JP4190821B2 - Vehicle trade-in price provision method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
  In the present invention, a server and an information terminal are connected via a communication network such as the Internet, a vehicle trade-in price is calculated by the server based on information input from the information terminal, and the vehicle trade-in price is calculated as the information terminal. The present invention relates to a vehicle purchase system to be provided.
[0002]
[Prior art]
  Generally, the trade-in price of a vehicle is determined empirically from the year of registration of the vehicle in the first year, the mileage, etc., and based on this determination, the vehicle is sold to a second-hand dealer or sent to a tender or auction. Or have been disposed of.
  Further, in order to sell a vehicle in use by a user, it has been necessary to bring the vehicle to a reseller and have it assessed.
[0003]
[Problems to be solved by the invention]
  However, trade-in prices based on human experience do not necessarily have a clear basis, and the variation among judges is not small. In addition, since accurate resale prediction cannot be performed, useless transportation and loss in auctions and auctions are caused. Moreover, the burden of the user who wishes to sell was also large.
[0004]
  Therefore, the present invention provides a system that allows a user to easily know and sell a trade-in price related to a vehicle currently in use by inputting vehicle type identification information, use period information, and mileage information from an information terminal. For the purpose.
  It is another object of the present invention to provide a system capable of obtaining output information based on past performance data by using a residual value calculation formula using multiple regression analysis.
[0005]
[Means for Solving the Problems]
  Claim 1Provision of vehicle trade-in price of the present invention describedMethodIs the manufacturer name, vehicle model name, vehicle application, vehicle shape, vehicle model grade, certified model, model designation number, classification number, mission, drive system, displacement, number of doors, popular model, capacity and loading capacity, engine model, Vehicle model database with vehicle type data such as number of engine cylinders, engine mechanism, tire size, supercharger, roof shape, exhaust gas regulations, body size, automobile tax classification, weight tax, insurance class, etc. Vehicle type that identifies the vehicle, such as the manufacturer name or model name, with data related to resold vehicles such as the expiration date, contract period, new vehicle price, sale price after expiration of the contract, mileage at the time of resale, assessment assessment at the time of resale Vehicle sales database with data,A residual value calculation-related database having data for multiple regression on the expected sale price, expected residual value, or expected residual value rate of the vehicle;Regarding already resold vehicles resold within a specified periodHas in the residual value calculation related databaseA residual value calculating means for calculating information on the expected sales amount, expected residual value, or expected residual value rate of the vehicle by using a module such as a correlation formula obtained by data, and a model designation number and a classification classification number , Or the first step that prompts the input of vehicle type specific information for narrowing down a specific vehicle type such as a vehicle type name and the input of usage period information such as the number of months since the first year registration or usage contract year or the usage contract period A second step, a third step for prompting input of mileage information during the actual use period, and extracting and extracting corresponding vehicle type information from the vehicle type database based on the input vehicle type specifying information Calculate the trade-in price by the remaining value calculation means based on the actual use period information and the mileage information that were input, and the fourth step that provides the vehicle type information and prompts for confirmation. in front ; And a fifth step of prompting the confirmation provides trade-in priceThis is a vehicle trade-in price provision method for data extraction condition input processing that specifies data extraction conditions to narrow down vehicle sales performance data that is the basis for residual value calculation, and for category items and popularity index for multiple regression analysis of residual value calculation Category item specification process for specifying two patterns of category items and an actual measurement value, calculation variable item specification process for specifying variable conditions for dependent variable items, independent variables, dummy variables and dummy variables used in multiple regression calculation, Vehicle sales record data that is the basis for the residual value calculation is extracted according to the data extraction conditions, and changes in the category item setting process and the calculation variable item designation process Data extraction / conversion processing that converts data according to conversion conditions, residual value calculation condition calculation condition definition step for defining residual value calculation conditions, vehicle sales extraction data by multiple regression analysis categories, and dummy variables Based on the actual data, the residual value calculation 1 process for calculating the average value, standard deviation, and score value, and the multiple regression analysis coefficient data calculated by the residual value calculation 1 process for the vehicle sale extraction data are used to calculate The popularity index calculation process for calculating the popularity index by the popularity index category by the regression analysis category, and the residual value using the variable obtained by adding the popularity index item to the scoring calculation variable item calculated by the residual value calculation 1 process as the calculation item variable According to the calculation 2 process, the residual value calculation is performed in accordance with the vehicle sales extraction data, the calculation variable item data, and the calculation category data defined in the residual value calculation formula calculation condition definition step. And a remaining value calculation equation calculation step for calculating, and updates the data of the remaining value calculation related database to be used for the remaining value calculation means periodically.
It is characterized by that.
[0006]
DETAILED DESCRIPTION OF THE INVENTION
  Of the present inventionFirstProvision of vehicle trade-in price according to the embodimentMethodIsData extraction condition input processing for specifying data extraction conditions for narrowing down vehicle sales record data on which residual value is calculated, category items for multiple regression analysis for residual value calculation, category items for two patterns for popularity index, and actual measurement values Category item specifying process to specify, dependent variable items to be used in multiple regression calculation, independent variable, dummy variable and dummy variable variable condition specifying process, and vehicle sales results that are the basis of residual value calculation Residual value calculation formula that defines the condition of residual value calculation by extracting data according to data extraction conditions and data extraction / conversion processing that converts conversion variables in category item setting processing and calculation variable item specification processing according to conversion conditions Based on the calculation condition definition step, vehicle sales extraction data by multiple regression analysis category, and dummy variable results data, the average value, standard Using the residual value calculation 1 process for calculating the deviation and the score value and the multiple regression analysis coefficient data calculated in the residual value calculation 1 process for the vehicle sale extraction data, the popularity index for each popular index category by the multiple regression analysis category The residual value calculation formula is calculated by the popularity index calculation processing for calculating the residual value calculation 2 and the residual value calculation 2 processing in which the popularity index item is added to the scoring calculation variable item calculated in the residual value calculation 1 processing. A residual value calculation related database for use in residual value calculation means, comprising a residual value calculation formula calculation step for calculating a residual value calculation formula in accordance with vehicle sales extraction data, calculation variable item data, and calculation category data defined in the condition definition step Update your data regularlyIs. According to the present embodiment, the trade-in price regarding the vehicle currently in use can be easily known by inputting the vehicle type identification information, the usage period information, and the travel distance information from the information terminal. In addition, since the vehicle type information extracted from the vehicle type database based on the input vehicle type specifying information is provided, it can be confirmed whether or not there is an error in the corresponding vehicle type.
[0007]
【Example】
  A vehicle purchase system according to an embodiment of the present invention will be described below.
  FIG. 1 is a flowchart showing the processing procedure of the vehicle purchase system according to this embodiment.
  The user accesses the system provided by the server from an information terminal connected via a communication network such as the Internet.
  The user first logs in from the menu screen, and the model specification number, classification classification number, or vehicle type identification information for narrowing down a specific vehicle type such as the vehicle type name, the number of months since the first year registration or use contract year, or the use contract period Etc. and the travel distance information during the actual use period are input, and these input data are transmitted to the server.
  The server temporarily stores the input data in the storage unit and searches for the corresponding vehicle type from the received vehicle type specifying information. This search includes manufacturer name, vehicle type, vehicle application, vehicle shape, vehicle grade, certified model, model designation number, classification number, mission, drive system, displacement, number of doors, popular model, capacity and load capacity, A vehicle type database having vehicle type data such as engine type, number of engine cylinders, engine mechanism, tire size, supercharger, roof shape, exhaust gas regulations, body size, vehicle tax classification, weight tax, insurance class, etc. is used.
  As a result of the search, if a plurality of types are applicable, the corresponding vehicle type information is transmitted to the user. This information is displayed in a list on the user information terminal.
  When a plurality of types of vehicles are applicable, the user specifies and transmits the corresponding vehicle types from the list display.
  If the server can identify one vehicle type, the trade-in price is calculated by the residual value calculation means based on this vehicle type information and the actual usage period information and mileage information already stored. The calculated trade-in price is transmitted to the user together with the corresponding vehicle type information.
  The user confirms whether or not the vehicle type is correct based on the received vehicle type information, and confirms the displayed trade-in price. If the displayed trade-in price is acceptable, the user transmits intention confirmation data.
  In the server, the intention confirmation data is registered in the database together with the user information, and input format information related to the sales contract is transmitted.
[0008]
  FIG. 2 is a screen transition diagram of the vehicle purchase system according to this embodiment.
  When the vehicle type search screen is shifted from the menu screen and one vehicle type can be specified by the vehicle type specifying information input on the vehicle type search screen, the trade-in price display screen is displayed. If the vehicle type identification information entered on the vehicle type search screen fails to identify a single vehicle type, the vehicle type list screen is displayed. When a specific vehicle type is selected on this vehicle type list screen, the trade-in price display screen appears. Move.
[0009]
  FIG. 3 to FIG. 6 are screen configuration diagrams of the vehicle purchase system according to the present embodiment, FIG. 3 is a menu screen, FIG. 4 is a vehicle type search screen, FIG. 5 vehicle type list screen, and FIG. It is.
  The menu screen in FIG. 3 has input fields for user ID and password. Also, a “login” button for instructing login and a “reset” button for canceling the input of the user ID and password are provided.
[0010]
  The vehicle type search screen of FIG. 4 has a configuration in which a vehicle type search method can be selected. In this embodiment, the vehicle type search screen has a check button that can select either “vehicle verification search” or “vehicle type name search”. ing.
  As input fields when “car verification search” is selected, “model classification number” and “classification classification number” are provided. Note that the “model classification number” and “classification classification number” are described in the vehicle verification, but are not normally recognized by the user. Therefore, the vehicle verification sample is displayed on the same screen as shown in the figure, and this vehicle It is preferable to display the corresponding column in the verification sample. As input fields when “model name search” is selected, “manufacturer name”, “model name”, and “displacement” are provided. However, these “manufacturer name”, “car model name” and “displacement” need to be input accurately, the car model name is limited to a certain number by specifying the manufacturer name, and the exhaust capacity is also predetermined. Therefore, it is preferable to use a pull-down selective input method for these input fields.
  In this embodiment, an input field of “first year / month” is provided as usage period information, and an input field of “travel distance” is provided as travel distance information. For these input fields, a selective input method using a pull-down method is preferable. By instructing a “display trade-in price” button, a corresponding vehicle type search under specified conditions is performed.
  As a result of the relevant vehicle type search, if there are a plurality of relevant vehicle types, the following processing is performed.
  When a search is made from “model designation number / classification designation number”, the vehicle with the lowest vehicle price is automatically selected, and a purchase price display screen is displayed. Further, when searching from “manufacturer name / car model name / displacement”, a transition is made to the car model list screen.
[0011]
  Candidates are displayed on the vehicle type list screen of FIG. In this candidate display, a manufacturer name and a car model name are displayed, and grade names as candidates are displayed. Also, at least one or more information of “displacement”, “mission”, “drive system”, “number of doors”, “capacity”, “vehicle price” and “release date” necessary to determine the applicable grade name It is preferable to display. As described above, when the vehicle type name search is specified in the search condition, if there are a plurality of target vehicle types, a search target vehicle type list of the specified condition is displayed.
  By selecting the corresponding vehicle type from the vehicle type list screen (pressing the selection button), the screen shifts to the trade-in price display screen shown in FIG.
[0012]
  The trade-in price display screen in FIG. 6 displays the detailed information of the corresponding vehicle type (designated vehicle type) and the trade-in price in the designated conditions (first registration date, usage elapsed period, total travel distance). At this time, the conditions specified on the vehicle type search screen (first registration date, total mileage) and usage elapsed period (system date-specified first registration date) are also displayed.
  When the initial registration date, usage elapsed period, and total mileage are changed and the “Trade price recalculation” button is pressed, the trade price is recalculated and displayed under the specified conditions. The usage period is automatically displayed as “system date-specified initial registration date”.
  In trade-in price calculation, it is preferable that only a system administrator can specify a rating of a plurality of ranks (for example, 1 to 5 ranks). When this rating change function is provided, a standard rating rank can be automatically set, and the trade-in price is multiplied by a preset coefficient by changing the rating rank by the administrator.
  As a result of specifying the above conditions and pressing the “recalculate trade-in price” button, an error content is displayed by displaying a trade-in price below 0 in the trade-in price display field. Examples of the error occurrence include a parameter error, a database connection error, no corresponding multiple regression analysis category, no corresponding popularity index category, no specified vehicle type data, no specified grade category data, and a database access error.
[0013]
  FIG. 7 is a system configuration diagram of the server side according to the present embodiment.
  The server-side system has a function of periodically updating data used for the residual value calculation means, and this data update function is performed in the residual value calculation formula calculation condition definition step and the residual value calculation formula calculation step.
  In the residual value calculation formula calculation condition definition step, a data extraction condition input process 11, a category item specification process 12, a calculation variable item specification process 13, and a data extraction / conversion process 14 are performed in order to define a residual value calculation condition. .
  In the data extraction condition input process 11, a data extraction condition for narrowing down vehicle sales record data that is a basis for calculating the residual value is designated. Here, as the data to be extracted, the vehicle sales performance data from the present to six months ago is targeted. The predetermined period for extracting data is determined in consideration of economic conditions, market trends, product cycles, data parameters, and the like. That is, it is preferable to set a shorter period for economic and market trends if the fluctuation is large. As for the product cycle, if the cycle period is long, the period may be set longer. It is important that there is a sufficient number of data parameters for statistical processing. Items that can be registered in the data extraction conditions are items registered as vehicle sales data. For example, elapsed months, monthly mileage, new vehicle price, displacement, light automatic classification (660 CC or less), automobile Tax classification (luxury car = 3000CC or higher), vehicle usage classification (passenger or not), old and new classification (elapsed months or less or not), fuel (gas or not), ABS Whether it is equipped or not.
[0014]
  Here, the car model database includes manufacturer name, car model name, vehicle use, vehicle shape, car model grade (car model name, grade name), certified model, common model (model designation number, category classification number), mission, drive system, exhaust Quantity, number of doors, capacity, loading capacity, engine type (motor model), number of engine cylinders, engine mechanism, tire size, turbocharger, roof shape, exhaust gas regulations, body size, body color, car tax classification, weight tax It has vehicle type data on items such as insurance class, popularity index, vehicle usage, vehicle shape, start of sale, end of sale. Here, the popularity index is an index that is ranked by the residual value rate in the classification classified by vehicle type. For example, if the residual value rate of Corolla and Civic are the same, and the residual value rate of Sunny is 2 rank lower than Corolla, the popularity index of Corolla is set to 25, the popularity index of Civic is set to 25, and the popularity index of Sunny is set to 22. Is done. The vehicle use is a classification of vehicles according to the use, and is classified into passenger cars, vans, buses, trucks, and the like. In addition, the vehicle sales database contains information on existing resold vehicles such as year of use contract, year of use contract expiration, period of use contract, new vehicle price, sale price after expiration of use contract, mileage at the time of resale, assessment evaluation at the time of resale, etc. The data is stored together with vehicle type data for specifying a vehicle such as a manufacturer name and a vehicle type name.
[0015]
  In category item designation processing 12, category items for multiple regression analysis for residual value calculation, category items for two patterns for popularity index, and actual measurement values (Y values) are designated. Here, as the category for the multiple regression analysis, the items estimated to have different fluctuation tendencies with respect to the calculation variable items for the multiple regression calculation are defined by category 1 to category 5 items, and grouped by combinations of the defined items. For example, the vehicle shape group is divided into three groups of SD / HT / HB / CP / CO, CW / PW, CV / BV, and other groups. Here, the vehicle shape group is a classification based on the number of doors and the outer shape. For example, a sedan (SD) if 4 doors + trunk, and a hatchback (HB) if 2 doors + tailgate (no 4-door specification). ) If 2 door + trunk, coupe or sports (CP), 2-4 door + tail gate or 4 door base full bonnet, bonnet wagon (BW), 3-4 door + tail gate or semi cab over If there is a cab wagon (CW). The fuel is classified according to whether it is a gasoline vehicle or not. A high-class vehicle is classified according to whether the average vehicle body price of the same model name exceeds a predetermined amount, for example, 2.5 million yen. On the other hand, as the category for the popularity index, the items estimated to be similar to the variable variables for the multiple regression calculation, but are different in the dependent variable to be calculated, are defined as category 1 to category 5 items. For example, the model name / manufacturer name, shape, and mission classification (whether or not the vehicle is an AT car) are defined. The measured value (Y value) is a target item for which a dependent variable is to be obtained, and either the sale amount or the sale rate is designated. Here, the sale rate is the amount of the successful bid / the price of the new car. Note that the values of Category 1 to Category 5 and Category 1 to Category 5 can be arbitrarily set by the server-side system, and can be calculated from any angle as the market environment changes.
[0016]
  In the calculation variable item designation process 13, a dependent variable item (calculation variable item) used in the multiple regression calculation is designated. In addition, variable conditions for independent variables, dummy variables, and dummy variables are specified. Here, the vehicle body price (score value), the displacement (score value), the number of elapsed months (LOG score value), and the monthly travel distance (score value) are used as independent variables. On the other hand, as a dummy variable, a light category (whether it is a light vehicle) and a year-end drop category (whether the registration month is from November to December) are used. As other dummy variables, automobile tax classification, vehicle shape classification, old and new classification, fuel classification, and specific vehicle classification can be used.
  The calculation variable item that can be defined is a maximum of 20 items that can be expressed by numerical values or decimal points, and specifies whether the variable is an independent variable or a dummy variable. An independent variable is an item that uses the item value of the vehicle sales record data as it is in the calculation, and instead of using the value as it is in the multiple regression calculation, it is converted into a score value and calculated as a dependent variable. Is done. For the independent variable item, it is specified whether the dependent variable is used as a definition item as it is (score value) or is used after LOG conversion (LOG score value). The dummy variable is a dependent variable that is defined as a logical value by specifying a conversion method (here, the travel distance is greater than 20,000), and is not a score value unlike an independent variable.
[0017]
  In the data extraction / conversion process 14, vehicle sales performance data that is a basis for calculating the remaining value is extracted according to the data extraction condition. Further, the conversion variable (dummy variable) in the category item setting process and the calculation variable item designation process is converted according to the conversion condition.
  The residual value calculation formula calculation step is for the case where data whose elapsed months are greater than 17 months is targeted according to the vehicle sales extraction data, calculation variable item data, and calculation category data defined in the residual value calculation formula calculation condition definition step. The multiple regression analysis process (residual value calculation formula calculation) is performed in two patterns when data whose elapsed months are less than 43 months is targeted. The processing procedure is performed in the order of residual value calculation 1 (multiple regression analysis calculation) process 15, popularity index calculation process 16, residual value calculation 2 (multiple regression analysis calculation) process 17.
[0018]
  In the residual value calculation 1 process 15, the average value, the standard deviation, and the score value are calculated based on the vehicle sales extraction data for each of the multiple regression analysis categories (hereinafter abbreviated as “category”) and the dummy variable performance data. For the average value, the average value of the calculation variable items is calculated for each category. SUM by category (value of the calculation variable item) divided by the number of data items by category. For the standard deviation, the standard deviation of the calculation variable item is calculated for each category. X = SUM ({value of calculated variable item by category−average value by category of the above calculation)} 2), where the standard deviation is obtained by √ (X ÷ number of data by category). For the score value (only the independent variable item), a score value or a LOG score value is calculated for each result data (by category / by calculation variable item). The designation of the score value or the LOG score value is performed by the calculation variable item designation processing 13 described above. Score value = (actual value of variable item−average by category) ÷ standard deviation by category. However, (actual value of variable item−average by category) is not an absolute value. LOG score value = (actual value of LOG variable item− (average LOG value by category) ÷ category LOG standard deviation value) However, the actual value of LOG variable item−average LOG value by category is not an absolute value. The score value or the LOG score value is used as a variable item for multiple regression analysis calculation in order to align the coefficient units between independent variable items. The analysis dependent variable is used as a calculation variable item (score value or LOG score value is used as an independent variable), and the actual measurement value (Y value) is calculated under the condition of vehicle sales extraction data (sales rate or sale price).
[0019]
  In the popularity index calculation process 16, the multiple regression analysis coefficient data calculated in the residual value calculation 1 process 15 is used as the vehicle sales extraction data, and is classified into the popularity index categories by the multiple regression analysis categories (hereinafter abbreviated as categories). Calculate the popularity index. The calculation procedure is performed in the order of a residual step, an average value step, a category-specific residual standard deviation step, and a popularity index step. In the residual step, the residual is obtained by the actual sales rate (or successful bid amount) −theoretical sale rate (or successful bid amount). In the average value step, an average value of residuals is calculated for each category. It is calculated by SUM (residual) by category / data count by category. In the category-specific residual standard deviation step, the standard deviation of the residual is calculated for each category. The calculated standard deviation is used for the rating of the remaining value calculation (user side function). X = SUM ({residual value by category−average value by category of the above calculation} 2), where the standard deviation is obtained by √ (X ÷ number of data by category). In the popularity index step, an average value of residuals is calculated for each popularity index category. The popularity index is SUM by the popularity index category (residual of the above calculation) divided by the number of data by the popularity index category. The calculated value is added as a popularity index value for each performance data and used as a variable item for residual value calculation 2 (multiple regression analysis). However, the value of the popularity index used in the residual value calculation (user-side function) differs depending on the number of data for each popularity index category.
[0020]
  In the residual value calculation 2 process 17, a variable obtained by adding a popularity index item to the scoring calculation variable item calculated in the residual value calculation 1 process 15 is used as a calculation item variable. The actual value (Y value) uses the value calculated in the residual value calculation 1 process 15. Of the data by popularity index category, data smaller than 5 is excluded. Multiple regression data is calculated for the above data.
[0021]
  In the server-side system, the residual value calculation related database 23 is periodically updated as described above. When a new vehicle type such as a new vehicle is added, the additional vehicle type data is additionally registered in the vehicle type database 21. In addition, the vehicle sale database 22 is periodically updated to vehicle sale result data from the present to six months ago. The server-side system includes a user database 24 for registering user information.
  The vehicle type search means 25 has a function of searching for the vehicle type from the vehicle type database 21 based on the model number (or authorized type) specified by the manufacturer number or the model designation number and the category classification number described in the vehicle verification, and the vehicle sale data search means 26 Alternatively, the vehicle sales database 22 has a function of searching for vehicle sales data related to the same vehicle type as the corresponding vehicle. The residual value calculation means 27 calculates the residual value from the given data (use period information and mileage information) and information obtained from the vehicle sale database 22 search result using a multiple regression equation.
[0022]
  Here, the residual value calculation means 27 selects a residual value calculation formula using the multiple regression analysis of the corresponding multiple regression category / popularity index category from the specified vehicle model conditions, and applies the calculation item to the selected residual value calculation formula. The residual value (trade-in price) is calculated. The item of the vehicle type condition information to be specified can be arbitrarily set according to the market trend. For example, the following vehicle type condition information can be set.
  As the vehicle type identification information, a model designation number, a classification classification number, or a manufacturer vehicle type name or specification is designated, and specific grade vehicle type information is selected. Furthermore, the search items from the selected grade model information include manufacturer name, model name, shape, fuel classification (whether it is a gasoline car), mission classification (whether it is an AT car), new car price, displacement , And the first year registration year can be used. On the other hand, distance, use period, and rating (1 to 5) can be set as the variation condition information.
  The residual value calculation formula to be used is performed in two patterns: a case where data whose elapsed months are 24 months or more and a case where data which is less than that are targeted. The popularity index is multiplied by the adjustment factor according to the number of popularity index categories. It is calculated based on the standard deviation of popularity index according to the specified rating.
  In response to the residual value (trade-in price) calculation request, the residual value calculation means 27 returns the residual value calculation result from the selection result of the vehicle sale database as a return value.
  The program of the remaining value calculation means 27 is modularized and supplied in a format such as a DLL file or a COM file format.
[0023]
  As described above, in the server-side system, when searching by the vehicle type search means 25 under the vehicle type name search, if there is a plurality of vehicle type information, it is transmitted to the information terminal as vehicle type list information. The vehicle sales data searched by the vehicle sales data search means based on the specified vehicle type and the trade-in price calculated by the residual value calculation means are transmitted to the information terminal.
  In the above embodiment, the server and the information terminal are connected via a communication network such as the Internet, the vehicle trade-in price is calculated by the server based on the information input from the information terminal, and the vehicle trade-in price is Has been described, but it can also be used as a system for providing information related to the trade-in price of the vehicle, and the communication network may be a dedicated line such as a LAN. In addition, it is possible to use even a system that is performed by a specific information processing apparatus without necessarily going through a communication network.
[0024]
【The invention's effect】
  As is clear from the description of the above embodiment, according to the present invention, the trade-in price regarding the vehicle currently in use can be easily obtained by inputting the vehicle type identification information, the usage period information, and the mileage information from the information terminal. Can know.
[Brief description of the drawings]
FIG. 1 is a flowchart showing a processing procedure of a vehicle purchase system according to an embodiment of the present invention.
FIG. 2 is a screen transition diagram of the vehicle purchase system according to the present embodiment.
FIG. 3 is a configuration diagram of a menu screen of a vehicle purchase system according to the present embodiment.
FIG. 4 is a configuration diagram of a vehicle type search screen of the vehicle purchase system according to the present embodiment.
FIG. 5 is a configuration diagram of a vehicle type list screen of the vehicle purchase system according to the present embodiment.
FIG. 6 is a block diagram of a trade-in price display screen for a vehicle purchase system according to the present embodiment.
FIG. 7 is a system configuration diagram of the server side according to the present embodiment.
[Explanation of symbols]
  21 Vehicle model database
  22 Vehicle sales database
  23 Residual value calculation related database
  24 user database
  25 Vehicle model search means
  26 Vehicle sales data search means
  27 Residual value calculation means

Claims (1)

Manufacturer name, vehicle type, vehicle application, vehicle shape, vehicle type grade, certified model, model designation number, category classification number, mission, drive system, displacement, number of doors, popular model, capacity and load capacity, engine model, engine Vehicle type database with vehicle type data such as the number of cylinders, engine mechanism, tire size, supercharger, roof shape, exhaust gas regulations, body size, vehicle tax classification, weight tax, insurance class, etc.
Data on the existing resale vehicle, such as the year of use contract, the year of use contract expiration, the use contract period, the new car price, the amount sold after the use contract expires, the mileage at the time of resale, and the assessment at the time of resale A vehicle sales database with vehicle type data for identifying vehicles such as
A residual value calculation-related database having data for multiple regression on the expected sale price, expected residual value, or expected residual value rate of the vehicle;
Information on the expected sale price, expected residual value, or expected residual value rate of a vehicle using a module such as a correlation formula obtained from data stored in the residual value calculation related database regarding resold vehicles resold within a predetermined period A residual value calculating means for calculating
With
A first step for prompting input of vehicle type identification information for narrowing down a specific vehicle type such as a model designation number, a category classification number, or a vehicle type name;
A second step that prompts the user to enter usage period information such as the number of months since the first year registration or usage contract year or the usage contract period;
A third step for prompting input of mileage information during the actual use period;
A fourth step of extracting corresponding vehicle type information from the vehicle type database based on the input vehicle type identification information, providing the extracted vehicle type information and prompting confirmation;
A fifth step of calculating a trade-in price by the residual value calculating means based on the inputted actual use period information and the mileage information, and providing the calculated trade-in price to prompt confirmation; ,
A vehicle trade-in price providing method comprising:
A data extraction condition input process for specifying a data extraction condition for narrowing down the vehicle sales record data on which the residual value is calculated,
A category item for multiple regression analysis of residual value calculation, a category item of two patterns for popularity index, and a category item specifying process for specifying an actual measurement value,
Calculation variable item specification processing that specifies variable conditions for dependent variable items, independent variables, dummy variables, and dummy variables used in multiple regression calculations,
Data extraction / conversion processing for extracting vehicle sales performance data, which is a basis for residual value calculation, in accordance with data extraction conditions, and converting conversion variables in the category item setting processing and calculation variable item designation processing in accordance with the conversion conditions;
A residual value calculation formula calculation condition definition step for defining a residual value calculation condition by
Residual value calculation 1 processing for calculating an average value, a standard deviation, and a score value based on vehicle sales extraction data by multiple regression analysis category and dummy variable performance data;
A popularity index calculation process for calculating a popularity index for each popularity index category for each multiple regression analysis category using the multiple regression analysis coefficient data calculated in the residual value calculation 1 process for vehicle sale extraction data;
A residual value calculation 2 process in which a variable obtained by adding a popularity index item to the scoring calculation variable item calculated in the residual value calculation 1 process is a calculation item variable;
A residual value calculation formula calculation step for calculating a residual value calculation formula according to vehicle sales extraction data, calculation variable item data, calculation category data defined in the residual value calculation formula calculation condition definition step,
A vehicle trade-in price providing method, wherein data in the residual value calculation related database used for the residual value calculation means is periodically updated.

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