Information processing device and method

Abstract

A server device 20 comprises: an effect calculation unit 23 which calculates an index value of an effect of a company-internal measure when the measure is assumed to be executed in each area, by using one of a plurality of effect calculation methods for calculating said index value; a demand calculation unit 24 which calculates an index value of potential demand for a company-internal service to be provided in each area, by using one of a plurality of demand calculation methods for calculating the index value; and an evaluation unit 25 which uses a calculation result from the effect calculation unit 23 and a calculation result from the demand calculation unit 24 to evaluate each area as a target for a measure.

Description

Information processing device and method

[0001] The present invention relates to a technique for evaluating an area that is the target of a policy.

[0002] For example, when a cashless payment service provider plans a measure to attract more merchants to its cashless payment service, it is important to select the target area for the measure. One possible method for selecting the target area for the measure is to select an area that will maximize the predicted sales amount obtained when the measure is implemented. In this type of method, the predicted value after the measure is implemented is generally calculated from the actual past sales amount in the target area.

[0003] For example, Patent Document 1 discloses an invention in which a trade area analysis system specifies a target area for trade area analysis on map data, and by performing a simulation for each store included in the specified target area, determines the parameters of a predetermined probability model so as to approximate the actual sales amount values ​​stored in a store database, and then predicts the sales amount forecast for a new store and the trade area spatial structure using the probability model with determined parameters.

[0004] Japanese Patent Application Laid-Open No. 2004-185539

[0005] The conventional methods described above may not be able to accurately calculate the above forecast values ​​because they do not take into account the remaining demand (i.e., potential demand) for the company's services in the target areas of the measures. For example, in areas where the company's services are not yet widespread but where there is a large potential demand for the company's services, forecast values ​​calculated based on actual past sales figures may contain large errors.

[0006] Therefore, the present invention aims to evaluate the target areas of a policy, taking into consideration both the effects of the policy and the potential demand for the company's services.

[0007] In order to solve the above problem, the present invention provides an information processing device comprising: an effect calculation unit that calculates an index value of the effect of a company's policy when the policy is assumed to be implemented in each region, using one of a plurality of effect calculation methods for calculating the index value; a demand calculation unit that calculates an index value of potential demand for the company's services provided in each region, using one of a plurality of demand calculation methods for calculating the index value; and an evaluation unit that evaluates each region as a target of the policy, using the calculation results by the effect calculation unit and the calculation results by the demand calculation unit.

[0008] According to the present invention, it is possible to evaluate the target areas of a policy, taking into consideration both the effects of the policy and the potential demand for the company's services.

[0009] FIG. 1 is a block diagram showing an example of the configuration of an information processing system 1 according to an embodiment of the present invention. FIG. 2 is a block diagram showing an example of the hardware configuration of a server device 20 according to the embodiment. FIG. 3 is a block diagram showing an example of the functional configuration of the server device 20. FIG. 4 is a diagram illustrating location information data according to the embodiment. FIG. 5 is a diagram illustrating startup history data according to the embodiment. FIG. 6 is a diagram illustrating payment information data according to the embodiment. FIG. 7 is a graph illustrating demand index values ​​and effect index values ​​calculated for each region. FIG. 8 is a flowchart showing an example of the operation of the server device 20.

[0010] [Embodiment] [Configuration] An embodiment of the present invention will be described below. In this embodiment, a case will be described in which a cashless payment business operator evaluates and selects a target area for a policy, such as developing affiliated stores for its cashless payment service. However, the present invention is not limited to such cashless payment services, and can be applied to various services, such as when a business operator providing a retail service evaluates and selects a target area for a policy, such as when developing a policy to open a new store.

[0011] FIG. 1 is a diagram illustrating an example of the configuration of an information processing system 1 according to an embodiment of the present invention. The information processing system 1 includes multiple user terminals 10 each portable by multiple users, a server device 20 corresponding to the information processing device of the present invention, multiple payment systems 30a, 30b, 30c, etc. that perform cashless payment processing, and a communication network 2 including a wireless communication network or a wired communication network that communicatively connects these. The user terminals 10 are wirelessly communicable computers such as smartphones, wearable devices, or tablets. The server device 20 may be composed of a single computer or multiple computers. Each payment system 30a, 30b, 30c, etc. is operated by a different cashless payment service provider. Hereinafter, the payment systems 30a, 30b, 30c, etc. will be collectively referred to as payment system 30.

[0012] User terminal 10 stores at least one payment application program for carrying out cashless payments such as QR code (registered trademark) payments and electronic money payments at stores, etc. By activating one of the stored payment application programs and performing a predetermined operation, user terminal 10 requests cashless payment from one of payment systems 30a, 30b, 30c, etc. operated by a cashless payment provider corresponding to that payment application program.

[0013] In this embodiment, a telecommunications carrier that provides communication services to user terminal 10 operates server device 20 and one of multiple cashless payment providers. In Figure 1, of payment systems 30a, 30b, 30c, etc., payment system 30a is assumed to be operated by the telecommunications carrier that provides communication services to user terminal 10.

[0014] Therefore, a telecommunications carrier (referred to as "our company") that provides communication services to user terminal 10 can determine the scale of cashless payments in a certain area (i.e., the sales amount of our company's cashless payment services) based on the payment information of cashless payments held by payment system 30a, but cannot determine the scale of cashless payments (i.e., the sales amount of other companies' cashless payment services) based on payment information held by payment systems 30b, 30c, etc. other than payment system 30a (i.e., payment information held by cashless payment carriers that correspond to other companies from the perspective of our company).

[0015] Therefore, server device 20 estimates the scale of cashless payments in the above-mentioned area using payment information held by payment system 30a and the launch history of one or more payment application programs stored in user terminal 10. Note that, since a telecommunications carrier operates both server device 20 and payment system 30a, in Figure 1, server device 20 and payment system 30a may be connected by a dedicated line, or payment system 30a may be configured to include server device 20.

[0016] FIG. 2 is a diagram showing the hardware configuration of the server device 20. The server device 20 is physically configured as a computer including a processor 2001, a memory 2002, a storage 2003, a communication device 2004, and a bus connecting these devices. Each of these devices operates using power supplied from a battery (not shown). In the following description, the term "device" can be interpreted as a circuit, a device, a unit, or the like. The hardware configuration of the server device 20 may be configured to include one or more of the devices shown in FIG. 2, or may be configured without including some of the devices. Furthermore, the server device 20 may be configured by communicating with multiple devices each having a different housing.

[0017] Each function in the server device 20 is realized by loading specified software (programs) onto hardware such as the processor 2001 and memory 2002, causing the processor 2001 to perform calculations, control communication via the communication device 2004, and control at least one of reading and writing data in the memory 2002 and storage 2003.

[0018] The processor 2001 controls the entire computer by running, for example, an operating system. The processor 2001 may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc. Furthermore, for example, a baseband signal processing unit, a call processing unit, etc. may be realized by the processor 2001.

[0019] The processor 2001 reads programs (program codes), software modules, data, etc. from at least one of the storage 2003 and the communication device 2004 into the memory 2002 and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described below. The functional blocks of the server device 20 may be implemented by a control program stored in the memory 2002 and running on the processor 2001. Various processes may be executed by one processor 2001, or may be executed simultaneously or sequentially by two or more processors 2001. The processor 2001 may be implemented by one or more chips. The programs may be transmitted to the server device 20 via a telecommunications line.

[0020] The memory 2002 is a computer-readable recording medium and may be composed of at least one of, for example, a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 2002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 2002 can store executable programs (program codes), software modules, etc. for implementing the method according to this embodiment.

[0021] Storage 2003 is a computer-readable recording medium, and may be configured by at least one of, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. Storage 2003 may also be called an auxiliary storage device.

[0022] The communication device 2004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also called, for example, a network device, a network controller, a network card, or a communication module.

[0023] Each device, such as the processor 2001 and the memory 2002, is connected by a bus for communicating information. The bus may be configured using a single bus, or may be configured using different buses between each device.

[0024] The server device 20 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 2001 may be implemented using at least one of these pieces of hardware.

[0025] The user terminal 10 is physically configured as a computer device including a processor, memory, storage, a communication device, an input device, an output device, and a bus connecting these devices. The processor, memory, and storage of the user terminal 10 are hardware similar to the processor 2001, memory 2002, and storage 2003 of the server device 20. The communication device of the user terminal 10 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. to realize at least one of frequency division duplex (FDD) and time division duplex (TDD). For example, the transmitting and receiving antenna, amplifier unit, transmitting and receiving unit, and transmission path interface may be realized by a communication device. The transmitting and receiving unit may be implemented as a transmitting unit and a receiving unit that are physically or logically separated. The input device of the user terminal 10 is an input device that accepts input from outside (e.g., a key, a microphone, a switch, a button, a GPS unit including a GPS antenna, etc.). The output device of the user terminal 10 is an output device (e.g., a display, a speaker, an LED lamp, etc.) that outputs to the outside. Note that the input device and the output device may be integrated into one device (e.g., a touch screen).

[0026] 3 is a block diagram showing the functional configuration of the server device 20. In the server device 20, a processor 2001 reads programs and the like from a storage 2003 into a memory 2002 and executes them, thereby realizing the functions of an acquisition unit 21, a storage unit 22, an effect calculation unit 23, a demand calculation unit 24, and an evaluation unit 25.

[0027] The acquisition unit 21 has a function for acquiring various information, such as acquiring payment information related to a cashless payment made by launching a payment application program stored in the user terminal 10, and location information related to the location where the cashless payment was made. As described above, the telecommunications carrier that provides communication services to the user terminal 10 operates the payment system 30a and the server device 20, and therefore the acquisition unit 21 of the server device 20 can acquire the payment information held by the payment system 30a. The acquisition unit 21 acquires the payment information from the payment system 30a along with a user ID for identifying the user using the user terminal 10.

[0028] The acquisition unit 21 also acquires location information indicating the location of the user terminal 10 together with the user ID, for example, from a positioning means (not shown). The positioning means referred to here may be any well-known positioning means, and may be, for example, a GPS unit provided in the user terminal 10, or a system that performs positioning of the user terminal 10 using a method known as base station positioning.

[0029] 4, the storage unit 22 stores the user ID and payment information acquired by the acquisition unit 21 in association with each other. The payment information includes at least the date and time of the cashless payment and the payment amount.

[0030] 5, the storage unit 22 stores the user ID and the location information acquired by the acquisition unit 21 in association with each other. This location information includes at least the date and time when the positioning of the user terminal 10 was performed and the location where the positioning was performed.

[0031] As described above, the payment information includes the payment date and time, and the location information includes the positioning date and time, so the location where the cashless payment was made can be identified by identifying a pair of payment information and location information that minimizes the difference between the payment date and time and the positioning date and time. Of course, the date and time of the cashless payment and the date and time of the positioning may not exactly match, but here, the location measured on the date and time of the positioning that is closest to the payment date and time is considered to be the location where the cashless payment was made.

[0032] The acquisition unit 21 also acquires the startup history and location information relating to the location at which the startup occurred for application programs for which payment information can be acquired by the acquisition unit 21 when launched on the user terminal 10, and application programs for which payment information is not acquired by the acquisition unit 21 even when launched on the user terminal 10. An application program for which payment information can be acquired by the acquisition unit 21 when launched on the user terminal 10 is a payment application program for requesting cashless payment from the payment system 30a operated by the telecommunications carrier (i.e., the company), and is hereinafter referred to as the company's payment application program.

[0033] In contrast, an application program for which payment information is not acquired by acquisition unit 21 even when activated on user terminal 10 is a payment application program for requesting cashless payment from payment systems 30b, 30c, etc. (i.e., payment systems operated by other companies) other than payment system 30a, and is hereinafter referred to as a "other company's payment application program." Note that one user terminal 10 may have multiple other company's payment application programs.

[0034] The operating system (OS) stored in the user terminal 10 has a function for saving a launch history when an application program is launched on the user terminal 10. This function is valid regardless of whether the launched application program is a company's own payment application program or a third-party payment application program. The launch history includes at least program identification information (e.g., program name) for identifying the launched application program and the launch date and time, and the acquisition unit 21 acquires this launch history from the user terminal 10 together with the user ID.

[0035] 6, the storage unit 22 stores the user ID acquired by the acquisition unit 21 in association with the launch history of each application program. The launch history includes at least the program name of each application program (e.g., application A, application B, application C, etc.) and the launch date and time of the application program.

[0036] As described above, the startup history includes the startup date and time, and the location information includes the positioning date and time, so the location at which each application program was started can be identified by identifying a pair of startup history and location information that minimizes the difference between the startup date and time and the positioning date and time. Of course, the date and time at which an application program was started and the date and time at which its positioning was performed may not exactly match, but here, the location that was determined at the date and time at which the positioning was performed that is closest to the date and time at which the application program was started is considered to be the location at which the application program was started.

[0037] Returning to the explanation of Figure 3, the effect calculation unit 23 calculates an index value of the effect of the policy (hereinafter referred to as the effect index value) assuming that the policy is implemented in each region by the operator of the payment system 30a.

[0038] This effect calculation method is a method for calculating an effect indicator value based on the difference in sales amount from the company's services at two points in time, before and after a measure implemented in the past, and includes the following multiple effect calculation methods.

[0039] (1-1) Method of calculating an effect index value using a growth rate found from the sales amounts of the company's services in each region at two past points in time: When the sales amount for month M in each region is s and the sales amount for month M' is s', the effect calculation unit 23 calculates the growth in sales amount per implementation of a measure as s - s' or (s - s') / s. The effect index value may be the value of this growth in sales amount, or may be a value obtained by adding or multiplying this growth rate to the sales amount immediately before the measure (the same applies below).

[0040] Here, for example, s = sales amount of the company's cashless payment service in each region for month M, and s' = sales amount of the company's cashless payment service in each region for month M'. Also, s = average sales amount of the company's cashless payment service in each region for months M' to M, and s' = average sales amount of the company's cashless payment service in each region for months M' to M. Here, sales amount of cashless payment services is the total amount of payments handled through cashless payment services (total transaction volume) (the same applies hereinafter).

[0041] (1-2) A method for calculating an effectiveness index value using the sales amount of the company's services at two points in the past in each region and the growth rate determined from the number of measures implemented in that region. When the sales amount in month M in each region is s and the sales amount in month M' is s', the effect calculation unit 23 calculates the growth in sales amount per implementation of m measures implemented in months M to M' as (s-s') / m or (s-s') / s·m.

[0042] As in the above method (1-1), for example, s = the sales amount of the company's cashless payment service in each region for month M, s' = the sales amount of the company's cashless payment service in each region for month M', s = the average sales amount of the company's cashless payment service in each region for months M' to M, and s' = the sales amount of the company's cashless payment service in each region for months M' to M.

[0043] (1-3) A method of calculating an effect index value based on causal inference technology using a growth rate obtained by removing natural increases and decreases not due to the implementation of measures from the growth rate calculated by the above method (1-1-2). When the sales amount for month M in each region is s, the sales amount for month M' is s', and the natural increase or decrease based on causal inference technology is Δ, the effect calculation unit 23 calculates the growth in sales amount per implementation of m measures carried out from month M' to month M as (s-s'-Δ) / m or (s-s'-Δ) / s·m.

[0044] For example, the effect calculation unit 23 uses propensity score matching technology for all regions in which no measures were implemented between month M' and month M to obtain homogeneous regions that are homogeneous as of month M' in which no measures were implemented. Here, the effect calculation unit 23 calculates Δ by setting Δ = t - t', where t = the sales amount of the company's cashless payment service in the homogeneous region for month M and t' = the sales amount of the company's cashless payment service in the homogeneous region for month M'. Furthermore, the effect calculation unit 23 uses synthetic control technology for all regions in which no measures were implemented between month M' and month M to obtain a hypothetical trend in the sales amount of the company's cashless payment service in each region from month M' to month M if the measures were not implemented in each region. Here, where t = the sales amount of the company's cashless payment service in each hypothetical region for month M and t' = the sales amount of the company's cashless payment service in each hypothetical region for month M', the effect calculation unit 23 calculates Δ by setting Δ = t - t'.

[0045] The above are examples of the effect calculation methods. Any of these multiple effect calculation methods can be used.

[0046] Returning to the explanation of FIG. 3, the demand calculation unit 24 calculates an index value of potential demand for the company's services provided in each region using one of a plurality of demand calculation methods for calculating the index value.

[0047] These demand calculation methods include the following multiple effect calculation methods.

[0048] (2-1) Method using payment amounts or percentages of payments made by users who have not subscribed to the company's cashless payment service using payment methods other than the company's cashless payment service (for example, sales amounts of other companies' cashless payment services, credit cards, cash payments, etc.): The demand calculation unit 24 generates cashless payment scale information regarding the scale of cashless payments in the analysis target area, using payment information acquired by the acquisition unit 21 for locations included in the area to be analyzed (hereinafter referred to as the analysis target area), such as a city, ward, town, village, or prefecture, and startup history acquired by the acquisition unit 21 for locations included in the analysis target area. The specific generation method is as follows.

[0049] Based on the payment information acquired by the acquisition unit 21 for locations included in the analysis area, it is possible to determine the amount of cashless payments processed by the payment system 30a in the analysis area. Specifically, when the analysis area and analysis period are specified, the demand calculation unit 24 extracts payment information processed at locations included in the analysis area during the analysis period from the content acquired and stored by the acquisition unit 21 as shown in Figures 4 and 5, and calculates the sum of the payment amounts included in the extracted payment information. This sum corresponds to the amount of cashless payments processed by the payment system 30a in the analysis area and analysis period, and will be referred to as the company's cashless payment amount M below.

[0050] Then, the demand calculation unit 24 calculates a coefficient A for the company's cashless payment amount M to generate cashless payment scale information including the amount processed by the payment systems 30b, 30c, etc. from the company's cashless payment amount M.

[0051] Specifically, the demand calculation unit 24 calculates the number of payments C1 using the first payment application program by referring to the contents acquired and stored by the acquisition unit 21 as illustrated in Figures 4 and 5 and counting the number of payment information processed during the analysis period at locations included in the analysis area.

[0052] Next, the demand calculation unit 24 counts the number of times the second payment application program has been launched during the analysis period at locations included in the analysis area, by referring to the content acquired and stored by the acquisition unit 21 as shown in Figures 4 and 6. In order to make a cashless payment using the second payment application program, it is necessary to launch the second payment application program, and so the number of times S2 the second payment application program has been launched can be regarded as the number of times cashless payments have been made using the second payment application program.

[0053] The generation unit then calculates the coefficient A by taking the number of payments C1 using the first payment application program as the denominator and the number of launches S2 of the second payment application program as the numerator.

[0054] In other words, coefficient A = (number of times the second payment application program is started S2) / (number of times payments are made using the first payment application program C1).

[0055] Then, the demand calculation unit 24 calculates the amount calculated by multiplying the coefficient A by the company's cashless payment amount M as the sales amount of the other company's cashless payment service.

[0056] Furthermore, it may be possible to investigate the scale of payment amounts by region, for example, from the results of a national census or a prefectural statistical survey. Therefore, the acquisition unit 21 acquires cashless payment scale information regarding the scale of cashless payments, which is obtained through a national census, a prefectural statistical survey, or the like. The cashless payment scale information is, for example, information that indicates the total amount of cashless payments in each region. The demand calculation unit 24 calculates the payment amount by credit card, cash, or the like by subtracting the sales amount of the company's cashless payment service in each region from the total amount of cashless payments in each region indicated by the cashless payment scale information. Furthermore, the demand calculation unit 24 may calculate, as the potential demand (demand index value) for the company's cashless payment service in each region, the ratio of the value obtained by subtracting the sales amount of the company's cashless payment service in each region from the total amount of cashless payments in each region indicated by the cashless payment scale information.

[0057] (2-2) Method using the number or percentage of affiliated stores affiliated with another company's cashless payment service: The number of affiliated stores affiliated with another company's cashless payment service can be identified through a survey of each store. Therefore, the acquisition unit 21 acquires the number of affiliated stores affiliated with another company's cashless payment service in each region, identified through such a survey. The demand calculation unit 24 calculates the number of affiliated stores affiliated with another company's cashless payment service in each region as the potential demand (demand index value) for the company's own cashless payment service in that region. Furthermore, the demand calculation unit 24 may calculate the ratio of the number of affiliated stores affiliated with the other company's cashless payment service in that region to the total number of affiliated stores affiliated with the company's own and other companies' cashless payment services in that region as the potential demand (demand index value) for the company's own cashless payment service in that region.

[0058] (2-3) Method using the number or percentage of users who have used another company's cashless payment service among users who have not subscribed to the company's cashless payment service: The number of users who have used another company's cashless payment service can be determined by counting the number of users who have launched another company's payment application on the user terminal 10. The demand calculation unit 24 calculates the number of users who have used another company's cashless payment service in each region as the potential demand (demand index value) for the company's cashless payment service in that region, for example by referring to the information exemplified in FIGS. 5 and 6 . The demand calculation unit 24 may also calculate the ratio of the number of users who have used another company's cashless payment service in that region to the total number of users who have used the company's and other companies' cashless payment services in that region as the potential demand (demand index value) for the company's cashless payment service in that region.

[0059] (2-4) Method using the number or percentage of payments made by users who have not subscribed to the company's cashless payment service using another company's cashless payment service: If the number of times the other company's payment application is launched on the user terminal 10 is considered to be the number of payments made using the other company's cashless payment service, the number of payments made using the other company's cashless payment service can be determined by counting the number of times the other company's payment application is launched. The demand calculation unit 24 calculates the number of payments made using the other company's cashless payment service in each region as the potential demand (demand index value) for the company's cashless payment service in that region, for example by referring to the information illustrated in FIGS. 5 and 6 . The demand calculation unit 24 may also calculate the ratio of the number of payments made using the other company's cashless payment service in that region to the number of payments made using the company's and the other company's cashless payment services in that region as the potential demand (demand index value) for the company's cashless payment service in that region.

[0060] (2-5) Method using the payment amount or percentage of payments made by users who can use the company's cashless payment service using payment methods other than the company's cashless payment service (for example, sales amounts for other companies' cashless payment services, credit cards, cash payments, etc.) As described above, the scale of payment amounts on a regional basis can sometimes be investigated from the results of, for example, a national census or a prefectural statistical survey. Therefore, the acquisition unit 21 acquires cashless payment scale information on the scale of cashless payments surveyed through a national census or a prefectural statistical survey. The demand calculation unit 24 subtracts the sales amount of the company's cashless payment service used by users who can use the company's cashless payment service in each region from the total amount of cashless payments in each region indicated by the cashless payment scale information, and calculates the resulting value as the potential demand (demand index value) for the company's cashless payment service in that region. In addition, the demand calculation unit 24 may calculate the potential demand (demand index value) for the company's cashless payment service in that region as the ratio of the total amount of cashless payments in each region indicated by the cashless payment scale information minus the sales amount of the company's cashless payment service used by users who can use the company's cashless payment service in each region.

[0061] (2-6) Method using payment amount or ratio when a user who can use the company's cashless payment service makes a payment using the company's cashless payment service at a member store that is a member of another company's cashless payment service: Member stores that are a member of another company's cashless payment service can be identified through surveys of each store. The acquisition unit 21 then acquires member stores that are a member of another company's cashless payment service in each region, identified through such surveys. The demand calculation unit 24 calculates the payment amount when a user who can use the company's cashless payment service makes a payment using the company's cashless payment service at a member store that is a member of the other company's cashless payment service, as the potential demand (demand index value) for the company's cashless payment service in that region. Furthermore, the demand calculation unit 24 calculates the ratio of the payment amount when a user who can use the company's cashless payment service makes a payment using the company's cashless payment service at a member store that is a member of another company's cashless payment service to the total payment amount when payments are made using the company's and other companies' cashless payment services in each region as the potential demand (demand index value) for the company's cashless payment service in that region. In other words, this demand calculation method calculates the demand index value based on the usage history of other companies' services.

[0062] (2-7) Method using payment amount or ratio when a user who can use the company's cashless payment service makes a payment using a payment method other than the cashless payment service (such as a credit card or cash payment) at a store where the company's cashless payment service is not available: When the payment amount when a user who can use the company's cashless payment service makes a payment using a payment method other than the cashless payment service (such as a credit card or cash payment) at a store where the company's cashless payment service is not available is known, the demand calculation unit 24 calculates the payment amount as the potential demand (demand index value) for the company's cashless payment service in that area. In addition, the demand calculation unit 24 may calculate the ratio of the payment amount to the total amount of cashless payments in each area indicated by the cashless payment scale information described above as the potential demand (demand index value) for the company's cashless payment service in that area.

[0063] (2-8) Method using payment amount or ratio when a user who can use the company's cashless payment service makes a payment using another company's cashless payment service at a store where the company's cashless payment service is available: When the payment amount when a user who can use the company's cashless payment service makes a payment using another company's cashless payment service at a store where the company's cashless payment service is available is known, the demand calculation unit 24 calculates the payment amount as the potential demand (demand index value) for the company's cashless payment service in that area. Furthermore, the demand calculation unit 24 may calculate the ratio of the payment amount to the total amount of cashless payments in each area indicated by the cashless payment scale information described above as the potential demand (demand index value) for the company's cashless payment service in that area. In other words, in this demand calculation method, the demand index value is calculated based on the usage history of other companies' services.

[0064] The above are examples of the demand calculation methods. Any of these multiple demand calculation methods can be used.

[0065] The evaluation unit 25 uses the calculation results by the effect calculation unit 23 and the calculation results by the demand calculation unit 24 to evaluate each region as a target of the policy.

[0066] FIG. 7 is a graph illustrating the demand index value and the effect index value calculated for each region (regions a1, a2, and a3). The evaluation unit 25 evaluates a region where the effect index value calculated by the effect calculation unit 23 is equal to or greater than the first threshold value and the demand index value calculated by the demand calculation unit 24 is equal to or greater than the second threshold value higher than the other regions. In the example of FIG. 7 , region a2, which corresponds to a region where the effect index value is equal to or greater than the first threshold value t1 and the demand index value is equal to or greater than the second threshold value t2, is evaluated higher than the other regions a1 and a3. For example, if a policy is to be implemented in a region where the policy effect is large and the potential demand is large, region a2 is selected as the policy implementation region. On the other hand, if a policy is to be implemented in a region where the policy effect is large and the potential demand is small (a region where the company's services are considered to be widely distributed), region a3 is selected as the policy implementation region.

[0067] Furthermore, the evaluation unit 25 may perform evaluation by weighting according to the ranking of the effect index value calculated by the effect calculation unit 23 and weighting according to the ranking of the demand index value calculated by the demand calculation unit 24. For example, the evaluation of a region that is ranked xth from the top on the coordinate axis of the effect index value and yth from the top on the coordinate axis of the demand index value is calculated by the formula w1×1 / x+w2×1 / y, where w1 is a constant determined for the effect index value and w2 is a constant determined for the demand index value.

[0068] [Operation] Next, the operation of this embodiment will be described. FIG. 8 is a flowchart showing an example of the operation of the server device 20. Before the process shown in FIG. 8 is started, the acquisition unit 21 acquires location information of each user's user terminal 10, for example, periodically or intermittently, and stores the location information in the storage unit 22 in association with the user ID of the user. Also, before the process shown in FIG. 8 is started, the acquisition unit 21 acquires payment information of each user, for example, when a cashless payment is made or periodically, and stores the payment information in the storage unit 22 in association with the user ID of the user. Also, before the process shown in FIG. 8 is started, the acquisition unit 21 acquires a startup history of each user terminal 10, for example, when a payment application program is started or periodically, and stores the startup history in the storage unit 22 in association with the user ID of the user.

[0069] In FIG. 8, the effect calculation unit 23 calculates an index value of the effect of a policy when it is assumed that the policy is implemented in each region by using one of a plurality of effect calculation methods (step S11).

[0070] The demand calculation unit 24 calculates an index value of potential demand for the company's services provided in each region using one of a plurality of demand calculation methods (step S12).

[0071] The evaluation unit 25 uses the calculation results by the effect calculation unit 23 and the calculation results by the demand calculation unit 24 to evaluate each region as a target of the policy (step S13).

[0072] According to the embodiment described above, it is possible to evaluate the target area of ​​a policy, taking into consideration both the effect of the policy and the potential demand for the company's services.

[0073] [Modifications] The present invention is not limited to the above-described embodiment. The above-described embodiment may be modified as follows. Furthermore, two or more of the following modifications may be combined and implemented.

[0074] The block diagrams used to explain the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (e.g., wired, wireless, etc.) and these multiple devices. The functional block may also be realized by combining software with the single device or multiple devices.

[0075] Functions include, but are not limited to, judgment, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0076] For example, the server device 20 in one embodiment of the present disclosure may function as a computer that performs the processing of the present disclosure.

[0077] Each aspect / embodiment described in the present disclosure may be applied to at least one of systems using LTE (Long Term Evolution), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 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)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, UWB (Ultra-Wide Band), Bluetooth (registered trademark), or other suitable systems, and next-generation systems extended based on these. Furthermore, a combination of multiple systems (e.g., a combination of at least one of LTE and LTE-A with 5G, etc.) may also be applied.

[0078] The present invention may also be an information processing method characterized by including an effect calculation step of calculating an index value of the effect of a company's policy assuming that the policy is implemented in each region using one of a plurality of effect calculation methods for calculating the index value; a demand calculation step of calculating an index value of potential demand for the company's services provided in each region using one of a plurality of demand calculation methods for calculating the index value; and an evaluation step of evaluating each region as a target for the policy using the calculation results of the effect calculation step and the calculation results of the demand calculation step. The processing procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be rearranged as long as there is no contradiction. For example, the methods described in this disclosure present various step elements in an exemplary order and are not limited to the specific order presented.

[0079] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be transmitted to another device.

[0080] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0081] 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 herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

[0082] Software, whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise, should be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc. Additionally, software, instructions, information, etc. may be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then such wired and / or wireless technologies are included within the definition of a transmission medium.

[0083] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof. Note that terms described in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings.

[0084] Furthermore, the information, parameters, etc. described in this disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information.

[0085] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0086] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0087] The "unit" in the configuration of each of the above devices may be replaced with "means," "circuit," "device," etc.

[0088] When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, when the term "or" is used in this disclosure, it is not intended to be an exclusive or.

[0089] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0090] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different."

[0091] 1: Information processing system, 2: Communication network, 20: Server device, 21: Acquisition unit, 22: Memory unit, 23: Effect calculation unit, 24: Demand calculation unit, 25: Evaluation unit, 2001: Processor, 2002: Memory, 2003: Storage, 2004: Communication device, 30a, 30b, 30c: Payment system, a1, a2, a3: Plots corresponding to regions.

Claims

1. An information processing device comprising: an effect calculation unit that calculates an index value of the effect of a company's measures assuming that the measures are implemented in each region, using one of a plurality of effect calculation methods for calculating the index value; a demand calculation unit that calculates an index value of potential demand for the company's services provided in each region, using one of a plurality of demand calculation methods for calculating the index value; and an evaluation unit that evaluates each region as a target of the measures using the calculation results by the effect calculation unit and the calculation results by the demand calculation unit.

2. The information processing device according to claim 1, characterized in that the multiple effect calculation methods include an effect calculation method that calculates an index value of the effect based on the difference in sales amount of the company's services at two points in time, before and after a measure implemented in the past.

3. The information processing device according to claim 2, wherein said plurality of demand calculation methods includes a demand calculation method for calculating an index value of said demand based on a usage history of services of other companies.

4. The information processing device described in claim 1, characterized in that the evaluation unit evaluates areas where the index value calculated by the effect calculation unit is equal to or greater than a first threshold and where the index value calculated by the demand calculation unit is equal to or greater than a second threshold higher than areas other than the area in question.

5. The information processing device according to claim 1, characterized in that the evaluation unit performs the evaluation by weighting the index values ​​calculated by the effect calculation unit according to the ranking of the index values ​​calculated by the demand calculation unit.

6. An information processing method comprising: an effect calculation step of calculating an index value of the effect of a company's policy assuming that the policy is implemented in each region, using one of a plurality of effect calculation methods for calculating the index value; a demand calculation step of calculating an index value of potential demand for the company's services provided in each region, using one of a plurality of demand calculation methods for calculating the index value; and an evaluation step of evaluating each region as a target of the policy, using the calculation results from the effect calculation step and the calculation results from the demand calculation step.

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