KR20210038530A - A System for Evaluating a Wholesale Price Index of a Product Based on Big Data and a Method for Evaluating a Wholesale Price Index of a Product Using the Same - Google Patents

Abstract

The present invention relates to a system for evaluating a wholesale price index for each product using big data and a method for evaluating a wholesale price index for each product using the same and, more specifically, to a system for evaluating a wholesale price index using big data and a method for evaluating a wholesale price index using the same, which can provide a favorable supply price to a supplier who supplies a product to various regions based on the determined wholesale price index. The system for evaluating a wholesale price index for each product using big data comprises: a supplier transaction module (13) for collecting supplier price information for one product; a buyer transaction module (14) for collecting buyer price information for the one product; an analysis server (11) for analyzing information collected from the supplier transaction module (13) and the buyer transaction module (14); a wholesale price index change calculation module (10) for generating wholesale index data by calculating a wholesale price index change for the entire product based on the information analyzed by the analysis server (11); and an individual supply determination module (18) which determines an individual supply price from the wholesale price index data determined by the wholesale price index change calculation module (10) and provides the individual supply price to the supplier transaction module (13).

Description

A System for Evaluating a Wholesale Price Index of a Product Based on Big Data and a Method for Evaluating a Wholesale Price Index of a Product Using the Same}

The present invention relates to a system for evaluating a wholesale index for each product using big data and a method for evaluating the wholesale index for each product, and can provide advantageous supply prices to suppliers who supply products to various regions based on the specifically determined wholesale index. The present invention relates to a wholesale index evaluation system using big data to enable and a method of evaluating the wholesale index by the system.

The wholesale price index or wholesale price index refers to the level of wholesale price according to the selling price of a wholesaler who directly trades with the producer, and can be used as an index representing the fluctuation of the price level. The wholesale index represents the price level of all commodities, and is calculated and disclosed based on the time set by public institutions. However, although such a wholesale price index can represent the monetary flow of the entire trading society macroscopically, it is not for each product, so it is difficult for a supplier of a specific product to determine a product supply price based on such a wholesale price index. In addition, since the wholesale price index is provided at the same value to suppliers located in different regions with different supply quantities, it may differ from the actual wholesale transaction index of a specific product. Therefore, it is necessary to calculate the wholesale index for each product based on the actual transaction. Such wholesale indices can be applied to trade in a variety of tangible or intangible commodities.

Patent Publication No. 10-2012-0026741 is a database in which the results of a questionnaire on online games are stored, an extraction unit that extracts the results of questionnaire items on game item value, character identity, game satisfaction, and item purchase intention among the databases. And an analysis unit for analyzing the online game item purchase index using the extracted questionnaire item result and the structural equation model, wherein the analysis unit calculates a path coefficient between the observation variable according to the survey result and the preset observation variable. A model application unit that applies the result of the questionnaire item on the game item value, character homogeneity, and game satisfaction to the structural equation model consisting of potential variables according to the structural equation model, and calculates a weight to be reflected in the questionnaire item on the intention to purchase the item from the structural equation model. Disclosed is a system for analyzing an online game item purchase index including a weight calculation unit and a purchase index calculation unit that calculates an online game item purchase index using the result of a questionnaire item for the item purchase intention and the calculated weight.

Patent Publication No. 10-2014-0056801 includes a purchase information collection unit that collects purchase information of a purchaser; Receives the purchase information from the purchase information collection unit, calculates a first index based on the number of purchases of the paid product commonly purchased by the purchaser and other purchasers and the total purchase amount of the paid product, and the first The purchaser by reflecting the contribution weight assigned according to the degree to which each of the index and the second index contributes to the purchase influence to each of the first index and the second index, and summing the first index and the second index reflecting the weight. Disclosed is a method of calculating a purchase influence index of a user including a purchase influence index calculation unit that calculates a purchase influence index of.

In the prior art, the item purchase index or the purchase influence index is calculated from a consumer's point of view and is difficult to be applied as a direct means for a supplier's price determination. The supplier needs to determine the supply price by applying external variables that affect the price based on the wholesale price index for each commodity. Therefore, the wholesale index needs to be determined to determine the supply price. The prior art does not disclose a method of determining such a wholesale index.

The present invention has the following objects to solve the problems of the prior art.

Prior Art 1: Patent Publication No. 10-2012-0026741 (Sungkyunkwan University Industry-Academic Cooperation Foundation, published on March 20, 2012) Online game item purchase index analysis system and its method Prior Art 2: Patent Publication No. 10-2014-0056801 (Sk Planet Co., Ltd., published on May 12, 2014) Method and apparatus for calculating user's purchase influence index

An object of the present invention is to use big data that allows suppliers to determine the supply price for each product in different regions by determining the wholesale index for each product and the wholesale index for each product in different regions. It is to provide a wholesale index evaluation system for each product and a method of evaluating the wholesale index by the system.

According to a preferred embodiment of the present invention, a system for evaluating a wholesale index for each product using big data includes: a supplier transaction module for collecting supplier price information for one product; A buyer transaction module for collecting price information of a buyer for the one product; An analysis server that analyzes information collected from a supplier transaction module and a buyer transaction module; A wholesale index fluctuation calculation module for generating wholesale index data by calculating a wholesale index fluctuation for the entire product based on the analyzed information from the analysis server; And an individual supply determination module that determines an individual supply price from the wholesale index data determined from the wholesale index variation calculation module and provides it to the supplier transaction module.

According to another suitable embodiment of the present invention, a supply amount information module for providing supply amount information for the one product to the analysis server and an environment variable module affecting the price of the one product are further included.

According to another suitable embodiment of the present invention, the analysis server includes: an alignment module for sorting information extracted from a plurality of information sources; A correlation index module for forming a correlation index by analyzing the correlation of the information arranged in the alignment module; A determination module that determines information for price determination from the correlation index module; And a reliability evaluation module for evaluating the reliability of the information determined in the determination module. And an index data module for determining index data from the information evaluated from the reliability evaluation module.

According to another suitable embodiment of the present invention, the alignment criterion of the alignment module is a time at which information is introduced and repeatability of information.

According to another suitable embodiment of the present invention, the correlation index forms a correlation map based on a predetermined extraction key and a degree of association.

According to another suitable embodiment of the present invention, a method of evaluating a wholesale index for each product includes: collecting price data for the single product; Analyzing the collected price data according to time and price; Calculating a wholesale index for each region based on the analyzed data; Determining whether there is an index difference by comparing the calculated wholesale indices for each region; Collecting related data affecting the wholesale index; Applying a compensation parameter based on the collected related data; Determining whether the wholesale index to which the compensation parameter is applied is within a set range; And determining an individual price index for each supplier.

The wholesale index evaluation system according to the present invention enables a wholesale product supplier to determine an appropriate supply price by allowing the fluctuation of the wholesale index to be evaluated in real time. In addition, the wholesale index evaluation system according to the present invention makes it possible to expand the supply area of the supplier by evaluating the fluctuation of the wholesale index for each region. In addition, the wholesale index evaluation system according to the present invention enables the wholesale supplier to determine the supply timing and quantity of goods.

1 is a block diagram showing an embodiment of a wholesale index evaluation system according to the present invention.
2 shows an embodiment of a process of selecting data for calculating a wholesale index using big data in the wholesale index evaluation system according to the present invention.
3 shows an embodiment of a process in which wholesale indices in different regions are evaluated.
4 shows an embodiment of a wholesale index evaluation process according to the present invention.

In the following, the present invention will be described in detail with reference to the embodiments shown in the accompanying drawings, but the embodiments are for a clear understanding of the present invention, and the present invention is not limited thereto. In the following description, components having the same reference numerals in different drawings have similar functions, so if they are not necessary for the understanding of the invention, they will not be described repeatedly, and well-known components will be briefly described or omitted, but the present invention It should not be understood as being excluded from the embodiment of.

1 is a block diagram showing an embodiment of a wholesale index evaluation system according to the present invention.

Referring to FIG. 1, the wholesale index evaluation system includes a supplier transaction module 13 for collecting supplier price information for one product; A buyer transaction module 14 for collecting price information of a buyer for the one product; An analysis server 11 for analyzing information collected from the supplier transaction module 13 and the buyer transaction module 14; A wholesale index fluctuation calculation module 10 for generating wholesale index data by calculating a wholesale index fluctuation for the entire product based on the analyzed information from the analysis server 11; And an individual supply determination module 18 that determines an individual supply price from the wholesale index data determined from the wholesale index fluctuation calculation module 10 and provides it to the supplier transaction module 13.

In the wholesale index evaluation system according to the present invention, the wholesale index means a wholesale index for each product, and means a supply price by a primary wholesale supplier or a secondary wholesale supplier. The wholesale index for each product may be, for example, products of the same type supplied by different manufacturers or the same products supplied by the same manufacturer. The wholesale index for each product is determined based on time and region and may fluctuate in real time. The transaction price for calculating the wholesale index for each product may be provided from a supplier or may be calculated from a purchase price of a buyer. Or it can be determined by the market transaction price.

The analysis server 11 has a function of collecting, classifying and analyzing price information for determining a wholesale index. The information on the wholesale index may be provided by the wholesale index, for example, from a wholesale index calculation agency 12 that officially aggregates the wholesale index. In this way, the wholesale index provided by the wholesale index calculation agency 12 corresponds to information that is delayed in time and corresponds to the wholesale index of the entire trading society, so it is difficult to become a real-time wholesale index that fluctuates according to time. Therefore, the supplier transaction module 13 and the buyer transaction module 14 may be connected to the analysis server 11 in order to obtain real-time price information. The supplier transaction module 13 may collect, for example, price information for one product predetermined from an auction site of a wholesale supplier. Alternatively, it is possible to directly contact a wholesale supplier or obtain wholesale price information for the single product from a member server for a wholesale supplier. The supplier transaction module 13 may acquire wholesale price information through an Internet site, direct contact, or an online transaction site that can provide information on all wholesale prices.

The buyer transaction module 14 for acquiring the information on the wholesale price may acquire information on the consumer price actually purchased by the consumer for the single product. Like the supplier transaction module 13, the buyer transaction module 14 may acquire information on consumer prices through an internet site, an offline store, or an online store. The wholesale price can be estimated from the thus obtained consumer price. In addition, the estimate of the wholesale price may be determined in advance by the analysis server. The analysis server 11 classifies and analyzes the wholesale price information obtained through the wholesale index calculation agency 12, the supplier transaction module 13, and the buyer transaction module 14 as described above, and then uses the wholesale index fluctuation calculation module 10. send. In addition, the wholesale index fluctuation calculation module 10 may calculate the wholesale index in real time based on the analysis information on the wholesale price transmitted from the analysis server 11. The wholesale index fluctuation calculation module 10 may generate wholesale index data or wholesale index fluctuation data based on a delivery time and region of the information. The wholesale index data means data on the change of the wholesale index over time of one product, and may be generated for each region. When the wholesale index data is generated, it may be created in the form of a graph or a chart, and the wholesale index data may be updated in real time according to a predetermined period. And the generated wholesale index data may be provided to the individual supply determination module 18. The individual supply determination module 18 may process the wholesale index data generated by the wholesale index fluctuation calculation module 10 into data including a supply price appropriate to each supplier. For example, different supply price information may be presented to different suppliers who supply the same product in different regions. The individual supply determination module 18 may be made as a server independent from the analysis server 11, and may be made as an Internet site accessible by various providers. A supplier through the individual supply determination module 18 may obtain a wholesale index or various information related to a wholesale transaction.

The analysis server 11 may be connected to the supply amount information module 15 and may be further connected to the environment variable module 16. The supply amount information module 15 may include a supply amount and an expected inventory amount of products currently being supplied to the trading market. The supply amount information module 15 may obtain information on the amount of supply through contact with information on the current trading market or a supplier and transmit the information to the analysis server 11. Alternatively, the supply amount information module 15 may obtain information on the supply amount by obtaining information through big data.

Another factor influencing wholesale indices is the trading environment. The environment variable module 16 may be installed in order to obtain information on the transaction environment. The environmental variable module 16 includes things such as seasonal factors, trends in buyers, or characteristics of each community. The environmental variable module 16 may acquire the effect of such an environmental variable on product consumption through big data. For example, it is possible to acquire the transaction status of a product in a specific region through various sources of information, and analyze the effect of one environmental variable on the product transaction. And it can be made into an environmental variable index and transmitted to the analysis server 11. The environmental variable index means that a number of environmental parameters affecting a product are determined, and the effect of each environmental parameter on a product in a specific region is made into an index. Such an index of environmental variables becomes an important index for determining individual supply to suppliers as there is a great need for big data to be applied.

As described above, the analysis server 11 according to the present invention calculates a real-time wholesale index of a trading society based on actual transaction information, and provides the calculated wholesale index to a supplier. The actual transaction information may be information provided from various information sources, and a large amount of data such as big data may be used as information for calculating the wholesale index.

In the following, a process in which a large amount of information such as big data is collected and processed for the calculation of the wholesale index is described.

2 shows an embodiment of a process of selecting data for calculating a wholesale index using big data in the wholesale index evaluation system according to the present invention.

Referring to FIG. 2, price information or product information from any information source 211, 212, 213 may be collected in the supplier transaction module 13 or the buyer transaction module 14 described above in order to calculate the wholesale index. . In addition, the collected information may be sorted by the sorting module 22. Specifically, price information and product information may be collected during a certain period of time, and may be sorted for filtering the collected information. The sorting module 22 may have a function of filtering the collected information. The alignment module 22 may include a time priority unit 221 and a repetition detection unit 222, and the time priority unit 221 is the same in information supplied from various information sources 211, 212, 213. Among the information determined as information, priority is given to information generated at a time close to the current point in time. And the repetition detection unit 222 gives priority based on the repetition level of the price information. In this way, information is sorted according to visual priority and repetition level, and, for example, information with low visual priority or information with low repetition level is excluded. For example, if price information is provided at 1 time and other price information is provided at time 2 on one web page, if time 2 is closer to the current time than time 1, price information at 1 time is excluded. Also, if 1 price is provided from 3 different web pages for the same product, and 2 prices are provided from 5 different web pages, 2 prices have priority. When price information is selected in the sorting module 22 in this way, the correlation index may be determined in the correlation index module 23. The correlation index is for determining the reliability of price information, and a correlation index may be determined according to an extraction key and a degree of correlation. The correlation index is for determining whether the obtained price information is actually related to a transaction, and may be formed according to a criterion provided by the extraction key unit 231 and the correlation unit 232. The extraction key unit 231 may combine two or more related terms according to the characteristics of the product. For example, words related to product names or characteristics and words related to transactions may be created as extraction keys. The extraction key unit 231 may generate various extraction keys according to the product for which the wholesale index is calculated, determine a correlation value for each extraction key, and provide it to the correlation index unit 23. The relevance unit 232 has a function of determining whether the obtained information is related to a transaction. The relevance unit 232 may determine a relevance value according to the source of the acquired information. For example, if the information is obtained from, for example, a trading site, the value of the relevance may increase. On the other hand, if the acquired information is a web page with a different subject, the relevance value may be lowered. When the extraction key and the criterion for determining the degree of association are generated as described above, the correlation index module 23 may determine a correlation index value for each price information based on this. In addition, price information having the determined correlation index value may be transmitted to the determination module 24. The determination module 24 may determine whether the price information transmitted from the correlation index module 23 can be data for determining the wholesale index. In addition, the determined information is transmitted to the reliability evaluation module 25 so that the reliability level may be determined. Reliability can compare each price information with previous price information or a wholesale index calculated from another wholesale index calculation agency, and evaluate the reliability based thereon. In addition, the information on which the reliability is evaluated may be transmitted to the index generation module 26. The index generation module 26 may generate a wholesale index by classifying the transmitted price information according to regions and times. In addition, the generated wholesale index may be converted into one price information by the feedback module 27 and input to the analysis server 11. The appropriateness of the wholesale index determined accordingly can be determined.

The analysis server 11 may obtain and process price information in various ways, and the wholesale index evaluation system according to the present invention is not limited to the presented embodiment.

As explained above, the wholesale index can be calculated hourly or regionally.

The following describes the process of calculating the wholesale index for each region and delivering it to the supplier.

3 shows an embodiment of a process in which wholesale indices in different regions are evaluated.

Referring to FIG. 3, different wholesale indices 311, 312, and 313 may be determined for different regions. In addition, different wholesale indices 311, 312, and 313 may be calculated by the analysis server and the wholesale index fluctuation calculation module described above. The wholesale index is a criterion for determining the wholesale supply price, and each supplier 38 may determine the wholesale supply price for different regions based on the wholesale index. When each supplier 38 determines a supply price for a different region, whether or not to supply a supply price or a supply price for the region should be determined according to the cause of the difference in the wholesale index. In this specification, the wholesale supply price determined based on the wholesale index is referred to as a price index. The price index may have different values for the same wholesale index depending on the supply quantity, supply timing or supply region of the supplier 38. In order to determine such a price index, the wholesale indices 311, 312, and 313 calculated for different regions may be transmitted to the comparison module 32. In addition, the wide-area wholesale index 351 for one product may be transmitted to the comparison module 32. The comparison module 32 may compare the difference between the wide-area wholesale index 351 and each of the wholesale indices 311, 312, and 313 and transmit the comparison to the price index analysis module 33. In addition, parameters affecting the wholesale indices 311, 312, 313, such as the number of suppliers, the amount of supply, the size of a consumption market, or other price indices, may be searched by the evaluation parameter module 34. In addition, the searched parameters may be transmitted to the price index analysis module 33. The price index analysis module 33 may determine a price index for each region. Regional price indices are similar to wholesale indices, but may differ from wholesale indices in that they reflect the trading environment. When the price index is analyzed by the price index analysis module 33 as described above, it may be transmitted to the individual index determination module 37. The individual index determination module 37 may calculate an appropriate supply price when each supplier 38 supplies a product to a specific region in the current state. The supplier 38 may calculate an individual index for each region for which a price index is determined according to a supply route, quantity of supply, or supply timing of the supplier. And according to the calculated individual indices, it is possible to determine the most favorable time, quantity and region for supply.

* As described above, the wholesale index evaluation system according to the present invention allows for each supplier 38 to determine the supply amount, supply timing, and wholesale supply price for the most advantageous region.

Hereinafter, a method of evaluating a wholesale index in a system according to the present invention having such a function will be described.

Figure 4 shows an embodiment of the wholesale index evaluation process according to the present invention.

Referring to FIG. 4, a method of evaluating a wholesale index for one product includes the steps of collecting price data for the one product (P41); Analyzing the collected price data according to time and price (P42); Calculating a regional wholesale index based on the analyzed data (P43); Determining whether there is a difference in the index by comparing the calculated wholesale indices for each region (P44) (P45); Collecting related data affecting the wholesale index (P46); Applying a compensation parameter based on the collected related data (P47); Determining whether the wholesale index to which the compensation parameter is applied is within a set range (P48); And determining an individual price index for each supplier (P49).

The wholesale index evaluation method according to the present invention is characterized in that the wholesale index for each region is calculated or evaluated by collecting and analyzing price information from suppliers, buyers, or various price information sources based on big data. Price data is collected based on big data for evaluation of the wholesale index (P41). Collected data must be large, must be obtained from various sources of information, must be collected in a short time, and reliability must be evaluated. The price information collected in this way may be classified and analyzed according to the acquired time and price, and classified by region (P42). The process of extracting valid data from the price information may be performed in the analysis server described above, and a price wholesale index for each region may be calculated based on the valid data (P43). In addition, the calculated regional wholesale index can be compared (P44). Regional wholesale indices may differ depending on product characteristics, primary or secondary wholesale supply regions, market size, or relationships with other products. In addition, differences in wholesale indices by region may not appear depending on the product. Accordingly, a range of an index difference that may have meaning according to a product may be determined, and whether or not an index difference is indicated (P45). If the regional wholesale index for one product does not show a difference outside the preset range, an individual price index for each supplier may be determined based on the regional wholesale index (P49). On the contrary, if the index difference is out of a predetermined range (YES), related data for each region may be collected (P46). The related data may include price indices, regional characteristics, or product characteristics of other products. When the related data is collected, a compensation parameter may be determined and applied accordingly (P47). According to the application of the compensation parameter, the price is changed according to the characteristics of each region, and it may be determined again whether the changed price is in a preset range (P48). If it is not in the preset range (NO), a weight is set for the compensation parameter (P481), and related data to be applied may be collected (P46). On the contrary, if it is in the set range (YES), an individual price index for the supplier can be determined (P49). Individual price indices can be determined according to the method described above.

The wholesale index for each region according to the present invention may be determined in various ways, and the present invention is not limited to the presented embodiments.

The wholesale index evaluation system according to the present invention enables a wholesale product supplier to determine an appropriate supply price by allowing the fluctuation of the wholesale index to be evaluated in real time. In addition, the wholesale index evaluation system according to the present invention makes it possible to expand the supply area of the supplier by evaluating the fluctuation of the wholesale index for each region. In addition, the wholesale index evaluation system according to the present invention enables the wholesale supplier to determine the supply timing and quantity of goods.

The present invention has been described in detail above with reference to the presented embodiments, but those of ordinary skill in this field will be able to make various modifications and modifications without departing from the technical spirit of the present invention with reference to the presented embodiments. . The present invention is not limited by such modifications and modifications, but is limited by the claims appended below.

10: wholesale index fluctuation calculation module 11: analysis server
12: Wholesale Index Calculation Agency 13: Supplier Transaction Module
14: buyer transaction module 15: supply information module
16: environment variable module 18: individual supply determination module
22: alignment module 23: correlation index module
24: decision module 25: trust evaluation module
26: index generation module 27: feedback module
32: comparison module 33: price index analysis module
34: evaluation parameters module 37: individual index determination module
38: suppliers 211, 212, 213: sources of information
221: time priority unit 222: repetition detection unit
231: extraction key unit 232: association degree unit
311, 312, 313: wholesale index 351: wide area wholesale index

Claims (1)

A supplier transaction module 13 for collecting supplier price information for one product;
A buyer transaction module 14 for collecting price information of a buyer for the one product;
An analysis server 11 for analyzing information collected from the supplier transaction module 13 and the buyer transaction module 14;
Wholesale that generates wholesale index data by calculating the fluctuation of the wholesale index representing the level of wholesale price according to the sales price of a wholesaler who directly trades with the producer for the whole product based on the information analyzed from the analysis server 11 An exponential change calculation module 10; And
Including an individual supply determination module 18 that determines an individual supply price from the wholesale index data determined from the wholesale index variation calculation module 10 and provides it to the supplier transaction module 13,
The analysis server 11 includes a sorting module 22 for sorting information extracted from a plurality of information sources 211, 212, 213; A correlation index module 23 for forming a correlation index by analyzing the correlation of the information arranged in the alignment module 22; A determination module 24 for determining information for price determination from the correlation index module 23; And a reliability evaluation module 25 for evaluating the reliability of the information determined in the determination module 24. And an index data module 26 for determining wholesale index data from the information evaluated from the reliability evaluation module 25,
The correlation index module 23 forms a correlation map based on a predetermined extraction key and a correlation degree,
The extraction key is made by combining two or more related terms including a word related to a product name or characteristic and a word related to a transaction, and the degree of association includes a value of a degree of association according to the source of the acquired information. Wholesale index evaluation system for each product using data.

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