JP7571875B2 - Behavioral change induction device, behavioral change induction method, and program - Google Patents

Description

The present invention relates to a behavior change induction device, a behavior change induction method, and a program.

As the problem of global warming becomes more serious, there is a need to reduce _CO2 emissions. In the Paris Agreement, Japan has set a target of reducing _CO2 emissions by 26% compared to 2013 levels by 2030. The household sector, which accounts for around 30% of _CO2 emissions, is particularly called for to make significant reductions in the Paris Agreement, but the current situation is that these have not been reduced sufficiently. The main sources of household _CO2 emissions are travel (transportation) and food, and lifestyle changes in these areas are being called for.

In the transportation sector, the spread of MaaS (Mobility as a service) is expected to improve the convenience of public transportation and encourage a shift from car travel to public transportation, thereby reducing _CO2 emissions.

MaaS is a service that allows users to use public transportation such as trains and buses as a single travel package without the stress of transferring. The main services of MaaS include route search services and unlimited taxi rides.

In route search services, the environmental impact of each route may be displayed, but generally the route is displayed in order of the shortest travel time. In addition, since there is a tendency to emphasize the shortening of travel time as a benefit of MaaS, the effect of promoting the reduction of environmental impact is thought to be limited (Non-Patent Document 1).

"MaaS can reduce your annual commute time by 2.7 days!?", Jidounten Lab, [online], <URL: https://jidounten-lab.com/u_maas-time-2-7>

In order to encourage users to choose routes with a lower environmental impact, it is necessary to add benefits to users, such as enjoyment.

The present invention has been made in consideration of the above points, and aims to encourage behavioral changes that are both environmentally friendly and beneficial to users.

In order to solve the above problem, the behavior change inducing device includes a route search unit that searches for a plurality of first routes in response to a route search request by a first user; an identification unit that identifies a plurality of second users who are acquaintances of the first user and for whom a second route including a section overlapping with any of the first routes has been searched, based on information suggesting a relationship between the first user; a first calculation unit that calculates a degree of strength of a relationship between the first user and each of the plurality of second users, based on an Internet search history by the first user and an Internet search history by each of the second users; and a calculation unit that calculates, for each of the second users, _CO2 emissions when the second user travels on the second route related to the second user and the first user travels on the first route including a section overlapping with the second route, and CO2 emissions when the second user and the first user travel on a route different from the second route or the first route. The system has a _second calculation unit that calculates the difference between the first and second emissions, and an output unit that ranks a plurality of the first routes including sections that overlap with the second route based on the degree of strength of the relationship and the difference, and outputs the ranking together with information indicating the second user associated with each of the first routes.

It has a low environmental impact and can encourage behavioral changes that are beneficial to users.

1 is a diagram illustrating an example of a hardware configuration of a behavior change inducing device 10 according to an embodiment of the present invention. 1 is a diagram illustrating an example of a functional configuration of a behavior change inducing device 10 according to an embodiment of the present invention. 11 is a flowchart illustrating an example of a processing procedure executed by the behavior change inducing device 10. FIG. 1 is a diagram showing an example of a relationship diagram. FIG. 11 is a diagram showing an example of a calculation result of the relevance of each group.

In an embodiment of the present invention, a behavior change induction device 10 is disclosed that presents a travel route that is enjoyable for the user and leads to reduced environmental impact, based on descriptive norms, which are a theory of behavior change.

Descriptive norms are a theory that posits that behavioral changes occur as a result of being influenced by the behavior of others. For example, when we see someone ignoring a traffic light, we perceive that it is the right thing to do and we will also ignore the traffic light (Kitaori et al., "The Influence of Descriptive Norms on Pedestrians' Traffic Light Ignorance," Social Psychology Research, vol. 16, pp.73-82, 2000).

When descriptive norms are applied to transportation behavior, if a person who was planning to travel to a destination by car learns that their friend will be using the train, they can be expected to join them in using the train. In this embodiment, the concept is to encourage a reduction in environmental impact in a fun way, based on the understanding that traveling with friends leads to enjoyment.

Therefore, the behavioral change inducing device 10 of the present embodiment assigns points to candidate routes from a departure point to a destination based on the enjoyment for the user and the _CO2 reduction rate, ranks them, and presents recommended routes. By recommending traveling with a friend, the enjoyment for the user is realized.

An embodiment of the present invention will now be described with reference to the drawings. Figure 1 is a diagram showing an example of the hardware configuration of a behavior change inducing device 10 in an embodiment of the present invention. The behavior change inducing device 10 in Figure 1 has a drive device 100, an auxiliary storage device 102, a memory device 103, a CPU 104, an interface device 105, etc., which are all interconnected by a bus B.

The program that realizes the processing in the behavior change induction device 10 is provided by a recording medium 101 such as a CD-ROM. When the recording medium 101 storing the program is set in the drive device 100, the program is installed from the recording medium 101 via the drive device 100 into the auxiliary storage device 102. However, the program does not necessarily have to be installed from the recording medium 101, but may be downloaded from another computer via a network. The auxiliary storage device 102 stores the installed program as well as necessary files, data, etc.

When an instruction to start a program is received, the memory device 103 reads out and stores the program from the auxiliary storage device 102. The CPU 104 executes functions related to the behavior change induction device 10 in accordance with the program stored in the memory device 103. The interface device 105 is used as an interface for connecting to a network.

2 is a diagram showing an example of the functional configuration of the behavior change inducing device 10 in an embodiment of the present invention. In FIG. 2, the behavior change inducing device 10 has a route search unit 11, a relationship network generation unit 12, a difference calculation unit 13, an analysis unit 14, and an output unit 15. Each of these units is realized by a process in which one or more programs installed in the behavior change inducing device 10 are executed by the CPU 104. The behavior change inducing device 10 also uses databases (storage units) such as a route search information DB 16, an SNS information DB 17, and a search history DB 18. Each of these databases can be realized using, for example, an auxiliary storage device 102, or a storage device that can be connected to the behavior change inducing device 10 via a network.

The following describes the processing procedure executed by the behavior change induction device 10. Figure 3 is a flowchart for explaining an example of the processing procedure executed by the behavior change induction device 10.

In step S101, the route search unit 11 receives a route search request from user A's terminal. The search request specifies a starting point (e.g., home), a destination, and a date (hereinafter, the "specified date", etc.). For ease of explanation, it is assumed here that some event (hereinafter, the "target event") is scheduled to be held at a certain location on the specified date. The target event may be an event in which unspecified people participate, or may be a private event among user A's friends. It is assumed that user A has requested a search for a route to get to the target event.

Next, in response to the search request, the route search unit 11 searches for multiple routes from the departure point to the destination on the specified date specified in the search request. In the route search, the means of transportation may be public transportation, may be a car, or may include walking in some sections. Here, it is assumed that routes using multiple types of transportation are searched. The route search unit 11 associates the route search results (information including the specified date and the multiple routes searched) with the user ID of user A and records them in the route search information DB 16. In other words, the route search information DB 16 records the search results of routes obtained by past route searches for user A and other users other than user A, as well as the history of user IDs.

Next, the relational network generation unit 12 identifies multiple acquaintances of user A based on the SNS (Social Networking Service) information stored in the SNS information DB 17 (S103). SNS information refers to information that may be obtained from an SNS. It is considered that the SNS information includes information suggesting acquaintances of user A (e.g., friends). For example, people who are set as friends of user A in the SNS, followers of user A's posts, etc. may be identified as acquaintances of user A. Note that the SNS information is not limited to information about a specific SNS. Acquaintances of user A may be identified based on multiple types of SNS information.

Next, the relationship network generation unit 12 acquires the route search results for the specified date by each acquaintance identified in step S103 from the route search information DB 16 (S104). That is, an acquaintance who plans to go to a certain place on the specified date is expected to be searching for a route to that place on the specified date as a user of the behavior change induction device 10. In step S103, multiple routes that are the route search results for the specified date are acquired for each such acquaintance.

Next, the relational network generation unit 12 identifies acquaintances (hereinafter referred to as "accompanying candidates") whose routes overlap with any of the routes included in the search results of user A, among the acquaintances whose routes were acquired in step S104 (S105). An overlapping route means that there is an identical section between one route and the other route that is traveled by the same means of transportation. In other words, an overlapping route means that one route includes a section that overlaps with the other route (at least partially overlaps). For example, if the entire section of one route is by car and the entire section of the other route is by car, these routes will overlap if there is an overlap between these routes. Also, for example, if both routes include a section traveled on the same train line from station A to station B, the two routes will overlap.

Note that in a section where a certain route overlaps with another route, the timing of passage in the search results for each route (for example, the departure and arrival times for the section in the case of a section from Station A to Station B) does not have to be a condition for route overlap. This is because such timing can be adjusted between User A and the accompanying candidates. It is also assumed that multiple routes have been searched for each of User A and each acquaintance, and acquaintances for whom one or more routes that overlap at least partially with at least one of User A's multiple routes have been searched are considered to be accompanying candidates.

In addition, potential accompaniment acquaintances do not necessarily have to be acquaintances with the same destination. However, if one of acquaintance A's acquaintances is attending the target event and uses public transportation, and there is only one section from a transfer point to the location of the target event, that person is likely to be identified as a potential accompaniment.

Next, the relationship network generation unit 12 determines whether or not there is an acquaintance relationship between each accompanying candidate based on the SNS information stored in the SNS information DB 17, and generates a relationship diagram showing the acquaintance relationships between user A and each accompanying candidate (S106).

Figure 4 is a diagram showing an example of a relationship diagram. As shown in Figure 4, the relationship diagram is a network (graph) in which nodes having user A or accompanying candidates as nodes and having acquaintance relationships are connected by edges. The relationship diagram has a structure in which the nodes of accompanying candidates are arranged radially from the node of user A. Acquaintance relationships are not limited to one-to-one relationships between user A and each accompanying candidate, and when multiple accompanying candidates including user A are acquaintances of each other, they become a closed-loop group of three or more people.

In the example of Figure 4, the node labeled "A" corresponds to the node of user A. The example of Figure 4 shows that accompanying candidates B to D are extracted in step S105, and that accompanying candidates B and C are acquaintances.

Next, the relational network generation unit 12 calculates a score (hereinafter referred to as "relevance") indicating the strength of the relationship (acquaintance relationship) of each group in which all members are mutual acquaintances in the relational diagram based on the SNS information stored in the SNS information DB 17 and the search history (Internet search history) stored in the search history DB 18 (S107). The higher the relevance value, the stronger the relationship.

In the example of Figure 4, the groups in which all members are acquaintances of each other are three groups: a group of three people, A, B, and C; a group of two people, A and D; and a group of two people, A and E. However, for each accompanying candidate, a pair of user A and the accompanying candidate may be identified as a group.

For example, the relevance of each group is calculated based on the presence or absence of a common community and hobby between the members in the group. Specifically, the relationship NW generation unit 12 identifies the community to which the members in the group belong based on SNS information, and adds 3 points for each common community to the relevance of the group. In addition, the relationship NW generation unit 12 estimates the hobby of each member in the group from the search history of each member in the group (for example, from search keywords, etc.), and adds 2 points for each common hobby to the relevance of the group. For a group with N members (three or more), if i of the N members have the above-mentioned common points, <additional points> x i/N points are added to the relevance. Here, <additional points> are 3 points for a common community and 2 points for a common hobby.

Note that the above is merely one example of a method for calculating relevance. Relevance may also be calculated based on commonalities other than commonalities of communities or commonalities of hobbies. For example, relevance may simply be calculated based on commonalities of search keywords.

Figure 5 is a diagram showing an example of the calculation results of the relevance of each group. Figure 5 shows an example in which the relevance of groups A, B, and C is 2, the relevance of groups A and D is 2, and the relevance of groups A and E is 4.

Next, the difference calculation unit 13 calculates the difference in CO2 emissions for each group between a case where members of the group travel together on routes that _overlap in part and a case where each member travels individually on a different route (here, the route with the shortest time (hereinafter, referred to as the "shortest route")) (S108). Traveling together refers to traveling together on a section that overlaps between the routes of each member of the group (for example, sharing a car if the means of transportation for that section is a car, or riding the same train, bus, etc. if the means of transportation for that section is public transportation).

An example of calculating the difference for groups A, B, and C in FIG. 5 will be described. Here, it is assumed that, among the routes searched for A, route a using a train or bus is a route that includes a section that overlaps with route b searched for B and route c searched for C. It is also assumed that routes b and c are both routes that use only buses. Therefore, in the bus section, user A can travel together with accompanying candidates B and C. That is, in this example, the _CO2 emissions when traveling together are calculated for the routes in which each uses a train or bus.

On the other hand, the shortest route for each of A, B, and C is assumed to be the route when traveling by car. Therefore, the _CO2 emissions when each member travels the shortest route are calculated for the route each member travels individually by car.

The _CO2 emissions of each person on each route are calculated from the travel time for each means of transportation (vehicle) and the _CO2 emissions unit value of each means of transportation.

In the above case, an example of calculating the difference in CO ₂ emissions for the group is as follows.

第１項は、各メンバが最短経路で移動する場合のＣＯ_２排出量を計算するための項である。第２項は、一緒に移動する場合のＣＯ_２排出量を計算するための項である。第１項及び第２項のそれぞれの左側の行列は、ユーザＡ、同行候補者Ｂ、同行候補者Ｃそれぞれが電車、車、バスに乗車する時間（分）を示し、右側の行列は各移動手段１分あたりのＣＯ_２排出原単位（ｇ－ＣＯ_２／分）である。当該ＣＯ_２排出原単位は、例えば、経路探索情報ＤＢ１６等の所定の記憶部に記憶されていればよい。

The first term is a term for calculating the amount of _CO2 emissions when each member travels by the shortest route. The second term is a term for calculating the amount of _CO2 emissions when traveling together. The left-hand matrix of each of the first and second terms indicates the time (minutes) that user A, accompanying candidate B, and accompanying candidate C take by train, car, and bus, respectively, and the right-hand matrix indicates the _CO2 emission intensity (g- _CO2 /min) per minute of each transportation means. The _CO2 emission intensity may be stored in a predetermined storage unit such as the route search information DB16, for example.

In the above example, the difference in CO ₂ emissions (ie, the amount of CO ₂ reduction when travelling together) is 3124.4 (g-CO ₂ ).

Next, the difference calculation unit 13 calculates, for each group, a _CO2 reduction rate when each member moves together, and converts the reduction rate into a score according to an arbitrary rank (S109). The calculation formula for the _CO2 reduction rate is as follows:

ここで、分子は、ステップＳ１０８において算出した差分である。分母は、数１における第１項である。したがって、ＡＢＣのグループのＣＯ_２削減率は６５％となる。０％～１００％の間を１０％ごとに１～１０の階級で分割すると、ＡＢＣのグループのＣＯ_２削減率の点数は７点となる。

Here, the numerator is the difference calculated in step S108, and the denominator is the first term in equation 1. Therefore, the _CO2 reduction rate of group ABC is 65%. If 0% to 100% is divided into 10-point scales from 1 to 10, the score of the _CO2 reduction rate of group ABC is 7 points.

Similarly, the points for the CO ₂ reduction rate are calculated for each of the groups AD and AE. Here, it is assumed that the point for the group AD is 5 points, and the point for the group AE is 6 points.

Next, the analysis unit 14 calculates a score for each group (hereinafter referred to as the "recommendation level") based on the following formula (S109).

すなわち、グループのＣＯ_２削減率の点数と、当該グループの関連度とをそれぞれが重み付け係数によって重み付けして合算した結果が、当該グループの推奨度として算出される。

That is, the score of the CO ₂ reduction rate of the group and the relevance degree of the group are weighted by the weighting coefficient and then added together to calculate the recommendation degree of the group.

For example, if the value of the weighting coefficient a for the CO ₂ reduction rate is 1 and the value of the weighting coefficient for the relevance is 2, the recommendation level of the ABC group is 11, as follows:
1 x 7 + 2 x 2 = 11
Similar calculations would give the AD group a score of 9 and the AE group a score of 14.

Next, the output unit 15 ranks the routes that overlap with the routes of other accompanying candidates of the group (hereinafter referred to as "overlapping routes") among the routes searched for user A based on the recommendation level, and outputs (transmits to user A's terminal) each overlapping route in an order based on the ranking result together with information indicating the accompanying candidates related to the overlapping route in the order based on the ranking result (S111). For example, the ranking result may be output so that overlapping routes are displayed in descending order of recommendation level. In this example, overlapping routes in each group are output as recommended routes in the order of AE, ABC, and AD, and accompanying candidates of each group are output. Note that the overlapping route in one group may be the same as the overlapping route in another group, or may be different. By outputting such information, it is possible to increase the possibility of inducing a behavioral change, such as user A, who was considering traveling by car via the shortest route, selecting a route that can be traveled with an acquaintance.

In addition, the _CO2 reduction effect is greater for group ABC than for group AD, but AD is more highly recommended (has a higher recommendation rank) due to the influence of relevance. In this way, although this embodiment does not necessarily maximize _CO2 reduction, it encourages reduction in environmental load by adding the benefit of being with acquaintances.

In the above example, routes that do not overlap with acquaintances' routes, such as the shortest route, are excluded from the output targets. Therefore, in consideration of the convenience of user A, the output unit 15 may output these routes. In this case, these routes may be output in a lower order than routes that have sections that overlap with acquaintances' routes.

As described above, this embodiment can encourage behavioral changes that are environmentally friendly and have benefits for users (such as the enjoyment of traveling with acquaintances).

In this embodiment, the relationship network generation unit 12 is an example of an identification unit and a first calculation unit. The difference calculation unit 13 is an example of a second calculation unit.

Although the embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and variations are possible within the scope of the gist of the present invention as described in the claims.

10 Behavior change induction device 11 Route search unit 12 Relation network generation unit 13 Difference calculation unit 14 Analysis unit 15 Output unit 16 Route search information DB
17 SNS information DB
18 Search history DB
100 Drive device 101 Recording medium 102 Auxiliary storage device 103 Memory device 104 CPU
105 Interface device B bus

Claims (5)

a route search unit that searches for a plurality of first routes in response to a route search request from a first user;
an identification unit that identifies a plurality of second users who are acquaintances of the first user and for whom a second route including a section overlapping any one of the first routes has been searched, based on information suggesting a relationship between the first user and the second user;
a first calculation unit that calculates a degree of strength of a relationship between the first user and each of the second users based on an Internet search history of the first user and an Internet search history of each of the second users;
a second calculation unit that calculates, for each of the second users, a difference between an amount of _CO2 emission when the second user moves on the second route related to the second user and the first user moves on the first route including a section overlapping with the second route, and an amount of _CO2 emission when the second user and the first user move on the second route or a route other than the first route;
an output unit that ranks a plurality of the first routes including sections overlapping with the second routes based on the degree of strength of the relationship and the difference, and outputs the ranking together with information indicating the second user related to each of the first routes;
A behavior change inducing device comprising: a route search unit that searches for a plurality of first routes in response to a route search request from a first user;
an identification unit that identifies a plurality of second users who are acquaintances of the first user and for whom a second route including a section overlapping any one of the first routes has been searched, based on information suggesting a relationship between the first user and the second user;
a first calculation unit that calculates a degree of strength of a relationship between the first user and each of the second users;
a second calculation unit that calculates, for each of the second users, a difference between an amount of _CO2 emission when the second user moves on the second route related to the second user and the first user moves on the first route including a section overlapping with the second route, and an amount of _CO2 emission when the second user and the first user move on the second route or a route other than the first route;
an output unit that ranks a plurality of the first routes including sections overlapping with the second routes based on the degree of strength of the relationship and the difference, and outputs the ranking together with information indicating the second user related to each of the first routes;
having
the output unit prioritizes the first routes including sections overlapping with the second routes based on a result of adding up the degrees of strength of the relationship and the differences that are weighted differently.
A behavior change induction device characterized by the above. a route search procedure for searching a plurality of first routes in response to a route search request from a first user;
a step of identifying a plurality of second users who are acquaintances of the first user and for whom a second route including a section overlapping any one of the first routes has been searched, based on information suggesting a relationship between the first user and the second user;
a first calculation step of calculating a degree of strength of a relationship between the first user and each of the second users based on an Internet search history of the first user and an Internet search history of each of the second users;
a second calculation step of calculating, for each of the second users, a difference between an amount of _CO2 emission when the second user travels on the second route related to the second user and the first user travels on the first route including a section overlapping with the second route, and an amount of _CO2 emission when the second user and the first user travel on the second route or a route other than the first route;
an output step of ranking the first routes including sections overlapping with the second routes based on the degree of strength of the relationship and the difference, and outputting the ranking together with information indicating the second user related to each of the first routes;
A behavior change induction method characterized by being executed by a computer. a route search procedure for searching a plurality of first routes in response to a route search request from a first user;
a step of identifying a plurality of second users who are acquaintances of the first user and for whom a second route including a section overlapping any one of the first routes has been searched, based on information suggesting a relationship between the first user and the second user;
a first calculation step of calculating a degree of strength of a relationship between the first user and each of the second users;
a second calculation step of calculating, for each of the second users, a difference between an amount of _CO2 emission when the second user travels on the second route related to the second user and the first user travels on the first route including a section overlapping with the second route, and an amount of _CO2 emission when the second user and the first user travel on the second route or a route other than the first route;
an output step of ranking the first routes including sections overlapping with the second routes based on the degree of strength of the relationship and the difference, and outputting the ranking together with information indicating the second user related to each of the first routes;
The computer executes
the output step includes: ranking the first routes including sections overlapping with the second routes based on a result of adding up the degrees of strength of the relationship and the differences with different weights.
A method for inducing behavioral change, comprising: A program for causing a computer to execute the method for inducing behavioral modification according to claim 3 or 4 .

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