Rental car price determination system

Abstract

The present invention relates to a rental car price determination system and, more specifically, to a rental car price determination system in which: a rental car use rate is predicted by analyzing a correlation between a use rate of rental cars and a reservation rate of accommodations in a tourist destination, and a rental car price is determined according to the predicted use rate, so that it is possible to determine a reasonable rental car price; and the rental car price is adjusted and provided in accordance with a rental car use state, a driving habit of a rental car reservation holder, a price change degree of nearby rental car companies, and whether a system-linked tourism product, etc. is purchased, so that the rationality of the rental car price can be increased.

Description

Rental car price determination system

[0001] The present invention relates to a rental car price determination system, and more particularly, to a rental car price determination system that analyzes the correlation between the reservation rate for accommodations in a tourist destination and the usage rate for rental cars to predict the rental car usage rate, and determines the rental car price according to the predicted usage rate, thereby enabling the determination of a reasonable rental car price, and that adjusts and provides the rental car price according to the rental car usage status, the driving habits of the rental car reservation holder, the degree of price changes at nearby rental car companies, and the purchase of tourism products linked to the system, thereby increasing the rationality of the rental car price.

[0002] In tourist destinations, rental cars are commonly used for the convenience of sightseeing, allowing people to rent cars for a certain period of time and then return them. In particular, rental cars are essential in islands like Jeju Island or tourist destinations with inconvenient public transportation.

[0003] However, since the prices of rental cars are set so differently by each company, tourists or consumers cannot recognize the appropriate price of rental cars. In addition, excessively high rental fees are set during peak season, and even in off-season, there are many cases where people are ripped off without receiving appropriate discounts.

[0004] Accordingly, a system for determining the price of a rental car has been applied for, as in the patent document below, but it only provides information on the basic standard price and a reasonable price determination is still not possible.

[0005] In addition, consumers' trust in rental car companies has significantly declined due to on-site requests for additional fees and poor management of rental cars. As a result, rental car users are flocking to large rental car companies, making it more difficult for small rental car companies to operate.

[0006] (Patent Document) Patent Publication No. 10-2015-0137979 (Published on December 9, 2015) "Rental Car Price Provision System"

[0007] The present invention has been devised to solve the above problems.

[0008] The purpose of the present invention is to provide a rental car price determination system that enables the determination of a reasonable rental car price by analyzing the correlation between the reservation rate for accommodations in a tourist destination and the rental car usage rate to predict the rental car usage rate and determining the rental car price based on the predicted usage rate.

[0009] The purpose of the present invention is to provide a rental car price determination system that can improve the accuracy of rental car usage rate analysis and prediction by reflecting weather information in the analysis of rental car usage rates and, with respect to accommodation reservation rates, using the reservation rates by grade of accommodations in the analysis of usage rates, excluding the reservation rates by group tours that are not related to rental car usage.

[0010] The purpose of the present invention is to provide a rental car price determination system that can increase the rationality of rental car prices by adjusting rental car prices according to the rental car usage status, the driving habits of the person making the rental car reservation, the degree of price changes at surrounding rental car companies, and whether or not to purchase tourism products linked to the system.

[0011] In order to achieve the above-mentioned purpose, the present invention is implemented by an embodiment having the following configuration.

[0012] According to one embodiment of the present invention, a rental car price determination system according to the present invention includes: a rental car that a user rents, uses, and returns for a certain period of time; a user terminal that searches for the rental car to select a rental car to use and receives information about the rental car; and an operation server that communicates with the user terminal to conclude a rental car use contract and manages information about the rental car; wherein the operation server analyzes a correlation between a reservation rate for accommodations in a tourist area and a rental car usage rate, predicts a rental car usage rate based on the analyzed correlation, and determines a rental car price based on the predicted usage rate.

[0013] According to another embodiment of the present invention, in the rental car price determination system according to the present invention, the operation server includes a usage rate analysis unit that analyzes the correlation between the reservation rate of an accommodation facility and the rental car usage rate, and a price determination unit that predicts the rental car usage rate according to the analysis result by the usage rate analysis unit and determines the rental price, and the usage rate analysis unit includes an accommodation information collection module that collects accommodation reservation information in a tourist area, a weather information collection module that collects weather information, a usage rate collection module that collects rental car usage rate information, a variable information input module that inputs variable information affecting the rental car usage rate, and a correlation learning module that analyzes the correlation between the input variables and the rental car usage rate, and the variable information input module includes a reservation rate input module by grade that inputs reservation rate information by grade of an accommodation facility, a group tour deduction module that deducts reservation information by group tour from the reservation rate of an accommodation facility, a temperature information input module that inputs temperature information of a tourist area, a rainfall input module that inputs rainfall information, a snowfall input module that inputs snowfall information, and a wind speed information. It is characterized in that it includes a wind speed input module, and the price determination unit includes a selection information receiving module that receives a user's rental car selection information, an accommodation reservation rate loading module that retrieves reservation rate information of an accommodation facility at the time of expected rental car use, a weather information loading module that retrieves weather information such as temperature, rainfall, snowfall, and wind speed, a correlation model input module that inputs the accommodation reservation rate and weather information into a correlation model derived by the correlation learning module to predict the rental car usage rate, a standard price setting module that sets a rental car rental price according to the predicted usage rate, and a price provision module that provides a rental price according to the set standard to the user.

[0014] According to another embodiment of the present invention, in the rental car price determination system according to the present invention, the operation server includes a vehicle condition reflection unit that reflects the condition of the vehicle in the rental car rental price, and the vehicle condition reflection unit is characterized in that it includes a usage information collection module that collects usage information of the rental car vehicle, a standard discount rate setting module that sets a discount rate of the rental price according to the rental car use period, a distance weight setting module that sets a weight according to the driving distance of the rental car vehicle, a repair information collection module that collects repair information of the rental car vehicle, a repair weight setting module that sets a weight according to the repair cost, a system weight setting module that sets a weight according to the type of repair part, a discount rate calculation module that calculates a discount rate by applying a distance weight, a repair weight, and a system weight to the standard discount rate set by the standard discount rate setting module, and a price adjustment module that adjusts the rental car rental price according to the calculated discount rate.

[0015] According to another embodiment of the present invention, in the rental car price determination system according to the present invention, the operation server includes a safe driving discount unit that reflects the user's driving habits in the rental car price, and the safe driving discount unit is characterized by including a driving information collection module that collects the user's driving information, a speeding index calculation module that calculates a speeding index according to the speeding time compared to the user's total driving time, a rapid acceleration index calculation module that calculates a rapid acceleration index according to the rapid acceleration time compared to the user's total driving time, a rapid deceleration index calculation module that calculates a rapid deceleration index according to the rapid deceleration time compared to the user's total driving time, a driving index calculation module that calculates a driving index for the user's driving habits by adding the speeding index, the rapid acceleration index, and the rapid deceleration index, and a discount rate determination module that determines a discount rate according to the calculated driving index.

[0016] According to another embodiment of the present invention, in the rental car price determination system according to the present invention, the operation server includes a vendor reflection unit that reflects a change in the rental price of rental car companies in a tourist area, and the vendor reflection unit is characterized by including a price information collection module that collects price information of rental car companies in a specific tourist area, a change rate calculation module that calculates a change rate of each company for the rental car rental price during a set period, an evaluation information collection module that collects evaluation information on each company, an evaluation information analysis module that analyzes the collected evaluation information, an evaluation index calculation module that calculates an evaluation index indicating a ratio of positive preference based on the analysis of the evaluation information, a price weight setting module that reflects the calculated evaluation index in the price change rate of each company, an average change rate calculation module that calculates an average value of the price change rate to which the evaluation index is reflected, and a price reflection module that reflects the calculated average change rate in the rental car price.

[0017] According to another embodiment of the present invention, in the rental car price determination system according to the present invention, the operation server includes a linked product discount section that provides a discount on the rental car price according to the purchase of a tourism-related product registered in the system, and the linked product discount section is characterized in that it includes a linked product registration module that registers information on accommodations, restaurants, tourist attractions, and tourism products of a specific tourist area that can be purchased in the system, a type-specific discount rate setting module that sets a discount rate for each type of tourism-related product, an average price calculation module that calculates an average price for each type of tourism-related product, a price index calculation module that calculates a price index according to a price ratio of the corresponding product to the average price for each type, and a discount rate adjustment module that adjusts the discount rate set by the type-specific discount rate setting module according to the calculated price index.

[0018] The present invention can obtain the following effects through the combination and use of the configuration described above and the following examples.

[0019] The present invention has the effect of enabling the determination of a reasonable rental car price by analyzing the correlation between the reservation rate for accommodations in a tourist destination and the rental car usage rate to predict the rental car usage rate and determining the rental car price based on the predicted usage rate.

[0020] The present invention has the effect of increasing the accuracy of rental car usage rate analysis and prediction by reflecting weather information in the analysis of rental car usage rates and, with respect to accommodation reservation rates, using the reservation rates by grade of accommodations in the analysis of usage rates, excluding the reservation rates by group tours that are not related to rental car usage.

[0021] The present invention has the effect of increasing the rationality of rental car prices by adjusting rental car prices based on the rental car usage status, the driving habits of the person making the rental car reservation, the degree of price changes at surrounding rental car companies, and the purchase of tourism products linked to the system.

[0022] Figure 1 is a configuration diagram of a rental car price determination system according to one embodiment of the present invention.

[0023] Figure 2 is a block diagram showing the configuration of the operating server.

[0024] Figure 3 is a block diagram showing the configuration of the usage rate analysis unit.

[0025] Figure 4 is a block diagram showing the configuration of a variable information input module.

[0026] Figure 5 is a block diagram showing the configuration of the price determination unit.

[0027] Figure 6 is a block diagram showing the configuration of the vehicle condition reflection unit.

[0028] Figure 7 is a block diagram showing the configuration of the safe driving discount department.

[0029] Figure 8 is a block diagram showing the configuration of the company reflection section.

[0030] Figure 9 is a block diagram showing the configuration of the linked product discount department.

[0031] * Explanation of symbols used in drawings

[0032] 100: Operation Server 1: Usage Analysis Department

[0033] 2: Pricing Department 3: Vehicle Condition Reflection Department

[0034] 4: Safe Driving Discount Department 5: Company Reflection Department

[0035] 6: Discount on related products 200: Rental car

[0036] 300: User terminal

[0037] Hereinafter, preferred embodiments of a rental car price determination system according to the present invention will be described in detail with reference to the attached drawings. In the following description of the present invention, if a detailed description of a known function or configuration is judged to unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted. Throughout the specification, when a part is said to "include" a certain component, this does not mean that other components are excluded, but rather that other components may be further included, unless specifically stated otherwise. In addition, terms such as "... part", "... module", etc. described in the specification mean a unit that processes at least one function or operation, and this may be implemented by hardware, software, or a combination of hardware and software.

[0038]

[0039] A rental car price determination system according to one embodiment of the present invention will be described with reference to FIGS. 1 to 9. The rental car price determination system includes: a rental car (200) that a user rents, uses, and returns for a certain period of time; a user terminal (300) that searches for the rental car (200) to select the rental car (200) to be used, and receives information about the rental car (200); and an operation server (100) that communicates with the user terminal (300) to enable a rental car (200) to be used and manages information about the rental car (200).

[0040] The above rental car price determination system relates to a system that automatically determines the rental car price, and allows rental car users to conclude usage contracts for rental cars (200) through an operation server (100), and to search for and select rental cars through a user terminal (300) connected to the operation server (100) via wired or wireless communication, and to conclude usage contracts. In particular, the system predicts rental car usage rates in a specific tourist area and determines rental car prices according to the predicted usage rates. To this end, the system analyzes and learns the correlation between the reservation rate of accommodations and rental car usage rates, and uses this to predict rental car usage rates. Accordingly, the user terminal (300) can be applied to various devices such as a smartphone, tablet, or PC capable of wired or wireless communication with the operation server (100), receives and displays rental car (200) information from the operation server (100), allows users to select a rental car (200) to use, and conclude usage contracts. It can also be provided with various information about rental cars (200).

[0041] The above-described operation server (100) communicates with a user terminal (300) via wired or wireless means, concludes a usage contract for a rental car (200), and manages and provides various information about the rental car (200), and in particular, determines the rental fee for the rental car (200). The operation server (100) utilizes the correlation between the reservation rate of an accommodation facility and the rental car usage rate to reasonably determine the rental fee for the rental car (200), and may reflect the rental car usage status, the driving habits of the rental car reservation holder, the degree of price changes at nearby rental car companies, and the purchase of tourism products linked to the system in the rental car rental fee. To this end, the operation server (100) may include a usage rate analysis unit (1), a price determination unit (2), a vehicle condition reflection unit (3), a safe driving discount unit (4), a company reflection unit (5), and a linked product discount unit (6).

[0042] The above-mentioned usage rate analysis unit (1) is configured to analyze the rental car usage rate, and can analyze the correlation between the reservation rate of tourist accommodations and the rental car usage rate using an artificial intelligence learning method using big data. The above-mentioned usage rate analysis unit (1) can reflect weather information that affects the rental car usage rate, and can analyze the correlation by rental car model. To this end, the above-mentioned usage rate analysis unit (1) can include an accommodation information collection module (11), a weather information collection module (12), a usage rate collection module (13), a variable information input module (14), and a correlation learning module (15).

[0043] The above accommodation information collection module (11) is configured to collect reservation information about accommodations in tourist areas, and can collect reservation information about accommodations in a specific tourist area where a rental car is rented from a reservation platform, etc.

[0044] The above weather information collection module (12) is configured to collect weather information at the time of rental car use, and can collect information such as temperature, rainfall, snowfall, and wind speed from the Korea Meteorological Administration, etc.

[0045] The above-mentioned usage rate collection module (13) is configured to collect information on rental car usage rates, and can be set to collect the ratio of the number of rental cars actually reserved and used to the total number of available rental cars as the usage rate. For example, the usage rate can be calculated and stored on a daily basis. At this time, the usage rate collection module (13) can be configured to collect usage rate information by classifying it by rental car vehicle type.

[0046] The above variable information input module (14) is configured to input variables that affect the rental car usage rate and analyze the correlation with the rental car usage rate, and may include a reservation rate input module by grade (141), a group tour discount module (142), a temperature information input module (143), a rainfall input module (144), a snowfall input module (145), and a wind speed input module (146).

[0047] The above-mentioned grade-based reservation rate input module (141) is configured to input the collected reservation rate information of accommodations by classifying them into different grades of accommodations. Since the usage of rental cars varies depending on the reservation grade of the accommodation, this is reflected in the correlation analysis. In other words, tourists who reserve low-grade accommodations are more likely to use public transportation rather than rental cars, and the higher the grade of accommodation used, the higher the grade of the rental car model. Therefore, this is reflected in the correlation analysis to increase the accuracy of the usage rate analysis.

[0048] The above group tour deduction module (142) is configured to deduct group tour reservation information from the information on the reservation rate of accommodation facilities. In the case of tourists reserving accommodation facilities through group tours, they are not related to the use of rental cars and use a separate vehicle chartered by the group, so they are excluded from the analysis of the rental car usage rate. At this time, the group tour deduction module (142) calculates the reservation rate by deducting the number of group tour reservations from the total number of accommodation facilities available for reservation at each accommodation facility.

[0049] The above temperature information input module (143), rainfall input module (144), snowfall input module (145), and wind speed input module (146) are configured to input temperature, rainfall, snowfall, and wind speed information as variables for usage rate analysis according to the collected weather information, thereby reflecting weather information that may affect rental car use in the usage rate analysis to increase the accuracy of the analysis.

[0050] The above correlation learning module (15) is configured to analyze the correlation between the variable input by the variable information input module (14) and the rental car usage rate, and derives a correlation model through artificial intelligence learning such as deep learning, machine learning, etc., such as an artificial neural network.

[0051] The above price determination unit (2) is configured to determine the rental car price, and the price is determined using the correlation model derived by the correlation learning module (15). More specifically, the price determination unit (2) predicts the rental car occupancy rate using the correlation model, and determines the price according to the predicted rental car occupancy rate. To this end, the price determination unit (2) may include a selection information receiving module (21), an accommodation reservation rate loading module (22), a weather information loading module (23), a correlation model input module (24), a standard price setting module (25), and a price provision module (26).

[0052] The above selection information receiving module (21) is configured to receive the user's rental car selection information, and can receive information on the type of rental car and the time of use.

[0053] The above-mentioned accommodation reservation rate loading module (22) is configured to retrieve reservation rate information regarding accommodation facilities at the time of rental car use, and can retrieve reservation rates regarding accommodation facilities in tourist areas where rental cars are rented from a reservation platform, etc. The above-mentioned accommodation reservation rate loading module (22) can calculate and retrieve reservation rates excluding reservation information due to group tours, and can retrieve reservation rate information classified by accommodation facility grade.

[0054] The above weather information loading module (23) is configured to retrieve weather information that affects the rental car usage rate, and can retrieve weather forecast information at the time of rental car usage. The above weather information loading module (23) can retrieve forecast information on temperature, rainfall, snowfall, and wind speed used in the usage rate analysis unit (1) from the Korea Meteorological Administration, etc.

[0055] The above correlation model input module (24) is configured to input variables for predicting rental car usage rate into the correlation model derived by the correlation learning module (15), and inputs information on reservation rates by grade of accommodations, temperature, rainfall, snowfall, and wind speed, after deducting reservation information for group tours, into the correlation model to predict rental car usage rate.

[0056] The above standard price setting module (25) is configured to set a standard price according to the rental car usage rate, and divides the rental car usage rate into multiple sections so that a standard price is set for each section.

[0057] The above price provision module (26) is configured to provide rental car rental price information to the user, and provides price information set according to the predicted rental car usage rate range.

[0058] The above vehicle condition reflection unit (3) is configured to reflect the vehicle condition in the rental car rental price, and can adjust the price by reflecting the rental car vehicle's usage period, mileage, and repair information. To this end, the vehicle condition reflection unit (3) may include a usage information collection module (31), a standard discount rate setting module (32), a distance weight setting module (33), a repair information collection module (34), a repair weight setting module (35), a system weight setting module (36), a discount rate calculation module (37), and a price adjustment module (38).

[0059] The above usage information collection module (31) is configured to collect usage information of a rental car vehicle, and can collect information such as usage period and driving distance.

[0060] The above standard discount rate setting module (32) is configured to set a discount rate for the rental price according to the period of use of the rental car vehicle, and a higher discount rate can be set as the period of use becomes longer.

[0061] The above distance weight setting module (33) is configured to set a weight according to the driving distance for the discount rate set by the standard discount rate setting module (32), and can divide the driving distance into multiple sections so that a higher weight is set as the driving distance becomes longer.

[0062] The above repair information collection module (34) is configured to collect repair information on rental cars, and can collect information on repair parts and repair costs.

[0063] The above repair weight setting module (35) is configured to set a weight according to repair costs, and can set a weight for a discount rate according to the accumulated repair costs for a specific rental car vehicle. The above repair weight setting module (35) can set a weight according to the repair cost amount range.

[0064] The above system weight setting module (36) is configured to set weights according to the type of repair parts, and can set weights for each repair part with respect to the weights set by the repair weight setting module (35). The above system weight setting module (36) can set higher weights for parts that have a greater impact on the function of the vehicle, such as the engine, transmission, and brakes.

[0065] The above discount rate calculation module (37) is configured to calculate a discount rate according to the condition of the rental car, and can calculate the discount rate by applying weights regarding mileage, repair costs, and repair parts to the discount rate according to the period of use set by the above standard discount rate setting module (32). Accordingly, the above discount rate calculation module (37) can calculate a higher discount rate as the period of use becomes longer, the mileage increases, and the repair costs are spent on important parts.

[0066] The above price adjustment module (38) is configured to adjust the rental car price according to the discount rate calculated by the discount rate calculation module (37), thereby enabling a reasonable price decision to be made by reflecting the vehicle's usage status in the rental price.

[0067] The above safe driving discount unit (4) is configured to reflect the user's driving habits in the rental car rental price, thereby providing a discount on the rental price to users who normally drive safely, thereby allowing the risk of damage to the rental car vehicle to be reflected in the rental price, and also helping to correct the users' driving habits. The above safe driving discount unit (44) may include a driving information collection module (41), a speeding index calculation module (42), a rapid acceleration index calculation module (43), a rapid deceleration index calculation module (44), a driving index calculation module (45), and a discount rate determination module (46).

[0068] The above driving information collection module (41) is configured to collect the user's driving information, and for example, can collect information such as driving route and driving speed collected through a navigation app, etc.

[0069] The above speeding index calculation module (42) is configured to calculate a speeding index indicating the degree of speeding of the user, and can calculate the ratio of speeding time to the total driving time of the user as the speeding index, and can calculate the ratio of speeding time based on the speed limit for each driving section.

[0070] The above-mentioned rapid acceleration index calculation module (43) is configured to calculate a rapid acceleration index indicating the degree of rapid acceleration of the user, and can calculate the ratio of rapid acceleration time to the total driving time of the user as a rapid acceleration index, and can set an acceleration that can be judged as rapid acceleration so that a comparison can be made.

[0071] The above-mentioned rapid deceleration index calculation module (44) is configured to calculate a rapid deceleration index indicating the degree of rapid deceleration of the user, and can calculate the ratio of rapid deceleration time to the total driving time of the user as a rapid deceleration index, and can set an acceleration that can be judged as rapid deceleration so that a comparison can be made.

[0072] The above driving index calculation module (45) is configured to calculate a driving index indicating the user's driving status, and can calculate the driving index by adding up the speeding index, rapid acceleration index, and rapid deceleration index. Therefore, a higher driving index indicates poor driving habits. In addition, rapid acceleration and rapid deceleration worsen the vehicle condition and increase the risk of accidents more than speeding, so weights can be assigned to the rapid acceleration index and rapid deceleration index to allow for the summation.

[0073] The above discount rate determination module (46) is configured to determine a discount rate based on the calculated driving index, such that a lower driving index provides a higher discount rate. The above discount rate determination module (46) can provide a discount on the rental car price when the driving index is below a certain value, and can divide the driving index into multiple sections when below a certain value and set a discount rate for each section.

[0074] The above-mentioned vendor reflection unit (5) is configured to reflect changes in rental prices of surrounding rental car companies, thereby allowing market trends to be reflected in the prices. In addition, the vendor reflection unit (5) can increase the utilization rate of rental cars by increasing the degree of reflection of price changes of companies with good reviews. To this end, the vendor reflection unit (5) may include a price information collection module (51), a change rate calculation module (52), an evaluation information collection module (53), an evaluation information analysis module (54), an evaluation index calculation module (55), a price weight setting module (56), an average change rate calculation module (57), and a price reflection module (58).

[0075] The above price information collection module (51) is configured to collect price information from surrounding rental car companies, and collects and stores price information from companies that rent out rental cars in tourist areas in real time.

[0076] The above change rate calculation module (52) is configured to calculate the degree of change in rental car prices, and calculates the change rate of rental car prices by company for each set period.

[0077] The above evaluation information collection module (53) is configured to collect evaluation information on rental car companies, and can collect review information on rental car companies online.

[0078] The above evaluation information analysis module (54) is configured to analyze the collected evaluation information, and can analyze the degree of preference for positive or negative information using techniques such as sentiment analysis.

[0079] The above evaluation index calculation module (55) is configured to calculate an evaluation index indicating the degree of evaluation for each rental car company, and can calculate the evaluation index based on the ratio of positive preference to the total collected evaluation information.

[0080] The above price weight setting module (56) is configured to set weights for price changes based on the evaluation index calculated for each company. Weights can be set based on the evaluation index, and a higher weight can be set for a higher evaluation index. Accordingly, the price changes of companies with higher evaluation indices can be more significantly reflected in the rental price.

[0081] The above average change rate calculation module (57) is configured to calculate the average change rate of rental prices of rental car companies, and can calculate the average value by applying the weight set by the price weight setting module (56) to the change rate for a set period of each company.

[0082] The above price reflection module (58) is configured to reflect the average value calculated by the average change rate calculation module (57) in the rental car price, thereby reflecting price changes according to market trends in determining the rental car price.

[0083] The above-mentioned linked product discount section (6) is configured to provide a discount on the rental car price according to the purchase of a tourism product linked to this system, thereby enabling the registration of tourism-related products such as accommodations, tourist destinations, tourism products, and restaurants through this system and enabling purchases thereof, thereby increasing the rental car utilization rate through linkage with tourism-related products and generating profits according to the registration of tourism products, and from the perspective of tourists, being able to purchase not only rental cars but also various tourism-related products through this system, thereby increasing the convenience of tourism. To this end, the above-mentioned linked product discount section (6) may include a linked product registration module (61), a type-specific discount rate setting module (62), an average price calculation module (63), a price index calculation module (64), and a discount rate adjustment module (65).

[0084] The above-mentioned linked product registration module (61) is configured to register tourism-related product information linked to the system, and can allow various tourism-related product information such as accommodation, tourist destinations, tourism products, and restaurants to be registered.

[0085] The above type-specific discount rate setting module (62) is configured to set a discount rate for each type of tourism-related product, and sets different discount rates depending on the type of tourism-related product, such as accommodation or tourist attraction.

[0086] The above average price calculation module (63) is configured to calculate the average price of tourism-related products by type, and calculates the average price for each type of tourism-related product.

[0087] The above price index calculation module (64) is configured to calculate a price index indicating the price level of a specific tourism-related product, and can calculate the price index based on the price ratio of the product to the average price of the types of tourism-related products.

[0088] The above discount rate adjustment module (65) adjusts the discount rate set by the type-specific discount rate setting module (62) based on a price index. The discount rate can be multiplied by the price index. Therefore, when purchasing higher-priced products within the same product category, a higher discount rate for rental cars can be offered.

[0089]

[0090] In the above, the applicant has described various embodiments of the present invention, but such embodiments are only examples of implementing the technical idea of ​​the present invention, and any change or modification that implements the technical idea of ​​the present invention should be interpreted as falling within the scope of the present invention.

Claims

1. A rental car that is rented, used, and returned by the user for a certain period of time; A user terminal that searches for the above rental cars, selects a rental car to use, and receives information about the rental car; It includes an operation server that communicates with the user terminal above to conclude a rental car use contract and manages information about the rental car; The above operating server is, A rental car price determination system characterized by analyzing the correlation between the reservation rate of accommodations in a tourist area and the rental car usage rate, predicting the rental car usage rate based on the analyzed correlation, and determining the rental car price based on the predicted usage rate.

2. In paragraph 1, the operating server It includes a usage rate analysis unit that analyzes the correlation between the reservation rate for accommodation and the rental car usage rate, and a price determination unit that predicts the rental car usage rate based on the analysis results by the usage rate analysis unit and determines the rental price. The above usage analysis section, It includes an accommodation information collection module that collects accommodation reservation information in tourist areas, a weather information collection module that collects weather information, a usage rate collection module that collects rental car usage rate information, a variable information input module that inputs variable information affecting rental car usage rate, and a correlation learning module that analyzes the correlation between the input variables and rental car usage rate. The above variable information input module is, It includes a grade-by-grade reservation rate input module for inputting reservation rate information by grade of the accommodation facility, a group tour deduction module for deducting reservation information by group tour from the reservation rate of the accommodation facility, a temperature information input module for inputting temperature information of the tourist area, a rainfall input module for inputting rainfall information, a snowfall input module for inputting snowfall information, and a wind speed input module for inputting wind speed information. The above price determination department, A rental car price determination system characterized by including a selection information receiving module for receiving a user's rental car selection information, an accommodation reservation rate loading module for loading reservation rate information of an accommodation facility at the time of expected rental car use, a weather information loading module for loading weather information such as temperature, rainfall, snowfall, and wind speed, a correlation model input module for predicting a rental car usage rate by inputting the accommodation reservation rate and weather information into a correlation model derived by the correlation learning module, a standard price setting module for setting a rental car price according to the predicted usage rate, and a price provision module for providing a rental price according to the set standard to the user.

3. In paragraph 1, the operating server Includes a vehicle condition reflection section that reflects the condition of the vehicle in the rental car rental price. The above vehicle condition reflection section is, A rental car price determination system characterized by including a usage information collection module that collects usage information of a rental car, a standard discount rate setting module that sets a discount rate for a rental price according to the usage period of the rental car, a distance weight setting module that sets a weight according to the driving distance of the rental car, a repair information collection module that collects repair information of the rental car, a repair weight setting module that sets a weight according to a repair cost, a system weight setting module that sets a weight according to the type of repair part, a discount rate calculation module that calculates a discount rate by applying a distance weight, a repair weight, and a system weight to a standard discount rate set by the standard discount rate setting module, and a price adjustment module that adjusts the rental car price according to the calculated discount rate.

4. In paragraph 1, the operating server Includes a safe driving discount that reflects the user's driving habits in the rental car rental price. The above safe driving discount is, A rental car price determination system characterized by including a driving information collection module that collects a user's driving information, a speeding index calculation module that calculates a speeding index according to speeding time compared to the user's total driving time, a rapid acceleration index calculation module that calculates a rapid acceleration index according to rapid acceleration time compared to the user's total driving time, a rapid deceleration index calculation module that calculates a rapid deceleration index according to rapid deceleration time compared to the user's total driving time, a driving index calculation module that calculates a driving index for the user's driving habits by adding up the speeding index, rapid acceleration index, and rapid deceleration index, and a discount rate determination module that determines a discount rate according to the calculated driving index.

5. In paragraph 1, the operating server Includes a company reflection section that reflects changes in rental prices of rental car companies in tourist areas. The above company reflection department is, A rental car price determination system characterized by including a price information collection module that collects price information of rental car companies in a specific tourist area, a change rate calculation module that calculates the change rate of each company for the rental car rental price over a set period, an evaluation information collection module that collects evaluation information on each company, an evaluation information analysis module that analyzes the collected evaluation information, an evaluation index calculation module that calculates an evaluation index indicating the ratio of positive preference based on the analysis of the evaluation information, a price weight setting module that reflects the calculated evaluation index in the price change rate of each company, an average change rate calculation module that calculates an average value of the price change rate to which the evaluation index is reflected, and a price reflection module that reflects the calculated average change rate in the rental car price.

6. In paragraph 1, the operating server Includes a discount section for related products that provides discounts on rental car prices based on the purchase of tourism-related products registered in the system. The above-mentioned discount on related products is A rental car price determination system characterized by including a linked product registration module that registers information on accommodations, restaurants, tourist attractions, and tourism products of a specific tourist area that can be purchased in the system, a type-specific discount rate setting module that sets a discount rate for each type of tourism-related product, an average price calculation module that calculates an average price for each type of tourism-related product, a price index calculation module that calculates a price index according to the price ratio of the corresponding product to the average price for each type, and a discount rate adjustment module that adjusts the discount rate set by the type-specific discount rate setting module according to the calculated price index.

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