forecasted sales and rent is maximized, so that both forecasted sales and rent are maximized, or all of these are balanced or maximized by a predetermined policy is performed on In addition, the output unit 104 may display a plurality of schedule candidates in ascending or descending order of schedule policy. It should be noted that the value is not limited to the maximum value, and may be increased or decreased from the current value, average value, or the like.

The output means 104 of the information processing apparatus 1 outputs the proposed schedule together with other information as necessary as information for display on the display units of the terminals 3a, 3b, . . . .

The terminals 3a, 3b, .

FIG. 8 is a schematic diagram showing a configuration example of a screen displayed on the borrower's terminal.

The screen 104c is displayed on the display screens of the terminals 3a, 3b, . It has a display area 104c- ₁ , a display area 104c- ₂ for displaying the schedule and rent of the real estate to be used, and an operation button 104c- ₃ for executing the real estate reservation according to the scheduled contents.

The predicted sales information 114 displayed in the display area 104c- ₁ , the schedule and rent displayed in the display area 104c- ₂ , etc. are, for example, minimized (or maximized) so that the predicted sales are maximized. , so that the difference between forecasted sales and rent is maximized, so that both forecasted sales and rent are maximized, or all of these are balanced or maximized by a predetermined policy Sales prediction means 102 and rent calculation means 103 decide. It should be noted that the value is not limited to the maximum value, and may be increased or decreased from the current value, average value, or the like.

The borrowers 5a, 5b, . . . confirm the contents of the schedule on the display screens of the terminals 3a, 3b, . to change the content and make a reservation. The terminals 3a, 3b, .

The reservation means 107 of the information processing apparatus 1 receives requests from the terminals 3a, 3b, .

(2-4) Lender Operation Management Lenders 4a, 4b, 4c, . . . operate terminals 2a, 2b, 2c, . The terminals 2a, 2b, 2c, .

FIG. 12 is a flow chart for explaining the lender's operational operation.

When the sales forecasting means 102 of the information processing device 1 receives the operation status confirmation request (S21; Yes), the lender information 111, the borrower information 112, the external information 116, the sales information 117, the learning result information 118, and the reservation information 119 (S22), the sales of each borrower in the specified period are predicted based on the obtained information (S23), and stored in the storage unit 11 as predicted sales information 114. FIG. The sales forecast method is the same as in step S3 of FIG. 10 described above.

In addition, the rent calculation means 103 of the information processing device 1 calculates the rent of the real estate of the landlord based on the landlord information 111, the landlord information 112, the external information 116, and the sales of the landlord predicted by the sales prediction means 102 ( S24), it is stored in the storage unit 11 as the proposed rent information 115. FIG.

The output means 104 of the information processing device 1 uses the sales information 117 and the reservation information 119 as operation results, combines the forecasted sales information 114 and the proposed rent information 115 of a plurality of tenants in the reservation available time zone, Along with information such as the information 112, a proposal is created together with other information as necessary (S25), and output as information for display on the display units of the terminals 2a, 2b, 2c, . . . (S26).

The terminals 2a, 2b, 2c, .

FIG. 9 is a schematic diagram showing a configuration example of a screen displayed on the lender's terminal.

_The screen 104d is displayed on the display screens of the terminals 2a, 2b, 2c, . It has an operation button _104d2 for editing the contents, and a display area _104d3 for displaying the contents such as sales information 117 and reservation information 119 in the real estate of the lender.

The display area _104d3 shows the tenant occupancy rate, sales efficiency (rental time x sales amount per area, for example, a numerical value obtained from (total sales amount ÷ (rental time x area))), real-time land prices ( (For example, based on the official land price of the Ministry of Land, Infrastructure, Transport and Tourism, the land value is indexed by comparing the sales efficiency of properties with similar surrounding conditions), and proposals for the current operational status and proposals. A button for adopting the recommendation to be operated when accepting the recommendation, a detail display button for displaying details, and information on the customer segment graphed are displayed.

Lenders 4a, 4b, 4c, ... confirm the contents of the display screens of terminals 2a, 2b, 2c, ..., and if they accept the proposal, they operate the button to adopt the recommendation, and if they want to confirm a more detailed schedule, click Details. Operate the display buttons as appropriate to check the details and arrange the operation status. The terminals 2a, 2b, 2c, .

The lender information registration means 100 of the information processing device 1 receives requests from the terminals 2a, 2b, 2c, . . . and updates the lender information 111. FIG.

(3) Learning Operation The external information acquisition means 105 of the information processing apparatus 1 acquires information such as weather, traffic, population density, etc. from the outside and stores it in the storage unit 11 as the external information 116. Business information such as sales is acquired during the business of the borrowers 5a, 5b, . . . Also, in conjunction with the update of the business information 117, the necessary items of the borrower information 112 are updated.

In addition, the external information acquisition means 105 acquires customer attribute data of real estate (including other real estate in the same area) and business, and updates the lender information 111 and the customer information 113 as needed.

The learning means 106 performs the prediction operation of the sales prediction means 102 based on the lender information 111, the borrower information 112, the customer information 113, the external information 116, the sales information 117, etc., using a decision tree (LightGBM), a (simple) Neural Network and time The learning result information 118 is updated by re-learning by a method such as a sequence neural network (LSTM). Specifically, supervised learning is performed so that the prediction result is sales information 117 based on the history of lender information 111, borrower information 112, customer information 113, external information 116, and the like. More specifically, the learning means 106 learns using the average business sales scale, real estate passerby attributes, and business customer attributes as feature amounts, and the sales influence degree as the result amount. Note that the learning means 106 may generate and re-learn the learning result information 118 for each lender unit, real estate unit, or borrower unit, or may be performed for another unit, or may be performed in common for the whole. good.

(Effect of Embodiment)
According to the above-described embodiment, the sales of the lessee in the properties of a plurality of lessors are predicted, the rent in the properties of the plurality of lessors is calculated based on the predicted sales, and a plurality of Since the real estate properties of each lender are rearranged and output, in a situation where a plurality of borrowers can select a plurality of lenders, a proposal can be made in consideration of the increase in sales of each of the borrowers.

In addition, since the sales forecast of multiple lessees and the operation status and operation forecast of the lessor are displayed based on the rent of the relevant lessee, it is possible to propose the operation to the lessor considering the increase in tenant fee income. .

Further, since the learning means 106 re-learns the learning result information 118 on the basis of the business information 117 as needed, it is possible to suppress the deterioration of the accuracy of the sales forecast by the sales forecasting means 102 .

[Other embodiments]
The present invention is not limited to the above-described embodiments, and various modifications are possible without departing from the scope of the present invention.

For example, the lender may include in the lender information 111 items that limit the borrower's business genre/sales scale/enterprise size (e.g. designation of particularly welcomed genres, rejection of future use of specific operators, business (including designations for other uses) may be provided. Uses other than real estate business include uses that affect the surrounding environment, such as live performances on the street and performances, and uses for other special uses. In the lender information 111, it may be set whether or not to respond to individual exchanges and negotiations when using for a special purpose.

In addition, the borrower may not only provide general sales and services, but also operate self-propelled delivery robots, delivery drones, and unmanned self-driving vehicles. It may be a temporary rental of real estate.

Although the functions of the means 100 to 107 of the control unit 10 are implemented by programs in the above embodiment, all or part of the means may be implemented by hardware such as ASIC. Also, the program used in the above embodiment can be stored in a recording medium such as a CD-ROM and provided. , 3a, 3b . . . , 6a, 6b, 6c . , 2c . . . , 3a, 3b . Further, the information processing apparatus 1 may be configured such that each function is distributed and operated by a plurality of apparatuses, or may be arranged on a cloud. In addition, replacement, deletion, addition, etc., of the steps described in the above embodiment are possible without changing the gist of the present invention.

1: information processing device 2a-2c: terminal 3a, 3b: terminal 4: network 4a-4c: lender 5a, 5b: borrower 6a-6c: terminal 7a-7c: customer 8a-8c: real estate 10: control unit 11: storage Unit 12: communication units 30a, 30b: mobile store 100: landlord information registration means 101: lessee information registration means 102: sales prediction means 103: rent calculation means 104: output means 105: external information acquisition means 106: learning means 107: reservation Means 110: Information processing program 111: Lender information 112: Tenant information 113: Customer information 114: Predicted sales information 115: Proposed rent information 116: External information 117: Sales information 118: Learning result information 119: Reservation information

Claims (10)

the computer,
a prediction means for predicting the sales of each lessor's property in a specified period based on lessee information including at least real estate information of one or more lessors and lessee information including at least business information of lessees; ,
a rent calculation means for calculating the rent of the real estate of each of the landlords based on the landlord information, the landlord information, and the sales of the landlord predicted by the prediction means;
An information processing program for functioning as an output means for outputting the sales forecast of the said lessee in each lessor's real estate and the rent of each said lessor's real estate. 2. The information processing program according to claim 1, wherein said rent calculation means calculates a rent for each predetermined unit period. The output means assigns a predetermined weight to the sales forecast of the lender, the rent of the real estate of the lender, or the sales forecast of the lender and the rent of the real estate of the lender, in the output order of the rent of the real estate of each of the lenders. 3. The information processing program according to claim 1, wherein the sums are output in ascending order or descending order. 4. The information processing program according to any one of claims 1 to 3, wherein the landlord information includes at least one of location, area, property of building, attributes of passers-by, preferential business category, and rental price. 5. The information processing program according to any one of claims 1 to 4, wherein the borrower information includes at least one of industry, customer attributes, and sales. The output means combines the sales of the borrower, the rent of the real estate of the lender, and the real estate of each of the lenders so as to increase or decrease the sum of the sales of the borrower and the rent of the lender's real estate for each unit time. 6. The information processing program according to any one of claims 1 to 5, wherein a schedule for using the tenant's real estate is generated and output. 2. The predicting means learns based on at least one of business data of the lessee and external information, and predicts the sales of the lessee in the real estate of each lessor based on the learning result of the learning. 7. The information processing program according to any one of 6. The prediction means divides the real estate into sections so that the total sales or total rent of multiple lessees increases or decreases, and calculates the sales of the lessee in each lessor's real estate during the period specified for the divided sections. The information processing program according to any one of claims 1 to 7, which predicts. 9. The rent calculation means according to any one of claims 1 to 8, wherein the real estate is divided into sections so that the total sales or the total rent of a plurality of tenants increases or decreases, and the rent is calculated for the divided sections. information processing program. a prediction means for predicting the sales of each lessor's property in a specified period based on lessee information including at least real estate information of one or more lessors and lessee information including at least business information of lessees; ,
a rent calculation means for calculating the rent of the real estate of each of the landlords based on the landlord information, the landlord information, and the sales of the landlord predicted by the prediction means;
An information processing apparatus having a sales forecast of the borrower in the real estate of each lender and an output means for outputting the rent of the real estate of each of the lenders.

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