JP2007310704A - Method of estimating service use change - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To promote service introduction of a user by making it possible to estimate change of amount of service use without spending labor of data input for simulation so much when estimating amount of service use of the service charged corresponding to amount of service provision, and not to require the supplier side to disclose detail of use charge. <P>SOLUTION: Amount of desired charge of a user to object service, the maximum charge option, and the minimum charge option are read. Characteristic value indicating change of amount of service use which the user supposes from the price, or characteristic value of amount of service use change distribution is estimated, and the propriety of service possibility is determined by comparing the characteristic value with change distribution characteristic value capable of providing service memorized beforehand. When service providing possibility is negative, the maximum charge option and the minimum charge option are decided so that the service can be provided from the distribution of estimated use charge. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a service usage fluctuation estimation method suitable for use in estimating usage fluctuations of services that are charged quantitatively according to the amount of services such as electricity charges, water charges, and telephone charges.

  As a technique for predicting fluctuations in service usage and usage charges of services that are charged quantitatively according to the amount of services such as electricity charges, water charges, telephone charges, etc., for example, the current supply in Patent Document 1 below Based on the consumption (utilization) of a resource (service) and the estimated future consumption calculated based on that consumption, the fee paid by the service user is predicted based on multiple contract conditions related to the use of that resource. A method is disclosed.

  Also, the following Patent Document 2 discloses a method for calculating a change in charge associated with a change in the charge set value by changing the charge set value for each condition when calculating the charge according to the usage amount. Has been.

  Further, the following Non-Patent Document 1 suggests that the concept of “price elasticity” quantifies the response to the price of the customer and uses it for business planning and the like.

JP 2002-297832 A JP 2002-296299 A Isamu Matsukawa, “Economic Analysis of Electricity Charges”, Nihon Crihonsha, April 1995, P20

  Patent Document 1 describes predicting the future power consumption based on the past power consumption. In addition, the power monitoring device of Patent Document 2 is configured to instantaneously send the measured power value to the monitor side, calculate the electricity bill, and easily change the charge setting on the monitor side.

  However, in the above prior art, in order to estimate the change in service usage of a user by simulation evaluation under various setting conditions, it is necessary to ask the user to change the setting conditions comprehensively. It will take. In addition, for the prediction calculation, it is necessary for the supplier side to present the base fee in advance, and there is a direct problem that the usage fee amount must be determined in advance and disclosed, If there is a gap between the two, there is a high possibility that the user will hesitate to introduce the service due to the disclosure of the usage fee amount.

  The present invention has been made to solve the above-described problems, and an object of the present invention is to provide a system for estimating fluctuations in service usage without requiring a user to input data for simulation. There is. It is another object of the present invention to provide a system that does not require the supplier side to disclose the details of the usage fee and facilitates the introduction of the service by the user.

  In the service usage fluctuation estimation method of the present invention, in order to estimate the service usage fluctuation assumed by the user, first, before the service is introduced, the user's desired charge amount, the maximum charge option and the minimum charge option are used. The desired purchase price for the target option contract when an optional contract is introduced is read. Then, the characteristic value indicating the service usage fluctuation assumed by the user and the service usage fluctuation distribution characteristic value are estimated from the price, and the characteristic distribution and the fluctuation distribution that can be provided and stored in advance are stored. By comparing the characteristic value, it is determined whether the service can be provided. By this means, it is possible to estimate the service usage fluctuation assumed by the user before the service introduction without taking the time and effort of setting various conditions and performing prediction calculation. On the other hand, since it is estimated by reading the user's desired price, there is no need for the supplier side to predetermine and disclose the usage fee amount in advance, and the user is hesitant to introduce the service due to the gap between the presented amount and the assumed user amount. It is possible to avoid this problem.

  ADVANTAGE OF THE INVENTION According to this invention, the system which estimates the fluctuation | variation of a service usage-amount can be provided, without taking the effort of the data input for a simulation so much to a user. Further, it is not necessary for the supplier side to disclose the details of the usage fee, and it is possible to provide a system that can promote the service introduction of the user.

  Hereinafter, each embodiment will be described with reference to FIGS. 1 to 7.

Embodiment 1
Hereinafter, a first embodiment will be described with reference to FIGS. 1 to 4.
First, the configuration of the service usage fluctuation estimation system according to the first embodiment will be described with reference to FIG.
FIG. 1 is a configuration diagram of a service use fluctuation estimation system according to the first embodiment.

  As shown in FIG. 1, the service usage fluctuation estimation system according to the present embodiment is connected to a computer 100, a display device 201, a keyboard 202, a mouse 203, and an external storage device 200.

  The computer 100 is a device for giving a command to a connected peripheral device and executing a program.

  The display device 201 is a device for displaying output information such as a liquid crystal display or a CRT.

  A keyboard 202 and a mouse 203 are input devices for a user to input information.

  The external storage device 200 is a device that stores a large amount of data such as a hard disk drive.

  The computer 100 has a configuration in which a processor 101, a main storage device 102, an external storage device interface 103, a graphic interface 104, an input / output interface 105, and a network interface 106 are connected via a bus 00.

  The program stored in the external storage device 200 is loaded into the main storage device 102 and executed by the processor 101. The external storage device 200 is connected to the external storage device interface 103, the display device 201 is connected to the graphic interface 104, and the input / output interface 105 is connected to input / output devices such as a keyboard 202 and a mouse 203, respectively.

  The computer 100 is connected to an external network such as a LAN or a WAN by a network interface 106.

  The external storage device 200 stores a service usage fluctuation estimation program 300.

  In the present embodiment, information such as a service desired price and an option desired price from a user is input from an input / output device such as a keyboard 202 or a mouse 203.

  The external storage device 200 stores the characteristic value of the service distribution variation distribution of the evaluation target service.

  The processor 101 executes a service usage fluctuation estimation program 300 described below, and can estimate the characteristic value of the service usage fluctuation distribution assumed by the user or provide the usage fluctuation distribution according to the read desired price. Comparison with the fluctuation distribution and determination of service availability from the comparison result.

  As shown in FIG. 1, the service usage fluctuation estimation program 300 includes a service usage fluctuation estimation unit 301, a service provision determination unit 302, a service provision form generation unit 303, and a service usage fee calculation unit 304 as shown in FIG.

  The service usage fluctuation estimation unit 301 is a part for estimating the usage fluctuation of a service. When a desired service price desired for introduction of the target service and an option presented in advance are added from an input device such as a keyboard 201 or a mouse 203. It is determined whether there is an input of the desired option price, and when there is an input, the characteristic value of the service usage fluctuation distribution assumed by the user from the service desired price and the option desired price, In this embodiment, assuming that the distribution shape of the service usage variation distribution is a normal distribution, the average value and the variance value are estimated and stored in the external storage device 200.

  The service provision determination unit 302 is a part that determines whether or not a service can be provided. The service provision determination unit 302 reads the characteristic value of the service provisionable variation distribution set in advance by the service provider from the external storage device 200, and the service utilization variation estimation unit 301. By comparing the characteristic values of the service usage fluctuation distribution calculated in step 1, it is determined whether or not the service provider can actually provide the service. In this embodiment, as will be described in detail later, the 5% percentile of the service usage variation distribution is larger than the 5% percentile of the service provision variation distribution, and the 95% percentile of the service utilization variation distribution is the service variation variation distribution. If it is smaller than 95%, it is determined that the service can be provided. In other cases, it is determined that the service cannot be provided.

  The service provision form generation unit 303 is a part that determines a new service provision form, specifically, an additional option for the service. When the service provision determination unit 302 determines that the service cannot be provided, the service provision form generation unit 303 selects any option for the target service. As a result, the optional condition, that is, the maximum charge price or the minimum charge price is estimated so as to be the provisionable condition of the service provision determination unit 302. If the service provision determination unit 302 determines that the service can be provided, it estimates how much the price can be reduced.

  The service usage fee calculation unit 304 is a part that calculates a service usage fee based on the service provision amount. Based on the option conditions estimated by the service provision form generation unit 303, the service usage fee calculation unit 304 calculates and displays the usage fee for the target user. Display on the device 201.

  In this embodiment, when the user inputs a desired price for the target service and an option desired price for any additional option to the target service, the service usage fluctuation assumed by the user in introducing the target service is estimated. In particular, an example of calculating the characteristic value of the service usage fluctuation distribution will be described. As a result, it is possible to estimate the service usage fluctuation assumed by the user before the service is introduced without taking the time and effort of setting various conditions and performing prediction calculations. Furthermore, since it is estimated from reading the user's desired price, there is no need for the supplier side to predetermine and disclose the amount of the usage fee in advance, and the user is hesitant to introduce the service due to the gap between the amount presented and the estimated user amount It is possible to avoid this problem.

Hereinafter, the process of estimating the service usage fluctuation of the service usage fluctuation system according to the first embodiment will be described with reference to FIGS. 2 and 3.
FIG. 2 is a flowchart showing a process for estimating the service usage fluctuation of the service usage fluctuation system according to the first embodiment.
FIG. 3 is a diagram for explaining the usage amount distribution when estimating the service usage fluctuation.

  First, an average service usage amount X0 assumed by the user is input from the input device, stored in the external storage device 200, and an amount unit price ΔY1 that can be paid for a change in usage amount from the average service usage amount X0 to a constant amount ΔX1 is input. The data is input from the device and stored in the external storage device 200 (step 201). Here, the usage amount change is, for example, a case where the average service usage amount X0 is increased by 10%, that is, ΔX1 = X0 × 0.1.

  If there is no input of the average service usage X0 and the unit price ΔY1 from the user, step 201 is repeated, and if there is an input, the process proceeds to step 202.

  Next, when an arbitrary maximum fee option is added, an amount Y3 that can be paid for the option itself is input from the input device and stored in the external storage device 200 (step 202). Here, the maximum fee option is a fee menu in which the amount to be paid becomes the maximum fee Y2 = ΔY1 × X2 regardless of the value of the usage amount when the usage amount by the user exceeds the usage amount threshold value X2. For example, when the usage threshold value X2 is set to twice the average service usage amount X0 X2 = X0 × 2.0, and this maximum fee option contract is added to the premise service contract, for that option An additional amount Y3 that can be paid is input from the input device and stored in the external storage device 200. However, if the additionally payable amount Y3 is input as 0, the set value of the usage amount threshold value X2 can be decreased stepwise until the payable amount Y3 is input as a value larger than 0. Read input of amount Y3 (> 0). For example, here, the usage threshold value X2 is decreased stepwise by 0.1 as X2 = X0 × (2.0−0.1 × i): i = 1, 2,. When an amount Y3 that can be paid greater than 0 is input, Y3 and the usage threshold X2 are input from the input device, stored in the external storage device 200, and the process proceeds to step 203.

  The distribution pattern of usage fluctuation assumed in the target service is input from the input device and stored in the external storage device 200 (step 203). For example, here, a distribution of assumed usage fluctuation is a normal distribution. If the distribution pattern of usage fluctuation is input, the process proceeds to step 204.

Next, from the average service usage amount X0, the monetary unit price ΔY1, the usage amount threshold value X2, and the amount Y3 that can be paid for the option itself, stored in step 201 and step 202, the characteristic value of the service usage fluctuation distribution assumed by the user is obtained. Is estimated (step 204). The characteristic value is the standard deviation σ of the service usage fluctuation distribution assumed by the user since the distribution handled in this example is a normal distribution in step 203. Here, as shown in FIG. 3, when assuming a service usage distribution according to a normal distribution with average X0 and standard deviation σ as shown in FIG. 3 of an average value of the hatched portion) that taken as the amount Y3 obtain payment option itself, the service that the user searches the ^~ standard deviation σ of the Y3 input and this difference matches, the user is assumed Estimate usage fluctuation distribution. For this purpose, first, an initial standard deviation value σ0 is set as the standard deviation σ 1 ^to an utilization distribution having an average of X0. The probability density function f (x) for the usage amount x of the usage distribution is a normal distribution and is calculated by the following (Equation 1).

  Further, an average value Y4 of a difference (a hatched portion in FIG. 3) generated depending on the presence / absence of the maximum fee option is calculated by the following (Equation 2).

Further, Y4 calculated in (Equation 2) is compared with the amount of money Y3 that can be paid to the option itself. If the sign of the difference (Y4−Y3) is negative, the usage distribution is changed in steps from the standard deviation σ ^to. Assuming the usage distribution increased by a certain amount, the average value Y4 of the difference (shaded portion in FIG. 3) generated by the presence / absence of the maximum fee option is calculated by (Equation 2).

On the other hand, assuming the usage distribution code that stepwise constant amount smaller ^~ standard deviation σ usage distribution in the case of positive differences (Y4-Y3), generated by the presence of up fee options by (Equation 2) The average value Y4 of the difference (the hatched portion in FIG. 3) is calculated. These changes of the standard deviation σ 1 ^to stepwise are repeated until the absolute value of the difference (Y4−Y3) becomes smaller than a predetermined value Y5, and the absolute value of the difference | (Y4−Y3) | The standard deviation σ 1 ^to be assumed when it becomes smaller is stored in the external storage device 200 as the standard deviation σ of the service usage fluctuation distribution assumed by the user.

Here, the option may be considered as a minimum fee option. In that case, if the usage fee threshold value X3 or less, the input of the discount amount Y6 expected when the minimum fee option of having the minimum fee paid is added from the input device, and instead of (Equation 2) using the following (equation 3), the absolute value of the difference | standard deviation of the assumed service variation distribution standard deviation sigma ^~ a user is assumed when it becomes smaller than the Y5 | (Y7-Y6) It is stored in the external storage device 200 as σ.

  In this manner, the characteristic value of the service usage fluctuation distribution assumed by the user is estimated from the average service usage amount X0, the monetary unit price ΔY1, the usage amount threshold value X2, and the amount Y3 that can be paid to the option itself. It becomes possible to do. Accordingly, it is possible to estimate a change in the amount of service usage assumed by the user before introducing the service without taking the time and effort of setting various conditions and performing prediction calculations. Furthermore, since it is estimated from reading the user's desired price, there is no need for the supplier side to predetermine and disclose the amount of the usage fee in advance, and the user is hesitant to introduce the service due to the gap between the amount presented and the estimated user amount It is possible to avoid this problem.

[Embodiment 2]
Hereinafter, the second embodiment will be described with reference to FIGS. 4 and 5.
FIG. 4 is a flowchart showing a process for determining whether or not a service can be provided by the service use fluctuation estimation system according to the second embodiment.
FIG. 5 is a diagram illustrating a comparison between the service distribution variation distribution and the estimated service utilization variation distribution.

  In this embodiment, when the characteristic value, average value X0, and standard deviation σ of the service usage fluctuation distribution are calculated according to the first embodiment, it is determined whether or not the service can be provided based on the characteristic value. The service provision determination unit 302 reads the characteristic value of the service distribution variation distribution preset by the service provider from the external storage device 200 and compares the characteristic value of the service utilization variation distribution calculated by the service utilization variation estimation unit 301.

  In the present embodiment, as shown in FIG. 5, the 5% percentile of the service usage fluctuation distribution is larger than the 5% percentile of the service provision fluctuation distribution, and the 95% percentile of the service usage fluctuation distribution is the service provision fluctuation distribution. It is determined that the service can be provided when it is smaller than 95% of the tile, and it is determined that the service cannot be provided otherwise.

  This eliminates the need for the supplier side to predetermine and disclose the amount of the usage fee in advance, making it possible to determine the gap with the estimated user amount and determine that the service can be provided, and the user is hesitant to introduce the service. It can be avoided.

  Hereinafter, the process for determining whether or not the service can be provided will be described with reference to FIG.

  The characteristic value of the assumed usage amount distribution A that can be provided and stored in advance in the external storage device 200 is read (step 301). Here, the assumed usage distribution that can provide the service is a normal distribution, and the average value XA and the standard deviation σA, which are characteristic values thereof, are read, and the process proceeds to step 302.

Next, the characteristic value of the service usage fluctuation distribution B calculated and stored in the process of the first embodiment is read (step 302). Here, service-variation distribution is a normal distribution, to migrate ^~ its characteristic value is an average value X0 and the standard deviation σ reads, in step 303.

  Next, the 5th percentile value and the 95th percentile value are expressed by the following (formula 4) from the characteristic value of the assumed usage distribution A that can be provided by the service and the characteristic value of the service usage fluctuation distribution B read in step 301 and step 302. (Step 303), and the process proceeds to Step 304.

  Next, the 5th percentile value PA1 of the assumed usage amount distribution A capable of providing the service and the 5th percentile value PB1 of the service usage fluctuation distribution B are compared (step 304). If PA1 <= PB1, the process proceeds to step 305. If PA1> PB1, it is determined that “cannot be provided: change required” (step 306), the determination result is stored in the external storage device 200, and the process ends. The processing in step 306 is a case where the supplier side gives up providing because there is a high probability that the estimated service usage fluctuation will reduce the service usage.

  Next, the 95th percentile value PA2 of the assumed usage distribution A that can provide the service and the 95th percentile value PB2 of the service usage fluctuation distribution B are compared (step 305). If PA2> = PB2, the process proceeds to step 307. It is determined that “can be provided”, the determination result is stored in the external storage device 200, and the process ends. If PA2 <PB2, it is determined that “provided: maximum charge option can be added” (step 308), the determination result is stored in the external storage device 200, and the process ends. The processing in step 308 is a case where the supplier sets the maximum option price for the convenience of the user because there is a high probability that the estimated service usage fluctuation increases the usage amount.

  As described above, whether the service can be provided by comparing the characteristic value of the assumed usage distribution that can provide the service with the characteristic value of the service usage fluctuation distribution calculated in the first embodiment by the processing of steps 301 to 308. Can be determined. This eliminates the need for the supplier side to predetermine and disclose the amount of the usage fee in advance, making it possible to determine the gap with the estimated user amount and determine that the service can be provided, and the user is hesitant to introduce the service. It can be avoided.

[Embodiment 3]
Hereinafter, a third embodiment will be described with reference to FIGS. 6 and 7.
FIG. 6 is a diagram for explaining the distribution of usage charges when the minimum charge option is set.
FIG. 7 is a diagram for explaining the distribution of usage charges when the maximum charge option is set.

  In the present embodiment, based on the determination result determined in the second embodiment, the optional conditions such as the maximum charge price and the minimum charge price are set so that the provision is possible by adding any option to the target service. presume. This eliminates the need for the supplier side to predetermine and disclose the usage fee amount in advance, making it possible to construct a service fee menu that can determine the gap with the user's estimated amount and provide services, and hesitates users to introduce the service. Can be avoided.

  When it is determined as “available” in the second embodiment (step 307 in FIG. 4), the usage fee stored in the external storage device 200 in advance is displayed on the display device 201 without changing the usage fee. .

  If it is determined in the second embodiment that “provision impossible: change required” (step 306 in FIG. 4), 95% or more of the usage fee calculated from the usage amount generated according to the service usage fluctuation distribution B is The minimum charge option is set so that it falls within the range of 95% of the usage fee calculated from the usage amount generated according to the assumed usage amount distribution A that can be provided.

  For example, here, a minimum charge option is added in which the minimum charge Z1 is paid when the usage threshold value X4 is set to X4 = XA−1.65 × σA or less than X4. This means that, as shown in FIG. 6 (c), a usage charge function is defined with the usage amount as a variable. As a result, as shown in FIGS. 6A and 6B, the distribution of the usage fee when the minimum fee option is added is reduced, and the possible value of the usage fee when the minimum fee option is added is The usage fee is included in the usage fee larger than the 5th percentile of the usage fee distribution calculated from the assumed usage amount distribution A that can be provided. That is, 100% of the usage fee calculated from the usage amount generated according to the service usage fluctuation distribution B is within 95% or less of the usage fee calculated from the usage amount generated according to the assumed usage amount distribution A that can provide the service. Will enter.

  In the second embodiment, when it is determined that “provided: maximum fee option can be added” (step 308 in FIG. 4), the supplier can obtain a usage fee within an allowable range even if the service is provided as it is. Although possible, here we set the highest price option that can be provided within the acceptable range. For example, when the usage amount threshold value X5 is set to X5 = XA + 1.65 × σA or more than X5, a maximum fee option for paying the maximum fee Z2 regardless of the usage amount is added. As a result, as shown in FIGS. 7A and 7B, the distribution of the usage fee when the maximum fee option is added is reduced, and the possible value of the usage fee when the maximum fee option is added is It is included in the usage fee smaller than the 95th percentile of the usage fee distribution calculated from the assumed usage amount distribution A that can be provided. That is, 100% of the usage fee calculated from the usage amount generated according to the service usage fluctuation distribution B is within 95% or less of the usage fee calculated from the usage amount generated according to the assumed usage amount distribution A that can provide the service. Will enter.

  As described above, according to the processing of this embodiment, based on the determination result determined in the second embodiment, an optional condition, in this case, the maximum charge price is set to be a provisionable condition by adding an arbitrary option to the target service. It is possible to estimate the minimum charge price. This eliminates the need for the supplier side to predetermine and disclose the usage fee amount in advance, making it possible to construct a service fee menu that can determine the gap with the user's estimated amount and provide services, and hesitates users to introduce the service. Can be avoided.

  For example, in the power supply service, the present invention can be used in a charge system in which a power supply service provider constructs a charge menu desired by a power consumer. Alternatively, the information utility service can be used in a fee system that constructs a fee menu according to the information utility capacity.

The lineblock diagram of the service use variation presumption system concerning a first embodiment. The flowchart which shows the process which estimates the service utilization fluctuation | variation of the service utilization fluctuation | variation system which concerns on 1st embodiment. The figure explaining the usage-amount distribution when estimating a service use fluctuation | variation. The flowchart which shows the process which determines the service provision availability of the service utilization fluctuation | variation estimation system of 2nd embodiment. The figure which showed the comparison with service distribution variation distribution and the estimated service utilization variation distribution. The figure explaining distribution of the usage fee when the minimum fee option is set. The figure explaining the distribution of the usage fee when the maximum fee option is set.

Explanation of symbols

00 ... Bus 101 ... Processor 102 ... Main storage device 103 ... External storage device 104 ... Graphic interface 105 ... Input / output interface 106 ... Network interface 201 ... Display device 202 ... Keyboard 203 ... Pointing device

Claims (7)

In a service usage fluctuation estimation method for a service that is charged according to the amount of service provided by a computer system,
The computer system includes an input device, a storage device, and a processor,
Inputting a user's desired price for the service from the input device and storing it in the storage device;
Inputting a user's desired price for an option to be added to the service from the input device, and storing it in the storage device;
Reading a characteristic value of a service distribution variation distribution from the storage device;
Reading a service desired price of a user for the service from the storage device;
Reading a user's desired option price for an option added to the service from the storage device;
The processor has a step of estimating a characteristic value of a service use fluctuation distribution for the user based on the read characteristic value of the service available fluctuation distribution, the service desired price, and the option desired price. Service usage fluctuation estimation method.   2. The service according to claim 1, further comprising the step of comparing the service-providable fluctuation distribution with the estimated service-use fluctuation distribution and determining whether or not the service can be provided based on a comparison result. Usage fluctuation estimation method.   2. The service usage fluctuation estimation method according to claim 1, wherein the option added to the service is a maximum charge option or a minimum charge option. further,
Inputting information on a service usage charge function with the service provision amount as a variable from the input device;
Newly inputting an additional option to the service from the input device;
Estimating a serviceable usage fee distribution based on the serviceable variation distribution read by the processor;
The processor estimating a service usage fee fluctuation distribution based on the information on the service usage charge function, the newly added additional option, and the estimated service usage fluctuation distribution;
2. The service usage fluctuation estimation method according to claim 1, wherein the processor obtains the additional option by comparing the service provisionable usage charge distribution and the service usage charge fluctuation distribution.   5. The service usage fluctuation estimation method according to claim 4, wherein the option added to the service is a maximum charge option or a minimum charge option. In a service use fluctuation estimation system that includes an input device, a storage device, and a processor and charges according to a service provision amount,
Means for inputting a user's desired price for the service from the input device and storing it in the storage device;
Means for inputting a user's desired price for an additional option to the service from the input device, and storing it in the storage device;
Means for reading a characteristic value of a serviceable variation distribution from the storage device;
Means for reading a service desired price of a user for the service from the storage device;
Means for reading a user's desired option price for an additional option to the service from the storage device;
The processor has means for estimating a characteristic value of the service usage fluctuation distribution for the user based on the read characteristic value of the service available fluctuation distribution, the desired service price, and the desired option price. Service usage fluctuation estimation system. The service use fluctuation estimation system according to claim 6, wherein the option added to the service is a maximum charge option or a minimum charge option.

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