Information processing device, calculation program, and calculation method

Abstract

Consumers can accurately express their WTP. The method includes instructing participants to input a desired purchase price for a product within a first price range, and if the desired purchase price is greater than or equal to (a set price set by a random number), the participant is paid (the first price - the set price).

Description

[Technical field]

[0001] The present invention relates to an information processing device, a computing program, and a computing method. [Background technology]

[0002] If WTP (Willingness to Pay) can be accurately set for new and existing products, sellers can maximize their profits without consumers feeling any loss. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2021-503638 Summary of the Invention [Problem to be solved by the invention]

[0004] However, it is difficult to find out consumers' WTP regarding new products and existing products. Therefore, it is possible to obtain WTP from consumers by using the concept of second-price auction (see, for example, Patent Document 1). However, even if the concept of second-price auction is simply adopted, it is difficult for consumers to accurately indicate their WTP.

[0005] The present invention has been made in consideration of the above-mentioned problems, and has an object to provide an information processing device, a calculation program, and a calculation method that enable consumers to accurately present their WTP. [Means for solving the problem]

[0006] The information processing device of the present invention is characterized in that it comprises a prior information output unit that outputs prior information including instructions to a participant to input a desired purchase amount for a product within a first amount range and information that if the desired purchase amount is greater than or equal to (a set amount set by a random number), (the first amount - the set amount) will be paid to the participant, and if the desired purchase amount is less than the set amount, the first amount will be paid to the participant; a setting unit that sets the set amount using a random number; an acquisition unit that acquires the desired purchase amount from the participant after the prior information output unit outputs the prior information; a calculation unit that calculates (the first amount - the set amount) as a second amount if the desired purchase amount is greater than or equal to the set amount, and sets the first amount to the second amount if the desired purchase amount is less than the set amount; a result output unit that outputs a result of the calculation unit; and a determination unit that, when the acquisition unit acquires the desired purchase amount from the participant multiple times, determines the second amount calculated by the calculation unit using the desired purchase amount last acquired by the acquisition unit as a third amount.

[0007] In the information processing device, the setting unit may set an upper limit and a lower limit for the set amount.

[0008] In the information processing device, the setting unit may use a probability distribution having a domain in a positive range as a method of generating random numbers having an upper limit and a lower limit.

[0009] In the information processing device, the setting unit may use a beta distribution as the probability distribution.

[0010] In the above information processing device, when the determination unit determines the third amount for multiple participants, the setting unit may adjust a random number for setting the set amount depending on a result of the determination unit's determination of the third amount for the multiple participants.

[0011] In the above information processing device, the setting unit may adjust the random number when the determination unit determines the third amount for a plurality of participants so that the ratio of participants among the plurality of participants whose desired purchase amount is greater than or equal to the set amount falls within a predetermined range.

[0012] The information processing device may further include an information providing unit that, when the determination unit determines the third amount for a plurality of participants, provides information regarding a sales forecast of the product in accordance with a result of the determination unit's determination of the third amount for the plurality of participants.

[0013] The calculation program of the present invention causes a computer to execute the following: a prior information output process for outputting prior information including instructions to a participant to input a desired purchase amount for a product within a first amount range, and information that if the desired purchase amount is greater than or equal to (a set amount set by a random number), (the first amount - the set amount) will be paid to the participant, and if the desired purchase amount is less than the set amount, the first amount will be paid to the participant; a setting process for setting the set amount using a random number; an acquisition process for acquiring the desired purchase amount from the participant after the prior information is output by the prior information output process; a calculation process for calculating (the first amount - the set amount) as a second amount if the desired purchase amount is greater than or equal to the set amount, and setting the first amount as the second amount if the desired purchase amount is less than the set amount; a result output process for outputting a result of the calculation process; and a determination process for determining, when the desired purchase amount is acquired from the participant multiple times by the acquisition process, the second amount calculated by the calculation process using the desired purchase amount last acquired in the acquisition process as a third amount.

[0014] The calculation method of the present invention is characterized in that a computer executes the following steps: a preliminary information output process that outputs preliminary information including instructions to a participant to input a desired purchase amount for a product within a first amount range, and information that if the desired purchase amount is greater than or equal to (a set amount set by a random number), (the first amount - the set amount) will be paid to the participant, and if the desired purchase amount is less than the set amount, the first amount will be paid to the participant; a setting process that sets the set amount using a random number; an acquisition process that acquires the desired purchase amount from the participant after the preliminary information is output by the preliminary information output process; a calculation process that calculates (the first amount - the set amount) as a second amount if the desired purchase amount is greater than or equal to the set amount, and sets the first amount as the second amount if the desired purchase amount is less than the set amount; a result output process that outputs a result of the calculation process; and a determination process that, when the desired purchase amount is acquired from the participant multiple times by the acquisition process, determines the second amount calculated by the calculation process using the desired purchase amount acquired last in the acquisition process as a third amount. Effect of the Invention

[0015] According to the present invention, it is possible to provide an information processing device, a calculation program, and a calculation method that enable a consumer to accurately present his / her WTP. [Brief description of the drawings]

[0016] [Figure 1] FIG. 13 is a diagram illustrating details of a first-price auction. [Diagram 2] FIG. 13 is a diagram illustrating details of a second-price auction. [Diagram 3] FIG. 1A is a block diagram of an information processing device according to an embodiment, FIG. 1B is a functional block diagram of a calculation device, and FIG. 1C is a block diagram for explaining a hardware configuration of the calculation device. [Figure 4] 11 is a flowchart illustrating an example of an operation of the information processing device. [Diagram 5]FIG. 11 is a diagram illustrating an example of advance information. [Figure 6] 13 is a flowchart showing details of a practice process. [Figure 7] FIG. 1 is a diagram illustrating an example of an outline of an embodiment. [Figure 8] FIG. 1 is a diagram illustrating an example of a demand forecast and a sales forecast. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] WTP: Willingness to Pay is the maximum amount that a consumer is willing to pay for a product or service. If WTP can be set accurately for new and existing products, sellers can obtain maximum profits without causing consumers to feel any loss. However, it is difficult to find out consumers' WTP for new and existing products. For example, from consumers' perspective, it is preferable for product prices to be as low as possible.

[0018] Therefore, it is possible to measure consumers' true WTP by imposing an economic commitment. One method for measuring consumers' true WTP is the Becker DeGroot Marscha (BDM) auction. BDM auctions are designed based on second-price auctions. Below, we explain BDM auctions while comparing first-price auctions and second-price auctions.

[0019] First, a first-price auction is a typical auction such as a public auction. In a first-price auction, the person who offers the highest purchase price becomes the winner and must pay the price they offered. However, in a first-price auction, even if you are the winner, you may feel that you should have offered a lower price. This is because there are cases where you have been forced to offer a high price in order to win.

[0020] This is where the second-price auction comes in. In a second-price auction, the winner is the person who offers the highest purchase price, but they also have to pay the second-highest purchase price among the auction participants. This creates an incentive to bid honestly at the maximum price willing to pay.

[0021] Below, we will explain the details of the first price auction mentioned above. Assume that consumer A is willing to pay a maximum of 300 yen for the product. In this case, WTP is 300 yen. Assume that the purchase price of rivals in the auction is 100 yen, 200 yen, 300 yen, or 400 yen, and that consumer A's purchase price is 100 yen, 200 yen, 300 yen, or 400 yen. Figure 1 shows consumer A's profits under the above assumptions.

[0022] As shown in Figure 1, for example, consumer A wishes to purchase the product for 200 yen, and his rival wishes to purchase the product for 300 yen. In this case, consumer A is not the winner, so he does not get the product. However, he does not have to pay any money. Therefore, consumer A's profit is 0 yen.

[0023] Next, let's say Consumer A wishes to purchase for 200 yen, and his rival also wishes to purchase for 200 yen. In this case, the person who wins the lottery will be the winner. The probability of winning and losing the lottery is 50%. If he wins the lottery, his profit will be 300 yen - 200 yen = 100 yen, and if he loses, his profit will be 0 yen. Therefore, the expected value is 100 yen x 50% + 0 yen x 50% = 50 yen. From the above, Consumer A's profit will be 50 yen.

[0024] Considering all other combinations, consumer A's profits are greatest when he offers 200 yen as his purchase price, which is lower than his WTP of 300 yen. Therefore, in a first-price auction, the difference between his WTP and the amount at which he can maximize his profits is large.

[0025] Next, we will explain the details of the second-price auction. As in the first-price auction, we assume that consumer A's WTP is 300 yen. We will assume that the purchase prices of rivals in the auction are 100 yen, 200 yen, 300 yen, or 400 yen, and that consumer A's purchase price is 100 yen, 200 yen, 300 yen, or 400 yen, respectively. Figure 2 shows consumer A's profits under the above assumptions.

[0026] As shown in Figure 2, for example, assume that consumer A wishes to purchase for 400 yen, and his rival wishes to purchase for 200 yen. In this case, he can buy a product for 200 yen that he would be willing to pay 300 yen for, so consumer A's profit is 100 yen.

[0027] Next, assume that Consumer A wishes to purchase for 200 yen, and his rival wishes to purchase for 300 yen. In this case, Consumer A cannot be the winner, so Consumer A's profit will be 0 yen.

[0028] Next, let's say Consumer A wishes to purchase for 200 yen, and his rival also wishes to purchase for 200 yen. In this case, the person who wins the lottery is the winner. The probability of winning and losing the lottery is 50%. If he wins the lottery, his profit will be 300 yen - 200 yen = 100 yen, and if he loses, his profit will be 0 yen. Therefore, the expected value is 100 yen x 50% + 0 yen x 50% = 50 yen. From the above, Consumer A's profit will be 50 yen.

[0029] Next, assume that consumer A sets his desired purchase price at 300 yen, the same as his WTP, and his rival's desired purchase price is 200 yen. In this case, consumer A's profit will be 100 yen, since he can buy the product he is willing to pay 300 yen for for 200 yen.

[0030] Even when considering all other combinations, Consumer A will make the most profit when he offers his WTP of 300 yen. Therefore, in a second-price auction, the difference between WTP and the amount at which Consumer A can make the most profit becomes smaller.

[0031] From the above, by holding a BDM auction, an incentive to honestly bid at the maximum willingness to pay works. Therefore, by setting the selling price of the product to the amount that the winner would actually pay in a BDM auction, it is possible to increase the profit of the seller without the consumer feeling that he or she has lost out. However, it is difficult for consumers to accurately present their WTP. In the following embodiment, an example in which a consumer can accurately present his or her WTP will be described.

[0032] (Embodiment) As an example, consider an event venue where new products and other products whose prices have not yet been decided are on display. Participants are invited to the event venue. The seller of the product wishes to know the fair price of the product. Therefore, the seller wishes to obtain WTP from the participants. The participants are given a first amount (for example, 1,000 yen) as a reward.

[0033] Fig. 3(a) is a block diagram of an information processing device 100 according to an embodiment. As illustrated in Fig. 3, the information processing device 100 includes a calculation device 10, an operation device 20, a notification device 30, and the like.

[0034] The operation device 20 is a device operated by the participants. The operation device 20 is, for example, an input device such as a keyboard, a mouse, or a touch panel. The notification device 30 is not particularly limited as long as it is a device that can notify the participants of information. For example, the notification device 30 may be a display device such as a liquid crystal screen, or may be an audio output device such as a speaker.

[0035] Fig. 3(b) is a functional block diagram of the calculation device 10. As illustrated in Fig. 3(b), the calculation device 10 functions as a prior information output unit 11, a setting unit 12, an acquisition unit 13, a calculation unit 14, a result output unit 15, a determination unit 16, an information provision unit 17, and the like.

[0036] FIG. 3(c) is a block diagram for explaining the hardware configuration of the arithmetic device 10. As illustrated in FIG. 3(c), the arithmetic device 10 includes a CPU 101, a RAM 102, a storage device 103, and the like. These devices are connected by a bus or the like. The CPU (Central Processing Unit) 101 is a central processing unit. The RAM (Random Access Memory) 102 is a volatile memory that temporarily stores a program executed by the CPU 101, data processed by the CPU 101, and the like. The storage device 103 is a non-volatile storage device. For example, a ROM (Read Only Memory), a solid state drive (SSD) such as a flash memory, a hard disk driven by a hard disk drive, and the like can be used as the storage device 103. The function of each part of the arithmetic device 10 is realized by the CPU 101 executing the arithmetic program stored in the storage device 103. The function of each part of the arithmetic device 10 may be configured by a dedicated circuit or the like.

[0037] 4 is a flowchart showing an example of the operation of the information processing device 100. Hereinafter, an example of the operation of the information processing device 100 will be described with reference to FIG.

[0038] First, the prior information output unit 11 outputs the prior information to the notification device 30 in order to notify the participants of the prior information (step S1). As a result, the notification device 30 notifies the participants of the prior information received from the prior information output unit 11. Fig. 5 is a diagram illustrating an example of the prior information. For example, the following prior information is notified to the participants. "Please honestly enter the amount you would like to pay for the product that is offered. The highest amount bid by the five people who answered before you, A yen, will be recorded. If your amount bid, B yen, is higher than the highest amount bid, A yen, then you can purchase the product offered for A yen. This is the game. <If you win> In addition to the prize, you will receive a reward of 1,000 yen minus the highest amount ever received, A yen. <If you lose> You get 1000 yen and the game ends there. Once you understand the rules, press the start button. When you press the start button, you will have three practice sessions and then one actual session.

[0039] Next, after the participant presses the start button using the operation device 20, the practice process is executed (step S2). The practice process is executed at least once. In this embodiment, the practice process is executed three times.

[0040] Fig. 6 is a flowchart showing details of the practice process. As illustrated in Fig. 6, the setting unit 12 sets a set amount (the above-mentioned maximum amount A yen) using a random number (step S11).

[0041] Next, the acquisition unit 13 acquires the desired purchase price input by the participant using the operation device 20 (step S12). Note that the products presented to the participant in this practice process are products for practice, which are different from those in the actual process described below. For example, the practice products and the actual products may be different products in the same category, such as beverages, or may be products in different categories, such as food and beverages.

[0042] Next, the calculation unit 14 calculates the second amount (step S13). Specifically, when the desired purchase amount is equal to or greater than the set amount, the calculation unit 14 calculates the second amount as (first amount - set amount), and when the desired purchase amount is less than the set amount, the calculation unit 14 sets the first amount as the second amount.

[0043] Next, the result output unit 15 outputs the calculation result of the calculation unit 14 in step S13 to the notification device 30 (step S14). As a result, the notification device 30 notifies the participant of the calculation result received from the calculation unit 14. Specifically, if the desired purchase amount is greater than or equal to the set amount, the notification device 30 notifies the participant that the participant is a winner and can win the prize, and notifies the participant of the second amount. If the desired purchase amount is less than the set amount, the notification device 30 notifies the participant that the participant is a loser and cannot win the prize, and notifies the participant of the second amount.

[0044] After the practice process in step S2 is completed, the actual process is executed. Specifically, the setting unit 12 sets a set amount (the above-mentioned maximum amount A yen) using a random number (step S3).

[0045] Next, the acquisition unit 13 acquires the desired purchase price input by the participant using the operation device 20 (step S4).

[0046] Next, the calculation unit 14 calculates the second amount (step S5). Specifically, if the desired purchase amount is equal to or greater than the set amount, the calculation unit 14 calculates the second amount as (first amount - set amount), and if the desired purchase amount is less than the set amount, the calculation unit 14 sets the first amount as the second amount.

[0047] Next, the result output unit 15 outputs the calculation result of the calculation unit 14 in step S5 to the notification device 30 (step S6). The notification device 30 then notifies the participant of the calculation result received from the calculation unit 14. Specifically, if the desired purchase amount is greater than or equal to the set amount, the notification device 30 notifies the participant that the participant is a winner and can win the prize, and notifies the participant of the second amount. If the desired purchase amount is less than the set amount, the notification device 30 notifies the participant that the participant is a loser and cannot win the prize, and notifies the participant of the second amount.

[0048] Next, the determination unit 16 determines the second amount calculated in step S5 as the third amount (step S7). The third amount is given to the participant.

[0049] FIG. 7 shows an overview of this embodiment.

[0050] Here, the effects of this embodiment will be described.

[0051] Since most ordinary consumers are not familiar with BDM auctions, if the actual process is executed without the practice process, participants may not be able to accurately present their WTP. For example, it is possible to explain the mechanism of the BDM auction to participants without executing the practice process, and then execute the actual process, but in this case, participants will not actually experience a BDM auction, so it is still difficult for them to present an accurate WTP.

[0052] In contrast, according to the present embodiment, the practice process is executed one or more times before the actual process is executed. In this case, participants can actually experience the BDM auction and can participate in the BDM auction after fully understanding the mechanism of the BDM auction. This allows participants to accurately present their WTP. Furthermore, since the set price is set using random numbers, it is possible to eliminate the seller's speculation and a fair set price is set. This allows participants to accurately present their WTP.

[0053] Since the number of participants is not limited to one, multiple participants will conduct the BDM auction according to the flowchart in Fig. 4. In this case, WTPs for the same product can be obtained from multiple participants. Therefore, the information providing unit 17 provides information on the sales forecast for the product according to the result of the determination of the third price by the determination unit 16 for the multiple participants.

[0054] As an example, the information providing unit 17 provides a demand forecast and a sales forecast by combining the result of the determination unit 16 determining the third amount for multiple participants with a marketing model. FIG. 8 is a diagram illustrating a demand forecast and a sales forecast. The information providing unit 17 is assumed to have acquired market research data and additional research data on the target product in the BDM auction in advance. The information providing unit 17 is assumed to have acquired market research data and additional research data on products in the same category other than the target product in the BDM auction in advance. The market research data includes the recognition rate and the shelving rate, attribute information and purchase route information for expanding and estimating them in the market, the sales scale of the entire category, and the like. The additional research data includes the repeat probability, the switchback probability, and the like.

[0055] First, the information provider 17 obtains the trial probability (=F) for each price under the condition that the target product of the BDM auction is recognized and available. Here, the trial probability refers to the probability of making a trial purchase (the probability of making a first purchase).

[0056] For example, the trial probability can be estimated as follows. First, the WTP of each consumer can be obtained by the above BDM auction. As mentioned above, WTP is the maximum amount a consumer is willing to pay for a product or service, so each consumer is likely to make the decision to try the new product if their WTP is equal to or lower than the price of the new product. From this information, the trial probability F of all consumers for each price is estimated.

[0057] Next, the information providing unit 17 obtains the awareness rate (= K) of the new product based on the market research data. The awareness rate is the ratio of the number of people who are aware of the new product to the total number of people in the market. Next, the information providing unit 17 obtains the shelving rate (= D) based on the market research data.

[0058] Next, the information providing unit 17 calculates the final cumulative trial probability T based on the trial probability F, the recognition rate K, and the shelving rate D. For example, the information providing unit 17 calculates T=F×K×D. This cumulative trial probability T corresponds to the proportion of people who purchase the new product on a trial basis (at least once) among the total number of people in the entire market.

[0059] Next, the information providing unit 17 obtains the repeat probability (=p) for each price for people who made a trial purchase based on the additional survey. The repeat probability p is the percentage of people who made a trial purchase (first purchase) who will purchase again at the next purchasing opportunity. Next, the information providing unit 17 obtains the switchback probability (=q) for each price for people who did not make a trial purchase based on the additional survey. The switchback probability q is the percentage of people who did not make a trial purchase (first purchase) who plan to purchase at the next purchasing opportunity.

[0060] Next, the information providing unit 17 calculates the final continuous purchase rate R of people who have made a trial based on the repeat probability p and the switchback probability q. For example, the information providing unit 17 calculates R=q / (1-p+q). The continuous purchase rate R is the ratio of people who make a trial purchase (first purchase) and continue to make a second or subsequent purchase.

[0061] Next, the information providing unit 17 calculates a long-term market share and demand forecast M based on the cumulative trial probability T and the continuous purchase rate R. The market share and demand forecast M is the final market share. For example, the information providing unit 17 calculates M=T×R.

[0062] Finally, the information providing unit 17 provides information on sales forecast based on the market share and demand forecast M and the sales scale of the entire category.

[0063] The set amount set by the setting unit 12 may be random, but it is preferable that the set amount is set within a range of realistically possible values. For example, for a new product of a 500 ml plastic bottle drink, 50 yen may be too cheap, and 500 yen may be too expensive. Therefore, it is preferable that the setting unit 12 generates random numbers with upper and lower limits. As a method for generating random numbers with upper and lower limits, for example, a probability distribution having a domain in a positive range can be used. As a probability distribution having a domain in a positive range, for example, a beta distribution can be used.

[0064] The beta distribution is a probability density function with two parameters, α and β, that takes values ​​in the range [0,1]. For a random variable x, the probability density function is f(x|α,β)=x α―1 (1-x) β-1 / B(α,β), where B(·) represents the beta function.

[0065] First, the distribution f * Let U be the upper limit and L be the lower limit.

[0066] Next, set the target median of the random numbers. * Let us assume that.

[0067] Next, M * percentile q in [U,L] of M* q M* is (M * -L) / (UL).

[0068] By taking advantage of the fact that the median of the beta distribution f can be approximated by (α-1 / 3) / (α+β-2 / 3), * Parameter α * and β * Here, β * Set an appropriate value for α * =(3βq M* -2q M* +1) / 3(1-q M* ) by f * (y|α* ,β * ) and set the beta random number f * The y is generated from f * is a random variable obeying

[0069] Transform y as z=y(UL)+L and set it as a random number z. This random number z has an upper limit U, a lower limit L, and a median M * The eigenvalues ​​follow a beta distribution with

[0070] When the information providing unit 17 provides information on the selling price of the product, further surveys may be conducted on the participants who have acquired the product, thereby enabling more accurate demand forecasting. Therefore, if too few participants acquire the product, it may be difficult to obtain a sample size for performing a correct demand forecast. On the other hand, if too many participants acquire the product, the auction becomes meaningless and an accurate WTP may not be obtained.

[0071] Therefore, when the third amount is determined for a plurality of participants for a specific product, the setting unit 12 may adjust the random number for setting the set amount according to the result of the determination unit 16 determining the third amount for the plurality of participants. For example, it is preferable to set the median of a probability distribution having a domain in a positive range so that the proportion of participants whose desired purchase amount is equal to or greater than the set amount among the plurality of participants is appropriate. In this way, the result of the new plurality of participants inputting the desired purchase amount according to the flowchart of FIG. 4 can be adjusted.

[0072] For example, if the number of participants whose desired purchase amount is equal to or greater than the set amount is small relative to the required sample size, it is preferable to adaptively change the probability distribution to reduce the median, and adjust so that the ratio of participants whose desired purchase amount is equal to or greater than the set amount is increased. In this way, it becomes possible to adjust the random number so that the ratio of participants whose desired purchase amount is equal to or greater than the set amount among the multiple participants falls within a predetermined range.

[0073] Alternatively, when there is a limit to the number of items that can be prepared, such as "goods" or "personal services," it is preferable to adaptively adjust the distribution so as to adjust the proportion of participants whose desired purchase amount is equal to or exceeds a set amount in accordance with the limit.

[0074] In the practice process, it is preferable to set the median of the distribution so that the ratio of participants whose desired purchase amount is equal to or exceeds the set amount is about 50%. In this way, participants can be made aware that if they do not input the desired purchase amount appropriately, there is a possibility that the desired purchase amount will not be equal to or exceeds the set amount.

[0075] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and variations are possible within the scope of the gist of the present invention described in the claims. [Explanation of symbols]

[0076] 10 Arithmetic unit 11 Advance information output section 12 Setting section 13 Acquisition Department 14 Calculation section 15 Result output section 16 Decision Section 17 Information Provision Department 20 Operating device 30 Notification device 100 Information processing device

Claims

1. a prior information output unit that outputs prior information including instructions to a participant to input a desired purchase amount for a product within a first amount range, and information that if the desired purchase amount is greater than or equal to (a set amount set by a random number), then (the first amount - the set amount) will be paid to the participant, and if the desired purchase amount is less than the set amount, then the first amount will be paid to the participant; A setting unit that sets the set amount by using a random number; an acquisition unit that acquires the desired purchase amount from the participant after the advance information output unit outputs the advance information; a calculation unit that calculates a second amount as (the first amount - the set amount) when the desired purchase amount is equal to or greater than the set amount, and that calculates the second amount as the first amount when the desired purchase amount is less than the set amount; A result output unit that outputs a result of the calculation unit; an information processing device characterized in that it comprises a determination unit that, when a series of operations in which the setting unit sets the set amount, the acquisition unit acquires the desired purchase amount, the calculation unit calculates the second amount, and the result output unit outputs the result of the calculation unit are performed multiple times, determines the second amount calculated by the calculation unit using the desired purchase amount last acquired by the acquisition unit as a third amount.

2. The information processing device according to claim 1 , wherein the setting unit sets an upper limit and a lower limit for the set amount.

3. 3. The information processing apparatus according to claim 2, wherein the setting unit uses a probability distribution having a domain in a positive range as a method of generating random numbers having an upper limit and a lower limit.

4. The information processing apparatus according to claim 3 , wherein the setting unit uses a beta distribution as the probability distribution.

5. The information processing device described in any one of claims 1 to 4, characterized in that when the determination unit determines the third amount for multiple participants, the setting unit adjusts a random number for setting the set amount depending on the result of the determination unit's determination of the third amount for the multiple participants.

6. The information processing device described in claim 5, characterized in that when the determination unit determines the third amount for a plurality of participants, the setting unit adjusts the random number so that the ratio of participants among the plurality of participants whose desired purchase amount is greater than or equal to the set amount falls within a predetermined range.

7. The information processing device according to claim 1, further comprising an information providing unit that, when the determination unit determines the third amount for a plurality of participants, provides information regarding a sales forecast of the product in accordance with a result of the determination unit's determination of the third amount for the plurality of participants.

8. On the computer, a prior information output process for outputting prior information including instructions to a participant to input a desired purchase amount for a product within a first amount range, and information that if the desired purchase amount is greater than or equal to (a set amount set by a random number), then (the first amount - the set amount) will be paid to the participant, and if the desired purchase amount is less than the set amount, then the first amount will be paid to the participant; A setting process for setting the set amount using a random number; an acquisition process for acquiring the desired purchase amount from the participant after the advance information is output by the advance information output process; a calculation process of calculating a second amount as (the first amount - the set amount) when the desired purchase amount is equal to or greater than the set amount, and calculating the first amount as the second amount when the desired purchase amount is less than the set amount; A result output process for outputting a result of the calculation process; a determination process for determining the second amount calculated by the calculation process using the desired purchase amount last obtained in the acquisition process as a third amount when a series of operations including setting the set amount in the setting process, obtaining the desired purchase amount in the acquisition process, calculating the second amount in the calculation process, and outputting the result of the calculation process in the result output process are performed multiple times.

9. The computer a prior information output process for outputting prior information including instructions to a participant to input a desired purchase amount for a product within a first amount range, and information that if the desired purchase amount is greater than or equal to (a set amount set by a random number), then (the first amount - the set amount) will be paid to the participant, and if the desired purchase amount is less than the set amount, then the first amount will be paid to the participant; A setting process for setting the set amount using a random number; an acquisition process for acquiring the desired purchase amount from the participant after the advance information is output by the advance information output process; a calculation process of calculating a second amount as (the first amount - the set amount) when the desired purchase amount is equal to or greater than the set amount, and calculating the first amount as the second amount when the desired purchase amount is less than the set amount; A result output process for outputting a result of the calculation process; a determination process for determining the second amount calculated by the calculation process using the desired purchase amount last obtained in the acquisition process as a third amount when a series of operations including setting the set amount in the setting process, obtaining the desired purchase amount in the acquisition process, calculating the second amount in the calculation process, and outputting the result of the calculation process in the result output process are performed multiple times.

Images