JP2002074071A - Optimum market price determining system by auction and record medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To determine optimum market price for a commodity. SOLUTION: For the commodity whose optimum market price is to be determined, internet auction is conducted by an auction-executing WWW server 22, and the bid information is stored in a bid information DB 26 through a database server 23. An optimum market price determination computing part 27 adds up the number of persons capable of making a successful bid at the respective prices, according to the stored bid information, obtains the approximate formula formed by exponent functions or polynomial for approximating the correlation of the rate of bidders capable of making a successful bid obtained by dividing the added number of bidders capable of making a successful bid at the respective prices by the number of total bids and the price in an approximate calculating part 27B, estimates a benefit to the market price by the approximate formula in a benefit estimating part 27C, and determines the optimum market price from the estimated benefit in an optimum price calculating part 27D.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention
Optimum sales price determination system for determining the correlation between sales price and demand quantitatively using an auction and determining the price expected to maximize profit based on the result, and such optimum sales price determination system The present invention relates to a computer-readable recording medium storing a program including an instruction for causing a computer to execute the above operation.

[0002]

2. Description of the Related Art There are generally two methods for determining the selling price of a product.

[0003] One is a method in which a desired purchase price is investigated by a questionnaire, hearing, or the like, and the result is analyzed by a statistical method to obtain an appropriate selling price.

Another method is to investigate the production cost, distribution cost, sales cost, and the like of a product, and obtain a sales price that is considered appropriate based on the results.

[0005]

However, in the former method of the price determination based on interviews and questionnaire surveys,
It is not clear whether the surveyed respondents really respond to the true desired price because they do not actually purchase.

Further, in order to improve the prediction accuracy, a large-scale survey is required, and the survey cost increases.

On the other hand, the latter method of determining a price based on cost has a problem that the number of sales cannot be predicted because the price is determined without depending on the market.

[0008] For this reason, defective stock or shortage occurs,
Often miss the right profits.

[0009] The present invention has been made in view of the above points, and has as its object to provide an optimum selling price determination system and a recording medium which can determine an optimum selling price of a product.

[0010]

In order to achieve the above object, an optimal selling price determination system using an auction according to the present invention provides an auction for conducting an auction through a telecommunication network for a product whose optimal selling price is to be determined. Execution means, bid information storage means for storing bid information of the auction by the auction execution means, and the number of successful bidders at each price are totaled based on the bid information stored in the bid information storage means. An aggregation function and an exponential function or a polynomial approximation formula that approximates the correlation between the bid price and the bidderable bidder rate obtained by dividing the number of bidders who can bid at each price calculated by the aggregation means by the total number of bids. Profit prediction for predicting a profit for a selling price using the approximate calculation means and the approximate expression obtained by the approximate calculation means And the step, characterized by comprising the optimal price determining means for determining an optimum price than expected profit from the profit prediction means.

Further, the system for determining an optimum selling price by an auction according to the present invention is a bidding information inputting means for inputting bidding information of an auction by a telecommunication network implemented for a product whose optimum selling price is to be determined, and the bidding information. Based on the bidding information input from the input means, totaling means for totaling the number of people who can make a successful bid at each price, and the total number of people who can make a successful bid at each price calculated by the above totaling means is calculated by the total number of bids. Approximate calculation means for obtaining an approximate expression consisting of an exponential function or a polynomial approximating the correlation between the divided bidder rate and the price, and using the approximate expression obtained by the approximate calculation means to calculate the profit for the selling price. Profit prediction means for predicting, and optimal price determination means for determining an optimal selling price based on the profit predicted by the profit prediction means. And butterflies.

[0012] A computer-readable recording medium according to the present invention provides a computer-readable recording medium for determining an optimal selling price of a product.
A process of executing an auction through a telecommunications network, a process of storing bid information of the auction, a process of counting the number of persons who can win a bid at each price based on the stored bid information, A process of obtaining an approximate expression consisting of an exponential function or a polynomial approximating the correlation between the price and the price of a bidder who can win a bid by dividing the number of bidders who can bid at each price by the total number of bids; And storing a program including an instruction for causing a computer to execute a process of predicting a profit with respect to a selling price and a process of determining an optimal selling price from the predicted profit.

Further, the computer-readable recording medium according to the present invention provides a bidding information for an auction by a telecommunications network implemented for a product whose optimal selling price is to be determined when determining an optimal selling price of the product. Based on the input bid information, the process of totaling the number of those who can make a successful bid at each price, and A process of obtaining an approximate expression consisting of an exponential function or a polynomial approximating the correlation between the divided bidder rate and the price, a process of predicting a profit with respect to a selling price by using the obtained approximate expression, And storing a program including an instruction for causing a computer to execute a process of determining an optimal selling price from the obtained profit.

That is, according to the system for determining an optimal selling price by an auction of the present invention and a computer-readable recording medium storing a program including an instruction for causing the computer to execute the operation of the optimal selling price determining system, By using the auction results of the auction conducted using the communication network, the correlation between the price of the product and the demand is quantitatively determined, and the profit is used when selling the product using this correlation. The maximum price is determined, whereby the optimal selling price of the product can be determined.

[0015]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Before describing the embodiments of the present invention in detail, first, the principles of the present invention will be described to facilitate understanding of the present invention.

For example, on 30 unpublished and rare "shochu M", Aug. 14, 1999
There is an Internet auction conducted between 00:00:00 on August 28 and 00:00 on August 28. This auction adopts a closed format in which the lowest bid price is 1 yen and the bid price is not disclosed, and the winning bid is an English format (power auction: bid at the highest bid price at the highest bid price) Method).

The announcement of this auction is made by sending e-mail to about 200,000 people. As a result, there are 314 bids, and the highest bid price is 11,100 yen and the lowest bid price is distributed. Was 1 yen. And
The lowest bid price was 5,000 yen, and bidders above that price won the bid price. During the event, the number of accesses to this auction page was about 1,300.

The method of determining the optimal price according to the present invention based on the results of an actual Internet auction will be described, taking as an example a new product "shochu M" put on the market.

FIG. 2A is a graph showing the result of the auction of the Internet auction. This graph shows the ratio of those who can bid at a certain price among all bidders. Here, the "person who can make a bid for a certain price" is the total number of people who have bid for the price or more. Those who think "I want to buy this product for 6,000 yen" include those who bid at 6,000 yen, as well as those who bid at a higher price, for example, those who bid at 8,000 yen. . That is, if a successful bid is decided at 6,000 yen, a person who bids at 8,000 yen can be obtained at a lower price of 2,000 yen, so the result should be more preferable.

FIG. 2A is a plot of the bid price and the percentage of successful bidders at that price.
Naturally, as the price increases, the bidder rate at that price decreases.

As shown in FIG. 2A, this distribution is characterized in that it can be very well approximated by an exponential function or a polynomial (in this example, an exponential function (y = 100e
^{-0.0 00448x} )). Note that な お^{2 in} the figure is a value indicating the ratio of the deviation between the approximate curve and the actual data, and this value is 1
Is higher, the approximation accuracy is better. The above exponential function or polynomial (hereinafter referred to as an approximate expression) quantitatively indicates how much the market size, that is, the sales amount changes when the price is changed.

Then, the present invention, based on this result,
It proposes a method for finding the optimal selling price for a product supplier. In other words, lowering the price increases the number of sales, but decreases the profit per unit.
However, raising the price reduces the number of sales and reduces profits. In other words, the balance between the number of sales and the price,
If you ask for the most profitable points, those points will be indicative of the selling price and the number of sales at that time that maximize profits.

In the above example, as shown in FIG. 2B, when the correspondence between the cost of this product and the profit price when the cost of the product is 5,000 yen is obtained, as a result, the price at which the profit is highest is obtained. Was shown to be about 7,000 yen.

The profit referred to here is the profit B (p) = (pc) * E (p). Here, p is the selling price, c is the production cost, and E (p) is the predicted number of sales per year at the selling price p. The annual sales forecast number E (p) is a value obtained by multiplying the approximate expression F (p) obtained from the bid price curve by a coefficient k determined by the auction execution period and the endurance period of the product. In the case of the above-mentioned shochu M, the auction is held once a month, and basically, the endurance period (time until consumption) is 0. And the market scale has expanded (20 at the time of the survey).
K = 314 * 12 * 60/20/100 = 113.04, taking into account that the number was 10,000, but the current is 600,000. 314 is the number of bids. Thus, benefits B (p) is, B (p) = (p -c) * E (p) = (p-c) * k * F (p) = (p-c) * 113.04 * 100e - ^0.000448p . This is 1,000 <p <10,50
When the calculation is performed between 0 (circle), the result as shown in FIG. 3A is obtained, and it is 3,000 <p <10,000.
The profit curve of FIG. 2B is plotted between (circles).

Accordingly, the price that takes the maximum value in the profit curve of FIG. 2B (about 7,000 yen in the figure)
Is the optimal price for the product.

An embodiment of the present invention will be described below with reference to the drawings. [First Embodiment] FIG. 1 is a diagram showing a configuration of an optimal selling price determination system by auction according to a first embodiment of the present invention.

That is, the manufacturing and sales company 20 and a plurality of customers 30 are connected via the Internet 10. The manufacturing and sales company 20 and each customer 30
It is needless to say that the connection is not limited to the one that can be directly connected to the Internet 10, but may be one that is connected via an Internet service provider. In addition, each customer 30
Any device may be used as a device connected to the Internet 10 to receive a service.

The manufacturing and sales company 20 has the mail distribution server 2
1. An auction execution WWW server 22, a database server 23, a product information database (DB) 24, a customer information DB 25, a bid information DB 26, an optimal price determination operation unit 27, and an input / output unit 28.

Here, the mail distribution server 21 is for transmitting an e-mail notification of an auction to the customer 30 based on the customer information registered in the customer information DB 25. In this case, the mail text is created by referring to the product information registered in the product information DB 24 and indicating what product is to be auctioned.

The auction execution WWW server 22 provides an Internet auction Web page created based on the product information registered in the product information DB 24. This Web page displays product information (product image, bid price, number of bids, number of bids, product description), forms for bidders to bid, and the like. The auction WWW server 22 also has a function of receiving a bid from the customer 30 via the Internet 10 and transferring the bid information to the database server 23.

The database server 23 has a product information DB
24, a customer information DB 25, and a bid information DB 26.
2 is registered in the bid information DB 26. The auction implementation WWW server 2
2 updates items such as the number of bids on the Web page of the Internet auction according to the bid information registered in the bid information DB 26.

The product information DB 24 stores the manufacturing and sales company 2
Numeral 0 is for registering information on products manufactured and sold. The information on the product includes, for example, data such as a product ID, a product name, a product classification, a selling price, a sales quantity, a lower limit price, an upper limit price, a product outline, a product image, and the like.

The customer DB 25 is for registering customer information of the manufacturing and sales company 20. The customer information includes, for example, customer ID, name, gender, age, address, telephone number, e-mail address, product purchase history, and the like. The customers registered in the customer DB 25 are not limited to the customers 30 who actually purchased the products in the past, but also customers who inquired about the products by some method,
Also included are customers who bid at the auction (customers who placed a bid but were not actually purchased because the bid price did not meet the conditions). Therefore, the auction implementation WW
Based on the bidding information passed from the W server 22 to the database server 23, the database server 23
This customer information DB 25 is also registered with information on the customer who has made a bid.

The bidding information DB 26 stores bidding information from the auction execution WWW server 22 via the database server 23. The bid information includes, for example, data such as a bid ID, a bidder ID, a product ID, a bid date, a bid amount, and the number of bids.

The optimal price determination calculating section 27 is for calculating the optimal price based on the bid information registered in the bid information DB 26, and includes a totaling section 27A, an approximate calculating section 27B, a profit predicting section 27C, an optimal price calculating section. It is composed of a part 27D.

The counting section 27A counts the number of persons who can make a successful bid at each price from the bid information registered in the bid information DB 26, and the approximate calculation section 27B calculates the total number of bids. Is calculated, and the correlation between the bidable bidder rate and the price is approximated by an exponential function or a polynomial. Profit prediction unit 27
C calculates the correspondence between the price and the profit using the approximation function obtained by the approximation calculation unit 27B, and the optimum price calculation unit 27D determines the optimum price from the correspondence result.

The input / output unit 28 is a user interface unit including a keyboard, a pointing device such as a mouse, a display, and the like. The input / output unit 28 inputs cost information of commodities necessary for the operation of the profit prediction unit 27C and calculates the optimal price. The optimal price determined by the unit 27D is displayed. The mail distribution server 21, the auction WWW server 22, the database server 23,
Product information database (DB) 24, customer information DB2
5. Bid information DB 26 and optimal price determination calculation unit 27
Can be realized by a personal computer. In this case, the input / output unit 28 is used to install a program or the like for realizing the function of each unit from a storage medium such as an FD or a CD-ROM into the personal computer. Drive device. Of course, such a program can be installed on a personal computer as a download via the Internet 10.

Next, the operation in such a configuration will be described. FIG. 3B is an operation flowchart of the optimal selling price determination system by auction according to the first embodiment of the present invention.

That is, first, in preparation for auction execution, a Web page for an Internet auction is created based on the product information registered in the product information DB 24 and registered in the auction WWW server 22 (step S1). Then, the product information and customer information DB 25 registered in the product information DB 24 by the mail distribution server 21.
An e-mail notifying that an auction will be held is created using the customer information registered in step S1 and transmitted to each customer 30 (step S2).

When the date and time of the Internet auction has come, the auction execution WWW server 22 accepts a bid from the customer 30 (step S3). The information is registered in the bid information DB 26 via the database server 23 (step S4). Further, the Web page of the Internet auction is updated according to the bid information (step S5). Thereafter, it is determined whether or not the end date and time of the Internet auction has come (step S).
6) If the date is still during the holding period, the above step S
Return to 3.

When the end date and time of the Internet auction is reached, the winning bidder is determined based on the result registered in the bidding information DB 26, the merchandise is sent to the winning bidder, and the mail is delivered. The notice of the successful bid is transmitted by e-mail by the server 21 (step S7). At this time, a Web page indicating the result of the successful bid may be made public by the auction execution WWW server 22.

Then, the totaling unit 27A of the optimum price determination calculating unit 27 totalizes the number of successful bidders at each price from the bid information registered in the bid information DB 26 (step S8). Here, the number of persons who can make a successful bid at each price is, as described above, the total number of persons who have bid at that price or higher.

Thereafter, the approximate calculation unit 27B calculates an approximate expression of the totaled number of successful bidders and the price (step S9). That is, by dividing the number of bidders at each price by the total number of bids, the bidderable bidder rate at each price is calculated, and the obtained bidderable bidder rates are plotted against the price. Then, a bid price curve as shown in FIG. 2A is obtained, and an approximate expression that approximates the bid price curve is calculated (step S9).

Next, the profit prediction unit 27C calculates the correspondence between price and profit using the approximation function obtained by the approximation calculation unit 27B (step S10). That is, by performing the above-described calculation, the profit obtained at each price is obtained as shown in FIG. At this time, the cost information required for calculating the profit is input from the input / output unit 28. It is needless to say that the cost information may be registered in advance in the product information DB 24 instead of being input from the input / output unit 28.

Then, the optimum price calculation section 27D obtains the correspondence between the calculated price and the profit, as shown in FIG.
Is determined as the optimal price from the profit curve as shown in FIG.
8 is displayed with the optimal price (step S12).

As described above, according to the first embodiment, the relation between the commodity price, the demand amount, and the profit can be obtained from the auction result of the Internet auction, and the optimal commodity price can be determined.

In addition, since the marketing research and the sales are integrated, the respective effects of reducing the research cost can be obtained. In other words, the cost is low because the survey is conducted on the Internet and uses almost no mailing costs such as a questionnaire survey. In addition, since the actual product is also sold, the profit can be used for the survey cost. For this reason, the cost can be greatly reduced as compared with a normal questionnaire.

Also, planned production and sales become possible,
Unnecessary inventory is not required. That is, it is generally said that the price decreases when the same product is repeatedly auctioned. However, with respect to the above “shochu M”, the optimal price obtained as in the present embodiment was set as the minimum bid price, and five auctions were held in the next seven months and verified. As shown in (A) and (B), it has been demonstrated that the price does not decrease.

[Second Embodiment] Next, a second embodiment of the present invention will be described.
The embodiment will be described with reference to FIG. In the second embodiment, the manufacturing and sales company 20 includes only the optimum price determination calculation unit 27 and the input / output unit 28 in the first embodiment, and the part for conducting the Internet auction is It is designed to be entrusted to an auction site 40 that is exclusively implemented.

That is, the mail delivery server 21 and the auction execution WWW server 2 in the first embodiment
2, database server 23, product information database (DB) 24, customer information DB 25, and bid information DB 2
6 is already provided in the auction site 40, so that the manufacturing and sales company 20 does not need to prepare equipment for that.

Then, the manufacturing and sales company 20 obtains bid information, which is the result of the auction, from the auction site 40 via the communication line 50 such as the Internet or a public line, and based on the information, obtains the optimum price determination calculation unit 27. Thus, the optimal price can be determined as in the first embodiment.

Of course, when sending bid information from the auction site 40 to the manufacturing and sales company 20, not only the communication line 50 but also a storage medium such as an FD or a CD-ROM may be used. It may be printed out and handed over.

[Third Embodiment] Next, a third embodiment of the present invention will be described.
An embodiment will be described. In the first and second embodiments, the system for determining the optimal price in the Internet market from the auction results of the Internet auction has been described. However, the present invention is applicable to the prediction of the market size including markets other than the Internet. Can be extended to

That is, a bid is an indication of an intention to "want to purchase the product at that price". Therefore, the person who bids at the price P can be considered to be willing to purchase the product even if it is less than that. Based on this concept, it is possible to predict the size of the market including those other than the Internet market by using the results of the Internet auction.

From the results of the auction, the Internet
・ Groups that can participate in the auction, that is, by e-mail
The number of people who can announce the_iPeople, oh
Did not receive a courtesy but thought that he was interested
Number of people (number of accessers) is N _aShown to be a person
If yes, the prevalence of those interested in this product (bidder
Rate) is N_a/ M_iIt is.

Here, it is assumed that a group that can participate in the Internet auction, that is, about 200,000 people who can announce the holding of the auction by e-mail is a sample group extracted from a market that sells commodities. With this premise, by multiplying the N _a / M _i to purchase possible layer M _a of products, it can be expected to number in the country of people who are interested in the product. In other _{words, N a / M i * M} a it is possible that the domestic number of people who are likely to purchase the product.

[0057] In this case, the market scale expected number of sales price p, if the number of buyer at 1 yen or more and N _b, equal to or less than.

Market size at selling price p: F (p) * N _b / M
_i * M _a For example, from the approximate expression of FIG.
In the case of 0, it can be seen that F (7000) = 4.3%. Since the number of people who wish to purchase for 1 yen or more is N _b = 314, 4.3 / 100 * 314 / 200,000 * 100,0
00,000 = 6,751 In other words, if it is possible to convey information about this product to all domestic markets, 6,755
It can be estimated that one demand is in Japan. If the buyer buys one each month, this product, if sold for 7,000 yen, indicates that there are approximately 80,000 markets a year.

Therefore, in the third embodiment, as shown in FIG. 6A, a market size prediction unit 27E for predicting such a market size is provided in the optimal price determination calculation unit 27. Then, the optimal price determination calculation unit 27 displays a screen of the sales volume prediction simulation as shown in FIG. 7 through the input / output unit 28, and inputs a list price to be predicted, thereby responding to the input list price. The market size is calculated and displayed on the input / output unit 28 as the expected sales unit year.

The profit prediction unit 27C and the optimal price calculation unit 27D also take into account such a market size, and
Profit prediction and optimal price determination may be performed.

[0061] In this case, the benefits B (p) is obtained by B (p) = (p- c) * F (p) * N b / M i * M a.

In calculating the profit, it is possible to use not the cost c but a partition price which is a price to be sold to a selling point.

That is, the profit prediction unit 27C is
As a result, the screen of the price setting simulation as shown in FIG. 8A is displayed, and by inputting the cost and the partition rate (partition price / list price), the partition price is automatically calculated, and the partition price is calculated. Then, the profit (gross profit) is calculated and displayed on the input / output unit 28.

Then, the optimum price calculation unit 27D obtains a profit curve from the result, and determines a price having a maximum value in the profit curve as an optimum price of the product. In this case, as shown in FIG. 8B, the optimum price is displayed together with the profit curve by the input / output unit 28. At this time, this display and the display of FIG. 8A may be displayed as separate windows, or may be switched and displayed by a predetermined key operation of the input / output unit 28.

[Fourth Embodiment] Next, a fourth embodiment of the present invention will be described.
An embodiment will be described. In the fourth embodiment, psychological elements (product attributes) such as color, size, and feel of the product
And the price are determined, and the optimal price is determined accordingly.

For example, an Internet auction was conducted assuming that two colors, rouge (crimson) and vaulte (dark green), could be selected for a certain product.
The result as shown in (B) was obtained.

From this figure, it can be seen that the color of rouge (crimson) is preferred by those with high prices, and that of vaulte (dark green) is preferred by those with low prices. Also, 5000
The circle is the transition point.

Therefore, the optimum price for each color can be determined based on this result, or the optimum price can be determined based on the sum of both colors. In particular, in the latter case, it is possible to predict the sales amount of the product of each color with respect to the optimum price, so that it is possible to avoid the shortage of the product of a specific color and the excess inventory. .

As described above, it has been difficult to find the correlation between the selling price and the demand amount for each product, but the method of the first to fourth embodiments can be used in a short time. And the correlation can be obtained quantitatively. This helps avoid unnecessary inventory and shortages due to inappropriate pricing, avoids unnecessary investment,
It is possible to make a planned production and sales plan, and to obtain the maximum profit.

Needless to say, such an optimal price can be determined without gathering a lot of people and holding an auction. Therefore, it is theoretically possible without using the Internet. Not a target. Therefore,
This can be realized only by using the Internet as in the above embodiment. However, the present invention is not limited to the Internet but may be applied to any computer network. For example, it is possible to improve the reliability and accuracy of data by holding a larger auction on a two-way TV in the future.

Although the above embodiment has been described by taking a manufacturing and selling company as an example, it is needless to say that the present invention can be similarly applied to a case where an intermediate company such as a wholesaler determines the selling price of goods purchased. .

Although the optimal selling price has been described as the price that can make the most profit, for example, when priority is given to the sales quantity over the profit, such as at the time of stock disposal, the price at which the quantity can be sold is the optimum price. Becomes Therefore, it is preferable to be able to select whether to determine the optimal price with the profit priority or the sales quantity priority.

[0073]

As described in detail above, according to the present invention,
An optimum sales price determination system and a recording medium that can determine an optimum sales price of a product can be provided.

[Brief description of the drawings]

FIG. 1 is a diagram showing a configuration of an optimal selling price determination system by auction according to a first embodiment of the present invention.

FIG. 2A is a graph showing a relationship between a bid price and a bidder rate in an Internet auction, and FIG. 2B is a diagram showing a predicted profit amount and a year in the case of a selling price and a cost of 5,000 yen. It is a figure showing the graph showing the relation with an expected sale number.

3A is a diagram showing original data of the graph of FIG. 2B, and FIG. 3B is a diagram showing an operation flowchart of an optimal auction price determination system by auction according to the first embodiment; It is.

FIG. 4A is a diagram showing the results of five Internet auctions at the optimal price determined by the auction-based optimal selling price determination system according to the first embodiment, and FIG. It is a figure showing a graph showing a result.

FIG. 5 is a diagram showing a configuration of an optimal selling price determination system by an auction according to a second embodiment of the present invention.

FIG. 6A is a diagram illustrating a configuration of an optimal price determination calculation unit in an optimal selling price determination system by auction according to a third embodiment of the present invention, and FIG. 6B is a diagram illustrating a fourth embodiment of the present invention. It is a figure showing the graph showing the relation between the bid price and the number of bids about a plurality of colors in the optimal selling price decision system by the auction concerning an embodiment.

FIG. 7 is a diagram showing a screen of a sales volume prediction simulation.

FIG. 8A is a diagram illustrating a screen of a price setting simulation, and FIG. 8B is a diagram illustrating a display example of a profit curve and an optimal price drawn based on data displayed on the screen of FIG. It is.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 Internet 20 Manufacturing / sales company 21 Mail distribution server 22 Auction execution WWW server 23 Database server 24 Product information DB 25 Customer information DB 26 Bid information DB 27 Optimal price determination calculation unit 27A Aggregation unit 27B Approximation calculation unit 27C Profit prediction unit 27D Optimal price Calculation unit 27E Market size prediction unit 28 Input / output unit 30 Customer 40 Auction site 50 Communication line

Claims (13)

[Claims] 1. An auction executing means for executing an auction through a telecommunication network for a product for which an optimum selling price is to be determined; a bid information storing means for storing bid information of an auction by the auction executing means; Totaling means for totaling the number of persons who can make a successful bid at each price based on the bid information stored in the storing means; and Approximate calculation means for obtaining an exponential function or a polynomial approximation formula that approximates the correlation between the divided bidder rate and the price, and using the approximate formula obtained by the approximation calculation means to calculate the profit for the selling price. Profit prediction means for predicting, and optimal price determination means for determining an optimal selling price based on the profit predicted by the profit prediction means. The optimal selling price determination system by auction characterized by doing. 2. A bid information inputting means for inputting bidding information of an auction by a telecommunication network implemented for a product for which an optimal selling price is to be determined, and based on bidding information inputted from the bidding information inputting means. Tallying means for counting the number of bidders who can make a bid at each price, and correlation between the bidder rate and the bidderable bidder number obtained by dividing the number of people who can bid at each price by the above tallying means by the total number of bids Approximation calculating means for obtaining an exponential function or a polynomial approximation formula for approximating; using the approximation formula obtained by the approximation calculation means, a profit prediction means for predicting a profit with respect to a selling price; An optimal selling price determining system by an auction, comprising: an optimal price determining means for determining an optimal selling price from predicted profits. 3. The optimal selling price determination system according to claim 1, wherein said optimal price determining means determines a price at which a profit is maximized as an optimal price. 4. The system according to claim 1, further comprising output means for outputting an optimum price determined by said optimum price determining means. 5. The profit predicting means calculates a sales price as p, a production cost as c, and an estimated number of sales per year at the sales price p as E.
(p), the estimated number of annual sales E (p) is a value obtained by multiplying the approximate expression F (p) obtained by the approximate calculation means by a coefficient k determined by the auction period and the endurance period of the product. , And the profit at each selling price B (p)
B (p) = (pc) * E (p). The system according to claim 1 or 2, wherein: 6. The system according to claim 5, further comprising an input unit for inputting the production cost. 7. The system according to claim 1, further comprising an e-mail transmitting means for notifying an auction to be held by e-mail via a telecommunication network. 8. The number of persons who have announced that an auction has been held is M
feature _i, the number of access's auction N _a, when the purchase possible layer of the product was M _a, that further comprising a total market size prediction means for predicting the total market size by N _a / M _i * M _a The optimal selling price determination system by an auction according to claim 1 or 2. 9. When the approximation formula obtained by the approximation calculation means is F (p), and _Nb is the number of buyers who want to purchase one yen or more, F (p) * _Nb / M _i * M the _a, claim 8, further comprising a price market size predicting means for predicting the market for sales price p
Optimal selling price determination system by auction described in. 10. An input means for inputting a sales price to be predicted, and an output means for outputting a market size predicted by the price-by-price market size prediction means for the sales price input by the input means. The optimal selling price determination system by an auction according to claim 9. 11. The system according to claim 1, wherein said bid information includes bid information for each product attribute when said product has a plurality of product attributes. 12. A process for executing an auction through a telecommunications network for a product for which an optimum selling price is to be determined when determining an optimum selling price of the product, a process for storing bid information of the auction, Based on the stored bidding information, a process of counting the number of bidders who can make a bid at each price, and a bidder who can bid by dividing the number of bidders who can make a bid at each of the collected prices by the total number of bids A process of obtaining an approximate expression consisting of an exponential function or a polynomial approximating the correlation between the rate and the price; a process of predicting a profit for the sales price using the obtained approximate expression; A computer-readable recording medium storing a process for determining a selling price and a program including an instruction for causing a computer to execute the process. 13. A process for inputting bidding information of an auction by a telecommunications network implemented for a product for which an optimal selling price is to be determined when determining an optimum selling price of the product, and the input bidding information. The process of totaling the number of successful bidders at each price based on the above, and the correlation between the bidderable bidder rate and the price by dividing the number of successful bidders at each of the aggregated prices by the total number of bids A process of obtaining an exponential function or a polynomial approximation formula approximating the above, a process of predicting a profit with respect to a sales price by using the obtained approximation formula, and a process of determining an optimal sales price from the predicted profit And a computer-readable recording medium storing a program including instructions for causing a computer to execute the following.