Recommendation device, recommendation system, recommendation method, and program

Abstract

To provide a recommendation device, a recommendation system, a recommendation method, and a program for periodically recommending the purchase of a product with a small greenhouse gas emission factor.SOLUTION: A recommendation device 1 includes: a database 11 in which an attribute of a product is associated with an emission factor indicating a greenhouse gas emission amount per unit price of the product; a calculation section 12 that calculates the greenhouse gas emission amount by a product purchased by a user on the basis of an input from a user device carried by the user and a database 11; and a recommendation section 13 that periodically generates recommendation information for recommending a product whose attribute matches that of a product purchased by the user within a predetermined period and of which the emission factor is smaller than that of the product purchased within the predetermined period.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a recommendation device, a recommendation system, a recommendation method, and a program. [Background technology]

[0002] Attention has been focused on environmental household accounting books that calculate and visualize greenhouse gas (e.g., carbon dioxide) emissions from energy consumption such as electricity, gas, or water. Patent Document 1 describes an environmental household accounting system in which a business manages sales data for each consumer and calculates greenhouse gas emissions for each consumer.

[0003] Patent Document 2 describes an environmental load reduction system that compares the greenhouse gas emissions advantages of products currently in use and products that are candidates for purchase, and determines whether or not to replace the products. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2010-282279 [Patent Document 2] Japanese Patent Application Laid-Open No. 2011-81511 Summary of the Invention [Problem to be solved by the invention]

[0005] The environmental household accounting system described in Patent Document 1 requires users to consider ways to reduce greenhouse gas emissions, which poses a problem in that it is difficult to change users' behavior to reduce greenhouse gas emissions.

[0006] In view of the above-mentioned problems, an object of the present disclosure is to provide a recommendation device, a recommendation system, a recommendation method, and a program that can periodically recommend the purchase of products with low greenhouse gas emission coefficients. [Means for solving the problem]

[0007] The recommendation device according to the present disclosure comprises: a database in which product attributes are associated with emission coefficients indicating greenhouse gas emissions per unit price of the product; a calculation unit that calculates greenhouse gas emissions caused by products purchased by a user based on an input from a user device carried by the user and the database; The system includes a recommendation unit that periodically generates recommendation information that recommends products whose attributes match those of products purchased by the user within a specified period and whose emission coefficients are smaller than those of the products purchased within the specified period.

[0008] The recommendation system according to the present disclosure comprises: a user device possessed by a user; a recommendation device including a database in which product attributes are associated with emission coefficients indicating greenhouse gas emissions per unit price of the product; The recommended device is Calculating greenhouse gas emissions from products purchased by the user based on input from the user device and the database; Recommendation information is periodically generated that recommends products whose attributes match those of products purchased by the user within a predetermined period and whose emission coefficients are smaller than those of the products purchased within the predetermined period.

[0009] The recommended method according to this disclosure is: The computer Calculating the greenhouse gas emissions of the products purchased by the user based on input from a user device owned by the user and a database in which product attributes are associated with emission coefficients indicating the greenhouse gas emissions per unit price of the products; Recommendation information is periodically generated that recommends products whose attributes match those of products purchased by the user within a predetermined period and whose emission coefficients are smaller than those of the products purchased within the predetermined period.

[0010] The program according to the present disclosure is On the computer, A process of calculating greenhouse gas emissions from products purchased by the user based on input from a user device owned by the user and a database in which product attributes are associated with emission coefficients indicating greenhouse gas emissions per unit price of the product; a process of periodically generating recommendation information that recommends products whose attributes match those of products purchased by the user within a predetermined period and whose emission coefficients are smaller than those of the products purchased by the user within the predetermined period; Execute the following. [Effects of the Invention]

[0011] The recommendation device, recommendation system, recommendation method, and program according to the present disclosure can periodically recommend the purchase of products with low greenhouse gas emission coefficients. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a block diagram showing a configuration of a recommendation device according to a first embodiment. [Figure 2] FIG. 10 is a block diagram showing the configuration of a recommendation system according to a second embodiment. [Figure 3] FIG. 10 is an explanatory diagram of an example of an emission coefficient database according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0013] Embodiment 1 Hereinafter, embodiments of the present invention will be described with reference to the drawings. Fig. 1 is a block diagram showing the configuration of a recommendation device 1 according to embodiment 1. The recommendation device 1 includes a database 11, a calculation unit 12, and a recommendation unit 13.

[0014] The recommendation device 1 is connected to a network (not shown). The network may be wired or wireless. A user device (not shown) is connected to the network.

[0015] Database 11 associates product attributes with emission coefficients that indicate the amount of greenhouse gas emissions per unit price of the product. Products include, for example, food products, daily necessities, gas, electricity, etc. Products may also include services such as cleaning. Attributes include item name, product name, payment destination (purchaser), etc. Greenhouse gases are, for example, carbon dioxide. Greenhouse gases may also include methane, nitrous oxide, etc.

[0016] The calculation unit 12 calculates the greenhouse gas emissions from products purchased by a user based on input from a user device carried by the user and the database 11. The user device is carried by the user. The user device is, for example, a smartphone or a PC (Personal Computer). The input from the user device may include the product name, price, etc. The calculation unit 12 extracts the emission coefficient of the purchased product from the database 11 and multiplies the extracted emission coefficient by the price to calculate the greenhouse gas emissions.

[0017] The recommendation unit 13 periodically generates recommendation information that recommends products that have attributes (e.g., item names) that match those of products purchased by the user within a predetermined period and have a smaller emission coefficient than the products purchased within the predetermined period. The recommendation device 1 is assumed to manage the user's purchase history for a predetermined period (e.g., one week). The recommendation unit 13 may, for example, refer to the database 11 to determine the products to recommend, and send an email to the user device containing a message encouraging the user to purchase the determined products.

[0018] The recommendation device 1 periodically recommends the purchase of products with low emission coefficients. The recommendation device 1 can contribute to reducing greenhouse gas emissions by encouraging the purchase of products with low emission coefficients.

[0019] The recommendation device 1 includes a processor, a memory, and a storage device (not shown). The storage device stores a computer program that implements the processing of the recommendation method according to the first embodiment. The processor then loads the computer program from the storage device into the memory and executes the computer program. This allows the processor to realize the functions of the calculation unit 12 and the recommendation unit 13.

[0020] Alternatively, the calculation unit 12 and the recommendation unit 13 may each be realized by dedicated hardware. Furthermore, some or all of the components of each device may be realized by general-purpose or dedicated circuits, processors, etc., or a combination of these. These may be configured by a single chip, or by multiple chips connected via a bus. Some or all of the components of each device may be realized by a combination of the above-mentioned circuits, etc., and programs. Furthermore, a CPU (Central Processing Unit), GPU (Graphics Processing Unit), FPGA (Field-Programmable Gate Array), quantum processor (quantum computer control chip), etc., may be used as the processor.

[0021] Furthermore, when some or all of the components of the recommendation device 1 are realized by multiple information processing devices, circuits, etc., the multiple information processing devices, circuits, etc. may be centrally or distributed. For example, the information processing devices, circuits, etc. may be realized in a form in which each is connected via a communication network, such as a client-server system or a cloud computing system. Furthermore, the functions of the recommendation device 1 may be provided in a SaaS (Software as a Service) format.

[0022] Embodiment 2 2 is a block diagram showing the configuration of a recommendation system 1000 according to embodiment 2. The recommendation system 1000 includes a user device 100 and an emission amount calculation server 200. The emission amount calculation server 200 is a specific example of the above-mentioned recommendation device 1. The user device 100 and the emission amount calculation server 200 are connected to each other so that data communication is possible.

[0023] The user device 100 is a terminal carried by a user, such as a smartphone or a PC (Personal Computer). The user device 100 includes an input device (e.g., a touch panel, a keyboard, or a mouse) and a display device (e.g., a display or a monitor), both of which are not shown.

[0024] The user device 100 transmits the expenditure information input by the user to the emission calculation server 200. The expenditure information includes the product name, price, and purchase location of the purchased product. The user may start software for creating an environmental household account book and input the expenditure information. The user may also use the user device 100 to register address information (e.g., prefecture name, city / town name), email address, and the like in advance in the emission calculation server 200.

[0025] The user device 100 also acquires information from the emission calculation server 200 and displays the environmental household account book on the display device. The user device 100 may also acquire information from a calculated emission database 230, which will be described later.

[0026] Furthermore, the user device 100 acquires recommendation information from the emission amount calculation server 200 and displays the recommendation information on the display device. The recommendation information includes information indicating the product name and purchase location of the recommended product.

[0027] The emission calculation server 200 is a specific example of the above-mentioned recommendation device 1. The emission calculation server 200 includes an emission coefficient database 210, an emission calculation unit 220, a calculated emission database 230, a ranking creation unit 240, and a recommendation information creation unit 250.

[0028] The emission coefficient database 210 is a specific example of the above-mentioned database 11. The emission coefficient database 210 stores attributes such as product names and emission coefficients in association with each other.

[0029] 3 shows a specific example of the emission coefficient database 210. The emission coefficient database 210 includes a field 211 indicating the payee (purchaser), a field 212 indicating the manufacturer, a field 213 indicating the product name, a field 214 indicating the emission coefficient, a field 215 indicating the validity period, and a field 216 indicating the region name. Fields 211, 212, 213, and 216 represent product attributes.

[0030] Field 211 indicates the payee of the purchased product, i.e., the supplier. Field 212 indicates the producer or manufacturer of the purchased product. Field 213 indicates the product name of the purchased product. Field 214 indicates the amount of carbon dioxide emissions per unit price of the purchased product. Field 215 indicates the validity period of the emission coefficient indicated in field 214. Field 216 indicates the sales region in which the purchased product is sold. The emission calculation server 200 receives the latest emission coefficients from each business and updates the emission coefficient database 210.

[0031] Information about one product is stored in each record of the emission coefficient database 210. For example, the example emission coefficient record 210a of the emission coefficient database 210 shown in Figure 3 indicates that the emission coefficient of beef produced by Company A and sold at Store T is 0.005 (unit: yen / kg). The emission coefficient record 210a also indicates that the validity period of the emission coefficient is from July 1, 2021 to July 31, 2021, and that the beef will be sold in Yokohama City.

[0032] Returning to FIG. 2, the explanation will be continued. The emission amount calculation unit 220 is a specific example of the calculation unit 12 described above. The emission amount calculation unit 220 acquires expenditure information including product names and prices from the user device 100. Next, the emission amount calculation unit 220 extracts an emission coefficient linked to the product name from the emission coefficient database 210. Next, the emission amount calculation unit 220 calculates the emission amount by multiplying the extracted emission coefficient by the acquired price. The emission amount calculation unit 220 associates the calculated emission amount with the product name and the user ID and registers it in the calculated emission amount database 230.

[0033] Furthermore, the emission amount calculation unit 220 outputs the calculated emission amount to the user device 100. This allows the user to check the carbon dioxide emission amount due to the purchased product.

[0034] The calculated emissions database 230 records the amount of carbon dioxide emissions for each product purchased by the user. The calculated emissions database 230 also records the purchase date of each product. The user device 100 may generate an environmental household account book by referencing the calculated emissions database 230. The environmental household account book includes the amount of carbon dioxide emissions for each of multiple products purchased by the user within a collection period (e.g., one month). The environmental household account book may also include the sum of the carbon dioxide emissions for each of the multiple products.

[0035] The ranking creation unit 240 calculates the sum of the carbon dioxide emissions for each of multiple products purchased within a collection period (for example, one week or one month). The ranking creation unit 240 creates a ranking of multiple users so that users with smaller sums of carbon dioxide emissions are ranked higher, and notifies each user of the ranking. This allows the recommendation system 1000 to increase each user's motivation to reduce their carbon dioxide emissions.

[0036] The ranking creation unit 240 may group multiple users based on household composition, region, age, gender, etc., and create a ranking for each group. Since carbon dioxide emissions may vary depending on household composition, etc., by appropriately grouping users, each user's motivation to reduce carbon dioxide emissions can be further improved. The emission calculation server 200 stores user information including each user's ID, region, age, etc. The emission calculation server 200 may associate user information with the environmental household account book.

[0037] The ranking creation unit 240 may send the ranking by email. The sent content may also include information about the rank of the user. For example, the ranking creation unit 240 sends a message such as, "Among households with the same household structure in the city or town where you live, your household is ranked ___ out of ___ people."

[0038] The recommendation information creating unit 250 is a specific example of the recommendation unit 13 described above. The recommendation information creating unit 250 periodically (for example, once a week) creates recommendation information that recommends products whose attributes (for example, product names) match those of products purchased by the user within a predetermined period (for example, one week) and whose emission coefficients are smaller than those of the products purchased within the predetermined period. The recommendation information creating unit 250 outputs the created recommendation information to the user device 100.

[0039] Referring to FIG. 3, milk from Company C has a smaller emission coefficient than milk from Company B. Both milk from Company C and milk from Company B are sold in Yokohama City. In such a case, the recommendation information creation unit 250 recommends to a user who has purchased milk from Company B sold at Store T that they purchase milk from Company C sold at Store I. The recommendation information creation unit 250 generates a message such as, for example, "Milk from Company C sold at Store I is recommended because it has a small carbon dioxide emission coefficient," and transmits it to the user device 100. If the recommendation information includes information indicating a purchase location (e.g., Store I), it can reduce the effort required for the user to research a purchase location. The recommendation information creation unit 250 may, for example, recommend products approximately once a week.

[0040] Specifically, the recommendation information creation unit 250 first identifies products purchased by each user within a predetermined period from the calculated emission amount database 230. Next, the recommendation information creation unit 250 extracts products from the emission coefficient database 210 that have the same product name and sales area as the identified product and have a smaller emission coefficient than the identified product. Then, the recommendation information creation unit 250 generates recommendation information that recommends the extracted products.

[0041] The recommendation information may recommend one product or multiple products. The recommended products may be determined according to the number of purchases. Furthermore, the recommendation information creating unit 250 may recommend products in order of their carbon dioxide emission reduction effect (for example, products with a large carbon dioxide emission).

[0042] The recommendation information creating unit 250 may make recommendations based on the rankings described above. The recommendation information creating unit 250 may send recommendation information only to users ranked low. This is because users ranked low are considered to be particularly in need of recommendation information.

[0043] The emission calculation server 200 may include a counting unit (not shown) that counts the number of times each product has been recommended. Since the number of sales of each product is expected to increase according to the number of times it has been recommended, producers and sellers of the product may wish to know the number of times it has been recommended.

[0044] Finally, the effects of the recommendation system 1000 will be explained. Although it is not a household account book for an actual household, there is something called an environmental household account book. When creating an environmental household account book, the user can calculate the household's carbon dioxide emissions from the energy usage fees for electricity, gas, water, etc. This technology makes it possible to present the carbon dioxide emissions to the user. However, the user had to think for themselves about how to reduce the carbon dioxide emissions based on the displayed figures. In addition, there was a problem that the changes in user behavior were not sustainable because the benefits were difficult to understand.

[0045] The recommendation system according to the second embodiment notifies each user of recommended information and rankings. This can increase the motivation of each user to reduce the amount of carbon dioxide emitted in their daily lives. This has the effect of leading to a reduction in carbon dioxide emissions by purchasing recommended products with low emission coefficients. Furthermore, by connecting multiple users with businesses that offer products with low carbon dioxide emissions, it is possible to promote the reduction of carbon dioxide emissions.

[0046] The present invention is not limited to the above-described embodiment, and can be modified as appropriate within the scope of the invention. [Explanation of symbols]

[0047] 1 Recommended Equipment 11 Database 12 Calculation section 13 Recommendation section 1000 Recommended Systems 100 User device 200 Emissions Calculation Server 210 Emission Factor Database 211, 212, 213, 214, 215, 216 Fields 220 Emissions Calculation Department 230 Calculated Emissions Database 240 Ranking Creation Department 250 Recommendation Information Creation Department

Claims

1. a database in which product attributes are associated with emission coefficients indicating greenhouse gas emissions per unit price of the product; a calculation unit that calculates greenhouse gas emissions caused by products purchased by a user based on an input from a user device carried by the user and the database; a recommendation unit that periodically generates recommendation information that recommends products whose attributes match those of products purchased by the user within a predetermined period and whose emission coefficients are smaller than those of the products purchased by the user within the predetermined period; The database registers the emission factors of a plurality of products that have the same attributes and are sold in different stores, The recommendation information includes information indicating a store that sells the recommended product. Recommended equipment.

2. The recommended device is a ranking creation unit that creates a ranking of a plurality of users so that users with smaller sums of greenhouse gas emissions for each of a plurality of products purchased within a collection period are ranked higher, and notifies each user of the ranking; The recommendation device of claim 1 , comprising:

3. The ranking creation unit Grouping a plurality of users based on their household structure, and creating the ranking for each group; The recommendation device according to claim 2 .

4. A counting section that counts the number of times each product is recommended for purchase; The recommendation device according to claim 1 , further comprising:

5. a user device possessed by a user; a recommendation device including a database in which product attributes are associated with emission coefficients indicating greenhouse gas emissions per unit price of the product; The recommended device is Calculating greenhouse gas emissions from products purchased by the user based on input from the user device and the database; periodically generating recommendation information that recommends products whose attributes match those of products purchased by the user within a predetermined period and whose emission coefficients are smaller than those of the products purchased by the user within the predetermined period; The database registers the emission factors of a plurality of products that have the same attributes and are sold in different stores, The recommendation information includes information indicating a store that sells the recommended product. Recommended system.

6. The recommended device is creating a ranking of the users so that the users with the lowest sum of greenhouse gas emissions for each of the multiple products purchased during the aggregation period are ranked higher, and notifying each user of the ranking; The recommendation system of claim 5.

7. The computer Calculating the greenhouse gas emissions of the products purchased by the user based on input from a user device owned by the user and a database in which product attributes are associated with emission coefficients indicating the greenhouse gas emissions per unit price of the products; periodically generating recommendation information that recommends products whose attributes match those of products purchased by the user within a predetermined period and whose emission coefficients are smaller than those of the products purchased by the user within the predetermined period; The database registers the emission factors of a plurality of products that have the same attributes and are sold in different stores, The recommendation information includes information indicating a store that sells the recommended product. Recommended method.

8. On the computer, A process of calculating greenhouse gas emissions from products purchased by the user based on input from a user device owned by the user and a database in which product attributes are associated with emission coefficients indicating greenhouse gas emissions per unit price of the product; a process of periodically generating recommendation information that recommends products whose attributes match those of products purchased by the user within a predetermined period and whose emission coefficients are smaller than those of the products purchased by the user within the predetermined period; Execute The database registers the emission factors of a plurality of products that have the same attributes and are sold in different stores, The recommendation information includes information indicating a store that sells the recommended product. program.

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