Real estate simulation device, real estate simulation method, and real estate simulation program

Abstract

To provide a real estate simulation device, real estate simulation method and real estate simulation program which can easily and highly accurately create simulation data of new contract data.SOLUTION: A real estate simulation device according to the embodiment comprises prediction data creation means which acquires a floor, area and use from a zone master with property and zone of contract data of the target as a key, specifies a record of an assumed rent master with the property, zone, floor and use as a key, specifies a record of a contract rule master with an area, area scale and use of the specified record of the assumed rent master as a key, refers to the specified records of the assumed rent master and contract rule master, and creates new contract data being simulation data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a real estate simulation device, a real estate simulation method, and a real estate simulation program. [Background technology]

[0002] For example, a real estate company may simulate the income and expenditure of rent for a rental property. Conventionally, a system for simulating a rental property is disclosed in, for example, Patent Document 1. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-173957 Summary of the Invention [Problem to be solved by the invention]

[0004] However, Patent Document 1 does not disclose anything about creating simulation data of new contract data simply and with high accuracy.

[0005] The present invention has been made in consideration of the above, and aims to provide a real estate simulation device, a real estate simulation method, and a real estate simulation program that are capable of creating simulation data for new contract data easily and with high accuracy. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the object, there is provided a real estate simulation device having a control unit, wherein the control unit stores contract data including a contract number, a business partner, a property, a plot, a contract start date, a contract end date, a monthly rent, a rent start date, and a cancellation date; a plot master in which the property, floor, plot, area, and use are associated and registered; a contract rule master in which the property, area, area size, use, the number of months from cancellation to contract conclusion, the number of months from contract conclusion to delivery, and the number of months from delivery to rent invoice are associated and registered; and a contract rule master in which the property, floor, use, plot, area, area size, monthly rent per tsubo, and monthly rent per tsubo are associated and registered. and a forecast data creation means configured to be accessible to the estimated rent master in which the property and plot of the target contract data are registered in association with the value of the property and plot, which acquires the floor, area, and use from the plot master using the property, plot, floor, and use as keys, which identifies a record of the estimated rent master using the property, plot, floor, and use as keys, which identifies a record of the contract rule master using the area, area size, and use of the identified record of the estimated rent master, and which creates new contract data, which is simulation data, by referring to the identified records of the estimated rent master and contract rule master.

[0007] According to another aspect of the present invention, the forecast data creation means may create billing data including the rent for each month based on the created new contract data.

[0008] According to another aspect of the present invention, the forecast data creation means calculates the monthly rent for the new contract data by multiplying the acquired area by the monthly unit price per tsubo in the estimated rent master, and calculates the contract start date by adding the number of months from the cancellation date in the contract rule master to the contract conclusion, The rent due date may be calculated as the contract start date + the number of months from the conclusion of the contract in the contract rule master to delivery + the number of months from delivery to when the rent is billed.

[0009] In addition, according to one aspect of the present invention, the forecast data creation means may obtain the floor, area, and use from the section master using the property and section of the target contract data as keys, identify a record in the estimated rent master using the property, section, floor, and use as keys, and create updated contract data, which is simulation data, by referring to the identified record in the estimated rent master.

[0010] According to another aspect of the present invention, the forecast data creation means may create billing data including the rent for each month based on the created renewal contract data.

[0011] According to another aspect of the present invention, the forecast data creation means may calculate the monthly rent for the updated contract data by multiplying the acquired area by the monthly price per tsubo in the estimated rent master.

[0012] In order to solve the above-mentioned problems and achieve the object, the present invention provides a real estate simulation method executed by an information processing device having a control unit, wherein the control unit executes a real estate simulation method by using a control unit to execute a real estate simulation method. The real estate simulation method executes a real estate simulation method by using a control unit to execute a real estate simulation method. The real estate simulation method executes a real estate simulation method by using a control unit. The real estate simulation method executes a real estate simulation method by using a control unit. The real estate simulation method executes a real estate simulation method by using a control unit. The real estate simulation method executes a real estate simulation method by using a control unit. and a forecast data creation process that is executed by the control unit to obtain the floor, area, and use from the section master using the property and section of the target contract data as keys, identify a record of the estimated rent master using the property, section, floor, and use as keys, identify a record of the contract rule master using the area, area size, and use of the identified record of the estimated rent master as keys, and create new contract data that is simulation data by referring to the identified records of the estimated rent master and contract rule master.

[0013] In order to solve the above-mentioned problems and achieve the object, the present invention provides a real estate simulation program to be executed by an information processing device having a control unit, the control unit including: a plot master in which contract data including a contract number, a business partner, a property, a plot, a contract start date, a contract end date, a monthly rent, a rent start date, and a cancellation date are associated and registered with a property, floor, plot, area, and use; a contract rule master in which the property, area, area size, use, the number of months from cancellation to contract conclusion, the number of months from contract conclusion to delivery, and the number of months from delivery to rent invoice are associated and registered; and a contract rule master in which the property, floor, use, plot, area, area size, and monthly rent per tsubo are associated and registered. and an estimated rent master registered in association with the property and plot of the target contract data, and the control unit is configured to execute a forecast data creation process in which the control unit acquires the floor, area, and use from the plot master using the property, plot, floor, and use as keys to identify a record of the estimated rent master, identifies a record of the contract rule master using the area, area size, and use of the identified record of the estimated rent master as keys, and creates new contract data, which is simulation data, by referring to the identified records of the estimated rent master and contract rule master. [Effects of the Invention]

[0014] According to the present invention, by automatically generating simulation data of new contract data, it is possible to easily and highly accurately create simulation data of new contract data. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a diagram for explaining examples of three patterns of debit methods: cumulative billing, single-month billing, and single-month multiple billing. [Figure 2] FIG. 2 is a diagram illustrating an example of the configuration of the supplier master. [Figure 3] FIG. 3 is a diagram illustrating an example of the configuration of the property master. [Figure 4] FIG. 4 is a diagram illustrating an example of the configuration of the floor master. [Figure 5] FIG. 5 is a diagram illustrating an example of the configuration of a section master. [Figure 6] FIG. 6 is a diagram illustrating an example of the configuration of the rental contract master. [Figure 7] FIG. 7 is a diagram illustrating an example of the configuration of the contract rule master. [Figure 8] FIG. 8 is a diagram illustrating an example of the configuration of the estimated rent master. [Figure 9] FIG. 9 is a diagram showing an example of the configuration of billing data. [Figure 10] FIG. 10 is a flowchart illustrating an outline of the overall processing of the control unit of the information processing device according to this embodiment. [Figure 11] FIG. 11 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to the present embodiment. [Figure 12] FIG. 12 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to the present embodiment. [Figure 13] FIG. 13 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to the present embodiment. [Figure 14] FIG. 14 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to the present embodiment. [Figure 15] FIG. 15 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to this embodiment. [Figure 16] FIG. 16 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to this embodiment. [Figure 17] FIG. 17 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to this embodiment. [Figure 18] FIG. 18 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to this embodiment. [Figure 19] FIG. 19 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to the present embodiment. [Figure 20] FIG. 20 is a diagram for explaining a specific example of processing by the control unit of the information processing device according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0016] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to the embodiment.

[0017] [1. Overview] For example, major real estate companies sometimes create income and expenditure simulations for rental properties, but without any established company rules, simulations are often performed based on the experience and intuition of each individual employee, preventing the creation of unified simulation data across the company. Furthermore, conducting simulations while referencing actual contract data is time-consuming, and there are often large discrepancies between the simulation results and actual results. As a result, not only the company's own forecasts but also the forecast income and expenditure figures reported to owners by the AM company often deviate from reality.

[0018] In this embodiment, although each person in charge has their own rules of thumb, if the company's rules and market evaluations can be made into a master and contract change predictions can be made, it is possible to carry out more precise simulations in a shorter period of time.

[0019] More specifically, in this embodiment, simulation data for new contract data is automatically generated based on contract data based on actual performance, for example, by referencing a contract rule master that specifies in-house rules for contracts by size and use, or an estimated rent master that reflects market evaluation, thereby making it possible to create simulation data for new contract data easily and with high accuracy.

[0020] The real estate simulation device of this embodiment is widely applicable to the real estate management industry (including companies that own their own properties, PM companies, etc.).

[0021] [2. Configuration] Fig. 1 is a block diagram showing an example of the configuration of a real estate simulation device 100 according to this embodiment. In Fig. 1, the real estate simulation device 100 includes a control unit 102, a communication interface unit 104, a storage unit 106, and an input / output interface unit 108. The units included in the real estate simulation device 100 are connected to each other so that they can communicate with each other via any communication path.

[0022] The communication interface unit 104 communicably connects the real estate simulation device 100 to the network 300 via a communication device such as a router and a wired or wireless communication line such as a dedicated line. The communication interface unit 104 has a function of communicating data with other devices via the communication line. Here, the network 300 has a function of connecting the real estate simulation device 100 to the server 200 and the bank system 400 so that they can communicate with each other, and is, for example, the Internet or a LAN (Local Area Network).

[0023] An input device 112 and an output device 114 are connected to the input / output interface unit 108. The output device 114 may be a monitor (including a home television), a speaker, or a printer. The input device 112 may be a keyboard, a mouse, a microphone, or a monitor that functions as a pointing device in cooperation with a mouse. Note that hereinafter, the output device 114 may be referred to as the monitor 114.

[0024] Various databases, tables, files, etc. are stored in the storage unit 106. Computer programs that work in conjunction with an OS (Operating System) to issue commands to a CPU (Central Processing Unit) to perform various processes are recorded in the storage unit 106. The storage unit 106 can be, for example, a memory device such as a RAM (Random Access Memory) or a ROM (Read Only Memory), a fixed disk device such as a hard disk, a flexible disk, an optical disk, etc.

[0025] The storage unit 106 includes a business partner master 106a, a property master 106b, a floor master 106c, a section master 106d, a rental contract master 106e, a contract rule master 106f, an estimated rent master 106g, and a data table 106h. Figure 2 shows an example of the configuration of the business partner master 106a. Figure 3 shows an example of the configuration of the property master 106b. Figure 4 shows an example of the configuration of the floor master 106c. Figure 5 shows an example of the configuration of the section master 106d. Figure 6 shows an example of the configuration of the rental contract master 106e. Figure 7 shows an example of the configuration of the contract rule master 106f. Figure 8 shows an example of the configuration of the estimated rent master 106g. Figure 9 shows an example of the configuration of billing data in the data table 106h. In the following description, all monetary amounts are expressed in yen, and the yen notation may be omitted.

[0026] The supplier master 106a is a master for storing information on suppliers (tenants, vendors, etc.). The supplier master 106a can be configured, for example, as shown in Fig. 2, as a table in which supplier CDs and supplier names are registered in association with each other. In the example shown in the figure, the first row contains supplier CD "10000001" and supplier name "Tenant A."

[0027] The property master 106b is a master for storing property information. For example, the property master 106b can be configured as a table in which property CDs and property names are associated and registered, as shown in Fig. 3. In the example shown in the figure, the first line contains the property CD "00000001" and the property name "Kyobashi Building."

[0028] The floor master 106c is a master for storing information about floors. For example, as shown in Fig. 4, the floor master 106c can be configured as a table in which property CDs, property names, floor CDs, and floor names are registered in association with each other. In the example shown in the figure, the first line contains property CD "00000001", property name "Kyobashi Building", floor CD "A", and floor name "1st Floor".

[0029] The partition master 106d is a master for storing information about partitions. For example, as shown in Fig. 5, the partition master 106d can be configured as a table in which property CD, property name, floor CD, partition CD, partition name, area, and use are registered in association with each other. In the example shown in the same figure, the first line contains property CD "00000001", property name "Kyobashi Building", floor CD "A", partition CD "1F-1", partition name "1st floor-1", area "100 tsubo", and use "office".

[0030] The rental contract master 106e is a master for holding contract data with tenants. Billing data is created based on the rental contract master 106e. When a contract is renewed or canceled, the rental contract master 106e increases the contract history number and stores the data. For example, as shown in Figure 6, the rental contract master 106e can be configured as a table or the like that registers contract data including the contract number, business partner CD, business partner name, property CD, property name, section CD, section name, contract history number, contract start date, contract end date, billing item, monthly amount, rent start date, and cancellation date.

[0031] In the example shown in the figure, the first line contains the contract number "A0000001," customer CD "10000001," customer name "Tenant A," property CD "00000001," property name "Kyobashi Building," section CD "1F-1," section name "1st floor-1," contract history number "1," contract start date "2021 / 6 / 1," contract end date "2022 / 5 / 31," invoice item "Rent," monthly amount "50,000," and rent due date "2021 / 6 / 1."

[0032] The contract rule master 106f is a master that defines the in-house rules for contracts by size, purpose, etc. As shown in Fig. 7, the contract rule master 106f can be configured with a table or the like that associates and registers the property CD, area, area size, purpose, cancellation-contract, contract-delivery, and delivery-rent.

[0033] "Area" is the area that manages the region to which the property belongs, and is classified, for example, as the Kanto area, Kansai area, Kyushu area, Chubu area, Tohoku area, etc. "Area size" is used to manage the size of the property, and is classified, for example, as large, medium, small, etc., based on the total floor area of ​​the building. "Use" is used to manage the main use of the property, and is classified, for example, as office, commercial, hotel, complex facility, etc. "Cancellation-contract" is the number of months from cancellation to contract conclusion. "Contract-delivery" is the number of months from contract conclusion to delivery. "Delivery-rent" is the number of months from delivery to when rent is charged.

[0034] In the example shown in the figure, the first line has the property CD "00000001", area "Kanto area", area size "medium", use "office", termination-contract "2.0", contract-delivery "1.0", and delivery-rental "1.0".

[0035] The expected rent master 106g is a master that specifies rents that reflect market valuation. For example, as shown in Figure 8, the expected rent master 106g can be configured as a table that associates and registers the property CD, floor CD, use, section CD, area, area size, one monthly item, monthly unit price for 1 tsubo, one monthly occurrence date, two monthly items, monthly unit price for 2 tsubo, and two monthly occurrence dates. The expected rent master 106g is updated with the latest information every time the market valuation changes.

[0036] In the example shown in the figure, the first line is the property "CD00000001", floor CD "A", use "office", section CD "1F-1", area "Kanto area", area size "medium", monthly item 1 "rent", monthly unit price per 1 tsubo "170", monthly 1 occurrence date "0: rent occurrence date", monthly item 2 "common area fee", monthly unit price per 2 tsubo "30", monthly 2 occurrence date "0: rent occurrence date".

[0037] The data table 106h is a file for storing various data such as billing data. The billing data is created based on the contract data. As shown in Figure 9(A), the billing data may include the contract number, contract history number, client CD, property CD, relevant month, billing item, and amount. In the example shown in the figure, the first line contains the contract number "A0000001," the contract history number "1," the client CD "10000001," the property CD "00000001," the relevant month "2021 / 6," the billing item "rent," and the amount "50,000." Figure 9(B) is a diagram showing the monthly income and expenditure (revenue) of the billing data. The monthly income and expenditure of the billing data can be confirmed on an income and expenditure confirmation screen (not shown).

[0038] 1, the control unit 102 is a CPU or the like that performs overall control of the real estate simulation device 100. The control unit 102 has an internal memory for storing control programs such as an OS, programs that define various processing procedures, required data, etc., and executes various information processing operations based on these stored programs.

[0039] The control unit 102 is configured to be able to access the business partner master 106a, property master 106b, floor master 106c, section master 106d, rental contract master 106e, contract rule master 106f, estimated rent master 106g, data table 106h, and the like, which are stored in the memory unit 106. Note that the business partner master 106a, property master 106b, floor master 106c, section master 106d, rental contract master 106e, contract rule master 106f, estimated rent master 106g, and data table 106h may be provided in another location (for example, server 200) as long as the control unit 102 is able to access them.

[0040] The control unit 102 conceptually includes a registration unit 102a, a simulation formulation environment creating unit 102b, a prediction data creating unit (simulation unit) 102c, and a screen display control unit 102d.

[0041] The registration unit 102a performs settings such as data input, addition, change, and update for the business partner master 106a, property master 106b, floor master 106c, section master 106d, rental contract master 106e, contract rule master 106f, and estimated rent master 106g in response to operator operations on a master maintenance screen (not shown).The registration unit 102a also creates billing data based on the contract data in the rental contract master 106e and stores it in a data table 106h.

[0042] When executing a simulation, the simulation formulation environment creation unit 102b imports billing data from the customer master 106a, property master 106b, floor master 106c, section master 106d, rental contract master 106e, and data table 106h, as well as the contract rule master 106f and estimated rent master 106g, to provide a simulation formulation environment.

[0043] The forecast data creation unit 102c obtains the floor, area, and use from the section master 106d using the property and section of the target contract data in the rental contract master 106e as keys, identifies a record in the estimated rent master 106g using the property, section, floor, and use as keys, identifies a record in the contract rule master 106f using the area, area size, and use of the identified record in the estimated rent master 106g as keys, and creates new contract data, which is simulation data, by referring to the identified records in the estimated rent master 106g and the contract rule master 106f.

[0044] Furthermore, the forecast data creating unit 102c may create billing data including the rent for each month based on the created new contract data.

[0045] In addition, for new contract data, the forecast data creation unit 102c may calculate the monthly rent by multiplying the acquired area by the monthly unit price per tsubo in the estimated rent master 106g, the contract start date by the cancellation date + the number of months from the cancellation in the contract rule master 106f to the contract conclusion, and the rent due date by the contract start date + the number of months from the contract conclusion in the contract rule master 106f to delivery + the number of months from delivery to the time rent is billed.

[0046] The forecast data creation unit 102c obtains the floor, area, and use from the section master 106d using the property and section of the target contract data in the rental contract master 106e as keys, identifies a record in the estimated rent master 106g using the property, section, floor, and use as keys, and creates updated contract data, which is simulation data, by referring to the identified record in the estimated rent master 106g.

[0047] The forecast data creating unit 102c may create billing data including the rent for each month based on the created updated contract data.

[0048] The forecast data creating unit 102c may calculate the monthly rent for the renewal contract data by multiplying the acquired area by the monthly unit price per tsubo in the estimated rent master 106g.

[0049] The screen display control unit 102d controls the display of various screens (for example, a master maintenance screen, a simulation environment planning screen, a prediction data creation screen, etc.) displayed on the monitor 114 and the reception of inputs.

[0050] [3. Specific Examples] A specific example of the processing performed by the control unit 102 of the real estate simulation device 100 according to this embodiment will be described with reference to FIGS.

[0051] (3-1. Overall processing) FIG. 10 is a flowchart for explaining an outline of the overall processing of the control unit 102 of the real estate simulation apparatus 100 according to this embodiment.

[0052] An overview of the overall processing of the control unit 102 of the real estate simulation device 100 in this embodiment will be described with reference to Fig. 10. In Fig. 10, the registration unit 102a executes registration processing for the performance environment (step S1). Specifically, in the registration processing, the registration unit 102a registers a business partner and sets data in the business partner master 106a in response to operations by an operator on a master maintenance screen (not shown).

[0053] The registration unit 102a also performs property registration and sets data in the property master 106b, floor master 106c, and section master 106d in response to an operator's operation on a master maintenance screen (not shown).

[0054] In addition, the registration unit 102a registers rental contracts, sets contract data in the rental contract master 106e in accordance with the operator's operations on a master maintenance screen (not shown), and creates billing data based on the contract data and stores it in a data table 106h.

[0055] The registration unit 102a also performs contract rule master maintenance and sets data in the contract rule master 106f in response to an operator's operation on a master maintenance screen (not shown).

[0056] The registration unit 102a also performs rental contract master maintenance and sets data in the estimated rent master 106g in response to an operator's operation on a master maintenance screen (not shown).

[0057] The simulation development environment creating unit 102b executes a simulation development environment creating process (step S2). Specifically, in the simulation development environment creating process, when executing a simulation, the simulation development environment creating unit 102b imports billing data from the business partner master 106a, property master 106b, floor master 106c, section master 106d, rental contract master 106e, and data table 106h, as well as the contract rule master 106f and estimated rent master 106g, and expands (copies) them into the work area of ​​the storage unit 106 to create a simulation environment.

[0058] If the contract rule master 106f and the estimated rent master 106g need to be changed, they can be changed in the simulation environment.

[0059] The forecast data creation unit 102c executes a forecast data creation process (step S3) to create new or renewed contract data (also called "simulation data" or "forecast data") based on the contract rule master 106f and the estimated rent master 106g, and creates billing data (also called "simulation data" or "forecast data") including monthly rent based on the new or renewed contract data.

[0060] Specifically, in the forecast data creation process, the forecast data creation unit 102c obtains the floor, area, and use from the section master 106d using the property and section of the target contract data in the rental contract master 106e as keys, identifies a record in the estimated rent master 106g using the property, section, floor, and use as keys, identifies a record in the contract rule master 106f using the area, area size, and use of the identified record in the estimated rent master 106g as keys, and creates new contract data, which is simulation data, by referring to the identified records in the estimated rent master 106g and contract rule master 106f.

[0061] Furthermore, the forecast data creating unit 102c may create billing data including the rent for each month based on the created new contract data.

[0062] In addition, for new contract data, the forecast data creation unit 102c may calculate the monthly rent by multiplying the acquired area by the monthly unit price per tsubo in the estimated rent master 106g, the contract start date by the cancellation date + the number of months from the cancellation in the contract rule master 106f to the contract conclusion, and the rent due date by the contract start date + the number of months from the contract conclusion in the contract rule master 106f to delivery + the number of months from delivery to the time rent is billed.

[0063] In addition, the forecast data creation unit 102c obtains the floor, area, and use from the section master 106d using the property and section of the target contract data in the rental contract master 106e as keys, identifies a record in the estimated rent master 106g using the property, section, floor, and use as keys, and creates updated contract data, which is simulation data, by referring to the identified record in the estimated rent master 106g.

[0064] Furthermore, the forecast data creating unit 102c may create billing data including the rent for each month based on the created updated contract data.

[0065] Furthermore, the forecast data creating unit 102c may calculate the monthly rent for the renewal contract data by multiplying the acquired area by the monthly price per tsubo in the estimated rent master 106g.

[0066] (3-2. Sample data) 2 to 9 and 11 to 20 are diagrams for explaining a specific example of the processing by the control unit 102 of the real estate simulation device 100 in this embodiment. A specific example of the processing by the control unit 102 of the real estate simulation device 100 in this embodiment will be explained with reference to the above Figs. 2 to 9 and 11 to 20.

[0067] 11 is a diagram showing a screen image of the simulation development environment creation screen. The simulation development environment creation screen has a field for specifying the target fiscal year and an execute button (not shown). When the operator specifies the fiscal year on the simulation development environment creation screen and presses the execute button (not shown), the forecast data creation unit 102c imports the master and data of the actual environment (customer master 106a, property master 106b, floor master 106c, section master 106d, rental contract master 106e, billing data in data table 106h, contract rule master 106f, and estimated rent master 106g) and copies them all at once to the work area (simulation environment) of the storage unit 106.

[0068] FIG. 12 is a diagram showing an example of the forecast data creation screen. The forecast data creation screen has a field for specifying the target fiscal year, a field for specifying the simulation period, and an execute button (not shown). The fiscal year is automatically set to the year specified on the simulation development environment creation screen. When the operator specifies the simulation period on the forecast data creation screen and presses the execute button (not shown), the forecast data creation unit (simulation unit) 102c creates forecast data (simulation data) for new and updated contract data for the specified simulation period based on the contract rule master 106f and the estimated rent master 106g for the contract data in the rental contract master 106e. The simulation period is specified to limit the period for processing load reasons.

[0069] (Logic for automatically creating new contract data) The logic for automatically creating new contract data will be described with reference to FIGS. 13 to 16. FIG. 13 is a diagram showing a detailed processing flow of the process for creating new contract data executed by the forecast data creation unit 102c. In FIG. 13, the floor CD, area, and use are acquired from the section master 106d using the property CD and section CD of the target contract data in the rental contract master 106e as keys (step S11). A record in the estimated rent master 106g is identified using the property CD, section CD, floor CD, and use as keys (step S12). A record in the contract rule master 106f is identified using the area, area size, and use of the identified record in the estimated rent master 106g as keys (step S13). New contract data, which is simulation data, is created by referring to the identified records in the estimated rent master 106g and the contract rule master 106f (step S14).

[0070] In this case, the monthly rent is calculated by multiplying the acquired area by the monthly price per tsubo in the estimated rent master 106g, the contract start date is calculated by adding the cancellation date plus the number of months from the cancellation in the contract rule master 106f until the contract is concluded, and the rent due date is calculated by adding the contract start date plus the number of months from the contract conclusion in the contract rule master 106f until delivery plus the number of months from delivery until the rent is billed.

[0071] Based on the created new contract data, billing data including the rent for each month is created (step S15).

[0072] Figure 14(A) shows an example of contract data that is the target of the rental contract master 106e in Figure 6. In the example shown in the figure, the contract number is "A0000002," the client CD is "10000002," the client name is "Tenant B," the property CD is "00000002," the property name is "Ginza Building," the section CD is "1F-2," the section name is "1F-2," the contract history number is "1," the contract start date is "2021 / 7 / 1," the contract end date is "2022 / 6 / 30," the billing item is "Rent," the monthly amount is "90,000," and the rent start date is "2021 / 7 / 1."

[0073] Figure 14(B) shows an example of billing data created based on the above contract data (data copied from the actual environment). The rent amounts for each month from the contract start date "2021 / 7 / 1" to the contract end date "2022 / 6 / 30" are listed.

[0074] 14(C) is a diagram showing the balance of the billing data. The balance can only be predicted up to the cancellation month.

[0075] Using the property CD "00000002" and section CD "1F-2" of the contract data as keys, the floor CD "A", area "500 tsubo" and use "office building" are obtained from the section master 106d of Figure 5, and using the property "00000002", section CD "1F-2", floor CD "A" and use "office" as keys, a record of the estimated rent master 106g of Figure 8 is identified, and using the area, area size and use of the identified record of the estimated rent master 106g as keys, a record of the contract rule master 106f is identified.

[0076] Fig. 15(A) is a diagram showing the identified record of the contract rule master 106f, and Fig. 15(B) is a diagram showing the identified record of the estimated rent master 106g.

[0077] Since the contract cancellation date in the contract data is "5 / 31 / 2022," referring to the contract rule master 106f, the cancellation-contract is "3.0," so the contract start date will be three months later, "9 / 1 / 2022." The contract end date is determined to be the same as the contract period of the contract being canceled (one year in this example), so it will be "8 / 31 / 2023." Furthermore, since "contract-delivery" is "1.5," the rent generation date is +1.5 months until delivery, and since "delivery-rent" is "1.5," it is +1.5 months from delivery until rent is generated, which is three months later, so it will be "12 / 1 / 2022."

[0078] Regarding the rent amount, the area of ​​the contract data obtained from the area master 106d is "500 tsubo", so when referring to the estimated rent master 106g, the monthly rent per tsubo is "200", so the rent amount is 500 x 200 = 100,000.

[0079] Figure 15(C) shows an example of new contract data automatically created in the simulation environment. The example shown in the figure includes the following: contract number "A9000001," client CD "90000001," client name "dummy tenant," property CD "00000002," property name "Ginza Building," section CD "1F-2," section name "1F-2," contract history number "1," contract start date "9 / 1 / 2022," contract end date "8 / 31 / 2023," billing item "rent," monthly amount "100,000," and rent due date "12 / 1 / 2022." The rent has been increased from "90,000" to "100,000."

[0080] Figure 16(A) shows an example of billing data created based on the new contract data. Figure 16(B) shows the monthly balance of the billing data, which is written below the original contract data. The monthly balance of the billing data can be checked on a balance confirmation screen (not shown).

[0081] (Automatic contract data update and creation logic) The automatic contract data update creation logic will be described with reference to Figures 17 to 20. Figure 17 is a diagram showing a detailed flow of the process of creating updated contract data executed by the forecast data creation unit 102c. In Figure 17, the floor CD, area, and purpose are obtained from the section master 106d using the property CD and section CD of the target contract data in the rental contract master 106e as keys (step S21). A record in the estimated rent master 106g is identified using the property CD, section CD, floor CD, and purpose as keys (step S22). The identified record in the estimated rent master 106g is referenced to create updated contract data, which is simulation data (step S23).

[0082] In this case, the monthly rent may be calculated by multiplying the acquired area by the monthly price per tsubo in the estimated rent master 106g.

[0083] Based on the created contract renewal data, billing data including the rent for each month is created (step S24).

[0084] Figure 18(A) shows an example of contract data that is the target of the rental contract master 106e in Figure 6. In the example shown in the figure, the contract number is "A0000003," the client CD is "10000003," the client name is "Tenant C," the property CD is "00000003," the property name is "Shinbashi Building," the section CD is "1F-1," the section name is "1F-1," the contract history number is "1," the contract start date is "2021 / 6 / 1," the contract end date is "2022 / 5 / 31," the billing item is "Rent," the monthly amount is "165,000," and the rent start date is "2021 / 6 / 1."

[0085] Figure 18(B) shows an example of billing data created based on the above contract data (data copied from the actual environment). The rent amounts for each month from the contract start date "2021 / 6 / 1" to the contract end date "2022 / 5 / 31" are listed.

[0086] 18(C) is a diagram showing the monthly income and expenditure of the billing data. The income and expenditure can only be predicted up to the end of the contract.

[0087] Using the property CD "00000003" and section CD "1F-1" of the contract data as keys, the floor CD "A", area "800 tsubo" and use "office building" are obtained from the section master 106d of Figure 5, and also using the property "00000003", section CD "1F-1", floor CD "A" and use "office" as keys, the record of the estimated rent master 106g of Figure 8 is identified.

[0088] FIG. 19A is a diagram showing the identified record of the estimated rent master 106g.

[0089] As the contract end date in the contract data is "5 / 31 / 2022", the "contract start date" of the updated contract will be +1 day, "6 / 1 / 2022". The "rent start date" will also be "6 / 1 / 2022". The "contract end date" will be determined to be the same as the contract period in the contract data (1 year in this example), so it will be "5 / 31 / 2023". As for the "rent amount", the area in the contract data is "800 tsubo", so when referring to the estimated rent master 106g, the monthly price per tsubo is "220", so 800 x 220 = 176,000.

[0090] Figure 19(B) shows an example of updated contract data automatically generated in the simulation environment. The second line in the figure shows an example of updated data, including the contract number "A0000003," client CD "10000003," client name "Tenant C," property CD "00000003," property name "Shinbashi Building," section CD "1F-1," section name "1F-1," contract history number "2," contract start date "6 / 1 / 2022," contract end date "5 / 31 / 2023," billing item "Rent," monthly amount "176,000," and rent due date "6 / 1 / 2022." The rent has been increased from "165,000" to "176,000."

[0091] Figure 20(A) shows an example of billing data created based on the update data of the contract data. Figure 20(B) shows the monthly balance of the billing data. The monthly balance of the billing data can be confirmed on a balance confirmation screen (not shown).

[0092] As described above, according to this embodiment, the rental contract master 106e registers contract data including the contract number, business partner, property, plot, contract start date, contract end date, monthly rent, rent start date, and cancellation date; the plot master 106d registers property, floor, plot, area, and use in association with each other; the contract rule master 106f registers property, area, area size, use, number of months from contract termination to contract conclusion, number of months from contract conclusion to delivery, and number of months from delivery to rent invoice in association with each other; and the estimated rent master 106f registers property, floor, use, plot, area, area size, and monthly rent per tsubo in association with each other. 06g, and a forecast data creation unit 102c that acquires the floor, area, and use from the section master using the property and section of the target contract data as keys, identifies the record of the estimated rent master using the property, section, floor, and use as keys, identifies the record of the contract rule master using the area, area size, and use of the identified record of the estimated rent master as keys, and creates new contract data that is simulation data by referring to the identified records of the estimated rent master and contract rule master, thereby making it possible to create simulation data for new contract data easily and with high accuracy.

[0093] [4. Contribution to the United Nations-led Sustainable Development Goals (SDGs)] This embodiment can contribute to improving business efficiency and promoting appropriate management decisions by companies, thereby contributing to the achievement of SDGs Goals 8 and 9.

[0094] Furthermore, this embodiment can contribute to reducing waste and promoting paperless and electronic systems, thereby contributing to the achievement of SDGs Goals 12, 13, and 15.

[0095] Furthermore, this embodiment can contribute to strengthening control and governance, which can contribute to the achievement of Goal 16 of the SDGs.

[0096] 5. Other Embodiments The present invention may be implemented in various different embodiments other than those described above within the scope of the technical concept set forth in the claims.

[0097] For example, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods.

[0098] Furthermore, the processing procedures, control procedures, specific names, information including parameters such as registered data and search conditions for each process, screen examples, and database configurations shown in this specification and drawings can be changed as desired unless otherwise specified.

[0099] Furthermore, with regard to the real estate simulation device 100, the components shown in the figures are functional concepts, and do not necessarily have to be physically configured as shown in the figures.

[0100] For example, all or any part of the processing functions of the real estate simulation device 100, particularly the processing functions performed by the control unit, may be implemented by a CPU and a program interpreted and executed by the CPU, or may be implemented as hardware using wired logic. The program is recorded on a non-transitory, computer-readable recording medium containing programmed instructions for causing the information processing device to execute the processes described in this embodiment, and is mechanically read by the real estate simulation device 100 as needed. That is, a computer program for providing instructions to the CPU in cooperation with the OS and performing various processes is recorded in a storage unit such as a ROM or HDD (Hard Disk Drive). This computer program is executed by being loaded into RAM, and cooperates with the CPU to form the control unit.

[0101] This computer program may also be stored in an application program server connected to the real estate simulation device 100 via any network, and all or part of it may be downloaded as needed.

[0102] Furthermore, the program for executing the processes described in this embodiment may be stored in a non-transitory computer-readable recording medium or configured as a program product. Here, the term "recording medium" includes any "portable physical medium" such as a memory card, a Universal Serial Bus (USB) memory, a Secure Digital (SD) card, a flexible disk, a magneto-optical disk, a ROM, an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable and Programmable Read Only Memory (EEPROM (registered trademark)), a Compact Disk Read Only Memory (CD-ROM), a Magneto-Optical disk (MO), a Digital Versatile Disk (DVD), and a Blu-ray (registered trademark) disc.

[0103] Furthermore, a "program" is a data processing method written in any language or description method, regardless of the format, such as source code or binary code. Note that a "program" is not necessarily limited to a single structure, but also includes a structure that is distributed as multiple modules or libraries, or a structure that achieves its function by cooperating with a separate program, such as an OS. Note that the specific configuration and reading procedure for reading a recording medium in each device shown in the embodiments, as well as the installation procedure after reading, can use well-known configurations and procedures.

[0104] The various databases stored in the memory unit are storage means such as memory devices such as RAM and ROM, fixed disk devices such as hard disks, flexible disks, and optical disks, and store various programs, tables, databases, and web page files used for various processes and providing websites.

[0105] The real estate simulation device 100 may be configured as an information processing device such as a known personal computer or workstation, or may be configured as the information processing device to which any peripheral device is connected. The real estate simulation device 100 may also be realized by installing software (including programs, data, etc.) that causes the device to perform the processing described in this embodiment.

[0106] Furthermore, the specific form of distribution and integration of the devices is not limited to that shown in the drawings, and all or part of them can be configured by functionally or physically distributing and integrating them in any unit depending on various additions or functional loads. In other words, the above-described embodiments can be implemented in any combination, or embodiments can be implemented selectively. [Explanation of symbols]

[0107] 100 Real Estate Simulation Device 102 Control section 102a Registration Department 102b Simulation Development Environment Creation Department 102c Forecast Data Creation Department 102d Screen display control unit 104 Communication interface unit 106 Storage section 106a Customer Master 106b Property Master 106c Floor Master 106d Section Master 106e Rental contract master 106f Contract Rule Master 106g Estimated rent master 106h Data Table 108 Input / Output Interface Section 112 Input Device 114 Output Device 300 Network

Claims

1. A real estate simulation device including a control unit, The control unit Contract data including contract number, customer, property, lot, contract start date, contract end date, monthly rent, rent start date, and termination date; A plot master that associates and registers property, floor, plot, area, and use, A contract rule master that associates and registers the property, area, area size, use, number of months from contract termination to contract conclusion, number of months from contract conclusion to delivery, and number of months from delivery to when rent is billed; The estimated rent master is a database that associates the property, floor, use, plot, area, floor size, and monthly rent per tsubo. It is configured to be accessible to a prediction data creation means for acquiring floor, area, and use from the section master using the property and section of the target contract data as keys, identifying a record of the estimated rent master using the property, section, floor, and use as keys, identifying a record of the contract rule master using the area, area size, and use of the identified estimated rent master record as keys, and creating new contract data, which is simulation data, by referring to the identified records of the estimated rent master and contract rule master; A real estate simulation device comprising:

2. 2. The real estate simulation device according to claim 1, wherein said forecast data creation means creates billing data including monthly rents based on the created new contract data.

3. The forecast data creation means performs the following on the new contract data: The monthly rent is calculated by multiplying the acquired area by the monthly unit price per tsubo in the estimated rent master. The contract start date is calculated by adding the cancellation date to the number of months from the cancellation of the contract rule master to the conclusion of the contract. The real estate simulation device according to claim 1 or 2, characterized in that the rent due date is calculated as the contract start date + the number of months from the contract conclusion in the contract rule master to delivery + the number of months from delivery to when rent is billed.

4. The real estate simulation device described in claim 1, characterized in that the forecast data creation means obtains the floor, area, and use from the section master using the property and section of the target contract data as keys, identifies the record of the estimated rent master using the property, section, floor, and use as keys, and creates updated contract data, which is simulation data, by referring to the identified record of the estimated rent master.

5. 5. The real estate simulation device according to claim 4, wherein said forecast data creating means creates billing data including monthly rents based on the created contract renewal data.

6. 6. The real estate simulation device according to claim 4, wherein the forecast data creation means calculates the monthly rent for the updated contract data by multiplying the acquired area by the monthly price per tsubo in the estimated rent master.

7. A real estate simulation method executed by an information processing device having a control unit, The control unit Contract data including contract number, customer, property, lot, contract start date, contract end date, monthly rent, rent start date, and termination date; A plot master that associates and registers property, floor, plot, area, and use, A contract rule master that associates and registers the property, area, area size, use, number of months from contract termination to contract conclusion, number of months from contract conclusion to delivery, and number of months from delivery to when rent is billed; The estimated rent master is a database that associates the property, floor, use, plot, area, floor size, and monthly rent per tsubo. It is configured to be accessible to Executed in the control unit: a forecast data creation process in which the property and plot of the target contract data are used as keys to obtain the floor, area, and use from the plot master, the property, plot, floor, and use are used as keys to identify the record of the estimated rent master, the area, area size, and use of the identified estimated rent master record are used as keys to identify the record of the contract rule master, and new contract data, which is simulation data, is created by referencing the identified records of the estimated rent master and contract rule master; A real estate simulation method comprising:

8. A real estate simulation program to be executed by an information processing device having a control unit, The control unit Contract data including contract number, customer, property, lot, contract start date, contract end date, monthly rent, rent start date, and termination date; A plot master that associates and registers property, floor, plot, area, and use, A contract rule master that associates and registers the property, area, area size, use, number of months from contract termination to contract conclusion, number of months from contract conclusion to delivery, and number of months from delivery to when rent is billed; The estimated rent master is a database that associates the property, floor, use, plot, area, floor size, and monthly rent per tsubo. It is configured to be accessible to In the control unit, a forecast data creation process in which the property and plot of the target contract data are used as keys to obtain the floor, area, and use from the plot master, the property, plot, floor, and use are used as keys to identify the record of the estimated rent master, the area, area size, and use of the identified estimated rent master record are used as keys to identify the record of the contract rule master, and new contract data, which is simulation data, is created by referencing the identified records of the estimated rent master and contract rule master; A real estate simulation program for running the following:

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